International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755

Volume.1 & Issue.7 Pages: 1-118

Editor-in-Chief Dr.K.V.L.N.Acharyulu

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*Dr.Jingjing Wang,Hunan University of Humanities,Science and Technology,Hunan, China.

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*Dr. K.GnanaSheela, ECE Department,Toc H Institute of Science & Technolog,Kerala,India.

*Dr.Abdullah,ZHDC, Delhi University,JLN Marg, New Delhi,India.

*Dr.Uliana Paskaleva, South-West University "Neofit Rilski", Technical, Blagoegvrad,Bulgaria.

*Dr.A.H.Srinivasa,Maharaja Institute of Technology,Mysore, India.

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*Dr. Mrs. Heena V Sanghani,Dept. of in Applied Science, Dr. Babasaheb Ambedkar College of Engineering and Research,Nagpur. Volume:1 & Issue:7 Article Author(s) & Title of the Article Page Number

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Characterization of Lipschitz spaces and the Zygmund Class using wavelet packets

Abdullah Department of Mathematics ZHDC, Delhi University JLN Marg, New Delhi-110 002, India. [email protected]

Abstract This paper deals with the characterization of Lipschitz spaces ( ), 0< <1 and the Zygmund class ( ) using wavelet packets and few results in this direction are proved. ∧ ℝ ∗ ∧ Keywords:ℝ Wavelet packets, multiresolution analysis, Lipschitz space and Zygmund class.

1. INTRODUCTION:

A simple, but powerful extension of wavelets and multiresolution analysis is wavelet packets, pioneered by Coifman, Meyer, Wickerhauser and other researchers [6, 7, 8, 14]. Discrete wavelet packets have been thoroughly studied by Wickerhauser [15], who has also developed computer programs and implemented them. The wavelet packets allow more flexibility in adapting the basis to the frequency contents of a signal and it is easy to develop a fast wavelet packet transform. The power of wavelet packet lies on the fact that we have much more freedom in deciding which basis function we use to represent the given function. The best basis selection criteria and application to image processing can be found in [9, 14].

Wavelet packet functions are generated by scaling and translating a family of basic function shapes, which include father wavelet and mother wavelet . In addition to and there is a whole range of wavelet packet functions . These functions are parameterized by an oscillation or frequency index . A father wavelet corresponds to =0,so .A mother wavelet corresponds to =1,so .Larger values of correspond to wavelet packets with more oscillations and higher frequency. = = Very recently, Ahmad, Kumar and Debnath have studied fourier transforms of wavelet packets in [2] and existence of unconditional wavelet packet bases in [3]. Certain results on wavelet packets have been studied by Ahmad and Abdullah in [1]. Jarrah, Kumar and Ahmad have studied certain characterization of wavelet packets in [11]. In the present paper, we study the characterization of Lipschitz spaces ( ), 0< <1,and the Zygmund class ( ) by using wavelet packets. Our results are generalizations of the results of Hernández and Weiss [10]. ∧ ℝ ∧∗ ℝ 2. PRELIMINARIES:

Throughout, the functions , and will stand for ( ) () () ), and ), respectively. ,,, ,,, ( ( Let and denote the set of integers and real numbers, respectively. For basic ideas, results on wavelets, wavelet packets and multiresolution analysis, we refer to [1, 2, 3, 4, 5, 10, 11, 12]. ℤ ℝ

1 Abdullah /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.1-13

Theorem 2.1 [13]. For 0< <1 we define the Lipschitz space ( ) as the set of all ∞( ) such that ∧≡ ∧ ℝ ∈ ℝ

The norm in is given by

∧ and, with this norm, is a Banach space.

Definition 2.2 [10].∧A function defined on belongs to the regularity class if there exist constants >0and >0such that ℝ ℝ ,,

Lemma 2.3 [10]. Let >0. Suppose that and satisfy

ℎ

with and independent of . Then, there exists a constant such that for all and , we have ∈ℝ ,,,∈ ℤ ≤

Lemma 2.4 [10]. Let >0 and . Suppose that and satisfy

≥ ∈ℕ ℎ

2 Abdullah /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.1-13

with , 0 +1, and independent of .Then, there exists a constant such that for all and , we have , ≤≤ ∈ℝ ,,,∈ℤ ≤

For 1}, let be the set of all functions defined on for which there exist constants >0and < ∞ =0,1,2,…, +1,such that ∈ ℕ ∪ {− ℝ ,

We write for the set of all functions defined on for which there exist constants >0 and <∞ such that ℳ ℝ

Definition 2.5 [10]. For a non-negative integer , let ; that is, if there exist constants >0, >0, <∞ and < ∞ =0,1,2,…, +1,such that ℝ = ∩ℳ ∈ℝ ,

3. MAIN RESULTS:

Let be a function which satisfies ∈ℝ

where =0 if 0 and =0,1,2,…, if >0, , (see [11]).

=−,Define (≤) to be the space of all ∞(∈ℤ) such that ≡ ℝ ≡ ∈ ℝ

where =0 if 0 and =0,1,2,…, if >0, .

3 Abdullah /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.1-13 In a norm is given by

where =0 if 0 and =0,1,2,…, if >0, .

Theorem=−, 3.1. For 0< <1,≤ and their norms are equivalent.∈ℤ Proof. Suppose that . Since∧ = we have ( ) =0 and, hence, ∈∧ ∈ℝ ∫ℝ

By (2.2) we have

Observe that

It follows from this inequality and (3.2) that and | | | | . Now, we assume that . By (3.1)∈ℝ we can write ≤∧ ∈

where ( ) ), and =0 if 0 and =0,1,2,…, if >0, . After taking absolute values inside the sum and separating the summation into two parts, we have =(− =−, ≤ ∈ℤ

4 Abdullah /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.1-13

Since

we have

To estimate we need to use the condition <1. Since , we have ∈

where the last inequality is due to the Mean Value Theorem. Since we want to estimate we have 1< log |, or equivalently, 2 | | <1. In this case − |ℎ ℎ

5 Abdullah /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.1-13

Thus, since <1, we have

The estimates we have found for and show that and

∈∧

Remark 3.2. Originally, the definition of , 0< <1, depends on the choice of the function . Theorem 3.1 shows that this definition is, in fact, independent of . Hence any two functions satisfying (2.3) and (3.1) give rise to≡ the same space , 0< <1, with equivalent norms. We shall use this freedom in the following. It makes sense to define by replacing by 1 in (2.1) and (2.2). Also, it makes sense to define by replacing by 1 in (3.2) and (3.3). The proof of Theorem 3.1 shows that if satisfies (2.3) and (3.1), then . But∧ the proof does not work to prove the reverse inclusion since the series that appears in (3.5) is not convergent when =1.In fact, we shall observe below that and do not coincides. ∧As⊂ we shall prove below, coincide with the Zygmund class of functions, ∞ ), defined as the set of all ) such that ∧ ∧∗≡∧∗ (ℝ ∈ (ℝ

Theorem 3.3. If and satisfies (3.1), then , and their norms are equivalent. ∈ℝ ∧∗= Proof. Suppose that , and assume, for now, that is even. Then, ( ) =0 and the evenness of allow us to write ∈∧∗ ∫ℝ

Using (3.6) we obtain

6 Abdullah /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.1-13

where the last inequality is due to part (ii) of (2.3). Thus, when is even belong to we have and ℝ ∧∗⊆ ≡

We now must show that (3.7) is true when is defined by a function not necessarily even. Choose satisfying, in addition to being even and belonging to , condition (3.1); then ℝ where ( ) ) ). Thus, by (3.7),

=(− =(

To estimate we use Lemma 2.4 with and ( = 1) to obtain

= ℎ=

To estimate we use Lemma 2.3 with and and obtain

= ℎ=

This shows that and | | | | when . Now, suppose that . By (3.1) we can write ∧∗⊆ ≡ ≤∧∗ ∈ℝ ∈

7 Abdullah /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.1-13

To estimate |, we have

We now estimate |. Since , we have | ∈

Using the Mean-Value theorem twice and taking into account the fact that 1 < log |, or equivalently, 2 | | <1, we have − |ℎ ℎ

Since

8 Abdullah /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.1-13

we deduce

These two estimates for | and | show that and | | ⊆∧∗

Remark 3.4. We observe that for these spaces the estimates when is large are more difficult than the corresponding ones for small. This is due to the fact that in the definition of only the large ∞ values of are important. In fact, if 0 the condition already implies ≤ ∈

Let >0 and write , for an and <1. Given and ∞ satisfying (3.1) we define ( ) as the space of all functions such that =+ ∈ℤ 0≤ ∈ℝ ≡ ℝ ≡ ∈ for all =2 ,2 +1,…,2 1, where =0 if 0 and =0,1,2,…, if >0, and the norm in is given by − =−, ≤ ∈ℤ for all =2 ,2 +1,…,2 1. The next theorem shows −that the definition of is independent of the choice of satisfying (3.1). ∈ℝ Theorem 3.5. Let >0for some and <1. If , satisfying (3.1), then, there exists a constant , 0< <∞ such that =+ ∈ℤ 0≤ ∈ℝ for all and for all =2 ,2 +1,…,2 1, where =0 if 0 and =0,1,2,…, if >0, . In particular, the definition of is independent of the choice of . ∈ − =−, ≤ ∈ℤ Proof. By (3.1) we can write

9 Abdullah /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.1-13

where ( ) ). Thus,

=(−

The estimate for is easy. By Lemma 2.3 with and , we deduce

= ℎ=

To estimate we use Lemma 2.4 with and to obtain

= ℎ=

Since +1 =1 >0. This proves the desired result.

We now− give the− characterization of >0, in terms of wavelet packets. Theorem 3.6. Let >0 for some , and <1,and be orthonormal ∞ wavelet packets. Then, if and only if ) and =+ ∈ℤ 0≤ ∈ℝ ∈ ∈ (ℝ

for all , where =0 if 0 and = 0, 1, 2, … , if >0, .

10 Abdullah /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.1-13

Proof. Assume that . Since ∈ we have

for all .

,Suppose, ∈ ℤ now, that ∞ ) and satisfies (3.11). Take to be any function belonging to . Since are orthonormal wavelet packets, we have ∈ (ℝ ℝ

Thus, if = 1, 2, …,

To estimate we use Lemma 2.4 with and to obtain

= ℎ= since +1 =1 >0.

To estimate − we use− Lemma 2.3 with and to obtain

= ℎ=

From (3.8); for =0; we have

when 0 and >0. Thus

≤

11 Abdullah /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.1-13

and, hence, . On combining∈ Theorem 3.6 with Theorems 3.1 and 3.3, we obtain the following corollary.

Corolarry 3.7. Let be orthonormal wavelet packets. Then:

(a) If and 0< <1, then if and only if ∞ ) and ∈ℝ ∈∧ ∈ (ℝ

where =0 if 0 and =0,1,2,…, if >0, .

(b) If =−,, then if and≤ only if ∞ ) and ∈ℤ ∈ℝ ∈∧∗ ∈ (ℝ

where =0 if 0 and =0,1,2,…, if >0, .

4. ACKNOWLEDGEMENTS:=−, ≤ ∈ℤ

The author is thankful to the referee for giving certain fruitful suggestions towards the improvement of the paper and also thankful to Prof. K Ahmad, who has suggested me to work in this direction.

6. REFERENCES:

1. K. Ahmad and Abdullah, Certain results on wavelet packets, J. Anal. appl., 4 (3) (2006), 179-199.

2. K. Ahmad, R. Kumar and L.Debnath, On Fourier transforms of wavelet packets, Zeit. Anal. Anwend., 20(2001), 579-588.

3. K. Ahmad, R. Kumar and L.Debnath, Existence of unconditional wavelet packet bases for the spaces ( ) and ), Taiwanese J. Math., 10(2006), 851-863. 4. C.K. ℝ Chui, ℋAn (ℝIntroduction to Wavelets, Academic Press, New York, 1992.

5. C.K. Chui and C.Li , Non-orthogonal wavelet packets, SIAM J. Math. Anal., 24(1993), 712-738.

6. R.R. Coifman, Y. Meyer, S.Quake and M.V. Wickerhauser, Signal processing and compression with wavelet packets, Technical report, Yale University, 1990.

7. R.R. Coifman, Y. Meyer, Orthonormal wavelet packet basis, preprint, Yale University, New Haven, CT, 1990.

8. R.R.Coifman, Y. Meyer and M.V. Wickerhauser , Size properties of wavelet packets , in ``Wavelets and Their Applications" (M.B. Ruskai et al., eds.) , Jones and Bartlett Publishers, Boston, 1992, 453- 470.

12 Abdullah /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.1-13

9. R.R.Coifman, Y. Meyer and M.V. Wickerhauser, Entropy-based algorithms for best basis selection, IEEE Trans. Inform. Theory, 38(2) (1992), 713-718.

10. E. Hernández and G. Weiss, A First Course on Wavelets, CRC Press, New York, 1996.

11. A.M. Jarrah, R. Kumar and K. Ahmad, Certain characterizations of wavelet packets, Atti Sem. Fis. Univ. Modena, 53(2005) 147-164.

12. S.G. Mallat, Multiresolution approximations and wavelet orthonormal bases of ( ), Trans. Amer. Math. Soc., 315 (1989), 69-87. ℝ 13. E.M. Stein, Singular Integrals and Differentiability Properties of Functions, Princeton University Press, Princeton, New Jersey, 1970.

14. M.V. Wickerhauser, Accoustic signal compression with wavelet packets, in: Wavelets: A Tutorial in Theory and Applications (C.K. Chui, ed.), Academic Press, Boston, (1992), 679-700.

15. M.V. Wickerhauser, Adapted Wavelet Analysis from Theory to Software, A.K. Peters, Ltd., Wellesley, 1994.

AUTHOR’S BRIEF BIOGRAPHY:

Dr. Abdullah : He has completed his Ph.D. from Jamia Millia Islamia, New Delhi in 2007 on topic “A Study of Function Spaces Using Wavelet Packets.” He is a Assistant Professor in Department of Mathematics, Zakir Husain Delhi College, University of Delhi, has been teaching undergraduate and postgraduate classes for the last 10 years. He has to his credit 10 research papers in Wavelet Analysis in various national and international journals.

13 Aruna Rai Vadde et.al / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue7 , 2014, pp.14-26

Wireless Sensor Network Facsimile Environment with MATLAB

1 Aruna Rai Vadde, 2 Ginbar Ensermu

1Department of Electrical and Computer 2Department of Electrical and Computer Engineering, College of Engineering and Engineering, College of Engineering and Technology, Wollega University, Ethiopia. Technology, Wollega University, Ethiopia. [email protected] [email protected]

Abstract

A remote sensor system comprises of spatially appropriated self-ruling sensors to agreeably screen physical or ecological conditions in this paper Distinctive methodology have utilized for reproduction and displaying of SN (Sensor Network) and WSN. Conventional methodologies comprise of different reproduction devices focused around diverse dialects. In this paper, MATLAB/Simulink was utilized to manufacture a complete WSN framework. Recreation technique incorporates building the fittings construction modeling of the transmitting hubs, displaying both the correspondence channel and the accepting expert hub structural engineering. Bluetooth was decided to attempt the physical layer correspondence as for distinctive channel parameters (i.e., Signal to Noise proportion, Attenuation and Interference). The reenactment model was inspected utilizing distinctive topologies under different conditions and various results were gathered. This new recreation technique demonstrates the capacity of the Simulink MATLAB to be a valuable and adaptable methodology to study the impact of distinctive physical layer parameters on the execution of remote sensor systems.

Keywords: wireless senor network, Simulink, Matlab

Introduction:

A remote sensor system comprises of spatially circulated self-sufficient sensors to helpfully screen physical or ecological conditions, for example, temperature, sound, vibration, weight, movement or toxins. The advancement of remote sensor systems was persuaded by military applications, for example, front line observation. They are presently utilized as a part of numerous modern and regular citizen application territories, including mechanical methodology checking and control, machine wellbeing observing, environment and living space observing, human services applications, home mechanization, and activity control [1-2].

A savvy sensor hub is a consolidation of sensing, transforming and correspondence advances. Figure 1 shows the essential design parts of a sensor hub. The sensing unit faculties the change of parameters, sign molding hardware readies the electrical signs to change over to the computerized area, the sensed simple sign is changed over and is utilized as the data to the application calculations or transforming unit, the memory helps handling of assignments and the

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 14 Aruna Rai Vadde et.al / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue7 , 2014, pp.14-25 transceiver is utilized for corresponding with different sensors or the base stations or sinks in Wsn[3], see figure 1.

Sensors can screen temperature, weight, moistness, soil cosmetics, vehicular development, commotion levels, lighting conditions, the vicinity or nonappearance of specific sorts of articles or substances, mechanical anxiety levels on connected items, and different properties. Their system may be seismic, attractive, warm, visual, infrared, acoustic, or radar. A keen sensor is additionally fit for recognizing toward oneself proof and determination toward oneself. The systems of shrewd sensors work in one of three courses: by an observable pathway to the target, (for example, visual sensors), by nearness to target, (for example, seismic sensors), and by proliferation like a wave with conceivable twisting, (for example, acoustic sensors)[4,5].

Figure 1. Basic architectural components of a smart sensor 1.1. GloMoSim/QualNet: GloMoSim [6] is a scalable simulation environment for wireless and wired network systems, which uses the parallel discrete-event simulation capability provided by Parsec [7], a c- based simulation language for sequential and parallel execution of discrete-event simulation models. Both, GloMoSim as well as Parsec, were developed by the Parallel Computing Lab. at UCLA. GloMoSim offers basic functionality to In this area, a choice of existing reenactment situations for WSNs is talked about. Fundamentally, the researched recreation situations can be separated into two significant sorts: versatile improvement and new advancement. The versatile improvement covers reproduction situations that as of now existed before the thought of WSNs developed. These reproduction situations were then reached out to help remote usefulness and were then adjusted for the use with WSNs. In contrast, new improvements spread new test systems, which were made exclusively for reenacting Wsns, considering sensor particular qualities from the earliest starting point. Both sorts have focal points and disservices, however essentially it © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 15 Aruna Rai Vadde et.al / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue7 , 2014, pp.14-25 can be expressed that while the evolutionary adjustment has a few preferences in reusing decently tried thoughts and source code and additionally the greater client and designer premise, the new improvements have their favorable circumstances in concentrating on the unique qualities and the working of sensor hubs.

Simulate wireless networks, even for ad hoc networks (e.g. AODV, DSR). However, the current version of GloMoSim does not offer any sensor network specific features in the default package so that without any further efforts no WSNs can be simulated meaningfully. In 2000 QualNet [6], [7], a commercial derivate of GloMoSim, was created and with GloMoSim 2.0, the last version of GloMoSim, was released under an academic license. From this point in time, no further improvements to GloMoSim were made, whereas the development of QualNet expedited. In October 2009, version 5.0 of QualNet was released including enhancements such as a new sensor network library for ZigBee, new network security library, parallel updates, new models (e.g. batter and energy), updates to current models as well as performance improvements. Furthermore, a new QT based GUI was added providing a scenario designer, a visualize to view network scenarios (2D and 3D), a packet tracer for debugging, an analyzer for statistics and a file editor to edit the scenarios directly.

1.2. OPNET Modeler Wireless Suite: OPNET Modeler Wireless Suite [8]–[10] is a commercial modeling and simulation tool for various types of wireless networks. It is developed by developed by OPNET Technologies, Inc. and based on the well-known product OPNET Modeler. The simulation environment uses a fast discrete event simulation engine operating with a 32-bit/ 64-bit fully parallel simulation kernel, which is available for Windows and Linux. The OPNET Modeler provides an object-oriented modeling approach and a hierarchical modeling environment. Although there are no special routing protocols for wireless sensor network available, at least different propagation and modulation techniques as well as a ZigBee (802.15.4) MAC layer are provided. Additional modules have to be customized or developed from the scratch. The simulations of wireless networks can be run as discrete event, hybrid or analytical, encompassing terrain, mobility and path-loss models. Due to the open interface external object files, libraries as well as other simulators can be integrated to the OPNET Modeler. Optional a System-in-the-Loop is available to interface simulations with live systems. Furthermore, the OPNET Modeler Wireless Suite provides grid computing support so that simulations can be executed in a distributed manner[11]. 1.3. TinyOS mote simulator: TOSSIM (TinyOS mote simulator) [12]–[15] is a discrete event simulator for TinyOS sensor networks that is part of the official TinyOS package. TOSSIM takes © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 16 Aruna Rai Vadde et.al / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue7 , 2014, pp.14-25 advantage of the component based architecture of TinyOS by integrating it transparently by providing a new hardware resource abstraction layer that simulates the TinyOS network stack at the bit level for normal PCs. Due to these approach low-level protocols up to top-level applications can be simulated with TOSSIM. TOSSIM has an external communication system so that transmitted packets can be monitored and even new packets can be injected to network. Furthermore, the configuration of the debug options is fine grained providing the desired debug output at runtime. TOSSIM offers three network connectivity models: simple connectivity, static connectivity and space connectivity. The running simulations can be visualized and controlled by the Java-based GUI TinyViz[16].

1.4. Mobility Framework: The Mobility Framework [22]–[24], developed in the Telecommunication Networks Group (TKN) at the Technical University of Berlin, provides only basic support for mobile and wireless networks. It includes some basic layers such as MAC layers (Aloha, CSMA) and network layers (flooding) as well as some basic mobility functionality and some basic application layer. MiXiM: MiXiM [15], [16] is a merger of several OMNeT++ frameworks to support mobile and wireless simulations. It uses the mobility support, the connection management, and the general structure from the Mobility Framework (MF); the radio propagation models from the CHannel SIMulator (ChSim); and the protocol library from the MAC simulator, the Positif framework [23], and the Mobility Framework.

1.5. Network Simulator: NS (the Network Simulator) [23], [24] is an object-oriented discrete event simulator targeting at networking research. NS-2 is written in C++ and OTcl, an object- oriented version of Tcl. A huge amount of contributed protocol source codes can be found on the website http://nsnam.isi.edu/nsnam/index.php/Contributed Code. among them there are also some for WSNs interesting wireless protocols such as different variations of 802.11, 802.16, IR- UWB, BlueTooth and 802.15.4. Despite the great number of contributing researchers the support for wireless sensor network specific protocols is rather low. As special wireless sensor network framework the Mannasim Framework [16] should be highlighted that provides sensor network specific protocols such as LEACH and Directed Diffusion. Also the extension NS2-MIUN [17] provides some wireless sensor network specific contributions with the focus on intrusion detection. SensorSim: SensorSim [18]–[14] is a simulation framework for modeling sensor networks that built up on NS-2. It provides additional features for modeling sensor networks such as sensor channel models, power models (battery and radio), lightweight protocol stacks for wireless micro-sensors, scenario generation and hybrid simulation.

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2. The proposed WSN simulation methodology The environment in which we build our simulation model was MATLAB. The name MATLAB stands for matrix laboratory. MATLAB, developed by Math Works Inc., is a software package for high performance numerical computation and visualization. The combination of analysis capabilities, flexibility, reliability, and powerful graphics makes MATLAB the premier software package for scientific researchers. MATLAB provides an interactive environment with hundreds of reliable and accurate built-in mathematical functions. These functions provide solutions to a broad range of mathematical including matrix algebra, complex arithmetic, linear systems, differential equations, signal processing, optimization, nonlinear systems, and many other types of scientific computations. The most important feature of MATLAB is its programming capability, which is very easy to learn and to use, and which allows user-developed functions. It also allows access to Fortran algorithms and C codes by means of external interfaces. There are several optional toolboxes written for special applications such as signal processing, control systems design, system identification, statistics, neural networks, fuzzy logic, symbolic computations, and others. MATLAB has been enhanced by the very powerful Simulink program[19]. Simulink is a software package for modeling, simulating, and analyzing dynamical systems. It supports linear and nonlinear systems, modeled in continuous time, sampled time, or a hybrid of the two. Systems can also be multi-rate, i.e., have different parts that are sampled or updated at different rates. For modeling, Simulink provides a graphical user interface (GUI) for building models as block diagrams, using click-and-drag mouse operations. With this interface, you can draw the models just as you would with pencil and paper (or as most textbooks depict them). Simulink includes a comprehensive block library of sinks, sources, linear and nonlinear components, and connectors. You can also customize and create your own blocks Models are hierarchical. This approach provides insight into how a model is organized and how its parts interact. After you define a model, you can simulate it, using a choice of integration methods, either from the Simulink menus or by entering commands in MATLAB's command window. The menus are particularly convenient for interactive work, while the command-line approach is very useful for running a batch of simulations (for example, if you are doing Monte Carlo simulations or want to sweep a parameter across a range of values). Using scopes and other display blocks, you can see the simulation results while the simulation is running. In addition, you can change parameters and immediately see what happens, for "what if" exploration. The simulation results can be put in the MATLAB workspace for post processing and visualization. And because MATLAB and Simulink are integrated, you can simulate, analyze, and © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 18 Aruna Rai Vadde et.al / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue7 , 2014, pp.14-25

revise your models in either environment at any point. [19].

2.1. Simulating a plain WSN in Simulink MATLAB In order to demonstrate the concepts of the suggested simulation methodology, a simple WSN model was built as shown in figure 2[16]. This network consisted of three sensors (slaves) sending their measured data samples to a master node. In this chapter, MATLAB Simulink communication block set was used to build a complete WSN system. Simulation procedure includes building the hardware architecture of the transmitting nodes, modeling both the communication channel and the receiving master node architecture. Bluetooth was chosen to undertake the physical layer communication with respect to different channel parameters (i.e., Signal to Noise ratio, Attenuation and Interference). The simulation model was examined using different topologies under various conditions and numerous results were collected. #Simple Example of generating the nodes in MATLAB:

BeconX=500;

BeconY=500; axes(handles.axes1); gca; hold on; hbecon=plot(BeconX,BeconY,'s') set(hbecon,'color','red','LineWidth',8);

Basic part of code is to randomly place the sensor nodes in the given space then connecting each two nodes if the distance between them less than or equal to the communication radius. Kindly check following Matlab code . clear; noOfNodes = 50; rand('state', 0); figure(1); clf; hold on; L = 1000; R = 200; % maximum range; netXloc = rand(1,noOfNodes)*L; netYloc = rand(1,noOfNodes)*L; for i = 1:noOfNodes plot(netXloc(i), netYloc(i), '.'); text(netXloc(i), netYloc(i), num2str(i)); for j = 1:noOfNodes distance = sqrt((netXloc(i) - netXloc(j))^2 + (netYloc(i) - netYloc(j))^2); if distance <= R matrix(i, j) = 1; % there is a link; © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 19 Aruna Rai Vadde et.al / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue7 , 2014, pp.14-25 line([netXloc(i) netXloc(j)], [netYloc(i) netYloc(j)], 'LineStyle', ':'); else matrix(i, j) = inf; end; end;

2.2. The architecture of the system could be explained as follows: 2.2.1 The transmitter: This system was based on Bluetooth technology that is considered as the backbone of transmission operation. Bluetooth is a short-range radio link technology that operates in the 2.4 GHz Industrial, Scientific, and Medical (ISM) band[16]. In this system we modulated the signal using Gaussian frequency shift keying (GFSK) over a radio channel with maximum capacity of 1 Mbps. The transmitter consists of the following blocks:

Sensor signal stage: It is represented by a sensor to sense the physical signals such as temperature, pressure…etc, then transducing them into an electrical signal. In addition, this stage includes the A/D convertor which converts the signal from Analog to Digital using 256 quantization level. Up-sampling to 64ksamples/s: Up-samples the input to a higher rate by inserting zeros between samples. Payload FEC encode: Encodes the data to enable error correction(an FEC encoder may include a binary convolutional encoder followed by a puncturing device). Bluetooth Clock: Each Bluetooth device has a free-running 28-bit Bluetooth clock. The clock ticks 3,200 times per second or once every 312.5 µsec, representing a clock rate of 3.2 KHz. Hop Sequence Generator: For devices to communicate with each other, they must transmit and receive on the same frequency at the same time. The hop sequence generator generates a sequence of hop frequencies in the range 0 to 78. It can generate either the connection state hop sequence, a random white sequence, or be fixed. Encoder and modulator: The 366 data bits are transmitted at 1 Mbps and modulated using Gaussian frequency shift keying (GFSK). GFSK effectively transmits +150 kHz signal relative to the carrier for a 1bit, and a 150 kHz signal for a 0 bit. The carrier signal isgenerated in the Simulink model by a baseband MFSK block set to 79 symbols and a separation of 1MHz. If a hop frequency value 0 is input, a -39MHz complex sinusoid is generated. If a 1 is entered, a -38 MHz complex sinusoid is generated and so on. In the model, the hop sequences are generated by a simple random number generator, not using the actual method specified in the standard. The transmitter is turned off after 366 bits using a Gain block to multiply the frame with a mask of 36600 ones and 26500 zeros.

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2.2.2. The medium which consists of the following blocks

AWGN Channel: The AWGN Channel block adds white Gaussian noise to a real or complex input signal. When the input signal is real, this block adds real Gaussian noise and produces a real output signal. When the input signal is complex, this block adds complex Gaussian noise and produces a complex output signal. Path Loss: This block reduces the amplitude of the input signal by an amount specified.The loss can be specified directly using the “Decibels” mode, or indirectly using the“Distance and Frequency” mode. The reciprocal of the loss is applied as a gain, e.g., a lossof +20 dB, which reduces the signal by a factor of 10 corresponds to a gain value of 0.1. 802.11b interferer: This block adds signals that have the same frequency of the data signal to make interference between the data signal and other signals( i.e. a Wireless Local Area Network (WLAN) transmission). Multiport Switch: In order to simulate the multiple access and multiplexing functions of the channel, this block was used. It chooses between a number of inputs. The first inputis called the control input, while the rest of the inputs are called data inputs. The value of the control input determines which data input is passed through to the output port.

3. The receiver consists of the following blocks: Hop Sequence Generator: same as said prior. Demodulation and interpreting: This piece is utilized to concentrate the first data bearing sign from a regulated transporter wave, and to recoup the data fights in it. zero-Order Hold: This square tests and holds its data for the determined test period. The square acknowledges one information and creates one yield, both of which can be scalar or vector. In the event that the info is a vector, all components of the vector are held for the same example period. un-cradle: This piece un-cushions a Mi-by-N casing based info into a 1-by-N test based yield. That is, inputs are un-supported line insightful so that every framework column turns into a free time- examine in the yield. The rate at which the square gets inputs is by and large short of what the rate at which the piece produces yields. down-testing to 8ksamples/s: This square down-examples the data to a lower rate by erasing the rehashing specimens. scope RX: It was utilized to show the got flag and contrast it and the first sign to find the framework conduct. As known, a resentful can includes up to seven slaves and one master. In this example three signals were sent from three sensors (slaves) to the receiving component (master) representing one © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 21 Aruna Rai Vadde et.al / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue7 , 2014, pp.14-25 piconet , the information obtained by the sensors are used to estimate the Bluetooth performance as well as to study the media effect. Noise and interference are added to the signals in order to simulate the channel effect and measure Bit Error Rate (BER) and Frame Error Rate (FER). The following figures show the system performance under different working conditions.

Figure 2. Signals sent from the three sensors

(a)SNR=20dB (b) SNR = 12dB

(a) SNR & BER (b) SNR&FER

Figure 3. Relationship between SNR & (BER, FER) © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 22 Aruna Rai Vadde et.al / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue7 , 2014, pp.14-25

(a) Average Rate=6 (b) Average Rate=12

(c) Average Rate=25 (d) Average Rate=50 (e)Average Rate=100 Figure 4. Received signals with different rate of interference

(a) SNR=15dB, Average Rate=6 (b) SNR=12dB, Average Rate=25

Figure 5. Received signals with different rate of interference & different SNR

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(a) Interference & BER (b) Interference & FER

Figure 6. Relationship between interference & (BER,FER)

4. Conclusions In this section, another reenactment procedure of remote sensor systems (WSN) was displayed. MATLAB/Simulink was utilized as the apparatus to assemble the reproduction environment. The quality of this reproduction technique falls in the capacity to study the impact of distinctive physical layer parameters (channel commotion and impedance, Signal to clamor degree… and so forth.) on the framework conduct. The other advantage of this strategy will be its adaptability in building the end hubs and sensors. This reenactment system could be utilized to manufacture diverse WSN sorts and opens the avenues to utilize the MATLAB as a part of this new file.

5. References

[1] Akyildiz, IF, Sankarasubramaniam, F, Cayirci, E, “A Survey on Sensor Networks”, IEEE Commun Mag 2002; 102-114. [2] Callaway, E., Gorday, P. , Hester, L., ”Home Networking with IEEE 802.15.4: A Developing Standard for Low-Rate Wireless Personal Area Networks”, IEEE Commun Mag 2002; 69-77. [3] Computer Science Division at UC Berkeley. [Online]. Available: http://www.cs.berkeley.edu/_pal/research/tossim.html, 2012 [4] Computer Science Division at UC Berkeley. Visualisation of a TOSSIM simulation with TinyViz. [Online]. Available: http://www.tinyos.net/tinyos-1.x/doc/tutorial/imgs/ tinyviz-screenshot1.gif, 2012. [5] Drytkiewicz, W., Sroka, S., Handziski, V., Koepke, A., Karl, H., “A mobility framework for omnet++,”in 3rd International OMNeT++ Workshop, 2003. [6] Gupta, G, Mukhopadhyay, SC, Sutherland, M., Demidenko, S., “Wireless Sensor Network for Selective Activity Monitoring in a home for the Elderly”, Proceedings of 2007 IEEE IMTC conference.

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Poland, Warsaw 2007; 1(3): 1-6. [7] Jiang, H., Wang, P. ,Liu, H., “Research on OPNET simulation model in wireless sensor networks,” Jisuanji Gongcheng/ Computer Engineering, vol. 33, no. 4, 2007. [8] Jurˇc´ık, P., Koubâa,A., “The IEEE 802.15. 4 OPNET Simulation Model: Reference Guide v2. 0,” 2007 [9] Lewis, F “Wireless Sensors Networks, Smart Environments: Technologies, Protocols, and Applications’, ed. Cook DJ, Das SK, John Wiley, New York, 2004; 1-18. [10] Levis, P., Lee, N.,Welsh, M., Culler, M., “TOSSIM: Accurate and scalable simulation of entire TinyOS applications,” in Proceedings of the 1st international conference on Embedded networked sensor systems. ACM New York, NY, USA, 2003, pp. 126–137 [11] Levis, P., Lee, N., “Tossim: A simulator for tinyos networks,” UC Berkeley, September,2003. [12] Löbbers, M., Willkomm, D., Köpke, A., Karl, H., “Framework for Simulation of Mobility in OMNeT++(Mobility Framework),” 2004. [13] MiXiM developers. MiXiM project. [Online]. Available: http://mixim.sourceforge.net/,2012. [14] Mobility Framework for OMNeT++ Community. [Online]. Available: http://mobility- fw.sourceforge.net, 2012. [15] Notani, S., “Performance Simulation of Multihop Routing Algorithms for Ad-Hoc Wireless Sensor Networks Using TOSSIM,” in Advanced Communication Technology,2008. ICACT 2008. 10th International Conference on, vol. 1, 2008. [16] OMNeT++ Community. OMNeT++ 4.0 IDE.[Online]. Available: http://omnetpp.org/doc/omnetpp40/ide-overview/pictures/img1.png, 2012. [17] OMNeT++ Community. (2010, May) OMNeT++. [Online]. Available: http://www.omnetpp.org/ [18] OPNET Technologies, Inc. [Online]. Available: http://www.opnet.com/support/des model library/images/MANET scrnsht.jpg, 2012. [19] OPNET Technologies, Inc. [Online]. Available: http://www.opnet.com/,2012. [20] QualNet. [Online]. Available: http://www.scalable-networks.com/products/qualnet/,2012.S. Technologies, “Qualnet v. 3.9. 5 user’s guide,” 2006. [21] Rabaey, J, Ammer, M, da Silva, J.L., D. Patel, and S. Roundy, “Picoradio supports ad hoc ultralow power wireless networking,” Computer, vol. 33, no. 7, pp. 42–48, July2000. [22] Varga, A., et al., “The OMNeT++ discrete event simulation system,” in Proceedings of the European Simulation Multiconference (ESM’2001), 2001, pp. 319–324.. [23] Varga, A., “OMNeT++ Discrete event simulation system. User Manual,” Technical University of Budapest, Dept. of Telecommunications, 2006. [24] Varga, A., Hornig, R., “An overview of the OMNeT++ simulation environment,” in Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops table of contents. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering) ICST, Brussels, Belgium, Belgium, 2008.

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AUTHOR’S BRIEF BIOGRAPHY:

Mr. Aruna Rai vadde, Presently Lecturer in Department of Electrical and Computer Engineering, College of Engineering and Technology, Wollega University , Ethiopia since 6 years. Previously worked as Software engineer at Singapore for 4 years.

Mr.Ginbar Ensermu, Working as a Lecturer in the department of Electrical & Computer Engineering, Wollega University, Ethiopia. I completed M.Sc in Electrical Power Engineering in Adama Science and Technology University, Ethiopia

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 26 Uliana Paskaleva et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.27-31 Calibration and Checking of Measurement Systems

Uliana Paskaleva, Ph.D

South-West University "Neofit Rilski", Technical College, 2700 Blagoegvrad, str. “Ivan Mihailov” 56 B, Bulgaria, email: [email protected]

Abstract In this research paper are presented scientifically valid method for defining of intervals for validation of measurement means and focuses on the problems in the regular calibration (checking) of measurement systems. It provides a methodology that allows to solve the optimization problem of the frequency of metrological checks / calibrations. Calculations were carried out on the basis of experimental studies and based on metrological refusals checked measuring instruments. The results demonstrate economic impact, provided that the scientifically based methodology applied in accredited laboratories, companies and others.

Keywords: measurement systems, quality control, metrology, calibration.

1. INTRODUCTION: The complexity of the modern technical systems and technologies, characterizing by availability of a large number of sources of instability about indexes of system and technologies functioning, stipulated by risen requirements versus there quality control. All of it concerns entirely the measurement systems, too, where the ins IMS as a rule are created on the base of the means of computing techniques and during the measurement process use a-priory and current information, but also and knowledge that is stored in the system. In the process of metrological and measurement technique development a great positive experience for determination of the error characteristics of the measurement results is obtained. In such a time there are know an essential number of methods for optimal inter examinational intervals of classical measuring tools [1,4,6]. In the process of metrological and measurement technique development a great positive experience for determination of the error characteristics of the measurement results is obtained. The existing methods do not directly be used for metrological assurance of IMS (build on modern informational technologies). It is necessary to solve the tasks concerning estimation of the characteristics of the measurement results` errors for non fixed early unlimited sets measurement situations (including on the base of the data and knowledge organization, saved in the system) [2, 5]. In the last 10-15 years an increasing attention about the approaches for optimization of the Complex Objects (CO), oriented to robust methods of design, functioning of CO, as well as creation and supporting of technological processes with assured minimal exchange of controlled indexes is observed. For example, the Japan’s scientist Taguchi, with its quality control system astonishes the word with its exclusive high effectivity [5]. The procedures of the robust modes of operation used in this system account the impact of the uncontrolled technological factors and the exploitation environment of CO. They are based on the use of sufficient simple methods of design experiment (DE) and special criteria for optimization of relationship” signal-noise” and technologies. There are knows different robust methods [1, 2, 4, 6], for optimization of quality control systems.

2. MATERIALS AND METHODS: 2.1. METROLOGICAL SUPPORT AND PROBLEMS The breach of serviceability of the devices is called refusal and it is one of the profound notion in the reliability theory. It can be bear in mind that about the complex measurement tools, as Intelligent Measurement Instrumentation (IMS) they are possible other states, because not every refuse leads to inertly serviceability breaking, but it is possible only decreasing of functioning effectivity. The refusal © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 27 Uliana Paskaleva et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.27-31 arises due to parameters`change of the devices or their` s components as result of internal physical and chemical processes in the conditions of external impacts. The random character of these processes stipulated a random character of the refusal arising. There are known different classifications of the refuses. About the intelligent instrumentation it is of interest, but may be the more expedient the classification on functional and parametric refuses [1,6,7]. The functional refuses lead to breaking of the normal functioning. The parametric refuses are connected mainly with change of one or more metrological characteristics- main error, sensitivity, input and output impedance. They are arised mainly as hidden, stabile refuses provocated by permanent changes of the parameters. The parametric refuses are of vital importance in measurement practice because theirs availability is hidden and leads to receiving of uncorrect information that supposes taking of uncorrect decisions, the quality making worse or scrap in the production, but in some plants to economical and social results. The hidden refuses can be finded out only by checking [3, 6, 8, 9]. The open refuses can be finded out in the exploitation process, but it leads to the inference, that the classical prediction mode for hidden refuses is a check. It is evidence that while changing interchecking intervals the percent of functioning defects of the measurement tools can be changed. Still it is not any scientific argumented methodology for determination of inter checking intervals. This question can be solved by using advanced means, that will be one of the concrete tasks or present article. Usually the state and firm metrological services define one and the same inter checking interval for a given class or king of measurement tools. It is worth to remark, that in the set of measurement tools for which a common interchecking interval is stated, can have as high stable (high fidelity), as and low stable (low fidelity) measurement tools. A part, the state of all of them one and the same requirements are imposed. The determination of unargumented small interchecking interval for high stable tools leads to redundant expenses from checks, but the determination of unargumented large intervals for the low stables tools leads to an increasing of the expenses, connected with a using of no good tools. Hence, it is evident the necessary of differentiated approach for determination of interchecking intervals. The sense of such a differentiated approach consists of setting of group inter checking intervals, i.e. for groups of tools with a common stability. In such a way it is possible to check the tools by different interchecking intervals. For grouping it is necessary to organize acquisition and storage of information about the check results for every concrete tool. Due to the large number of tools it is not always possible even while a computing technique is used. That is while the determination of group interchecking intervals is expediently for standard tools with high precision, and with high metrological characteristics. A partial case of group ICI (inter checking intervals) are the individual ICI, i.e. while they are defined for every tool individually [1,8]. So, ISI can be broken down in common, group and individual. Last but not least is the question for the choice of criterion for definition of ICI – this criterion can correctly reflects the main goal of the system for assurance of the unity of the exploited measurement instrumentation. In the literature, several known criteria - economic, technical, mixed (combined), and others [1,2,4,6]. The economical criterion is based on the reduction of common economical expenses that define 2 components - expenses from exploitation of unworkable tool and expenses from servicing of tools. ISI, for which the common expenses are minimal, is called optimal.

2.2. Intelligent Measurement Systems

With the move-in of controllers the approach to constructing measurement instruments and systems has radically changed – the controller becomes an integral part. This trend is found in the creation of a new class of devices – Intelligent Measurement Systems (IMS). The program management significantly reduces their cost and increases the accuracy of measurement (automatic compensation of systematic errors, automatic reset, self-testing, auto-calibration, reduction of random errors by multiple repeated measurements, etc [7]. Example: Saving time by processing and analyzing your measurements in real-time, instead of offline - as in the figure below [7].

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 28 Uliana Paskaleva et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.27-31

Fig. 1.Processing and analyzing your measurements in real-time.

However, the problems described above, there are also here - especially when it comes to mistakes that bring primary transducers connected to the smart metering systems. 2.3. Methodology for determining the inspection intervals based on the statistics of failures of measurement tools: In exponential distribution of uptime is valid [1]: -t (1) Pte()= T, where: t is the time when, at which the probability of trouble-free operation; T - time for reliable operation. 1. The statistical probability of reliable operation is defined [1]:

N-n(t) n(t) (2) P()t = =1- = P , N N M1 where: N is number of measurement systems to be tested; n(t)- number of measuring systems with failure for time (t) . 2. The size of the new range of verification acceptable probability of trouble-free operation is determined by the formula:

ln Pperm. (3) tt21= , ln PM 1 3. For information and electronic measuring instruments permissible probability of trouble-free operation is considered 0.85 to 0.95 or more, depending on the purpose [6].

4. Take the number n2 of refusal on metrological failure period t 2 . 5. From (2) determine P statistical probability of trouble-free operation. If the value of the statistical M 2 probability of trouble-free operation P is no different than the permissible probability of trouble-free M 2

operation Pperm. , the size of the next inspection interval shall be taken as t 2 . Otherwise, the next inspection interval is determined by the formula:

ln Pperm. (4) tt32= ln PM 1 In the absence of sufficient experimental data can be made part of the calculations, for example, at least for the first interval - ICI (inter checking intervals). In laboratory specialists from BIM (Bulgarian Institute of Metrology ) - Blagoevgrad committed these metrological checks electrocardiographs type Cardiofax - 9000 (produced in NIHON KOHDEN CORPORATION Japan): © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 29 Uliana Paskaleva et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.27-31

Table 1

Number of Number of Number of electrocardiograp metrological visible hs Cardiofax – refuses refusals 9000 - no refuses 59 (2009 year) 0 0

60 (2010 year) 0 1

61 (2011 year) 1 1

Calculated on a shortened version of the new methodology of the inspection intervals electrocardiograph are 92 months.

3. RESULTS AND DISCUSSION: Calculated on a shortened version of the new methodology of the inspection intervals electrocardiograph are 92 months. Actually, now electrocardiograph checking in regulations every two years. Actually not apply scientifically sound methodologies for inspection intervals, which is not cost effective.

4. CONCLUSION: Presented a scientifically sound methodology for calculating intervals of inspection / calibration of electronic measuring systems. It is compiled from the metrological failures, and based on the statistics of measurement tools with refusals. Experimental study is done on the basis of this applied research methodology. The conclusions are made in relation to future economic performance, provided that the institutions take real steps towards the introduction of such scientifically justified methods for the determination of the calibration interval in metrological practice.

5. ACKNOWLEDGEMENTS: The author would like to thank the team of IJMSET for the opportunity for possible publication.

6. REFERENCES: [1]. Bogdanov, G. P. ,Kuznecov, B. P., „Metrologicheskoe obespechenie i эksploataciia izmeritelьnoj tehniki”, Moskva, RADIO I SVIaZЬ, 1990. [2]. Chingova, R., “Izsledvane na trieneto pri niakoi pamuchni tykani”, South-West University „N. Rilsky”, Blagoevgrad, ISBN 978-954-680-913-1, 2013. [3]. Kalchev I. “Control and self diagnosis in m p-based measurement systems”, Second Intern. Symp. on Measurement Technology and Intelligent Instruments, Chongqing-Wuhan, China,1993. [4]. Patev Hr., Interdisciplinary connections and integrative approach to the educational content of the engineering and economical foundation of technical disciplines and modules: Introduction to industrial production; Metrology and measuring equipment; Technical documentation, engineering design and graphics; Materials and general technology; Monograph Part I, Publishing House SWU "N. Rilski"- Blagoevgrad, 2011, ISBN 978-954-680-751-9. [5]. Paskalevа Ul., “MEASUREMENT AND AUTOMATOIN”, Jurnal Economics &Manegement”, Faculty of Economics South-West University „N. Rilsky”, Blagoevgrad, 2010/2; pp 62-67, ISSN 1312-594Х. [6]. Radaev, N.N. „Theoreticheskoe raspredelenie narabotki na otkaz pri extremalnah vnesnih vozdeistviah, ” Izmeritelnaia tehnica”, 10/2000, str.3-6, Moskva, Izdatelstvo standartov. [7] http://www.ni.com [8]. http://www.sasm.government.bg/ [9]. http://odinmetrology.com/calibration_other.html

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 30 Uliana Paskaleva et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.27-31

AUTHOR’S BRIEF BIOGRAPHY:

Uliana Paskaleva is assistant professor, (PhD in Electrical Engineering) in South-West University, Technical College, Department "Electronic and Communication Engineering”, Bulgaria, Blagoevgrad. Lecturer of courses "Electrical Measurements", "Measurement in Electronics", "Measurements in Communications”, "Design and reliability of electronic equipment". She graduated in Technical University, Sofia - Master of Electrical Engineering. Specialisation: “Metrology - Electrical Measurements” - Technical University, Sofia in 1983. She defended a doctor`s degree in 2008. Her papers more than 35 were published. In South-West University, Technical College, she is from 1990. Her hobby is poetry and nature, she has published four books of poetry.

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 31 A. H. Srinivasa et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.32-40

Unsteady MHD Laminar Boundary Layer Flow and Heat Transfer due to an Impulsively Stretching Surface

A.H.Srinivasa 1 A.T.Eswara 2 Department of Mathematics Department of Mathematics Maharaja Institute of Technology, PES College of Engineering, Mysore - 571348, India. Mandya - 571401, India. [email protected] [email protected]

Abstract The unsteady, incompressible boundary layer flow caused by an impulsively stretching surface under the influence of a transverse magnetic field is investigated. The partial differential equations governing the laminar flow, under boundary-layer approximations, are non-dimensionalised using similarity transformations and then solved numerically using an efficient, implicit finite-difference scheme known as Keller-box method. The numerical solutions are obtained for all dimensionless time from initial unsteady state flow to final steady-state, uniformly valid in the whole spatial region. The numerical results for the surface shear stress and heat transfer parameter are compared with those of the analytical approach results, and they are found to be in good agreement. It is observed that there is a smooth transition from the small time solution to the large time solution. The magnetic field significantly affects the flow field and skin friction as well as heat transfer coefficients. Indeed, skin friction and heat transfer coefficient found to decrease rapidly, initially, in small time interval before attaining a steady-state for large time. Also, the heat transfer coefficient is strongly affected by viscous dissipation. The thickness of thermal boundary layer decreases with increase of viscous dissipation parameter.

Keywords: Unsteady flow, Laminar boundary layer, Impulsive – motion, Skin friction, Heat transfer, Magnetic field, Stretching sheet, Viscous dissipation.

1. INTRODUCTION:

The description of flow and heat transfer in the boundary layer induced by a stretching surface has many important technological applications such as the cooling of an infinite metallic plate in a cooling bath, the aerodynamic extrusion of plastic sheets, the cooling and/or drying of paper and textiles, and glass fiber production. The physical situation was recognized as a backward boundary layer problem by Sakiadis [1], who investigated the flow behavior on continuous moving surfaces which are substantially different from those of boundary layer flows on stationary surfaces. The thermal behavior of the problem was studied by Erickson et al.[2] using integral methods and experimentally verified by Tsou et al.[3]. Subsequently, several aspects of the above boundary layer problem of moving or stretching surface were considered many researchers [4-8]. All the above investigators restricted their analysis to flow and heat transfer in the absence of magnetic field. In recent years, the study of the magnetohydrodynamic (MHD) boundary layer flow of a fluid over a stretching surface has become more important industrially and is considered as a fundamental problem in fluid dynamics. Indeed, MHD laminar boundary layer behavior over a stretching surface is a significant type of flow having wide applications in metallurgy and chemical engineering. Numerous investigations have been conducted on the MHD flows and heat transfer. MHD was initially known in the field of astrophysics and geophysics and later becomes very important in engineering and industrial process. For example, MHD can be found in MHD accelerator and generators, electric transformers, power generators, refrigeration coils, pumps, meters, bearing, petroleum production and metallurgical processes which involve cooling of continuous strips or filaments. In metallurgical processes, the rates of cooling and stretching of the strips can be controlled © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future”

32 A. H. Srinivasa et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.32-40 by drawing the strips in an electrically conducting fluid subject to a magnetic field, so that a final product of desired characteristics can be achieved. In view of these applications, Pavlov [9] investigated the flow of an electrically conducting fluid caused solely by the stretching of an elastic sheet in the presence of a uniform magnetic field. Chakrabarti and Gupta [10] considered the flow and heat transfer of electrically conducting fluid past a porous stretching sheet and presented analytical solution for the flow and the numerical solution for the heat transform problem. The flow and (or) heat transfer over a moving surface in the presence of a magnetic field have been investigated by Andersson[11], Vajravelu and Hadjinicolaou [12], Pop and Na [13] and Kumari and Nath [14]. The boundary layer flow of Newtonian fluid caused by a stretching sheet according to a power law velocity in the presence of a transverse magnetic field, is investigated by Chiam [15]. The studies reported above deal with steady flows. However, the flow problem will become unsteady due to impulsive change in the surface velocity of a moving stretching surface. The unsteady flow on a stretching surface is an important problem, since it is not always possible to maintain steady-state conditions. Pop and Na [16] and Nazar et al.[17] have considered the time-dependent boundary layer flow due to an impulsively stretching surface. However, Elbashbeshy and Bazid [18] investigated the unsteady flow and heat transfer over a stretching sheet in a laminar boundary-layer. Further, Sharidan et al.[19] obtained the similar solutions for the unsteady boundary layer and heat transfer due to a stretching surface. Moreover, Ishak et al. [20] extended the dimension of the problem of heat transfer due to stretching sheet to unsteady laminar boundary layer flow and heat transfer due to a stretching vertical surface. Awang Kechil and Hashim [21] presented series solutions for unsteady boundary- layer flows due to impulsively stretched plate, in the absence of magnetic field. Recently, Srinivasa and Eswara [22] have investigated unsteady momentum transfer in the laminar boundary layer flow due to an impulsive stretching surface in the presence of a transverse magnetic field. In several engineering applications of contemporary interest, unsteadiness has become an integral part of boundary-layer flow and heat transfer problems. To be specific, when a flat surface is impulsively stretched in an ambient quiscent fluid, the inviscid (potential) flow is developed almost immediately, but the viscous flow within the boundary layer develops slowly and it becomes a fully developed flow after some time. The development of the boundary layer takes place in two stages. For small time, the flow is dominated by the viscous forces and the convective acceleration plays only a minor role in the flow development. On the other hand, for large time, the flow is dominated by the viscous forces and the convective acceleration, and the unsteady acceleration plays a minor role in the flow development. For small time, the flow is unsteady and for large time, it becomes steady. For the intermediate region, there is a smooth transition from unsteady to steady flow which takes place without a singularity or flow instability. The objective of this paper is to analyse the unsteady, MHD laminar boundary layer flow and heat transfer development caused by an impulsively stretching surface. The non-linear partial differential equations governing the problem are reduced to a system of non-linear ordinary differential equations by applying a suitable similarity transformation. These non-linear ordinary differential equations are solved numerically by the Keller-box [23] method for different values of the pertinent parameters. An analytical solutions is also obtained for initial unsteady state as well as final steady-state regimes.

2. MATHEMATICAL FORMULATION:

Let us consider unsteady, laminar incompressible two-dimensional boundary layer flow of a viscous, electrically conducting fluid past a semi-infinite stretching surface conciding with y = 0, and the flow being confined to y > 0, where y is the co-ordinate measured normal to the stretching surface. Prior to the time t = 0, the surface is at rest in an unbounded quiescent fluid with uniform temperature T¥. At time t ³ 0, the surface is suddenly stretched with velocity U = ax (a is positive constant) and x is coordinate measured along the stretching surface, keeping the origin fixed (See Fig. 1). The impulsive change in the surface velocity gives rise to unsteadiness in the flow field. The stretching surface is maintained at constant temperature Tw and is assumed to be greater than ambient temperature T¥.

33 A. H. Srinivasa et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.32-40

Fig. 1. Physical Model and coordinate system

A transverse magnetic field of uniform strength B(x) is applied in y-direction normal to the stretching 0 surface and it is assumed that the magnetic Reynolds number is small so that induced magnetic field is neglected, in comparison to the applied magnetic field. Further, since there is no external electric field, the electric field due to polarization of charges is negligible. The effect of viscous dissipation is included in the analysis. Under the above assumption, the boundary-layer equations based on conservation of mass, momentum and energy, governing the forced convection flow are [22]: ¶u ¶v + = 0 (1) ¶x ¶y 2 ¶u ¶u ¶u ¶ 2u s B (x) + u + v =n - 0 u (2) ¶t ¶x ¶y ¶y 2 r

2 2 2 ¶T ¶T ¶T ¶ T m æ ¶u ö s B (x) 2 + u + v = a + ç ÷ + u (3) ¶t ¶x ¶y 2 rc è ¶y ø rc ¶y p p The initial and boundary conditions are given by t < 0 : u ( x, y, t ) = v( x, y, t) = 0, T ( x, y, t) = T for all x, y ¥ t ³ 0 : u ( x, y,t ) = U = ax (a > 0), v( x, y,t ) = 0, T (x, y,t ) =T at y = 0 ü (4) w ý u ( x, y,t ) = 0, T (x, y,t ) = T ¥ as y ® ¥ þ Here u and v are velocity components along x and y - directions, respectively; s, r and n denote, respectively, electrical conductivity, density and kinematic viscosity; U is surface velocity and a is a

positive constant, cp is specific heat, m is dynamic viscosity, r is fluid density, a is thermal diffusivity. The subscripts e, w, and ¥ denote conditions at the edge of the boundary-layer, on the wall and in the free stream, respectively. Following Srinivasa and Eswara [22], we define new similarity variables given by h = (a n )1 2 x -1 2 y, x = 1 - exp( -t*), t* = at y ( x, y , t ) = (an )1 2 x 1 2 xf (h ,x )

1 2 n u =axf ¢(h,x), v =-()anx1 2 f (h,x), Pr = a T = T + T - T G(h,x ) ¥ ( w ¥ ) ¶f sB2(x) U2 f ¢ = , M = , Ec= (5) ¶h ar (Tw -T¥) cP where y is stream function which is defined as u = ¶y ¶y and v = -¶y ¶x. It is worth mentioning that the time scale x conveniently chosen as above, permits the region of time integration 0 £ x < ¥ may

34 A. H. Srinivasa et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.32-40 become finite viz., 0 £ x £ 1. Using the above transformations in Equations (1) - (3) we find that continuity equation (1) is identically satisfied, and equations (2) and (3) reduced respectively, to

2 2 ¶3 f 1 ¶ 2 f é æ ¶ 2 f ö æ ¶f ö ¶f ù ¶ f ç ÷ ç ÷ æ ö (6) + (1- x )h +x ê f - ç ÷ - Mç ÷ú = x(1-x ) 3 2 2 ç 2 ÷ ¶h ¶h ¶h¶x ¶h ¶h ëê è ¶h ø è ø è øûú 1 ¶ 2G ¶G ¶G ¶G + 2 -1h (1 - x ) + xf + Ec[f ¢¢ 2 + Mxf ¢ 2 ]= x (1 - x ) (7) Pr ¶h 2 ¶h ¶h ¶x The transformed boundary conditions (4) become f (0, x ) = f ¢(0, x ) = 1. f ¢(¥ , x ) = 0 ü ý (8) G (0, x ) = 1 G (¥ , x ) = 0 þ Here h pseudo similarity variable; x is dimensionless time; t* is the dimensionless time; f is the dimensionless stream function, f ¢ is the dimensionless velocity; G is dimensionless temperature, Pr is the Prandtl number, Ec is the Eckert number and M is the non dimensionless magnetic parameter. The subscript x denotes partial derivative with respect to x and prime (‘) denotes derivatives with respect toh. The physical quantities of engineering interest are the skin friction and heat transfer coefficients given by 1 2t w 2 2 (9) C f (Rex ) = - = - f ¢¢(0,x) rU 2 x

where the wall shear stress tw is given by æ ¶u ö (10) t w = mç ÷ è ¶y ø y =0 and æ ¶T ö xç ÷ 1 - è ¶y ø y=0 1 2 (11) Nu()Re x = - = - G¢(0,x) Tw -T¥ x 2 where Rex = (ax n) is the local Reynolds number.

3. ANALYTICAL SOLUTION:

Further, we obtain two particular cases of this problem under consideration. (i) Initial unsteady-state flow (t* = 0): For the early unsteady flow regime 0 < t << 1, we have x = 0, and equations (6) and (7) becomes ordinary differential equation viz., (assuming Ec = 0) ¶¶32ffæöh +=ç÷ 0 (12) ¶¶hh32èø2

1 ¶ 2G æh ö¶G + ç ÷ = 0 (13) Pr ¶h 2 è 2 ø ¶h assuming Ec = 0, in Eqn.(7) along with corresponding boundary conditions (8) become

f (0,0) = f ¢(0,0) = 1. f ¢(¥,0) = 0 .G (0,0) = 1 G (¥,0) = 0 (14)

Here f stands for f (h, z) @ f(h, 0) º f(h) and the prime denote differentiation with respect to h. The above equations (12) - (13) with boundary conditions (14) admit exact solutions which are given by

35 A. H. Srinivasa et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.32-40 f ¢ = erfc (h / 2) 2 é æ h 2 öùü f (h ,0) = herfc (h / 2) + 1 - exp ç ÷ ê ç ÷úï (15) p ë è 4 øû æ h Pr ö ý ç ÷ G(h ,0) = erfc ç ÷ ï è 2 ø þï 2 +¥ where erfc (h ) = ò exp( - z 2 )dz is the complementary error function p h Hence 1 Pr f ¢¢(0) = , G¢(0) = - (16) p p (ii). Final steady state flow (t* ®+¥) For this case, x = 1 and equations (6) and (7) becomes ordinary differential equation viz., 2 ¶3 fæö¶¶¶2 fffæö æö +fM --=0 (17) ç÷2 ç÷ ç÷ ¶h3 èø¶¶¶hhhèø èø 1 ¶ 2G ¶G + f + Ec[f ¢¢ 2 + Mf ¢ 2 ] = 0 (18) Pr ¶h 2 ¶h with boundary conditions (8) become

f ( 0 ,1) = f ¢( 0 ,1) = 1 . f ¢( ¥ ,1) = 0 ü ý (19) G ( 0 ,1) = 1 G ( ¥ ,1) = 0 þ By assuming Ec = 0 and Pr = 1.0, we can obtain the exact solution of equations (18) and (19) as

f (h,1) = b -1[1 - exp(-bh )] (20) where, b = (1 + M ) , and G (h ,1) = e(e - 1) -1[1 - exp( -e -h )] (21)

4. NUMERICAL METHOD: The system of nonlinear partial differential equations (6) and (7) subject to boundary conditions (8) is solved numerically using an implicit finite-difference scheme known as Keller-box method as described in Cebeci and Bradshaw [23]. This method is unconditionally stable and has a second order accuracy with arbitrary spacing. The method has the following four main steps: · Reduce (6) and (7) to a system of first order equations; · Write the difference equations using central differences; · Linearize the resulting algebraic equations by Newton’s method and write them in matrix - vector form; · Solve the linear system by block-tridiagonal-elimination technique. To conserve the space, the details of the entire solution procedure of Keller-box method are not presented here. Numerical computations were carried out with the step size Dh in h-direction and the edge of the boundary layer h∞ has been adjusted to maintain the necessary accuracy. The values of Dh between 0.001 to 0.1 were used so that numerical solutions obtained are independent of Dh chosen, at least up to four decimal places. However, a uniform grid Dh = 0.01 was found to be satisfactory for a convergence criterion of 10-5 which gives accuracy to four decimal places.

5. RESULTS AND DISCUSSION: In order to validate the accuracy of our method, the numerical values of f¢¢(0,)x for the range0 £ x £ 1 obtained in this study, in the absence of magnetic field (M = 0), have been compared in Table 1, with those of Awang Kechil and Hashim [21] and with those of Srinivasa and Eswara [22] when M = 0.5. Our numerical results are in good agreement with those of [21, 22]. © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future”

36 A. H. Srinivasa et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.32-40 Table 1. Comparison of f ¢¢(0,)x with those of Awang Kechil and Hashim [21] and Srinivasa and Eswara[22]when M = 0.0 M = 0.0 M = 0.5 x Present Awang Kechil Present Srinivasa Results and Hashim [22] Results and Eswara[23] 0.0 -0.5643740 -0.5643740 -0.564512 -0.564512 0.1 -0.6106120 -0.6150550 -0.637973 -0.637972 0.3 -0.7115610 -0.7115696 -0.779324 -0.779322 0.5 -0.8004117 -0.8018198 -0.913765 -0.913763 0.7 -0.8873160 -0.8856581 -1.041896 -1.041894 0.8 -0.9200550 -0.9252701 -1.103797 -1.103793 0.9 -0.9623398 -0.9633761 -1.164412 -1.164412 1.0 -1.0000000 -1.0000000 -1.223941 -1.223941 Further, we have compared our analytical solutions (exact solutions) of surface shear stress [ f ¢¢(0,)x ] and [G¢(0,x)] for the steady state flow (ξ =1.0), in Table 2, in the presence of magnetic field M (0 £ M £ 1). It is clear from the Table 2 that numerical results obtained by the Keller-box method are almost identical with those of exact solutions. Table 2. Comparison of surface shear stress with exact solution (Analytical solution) when Pr = 1.0) ξ = 1.0 M Present Results Exact solution 0.0 -1.000000 -1.000000 0.2 -1.095881 -1.095440 0.4 -1.183360 -1.183215 0.5 -1.224865 -1.224740 0.6 -1.265045 -1.264911 0.8 -1.341854 -1.341640 1.0 -1.414519 -1.414213

1/2 The effect of magnetic field parameter (M) on the skin friction coefficient [Cf(ReL) ] and heat 1/2 transfer coefficient[Nu(ReL) ] is shown in Fig 2. It is found in these figures that, when x = 0 (i.e., at t*= 0, at the start of impulsive motion), the velocity and temperature is independent of M, while the 1/2 effect of M becomes more important as x increases. For a fixed x (x > 0), Cf(ReL) increases and 1/2 Nu(ReL) decreases with the increase of magnetic parameter M and the effect of M becomes most significant at x = 1.0 (i.e., as t* ®∞) when the steady state is reached. The percentage of decrease in skin friction coefficient is 70.67 % and increase in heat transfer coefficient is 1.83% near x = 0.5 in the range of M (0 £ M £ 1). Further, there is a smooth transition from the small-time solution (unsteady state) to the large-time solution (steady state), irrespective of values of M. 5.50 Pr = 0.72, Ec = 0.0 (a) Pr = 0.72, Ec = 0.0 (b) 2.0

1.6 1/2 ) L

M = 0.0, 0.5, 1.0 -1/2 )

1.2L (Re f C Nu(Re

2.75 0.8

0.4 M = 0.0, 0.5, 1.0

0.0 0.5 1.0 0.0 0.5 1.0 x x Fig. 2 Effect of magnetic field (M) on skin friction coefficient and heat transfer coefficient

Further, Fig.3 shows the effect of magnetic field (M) on dimensionless velocity f ¢ and temperature (G) profiles at x = 0:5. The magnitude of the velocity decreases but temperature increases with the increase of magnetic field. It is true for all values of x. © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future”

37 A. H. Srinivasa et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.32-40 1.0 1.0 (b) Pr = 0.72 (a) Pr = 0.72 Ec = 0.0 Ec = 0.0 x = 0.5 x = 0.5

M = 0.0, 0.5,1.0 f'

0.5 G 0.5 M = 0.0, 0.5,1.0

0.0 0.0 0 3 6 0 3 6 h h Fig. 3. Effect of magnetic field (M) on (a) velocity and (b) temperature profiles

The variation of dimensionless velocity profile f ¢ and temperature profile (G) with time (x) is illustrated in Fig.4, under the influence of uniform magnetic M (M = 0.5). It is evident from this figure that increase in x results in the reduction of momentum boundary layer thickness and growing of thermal boundary layer thickness [See Fig 4(a)] and growing of thermal boundary layer thickness[See Fig 4(b)]. which confirms the decrease of velocity and increase in temperature inside the boundary layer for all times Further, the velocity and temperature profiles decrease monotonically with the distance from the surface and finally become zero for away from it, satisfying the boundary conditions asymptotically, and thus supporting the numerical results obtained. 1.0 1.0 (a) Pr = 0.7 (b) Pr = 0.72 Ec = 0.0 Ec = 0.0 M = 0.5 M = 0.5 f' 0.5 G 0.5 x = 0.1, 0.5,1.0 x = 0.1, 0.5, 1.0

0.0 0.0 0 3 6 0 3 6 h h Fig. 4 (a) Velocity and (b) temperature profiles for various values of x when M = 0.5

-1/2 The viscous dissipation (Ec) is on heat transfer coefficient [Nu(ReL) ] and temperature profile (G) in the presence of magnetic field (M = 0.5) are shown in Fig. 5(a) and 5(b) respectively. It is noticed -1/2 that due to impulsive motion Nu(ReL) becomes higher for small time (t* = 0 or x = 0) after the start of the motion, and, later, decreases continuously and reach steady - state values at large time ( x = 1 or -1/2 t* ® ¥). Due to increase of Ec, Nu(ReL) decreases. On the other hand for Ec > 0, the temperature profile (G) exhibits overshoot within the boundary layer before reaching zero value at the edge of the boundary layer [See fig 5(b)]. This implies that the temperature of the fluid near the wall is greater than that at the wall. Due to viscous dissipation, the fluid near the wall heats up and its temperature become more than the wall, although the wall is maintained at constant higher temperature. Thus the cooler free stream is unable to cool the hot wall due to the heat cushion provided by frictional heating, therefore the wall instead of cooled, will get heated. Moreover, for Ec > 0, Fig.5 (a) displays that -1/2 Nu(ReL) becomes negative indicating the reversal of the direction of heat transfer, i.e., from wall to fluid, instead of fluid to wall (which are also observed by the corresponding overshoot in temperature profiles). Further, when Ec < 0 (i.e. when Tw< T¥ ), the temperature profile (G) exhibits undershoot within the boundary layer before reaching zero value at the edge of the boundary layer [See fig 5(b)]. This means that the temperature of the fluid within the boundary layer attains greater value than free stream temperature which is again due to the viscous dissipation heating as explained above in details. In fact, at x = 0.6, the heat transfer coefficient reduces from 0.008 to -0.291 when Ec varies from 0 to 2.0. However, in the absence of viscous dissipation (Ec = 0), heat transfer takes place in the usual way

38 A. H. Srinivasa et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.32-40 1/2 (i.e., from wall to fluid). The skin friction Cf(ReL) and velocity field f ¢ is unaffected by viscous dissipation parameter (Ec) since Ec occurs only in energy equation. 2.8 Pr = 0.72 (a) 1.5 (b) 2.4 M = 0.5 Pr = 0.72 M = 0.5 2.0 x = 1.0 1.0 1.6 -1/2

) Ec = -2.0 L

1.2 G

Nu(Re 0.5 0.8 0.0 Ec = -2.0, 0.0, 2.0

0.4

0.0 2.0 0.0

-0.4 0.0 0.5 1.0 0 3 6 x h Fig.5. Effect of viscous dissipation on (a) heat transfer coefficient and (b) temperature profile

6. CONCLUSION: The unsteady laminar boundary-layer flow caused by an impulsively stretching surface in the presence of a transverse magnetic field have been studied both numerically and analytically. The problem is formulated in such a way that, the impulsive change in the surface velocity give rise to unsteadiness in the flow field. The governing partial differential equations are solved numerically, using Keller box method for the entire transient from t* = 0 (initial state) to t* ®¥ (final steady state). Also, the equations governing the early unsteady flow (0 < t* << 1) and final steady flow (t* ®¥ ), are solved analytically, and the present numerical solutions match both these, large time and small time (analytical) solutions. From the present investigation, it is found that the magnetic field exerts significant influence on skin friction coefficient and heat transfer coefficient for all times. As magnetic parameter increases the skin friction coefficient increases while, the heat transfer coefficient decreases. In fact, magnetic field reduces the momentum boundary layer thickness and increases the thermal boundary layer thickness. Indeed, both skin friction and heat transfer coefficients are at higher values during the initial impulsive unsteady motion, and later found to decrease monotonically as steady state is reached. There is a smooth transition from the small-time solution to the large-time solution. Also, the heat transfer coefficient is found to depend strongly on viscous dissipation, but its effect on skin friction coefficient is comparatively very less. Further, both skin friction and heat transfer coefficients increases with the increase of Prandtl number (Pr) due to the reduction in the velocity and temperature inside the boundary layer.

7. ACKNOWLEDGEMENTS: One of the author A.H. Srinivasa thanks Principal and the Management of Maharaja Institute of Technology, Mysore-571 438 for their kind support.

8. REFERENCES: [1] Sakiadis, B. C.: Boundary layer behavior on continuous solid surfaces: I. The Boundarylayer equations for two-dimensional and axisymmetric flow. A.I.Ch.E J., 7, pp. 26-28,1961. [2] Erickson, L. E. , Fan, L. T. and Fox, V. G.: Heat and Mass Transfer on a continuous flat plate with suction / injection. Ind. Eng. Chem. Fund, 5, pp. 19-25, 1966. [3] Tsou. F. K., Sparrow, E. M. and Goldstein, R. J.: Flow and heat transfer in the boundarylayer on a continuous moving surface. Int. J. Heat Mass Transfer, 10, pp. 219-235, 1967. [4] Crane, L. J.: Flow past a stretching plate.Z. Angew Math Phys (ZAMP), 21, pp. 645-647,1970. [5] Magyari, Ali, M. E. and Keller, B.: Heat and mass transfer characteristics of the selfsimilarboundary layer flows induced by continuous surface stretched with rapidly decreasing velocities. Int. J. Heat Mass Transfer 38, pp. 65-74, 2001. [6] Grubka, L. J. and Bobba, K. M.: Heat transfer characteristics of a continuous stretchingsurface with variable temperature. ASME J. Heat Transfer. 107, pp.248-250, 1985.

39 A. H. Srinivasa et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.32-40 [7] Vleggaar, J.: Laminar boundary layer behavior on continuous accelerating surfaces.Chem. Eng. Sci. 32, pp. 1517-1525, 1977. [8] Soundalgekar, V. M. and Ramanamurthy, T. V.: Heat transfer in the flow past a continuousmoving plate with variable temperature. WarmeStoffubert, 14, pp. 91-93, 1980. [9] Pavlov, B.: Magnetohydrodynamic flow of an incompressible viscous fluid caused by the deformation of a plane surface. Magn. Gidrondin, 4, 146-152, 1974. [10] Chakrabarthi, A. Gupta, A.S.: A note on MHD flow over a stretching permeable surface.Q.Appl.Math, 37, pp. 73-78, 1979. [11] Andersson, H. I. : MHD flow of a viscous fluid past stretching surface. Acta Mech,95,pp. 227-230, 1992. [12] Vajravelu, K. and Hadjinicolaou, A.: Convective heat transfer in an electrically conductingfluid at a stretching surface with uniform free stream. Int. J. Eng. Sci, 35, pp. 469-478,1996. [13] Pop, I and Na, T. Y.: A note on MHD flow over a stretching permeable surface. Mech.Research Communications. 25, pp. 263-269, 1998. [14] Kumari, M. and Nath, G.: Flow and heat transfer in a stagnation-point flow over astretching sheet with a magnetic field. Mech. Research Communications. 26, pp.469-478,1999. [15] Chiam, T. : Magneto hydrodynamic boundary layer flow due to continuous moving flat plate. Comput. Math. Appl, 26, pp. 1-8, 1993. [16] Pop, I. and Na, T. Y.: Unsteady flow past a stretching sheet. Mech. Research Communications.23, pp. 413-422, 1996. [17] Nazar, R., Amin, N. and Pop, I.: Unsteady boundary layer flow due to a stretching surface in a rotating fluid. Mech. Research Communications,31, pp.121- 2004. [18] Elbashbeshy, E. M. A. and Bazid, M. A. A.: Heat transfer over an unsteady stretching surface. Int. J. Heat Mass Transfer, 41, pp. 1-4, 2004. [19] Sharidan, S. Mahood, T and Pop, I.: Similar solutions for the unsteady boundary layerflow and heat transfer for due to a stretching sheet. Int. J. of Applied Mechanics and Engineering, 11, pp. 647-654, 2006. [20] Ishak, A. Nazar, R. and Pop, I.: Boundary layer fow and heat transfer over unsteadystretching vertical surface.Meccanica, 44, pp. 369-375, 2009. [21] Awang Kechil, S. and Hashim, I.: Series solution for unsteady boundary layer flows due to impulsively stretching plate. Chinese Physics Letters, 24, pp.139-142 2007. [22] Srinivasa, A. H. and Eswara, A. T.: Unsteady MHD laminar boundary layer flow due toan impulsively stretching surface. Proc. Int. Conference on Applied and Engineering Mathematics: World Congress of Engineers (WCE), pp. 252- 255, London, 2011. [23] A Cebeci, T and Bradshaw, P. : Physical and Computational Aspects of Convective Heat Transfer. Springer-Verlag, New York, 1988.

AUTHOR’S BRIEF BIOGRAPHY:

Dr. A.H. Srinivasa : He is working currently as Associate Professor & Head in the Department of Mathematics, Maharaja Institute of Technology Mysore -571438. He has published 13 research papers in various national and international journals.

Prof. Dr.A.T. Eswara: Currently he is working as Professor & Head in the Department of Mathematics, P.E.S.College of Engineering, Mandya 571401. He has successfully Guided 3 Ph.D. scholars. His papers more than 35 were published in various esteemed reputable National & International Journals. Now, he is guiding 2 Ph.D. scholars.

40 Dr. Smruti Tekale et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.41-47

STUDY OF Cu (II):HPHOPD EXTRACTED COMPLEX BY USING MATHEMATICAL METHODS

1 Dr. Smruti Tekale 2 3 Assistant Professor Dr. Sudheer Lingayat Dr. Prafullachandra Tekale Department of Applied Chemistry Department of Chemistry Department of Chemistry Vidyalankar Institute of technology G. N. Khalsa College G. N. Khalsa College Mumbai, India Matunga, India Matunga, India [email protected] [email protected]

Abstract 1-phenyl-1-hydrazonyl-2-oximino propane–1,2–dione reagent forms a complex with Cu (II) from aqueous phase and can be quantitatively extracted in n-butanol at pH = 9.4. Current work explores the determination of the combining ratio of metal and reagent of extracted species in the organic phase using various mathematical methods like Continuous Variation method, Slope ratio method and Mole ratio method. It was observed that the ratio of Cu(II) : 1-phenyl-1-hydrazonyl-2- oximino propane – 1,2 – dione reagent was 1:2. The mechanism of the extraction process is also proposed.

Keywords: extractive spectrophotometric, Continuous Variation method, Slope ratio method and Mole ratio method

1. INTRODUCTION: Solvent extraction is an important method in separation science [1-3]. Extractive spectrophotometric is a method, in which a metal forms a complex with the complexing agent in aqueous phase. Further this complex is extracted in organic phase at suitable conditions. The composition of coloured complex can be determined by spectrophotometry [4 - 6]. The ratio of metal : Ligand in the complex can be determined by using mathematical methods used for of are Job’s Method of Continuous Variation Slope ratio method and Mole ratio method [7]. In Job’s Method of Continuous Variation, the total number of moles of reactants throughout a series of mixtures and reactants are constant, but varies the mole fraction of each reactant from mixture to mixture [8, 9]. Slope ratio method and Mole ratio method are used to find the combining ratio of metal and reagent [10 - 11].

2. MATERIALS AND METHODS: 1-phenyl-1-hydrazonyl-2-oximino propane–1, 2– dione (HPHOPD) forms a complex with Cu (II) and can be quantitatively extracted in n-butanol at pH = 9.4. [12]. All chemicals and solvents used in this study were A. R. grade from s. d. fine. The stock solution of Cu (II) was prepared from Copper sulphate salt and was standardized by diethyldithiocarbamate method. A digital pH meter, (Elico Private Ltd, India) with a combined glass and calomel electrode (Toshniwal - Mollar, India) and UV 2100 spectrophotometer (Shimadzu) with glass cells of path length 1 cm was used. Preparation of solutions for Calibration curve A series of solutions containing known amounts of concentration of Cu (0.1 – 1.0 ppm) were prepared. 10.0 cm3 containing variable amount of Cu (II) and 2.0 cm3 of 0.1 % HPHOPD in ethanol. The pH of the aqueous phase was adjusted to 9.4 and was extracted with 10.0 cm3 organic phase of n- Butanol. The absorbance of the coloured complex in each was measured at 345 nm. The graph of absorbance against concentration of metal was plotted (Figure 1). Preparation of solutions for Job’s continuous variation method Aliquots of 1x 10-3 M Cu(II) solution were prepared. The HPHOPD solution in ethanol (reagent solution) was prepared 1x 10-3 M. The pH of metal solutions were maintained at 9.4 © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future”

41 Dr. Smruti Tekale et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.41-47 The solutions were transferred to 100 cm3 separatory funnel. The organic extracts were collected in 10 cm3 standard volumetric flasks. The absorbance was measured at 345 nm wavelength using suitable diluents as blank (Table2). The absorbance was plotted against the ratio of concentration of metal to the total concentration of metal and the reagent (Figure 2). Preparation of solutions for slope ratio method To a fixed amount of metal concentration, the molar ratio of reagent was varied in such a way that the extraction of the metal was in the range of 10-90 % in the organic phase. Different molar solutions 10.0 cm3 of the reagent (HPHOPD) (0.5 X10-3 - 2.5 X10-3 ) in n-Butanol were added to the 10.0 cm3 containing 100 μg of Cu (II) solutions and the extraction was carried out using suitable solvent (extractant) and the absorbance was determined at 345nm. The amount of metal remaining in aqueous phase in each case was determined by standard methods. The logarithm values of distribution coefficients were calculated and then plotted against logarithm values of concentration of the reagent (Figure 3). Preparation of the solutions for mole ratio method A series of solution each containing metal solution of concentration 1x10-3 M was treated with increasing amount of reagent solution such that the molar proportion of reagent : metal were 0.5 to 5.0. The pH value of these solutions were adjusted to 9.4 and then the solutions were equilibrate with 10.0 cm3 n-butanol. The absorbance values were plotted against mole ratio of reagent to metal (Figure4).

3. RESULTS AND DISCUSSION: Calibration Curve Method Calibration graph for this method was constructed under the optimum conditions. The calibration curve plot (Figure 1) was a straight line. Therefore, Beer’s law was obeyed in the range 1.0 – 10.0 ppm. The molar absorptivity was found to be 0.35 X 10 3 L mol –1cm-1 which indicates that the method is sensitive. Sandell sensitivity was also calculated and was found to be 0.35 μg cm-2 respectively.

0.6

0.5

0.4

0.3

0.2

Absorbance 0.1

0 Figure 1. Calibration0.5 Curve 1

The amount of metal can be determined from the calibration curve obtained by plotting absorbance values against the corresponding concentration of metal. The percent extraction (%E) was calculated as follows:

42 Dr. Smruti Tekale et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.41-47 V % E = 100 [1 - ( w ) n ] V o D + V w

where,

Total concentrat ion of solute in organic phase D = Total concentration of solute in aqueous phase

Vw / Vo is volume ratio volume of aqueous phase/ organic phase n is number of extraction. Separation Factor If extraction of one particular solute in the presence of number of other solutes is desired then the extent of separation is dependent on the Separation factor (β). If two solutes A and B having their distribution ratios DA and DB are present in the aqueous phase and if DA>> DB then the extent to which A will be extracted will be given by Separation factor (β)where D b = A D B More effective separation is made possible by adjusting the volume ratio of two phases [14] according Bush –Denson’s equation. The equation is V 1 O = VW DA DB Successive extraction helps to increase the efficiency of extraction. It is possible to enhance to suppress the extraction of particular solute by adjustment of pH or by complexation or any other suitable mechanism. To extract Co(II) from the mixture of other metal ions the pH of the aqueous solution was adjusted to 9.4.

Job’s Continuous Variation Method for detection of Metal to Ligand Complex The Absorbance values of corresponding mole fraction was measured at 345 nm wavelength using suitable diluent as blank (Table2). Table 2 Job’s Continuous Variation Method

Sr. Volume of Volume of Mole fraction Absorbance No. Cu (II) in HPHOPD [Cu (II)] (A) cm3 in cm3 [Cu (II)] + [HPHOPD] 1 2.0 0 1.0 0.018 2 1.8 0.2 0.9 0.032 3 1.6 0.4 0.8 0.058 4 1.5 0.5 0.75 0.068 5 1.4 0.6 0.70 0.092 6 1.2 0.8 0.60 0.124 7 1.1 0.9 0.55 0.184 8 1.0 1.0 0.50 0.264 9 0.9 1.1 0.45 0.337 10 0.8 1.2 0.40 0.393 11 0.7 1.3 0.35 0.508 12 0.6 1.4 0.30 0.410

43 Dr. Smruti Tekale et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.41-47 13 0.5 1.5 0.25 0.346 14 0.4 1.6 0.20 0.268 15 0.3 1.7 0.15 0.195 16 0.2 1.8 0.10 0.132 17 0.1 1.9 0.05 0.068 18 0 2.0 --

For determination of the extracted species, the absorbance was plotted against the ratio of concentration of metal to the total concentration of metal and the reagent (Figure 2). The maximum absorbance value was observed at the combining ratio of Cu(II) : HPHOPD is 1:2.

Figure 2. Job’s Continuous Variation Plot

Slope ratio Method The logarithm values of distribution coefficients were calculated and then plotted against logarithm values of concentration of the reagent (Figure 3). The slope of the plot was observed to be 2. Therefore, the Mole ratio of Cu(II) : HPHOPD is 1:2.

3.6

3.2

2.8

2.4

2 log D

1.6

1.2

0.8

0.4

0 -3.5 -3 -2.5 -2

log R

Figure 3. Slope Ratio Plot

44 Dr. Smruti Tekale et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.41-47 Mole ratio method In mole ratio method, a series of solution is prepared in which the analytical concentration of one reactant is held constant while that of other is varied. A plot of absorbance versus mole ratio of the reactants is then prepared. If the reaction is sufficiently complete, two straight lines of different slopes are obtained. The intersection of the extrapolated lines corresponds to the combining ratio in the complex. From Figure 4 it was the intersection of the extrapolated lines indicates the combining ratio is Cu(II) : HPHOPD 1:2.

Figure 4 Plot of Mole ratio method

Chelation A polydentate ligand when co-ordinates with metal ion a closed ring structure known as ‘chelate’ results and the process is called as chelation [13, 14]. Cationic charge on metal ion influences its activity and also its ability to form complexes. Highly charged cations are more acidic and hence form more stable complexes. Charge concentrations of anion, which is a measure of its acidity is also responsible for complexation. Stability of the metal complexes increases with charge concentration or ionization potential of metal ions. Electronegativity of the donor atoms of the basic group, size and number of rings formed influence chelate formation. Stronger bonds are formed with donor atoms of lower electronegativity. Thus complexes that involve ‘N’ and ‘S’ as donor atoms are more stable than those involving ‘O’ as donor atoms. Mechanism of the extraction reaction The mechanism of the reaction is as follows M +n + bB « MBn + b 0 n + - n + - MB + nX Û çæ MB ,nx ÷ö b è b ø In above equation M : Cu Metal B : Neutral ligand

45 Dr. Smruti Tekale et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.41-47

CH3

C C

H2N N N OH H2 N 1-Phenyl-1-hydrazonyl-2-oximinopropane 1,2 dione [HPHOPD] X- : is anion for pairing with cations Y+ : Suitable cation required to form an ion pair

4. CONCLUSION: Mathematical methods like Job’s Method of Continuous Variation, Slope ratio method and Mole ratio method were used for determination of Cu(II) : HPHOPD extracted complex. The combining ratio of Cu(II) : HPHOPD was found to be 1:2. The Mechanism of the extraction reaction was also proposed.

5. ACKNOWLEDGEMENTS:

6. REFERENCES:

[1] Kojiro Shimojo and Masahiro Goto, Solvent Extraction and Stripping of Silver Ions in Room-Temperature Ionic Liquids Containing Calixarenes, Anal. Chem., 76 (17), 5039–5044, 2004. [2] Kathryn C. Sole, J. Brent Hiskey, Solvent extraction of copper by Cyanex 272, Cyanex 302 and Cyanex 301, Hydrometallurgy, 37(2), 129–147,1995. [3] P. P.Tekale, R. S Lokhande, S. K Lingayat, R. R. Shelar, A. C. Suthar, S. P. Tekale , Extractive Spectrophotometric Determination of Cobalt (II) and Iron (II) From Pharmaceutical Samples, International Journal of Pharma World Research, 2010, 4(1), 1- 20. [4] P. Tekale, S P. Tekale, S. K. Lingayat, Chandra B. Maurya and A. P. Rajale, Development of Selective Extractive Spectrophotometric Method for determination of Aluminum (III) from Synthetic Mixtures, Water and Alloy Samples by using 1-phenyl-1-hydrazonyl-2-oximino propane –1,2–dione Reagent, International Journal of Inorganic and Bioinorganic Chemistry 2(2012) 23-26. [5] P. Tekale, S P. Tekale, S. K. Lingayat “QUANTITATIVE DETERMINATION OF Ni (II) IN VEGETABLE OILS BY EXTRACTIVE SPECTROPHOTOMETRIC METHOD”, Bionano Frontier, 2010, 3, 348 -351. [6] P. Tekale, S P. Tekale, S. K. Lingayat, ESTTMATION OF MANGANESE (Il) FROM WATER, FOOD AND PHARMACEUTTCAL SAMPLES USING 1-PHENYL-1-HYDRAZONYL-2-OXIMINO PROPANE -1, 2 -DIONE REAGENT, Bioscience Discovery, 2 (2):155-158, June 2011. [7] Rama S. Lokhande, Poonam P. Shevde, Sushama M. Lele, International Journal of Chem Tech Research, 4, (2012) 877-881. [8] Werner Likussar , D. F. Boltz, Theory of continuous variations plots and a new method for spectrophotometric determination of extraction and formation constants, Anal. Chem., 43 (1971), 1265–1272. DOI: 10.1021/ac60304a006 [9] Thakkar SV, Allegre KM, Joshi SB, Volkin DB, Middaugh CR, An application of ultraviolet spectroscopy to study interactions in proteins solutions at high concentrations, J Pharm Sci. 101(2012) 3051-61. doi: 10.1002/jps.23188. [10] Masoud MS, Ali AE, Haggag SS, Nasr NM, Spectroscopic studies on gallic acid and its azo derivatives and their iron(III) complexes, Spectrochim Acta A Mol Biomol Spectrosc., 120 (2014), 505-11. doi: 10.1016/j.saa.2013.10.054. [11] Joseph S. Renny, Laura L. Tomasevich, Evan H. Tallmadge, and David B. Collum, Method of Continuous Variations: Applications of Job Plots to the Study of Molecular Associations in Organometallic Chemistry, Angew. Chem.Int.Ed. 52 (2013),2–8. DOI: 10.1002/anie.201304157 [12] P. Tekale, S. Tekale, S. Lingayat and P N Pabrekar, Extractive Spectrophotometric Determination of Copper (II) using 1-phenyl-1-hydrazonyl-2-oximino propane –1, 2 –dione, Science Research Reporter 1(2011) 83 – 87.

46 Dr. Smruti Tekale et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.41-47 http://www.jsrr.in/Volume%201%20No%202/Tekale%2040-44.pdf [13] Valcarcel, Miguel, Principles of Analytical Chemistry, A Textbook, Springer Publication, 2000. [14] F. W. Field and D. Kclay. “Priciples and Practice of Analytical Chemistry” 3rd edn. Blackie and Sons Ltd. Ch. 4 (1990).

AUTHOR’S BRIEF BIOGRAPHY : Dr. Smruti Tekale had done Ph. D., PDF from Institute of Chemical Technology, Matunga, Mumbai, India.

47 T.Arun Kumar et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.48-56

Heat transfer due to permeable stretching wall in presence of transverse magnetic field with heat generation / absorption.

T. Arun Kumar Department of Mathematics, University College of Science, Osmania University, Hyderabad 500 007, email:[email protected]

Abstract

Exact similarity solution for the viscous flow due to stretching surface in the presence of magnetic field is derived. Adopting the similarity transformation, governing nonlinear partial differential equations of the problem are transformed to nonlinear ordinary differential equations. Then the numerical solution of the problem is derived using Quasilinearization of Newton’s method. Two cases of heat transfer are considered. The sheet (a) with prescribed surface temperature and (b) the prescribed wall heat flux .both the cases are further extended to study the heat transfer due to suction and injection. A simple relation for the two cases of heat transfer is obtained. Keywords: Magnetic field, Heat source, Heat absorption, Heat flux, Quasilinearization of Newton’s method.

1. INTRODUCTION: Flow problem with obvious relevance to polymer extrusion is an interesting area of present- day research. In a melt-spinning process, the extrudate from the die is generally drawn and simultaneously stretched into a filament or sheet, which is thereafter solidified through rapid quenching or gradual cooling by unidirectional orientation to the extradite, the by improving its mechanical properties and the quality of the final product greatly depends on the rate of cooking. Crane [1] studied the two-dimensional boundary –layer flow caused by the stretching of the sheet which moves in its own plane at a velocity that varies linearly with the distance from the slit. This problem was extended to heat and mass transfer with suction or blowing by Gupta and Gupta [2] who studied the temperature and concentration distributions for isothermal case. Dutta, Roy and Gupta [3] analyzed the temperature distribution in the flow over a stretching sheet with uniform heat flux. Grubka and Bobba [4] studied the heat transfer characteristics of a continuous stretching surface with variable temperature. Further study of magnetohydrodynamic (MHD) flow of an electrically conducting fluid due to the stretching of the sheet is of considerable interest in modern metallurgical and metal-working process. To be more specific, it may be mentioned that many metallurgical processes involve cooling of the continuous strips or filaments by drawing them through a quiescent fluid and that in process of the drawing, these strips are sometimes stretched. Mention may be made © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 48 T.Arun Kumar et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.48-56 of drawing, annealing and thinning of copper wires. In all these cases the propertied of the final product depend to a great extent on the rate of cooling. By drawing such strips in an electrically conducting fluid subject to a magnetic field, the rate of cooling can be controlled and final products of the desired characteristics might be achieved. Pavlov [5] presented an exact similarity solution of the boundary-layer equation for the steady tow-dimensional flow of a surface in a uniform transverse magnetic field. In this analysis he has neglected the induced magnetic field under the assumption of small magnetic Reynolds number. Anderson [6] has demonstrated that the similarity solution derived by Pavlov [5] is not only a boundary layer equation but also represents an exact solution of the complete Navier-Stokes equation. Chakrabarti and Gupta [7] extended the above analysis to Pavlov to study the temperature distribution for isothermal boundary when a uniform suction is applied at the surface. It would be of interest to study the effects of power-law variations of temperature and heat flux distribution on the heat transfer characteristics of stretching sheet in presence of a uniform transverse magnetic field subject to suction and blowing. B.S Dandapat, S.N. Singh, R.P. Singh [9] has studied the heat transfer on a stretching sheet in presence of a transverse magnetic field with suction and blowing for different types of thermal boundary conditions on the surface. Here we propose to study the heat transfer due to a permeable stretching wall in presence of transverse magnetic field with heat generation / absorption. 2. MATHEMATICAL FORMULATIONS:

Consider the flow of an incompressible electrically conducting fluid (with electrical conductivity σ and thermal diffusivity α) due to the stretching of a permeable flat sheet. It is assumed that the speed of a point on the sheet is proportional to its distance from the slit at x=0, y =0. Further we assume that the sheet lies in the x-z plane and is stretched along the x axis. A uniform transverse magnetic field Bo acts parallel to the y axis and the conducting fluid occupies the half space y > 0. We have also assumed that the sheet is subjected to either (a) prescribed surface temperature or (b) prescribed wall heat flux. The steady velocity field [u(x, y), v(x, y), 0] that developed due to the stretching of the sheet with velocity Ax satisfies the boundary-layer equation of mass, momentum and thermal energy. ¶u ¶v + = 0 ………. (1) ¶x ¶y

¶u ¶u ¶ 2u æ sB 2 ö u + v = v - ç 0 ÷u ……… (2) 2 ç ÷ ¶x ¶y ¶y è r ø ¶T ¶T ¶ 2T u + v = a + Q(T - T ) ……….. (3) ¶x ¶y ¶y 2 ¥ where the induced magnetic field is neglected by assuming the flow for small magnetic Reynolds number, as justified by Shercliff [8]. It is also assumed that the eternal electrical field due to

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 49 T.Arun Kumar et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.48-56 polarization of charges is negligible. Further we assume that ν, the kinematic viscosity of the ambient fluid, is constant and the gravity force gives rise to a hydrostatic pressure variation in the liquid. In order to justify the boundary layer approximation, length scale in the primary flow direction should be significantly larger than the length scale in the cross stream direction. In fact, the flow takes place within a thin layer of thickness (v/A)1/2 due to the stretching of the sheet, the scale ratio x/(v/A)1/2>>1. 2 Further it is possible to define a local Reynolds number Rex=Ux/v =Ax /v which initially equals the square of the above scale ratio. Thus, just as in aerodynamic boundary layer theory, cross-stream diffusion of momentum and thermal energy can only be neglected at a high Reynolds number. The corresponding boundary conditions are: u(x, 0)=Ax, v(x,0)=Vw(x), u(x, ∞ )=0 ………..(4) either Tw(x, 0) =T1(x), T (x, ∞) =T∞ ….... (5) ¶T or - k = q (x) for y = 0, T(x, ¥ )= T∞ .……… (6) ¶y w where Vw denotes the lateral mass flux of velocity which occurs due to suction or injection. Tw , T¥ and qw denote the temperature at the wall, temperature at a large distance from the wall and heat flux at the wall, respectively. Assuming the functional structure of the similarity solutions in the form u(x, y) = Axf ' (h) …… (7)

v(x, y) = -(vA)1/2 f (h) ……. (8) h = (A / v)1/ 2 y ....…..(9) and substituting eqn (7) to (9) in the system of equations eqn (1) to (3) ,it can be shown that similarity solution of the above set of boundary equations exists and reduces to f ''' + ff '' - ( f ' ) 2 - mf ' = 0 ………….. (10) Subject to the boundary conditions

f (0) = f , f ' (0) = 1, f ' (¥ ) = 0 w ….… (11)

sb 2 -V Where m º 0 and f º w denote the magnetic parameter, suction/injection Ar w (vA)1/ 2 parameter, respectively and prime (‘) denotes derivative with respect to

The similarity variable η. in eqn (11), fw = 0 corresponds to an impermeable wall, fw > 0 and fw < 0 denote respectively the suction and injection of the fluid through the permeable wall. HEAT TRANSFER: In this section we are interested to study the heat transfer for two different heating processes. PRESCRIBED SURFACE TEMPERATURE: We assign a general functional structure in eqn (5) to prescribe the temperature at the boundary as © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 50 T.Arun Kumar et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.48-56 r Tw = T1 (x) = T¥ + Cx for y = 0 …………. (12)

and T = T¥ as y ® ¥, ……….. (13)

where r is the temperature parameter and T¥ denote temperature at a large distance from the wall and it is constant. For r = 0, the thermal boundary will be isothermal. Introducing T - T q (h) = ¥ in equation (3.2.3) and using eqn (9) we get Tw -T¥

'' ' ' q + pr fq + pr [b - rf ]q = 0 ………………… (14)

Where p = v is the Prandtl number. The corresponding boundary conditions (5) reduces to r a q (0) = 1 , q (¥) = 0. …………….. (15)

PRESCRIBED WALL HEAT FLUX: In this case the thermal boundary conditions will be ¶T - k = q = Dx s for y = 0 …….(16) ¶y w And

T = T¥ as y ® ¥ ………..(17) where s is the heat flux parameter. For s = 0 the stretching sheet is under uniform heat flux. We assume the similar solution as Dx s T = T + v g(h) ……………….. (18) ¥ K A Where h = (A/v)1/2 y using eqn (1) and (2) in (3) we get

'' ' ' …………….. (19) g + pr fg + pr [b - sf ]g = 0 The corresponding boundary conditions (2) and (3) reduces to g ' (0) = 1 , g(¥) = 0. ………………….. (20)

3. METHOD OF SOLUTION: Eqs. (10), (14) and (9) with boundary conditions (11), (15) and (19) is solved using Quasilinearization of Newton’s method.

4. RESULTS AND DISCUSSION: To get insight into the problem, a few figures are drawn by evaluating Eqs (1) for different values of the parameters. It is clear from the Figure (1) that when magnetic parameter increases either for suction or injection f′ (η) decreases for all values of η. Further Figure (2) represents the variation of f′ (η) with respect to η for different values of suction, injection and magnetic parameters. It is clear © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 51 T.Arun Kumar et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.48-56 that as suction/ injection parameter increases, f′ (η) increases. This is due to the fact that the increase of magnetic parameter implies the increase of Lorentz force which puts greater resistance to the flow, and as a result the flow decelerates. Figures (3) and (4) shows the temperature variation with η for different values of Prandtl number and the temperature parameter. Figure (3) shows that with increasing Prandtl number the temperature profile decreases in PST case and Figure (4) shows that with increasing temperature parameter temperature profile decreases in PST case. For r > 0 heat flows from the stretching surface to the ambient fluid and for r < 0 the wall temperature gradient is positive and heat flows into the stretching surface from the ambient fluid. And from the figure (5) it is observed that as the magnetic parameter increase the temperature profile in PST case increases, and from the figure (6) we can notice the variation of temperature in PST case with similarity variable η for different values of source / sink parameter β. The presence of heat source β > 0 in the boundary layer generates the energy, which causes the temperature of the fluid to increase, whereas, the presence of heat sink β < 0 in the boundary layer leads to absorption of energy, which cause a decrease in the temperature of the fluid. Figures (6) – (10) show the effect of Prandtl number, magnetic parameter, heat flux parameter, and heat source or sink respectively on temperature in PHF case. Through these figures we can clearly observe that the effect of these parameters on temperature in PHF is same as that of these parameter effects in PST case.

5. CONCLUSIONS:

(1). when magnetic parameter increases either for suction or injection f′ (η) decreases for all values of η. (2). It is clear that as suction/ injection parameter increases, f′ (η) increases. This is due to the fact that the increase of magnetic parameter. (3). increasing Prandtl number the temperature profile decreases in PST case. increasing temperature parameter temperature profile decreases in PST case. (4). The magnetic parameter increase the temperature profile in PST case increases. The presence of heat source β > 0 in the boundary layer generates the energy, which causes the temperature of the fluid to increase, whereas, the presence of heat sink β < 0 in the boundary layer leads to absorption of energy, which cause a decrease in the temperature of the fluid.

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 52 T.Arun Kumar et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.48-56

1 m=1 0.8 m=2 m=3 f ’ 0.6

0.4

0 0 2 4 6 8 10 12

Fig(1) Effect of magnetic parameter on velocity field.

1 fw= -0.4 0.8 fw= -0.2 fw= 0.0 f ' 0.6 fw= 0.2 fw= 0.4 0.4

0 0 2 4 6 8 10 12

η Fig(2) Effect of suction/injection parameter on velocity field.

1.2

1 Pr=0.73 Pr=6.75 0.8 Pr=7.0 θ 0.6

0.4

0.2

0 0 2 4 6 8 10 12 η

Fig(3) Effect of Prandtl number on temperature profile in PST case.

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 53 T.Arun Kumar et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.48-56

1.2

1 r = -4 r = -2 0.8 r = 0 θ 0.6 r = 2 r = 4 0.4

0.2

0 0 2 4 6 8 10 η

Fig(4) Effect of temperature parameter on temperature profile in PST case.

1.2

1 m=1 0.8 m=2 m=3 θ 0.6

0.4

0.2

0 0 2 4 6 8 10 12 η

Fig(5) Effect of magnetic parameter on temperature profile in PST case.

1.2

0.8 β= 1.0 β= 0.5 θ 0.6 β=0.0 β= -0.5 0.4 β= -1.0

0.2

0 0 0.5 1 1.5 2 η

Fig(6) Effect of source/sink parameter on temperature profile in PST case. © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 54 T.Arun Kumar et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.48-56

2.5 Pr=0.73 Pr=0.65 2 Pr=7.00 g 1.5

0.5

0 0 2 4 6 8 10 12 η Fig(7) Effect of Prandtl number on temperature profile in PHF case.

2.5

2 s = -4 s = -2 g 1.5 s = 0 s = 2 1 s = 4

0.5

0 0 2 4 6 8 10 12 η

Fig(8) Effect of heat flux parameter on temperature profile in PHF case.

2.5 m=1 2 m=2 m=3 g 1.5

0.5

0 0 2 4 6 8 10 12 η Fig(9) Effect of magnetic parameter on temperature profile in PHF case. © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 55 T.Arun Kumar et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.48-56

1 0.9 0.8 0.7 β= -1.0 0.6 β= -0.5 g 0.5 β= 0.0 0.4 β= 0.5 0.3 β=1.0 0.2 0.1 0 0 0.5 1 1.5 2 η

Fig(10) Effect of source/sink parameter on temperature profile in PHF case.

6. REFERENCES: [1] L.E Crane, Flow past a stretching plane, Z.A.M.P., 21,645-647, 1970. [2] P.S. Gupta and A.S. Gupta, Heat and mass transfer on a stretching sheet with suction or blowing, Can. J. Chem. Eng., 55,744-746,1977. [3] B.K. Dutta, P.Roy and A.S. Gupta, Temperature field in flow over a stretching sheet with uniform heat flux, Int. commun.,Heat Mass Transfer, 12,89-94,1985. [4] L.J.Grubka and K.M.Bobba, Heat transfer characteristics of a continuous stretching surface with variable temperature, J. Heat Trans., -T ASME, 107,248-250, 1985. [5] K.B. Pavlov, Magnetohydrodynamic flow of an incompressible viscous fluid caused by deformation of a plane surface, Magnitnaya Gidrodianmica, 4,146-147, 1974. [6] H.I.Anderson, An exact solution of the Navier-Stokes equation for magnetohydrodynamic flow, Acta Mechanica, 113,241-244, 1995. [7] A.Chakrabarti and A.S Gupta, Hydromagnetic flow and heat transfer over a stretched sheet, Quart. Appl. Math., 37, 73-78, 1979. [8] J.A.Shercliff, A textbook of magneto hydrodynamics, Pergamon Press, 1965. [9] B.S.Dandapat, S.N. Singh, R.P. Singh, Heat transfer due to permeable stretching wall in presence of transverse magnetic field, Arch. Mech., 56,2, PP.87-101, Warszawa 2004. [10] R. E. Bellman and R. E. Kalaba, Quasilinearization and Nonlinear Boundary Value Problems, Elsevier Publishing Company, New York, 1965.

AUTHOR’S BREIF BIOGRAPHY:

Dr.T.Arun Kumar: He is presently working as Mathematics lecturer in SR&BGNR Govt Degree and P.G College, Khammam, Telangana, India. He has been teaching mathematics for the last three (3) years for undergraduate students, he also published 8 research articles, and he has attended national seminars and Conferences and workshops.

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 56 Brindha.R et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.57-60

Secure watermark detection in compressive sensed domain

Brindha.R1 Bagavathi Shivakumar.C2 ME Communication systems, Assistant professor, Department of Electronics & Communication, Department of Electronics & Communication, Sri Sakthi institute of Engineering & Technology, Sri Sakthi institute of Engineering & Technology, Coimbatore. Coimbatore. [email protected] [email protected]

Abstract Security is an important issue in the field of communication. While transmitting data through a network there is a chance for the data or information to get by an unauthorized person. So it is essential to take counter measures to provide confidentiality to our data as well as to prevent the unwanted access. Water marking is a process that enable us to hide our data in a medium like image. The medium is known as cover object. The main objective of the proposed work is to perform watermarking and to recover the data with minimized error.

Keywords—water mark, security, confidential

1. INTRODUCTION: A watermark is a identifiable image or pattern in paper that appears as a variety of shades of lightness/darkness when viewed by transmit light (or when view by reflect light, atop a dark environment), caused by thickness or breadth variation in the paper. Watermarks have been used on postage trample, money, and other government documents to depress counterfeit. There are two main ways of producing watermarks in paper; the dandy roll process, and the more complex cylinder mould process. Watermarks vary greatly in their visibility; while some are obvious on casual scrutiny, others require some study to pick out. Various aids have been developed, such as watermark fluid that wets the paper without harmful it. Watermarks are often used as security features of banknotes, passports, postage stamps and other documents to prevent counterfeit. A watermark is very useful in the examination of paper because it can be used for dating, identifying sizes, mill trade name and locations, and decisive the quality of a sheet of paper. Encoding an identify code into digitized music, video, picture or other fle is known as a digital watermark.

2. RELATED WORK: The present watermarking scheme is fail to make a decision the correct possession of an image. The key problems are then identified, and some important requirements for a valid invisible watermark detection. The digital watermarking has been proposed by the copy right protection of an data or image . This technique is mainly based on the encoding schemes. Usual secure watermark detection techniques are designed to convince a verifier whether or not a watermark is fixed without disclosing the watermark pattern so that an un trusted verifier cannot remove the watermark from the watermark protected copy In this paper, we propose a compressive sensing based privacy preserve watermark detection structure that leverages secure multiparty computation and the cloud. It has been shown that many signal processing algorithms performed in the CS domain have very close performance as performed in the original domain .Using random matrix transformation for privacy preserving data- mining has also been proposed, which proposed a accidental projection data perturbation approach for privacy preserving joint data-mining. The proposed a secure image retrieval system through random projection and have proven that the proposed random outcrop domain multimedia retrieval system is secure under the Cipher copy Only Attack model (COA) and the semi-honest model . Furthermore

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 57 Brindha.R et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.57-60 that CS transformation can achieve computationally secure encryption. These works indicate that signal processing or data-mining in the CS domain is feasible and is computationally secure under certain conditions. In our framework, the target image/multimedia data is possessed by the image holder only. A compressive sensing matrix is issued by a certificate authority (CA) server to the image holder. The image holder transforms the DCT coefficients of the image data to a compressive sensing domain before outsources it to the cloud. For secure watermark detection, the watermark is transformed to the same compressive sensing domain using a secure multiparty computation (MPC) protocol and then sent to the cloud. The cloud only has the data in the compressive sensing domain. Without the compressive sensing matrix, the cloud cannot reveal the original multimedia data and the watermark pattern. The cloud will perform watermark detection in the compressive sensing domain. The image data in the compressive sensing domain can be stored in the cloud and reused for detection of watermark from many other watermark owners. 2.1 Introduction to Compressed Sensing Theory Compacted sensing provides a new framework to jointly calculate and compress a light signal for sensors that need less taster resources than traditional approaches. Given a signal on some basis , The theory of dense sensing shows that x can be improved from m compressed measurements with high possibility when m = cK log(N) , where c ≥ 1 is the over variety factor[15].

3. PROPOSED METHOD: In this research work we proposed an algorithm to hide an image in another image using watermarking. We retrieved the hidden image and also checked the performance of the algorithm. SNR, PSNR and BER are calculated to monitor the performance. ALGORITHM · To store the image in a variable · Read that image and store in different location · Take the copy right image and store it · Then read the copy right image · Convert that image into binary image and store it message · Take the watermarking of original image and message and save the water mark image · To calculate the performance of orginal image and watermark image. · Then load the watermark image · Store the water mark image in particular location · Read the stored image · Change the message size · Then retrieved the watermark image · Plot the recovered watermark · Display the number of wrong bits · Display the bit difference · Then finally display the bit error rate

4. SIMULATION The simulation is done with the help of MATLAB which stands for Matrix Laboratory.water marking is done on a 512×512 cover object.the image which is to be hidden is of size 19×52.the cover object and water marked image is shown.

SNR 35.2095 MSE 27.0074 PSNR 32.3167 BER 0

Table 1. The SNR, PSNR, MSE and BER obtained as shown

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 58 Brindha.R et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.57-60

Fig 2. Water marked image Fig 1.imaginative image

Fig 3. Recovered watermark image

5. CONCLUSION: The watermarking and retrieving of the watermarked image is implemented using MATLAB. The SNR ,PSNR,and MSE is calculated, to evaluate the accuracy of watermarking and its detection.the BER is found out to identify the matching between embedded image and retrieved image.

6. ACKNOWLEDGEMENTS:

First of all we sincerely thank the almighty who is most beneficent and merciful for giving us knowledge and courage to complete the project work successfully. We also express our gratitude to all the teaching and non-teaching staff of the college especially to our department for their encouragement and help done during our work. Finally, we appreciate the patience and solid support of our parents and enthusiastic friends for their encouragement and moral support for this effort.

7. REFERENCES:

[1] T. Bianchi and A. Piva, “Secure watermarking for multimedia content protection: A review of its benefits and open issues,” IEEE Signal Process. Mag., vol. 30, no. 2, pp. 87–96, Mar. 2013. [2] J. Eggers, J. Su, and B. Girod, “Public key watermarking by eigenvectors of linear transforms,” in Proc. Euro. Signal Process. Conf., 2000. [3] A. Adelsbach and A. Sadeghi, “Zero-knowledge watermark detection and proof of ownership,” in Proc. 4th Int. Workshop Inf. Hiding, vol. 2137. 2001, pp. 273–288. © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 59 Brindha.R et.al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.57-60 [4] M . Malkin and T. Kalker, “A cryptographic method for secure watermark detection,” in Proc. 8th Int. Workshop Inf. Hiding, 2006, pp. 26–41. [5] W. Zeng and B. Liu, “A statistical watermark detection technique without using original images for resolving rightful ownerships of digital images,” IEEE Trans. Image Process., vol. 8, no. 11, pp. 1534– 1548,.

AUTHOR’S BRIEF BIOGRAPHY:

R.BRINDHA did her Bachelor of engineering in st.michael college of Engineering and Technology and doing Master of Engineering in Sri Shakthi Institute of Engineering and Technology. Presented one papers in international conference and one paper in national conference.

C.Bagavathi Shivakumar did her master of technology in VLSI Design and presently working as assistant professor at Sri Shakthi Institute of Engineering and Technology.

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 60 Jagruti S.Wankhade et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.61-70 A Review on Analyzing Web Application for Detection of Unsecured Information

Ms. Jagruti S.Wankhade Information Technology J.D.I.E.T,Yavatmal Maharashtra, India [email protected]

Abstract Now a day’s everyone is using the internet for their professional as well as personal work. Internet is nothing but the of common route to the user to access any information from any corner of the world. As we know Internet is the collection unlimited web application. Web applications are the most common way to make services and data available on the Internet. Web application is the collection of no of web pages. During information transmission no. of none secured data /information exchange every time from one location to another location which is very harmful for the original data. There may be possibilities that original data can be altered and send to the another location which crates miscommunication between two system which is called as vulnerabilities Unfortunately, with the increase in the number and complexity of these applications, there has also been an increase in the number and complexity of vulnerabilities. In this paper we focus on all of these security problems to make web transactions more secured Current techniques to identify security problems in web applications have mostly focused on input validation flaws, such as cross site scripting and SQL injection, with much less attention devoted to application logic vulnerabilities. we first use dynamic analysis and observe the normal operation of a web application to infer a simple set of behavioral specifications. Then, leveraging the knowledge about the typical execution paradigm of web applications, we filter the learned specifications to reduce false positives, and we use model checking over symbolic input to identify program paths that are likely to violate these specifications under specific conditions, indicating the presence of a certain type of web application logic flaws. We developed a tool, called Waler, based on our ideas, and we applied it to a number of web applications, finding previously- unknown logic vulnerabilities. Keywords: Dynamic analysis, Model Checking, Waler

1. INTRODUCTION: Internet is one of the necessary for every technical as well as normal person, without internet we can’t imagine the world so we can say that internet provides the one common path for searching any information and provide the services on the internet. They are used for mission-critical tasks and frequently handle sensitive user data. Unfortunately, web applications are often implemented by developers with limited security skills, who often have to deal with time-to-market pressure and financial constraints. As a result, the number of web application vulnerabilities has increased sharply. This is reflected in the Symantec Global Internet Security Threat Report, which was published in April 2009 [12]. Most recent research on vulnerability analysis for web applications has focused on the identification and mitigation of input validation flaws. Non secured data is characterized by the fact that a web application uses external input as part of a sensitive operation without first checking or sanitizing it properly. In this an application sends to a client output that is not sufficiently checked. This allows an attacker to inject malicious JavaScript code into the output, which is then executed on the client’s browser due to this it is possible to provide a concise and general specification that captures the essential characteristics of these vulnerabilities. That is, given a programming environment, it is possible to specify a set of functions that read inputs (called sources), a set of functions that represent security-sensitive operations (called sinks), and a set of functions that check data for malicious, content. Then, various static and dynamic analysis techniques can be used to ensure that there are no unchecked data flows from sources to sinks. Since the specification of input validation flaws is independent of the application logic, once a detection system is available, it can be used to find bugs in many applications. © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 61 Jagruti S.Wankhade et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.61-70 In this paper, we take a first step toward the automated detection of application logic vulnerabilities. Our approach operates in two steps. In the first step, we infer specifications that (partially) capture a web application’s logic. These specifications are in the form of likely invariants, which are derived by analyzing the dynamic execution traces of the web application during normal operation. The intuition is that the observed, normal behavior allows one to model properties that are likely intended by the programmer. This step is necessary to automatically obtain specifications that reflect the business logic of a particular web application. In the second step, we analyze the inferred specifications with respect to the web application’s code and identify violations. In the second step of the analysis, we use model checking over symbolic input to analyze the inferred specifications with respect to the web application’s code and to identify which real invariants can be violated. We had to extend existing model checking tools with new mechanisms to take into account the unique characteristics of web applications. These characteristics include the fact that web applications are composed of modules that can be invoked in any order and that the state of the web application must also take into account the contents of back-end databases and other session-related storage facilities In summary, this paper makes the following contributions: · We extend existing dynamic analysis techniques to derive program invariants for a class of web applications, taking into account their particular execution paradigm. · We identify novel techniques for the identification Of invariants that are “real” with high probability and likely associated with the security-relevant behavior of a web application, pruning a large number of spurious invariants · We extend existing model checking techniques to Take into account the characteristics of web applications. Using this approach, we are able to identify the occurrence of two classes of web application logic flaws. · We implemented our ideas in a tool, called Waler, and we used it to analyze a number of servlet-based web applications, identifying previously-unknown application logic flaws. 2. DETECTION TECHNIQUE: Web application vulnerabilities can be divided into two main categories, depending on how vulnerability can be detected: 1. Vulnerabilities that have common characteristics across different applications 2. Vulnerabilities that is application-specific. Well-known vulnerabilities such as XSS and SQL injection belong to the first category. These two vulnerabilities are characterized by the fact that a web application uses external input as part of a sensitive operation without first checking or sanitizing it. To detect web application logic vulnerabilities automatically, one needs to provide the detection tool with a specification of the application’s intended behavior. Unfortunately, these specifications, whether formal or informal, are rarely available. Therefore, in this work, we propose an automated way to detect application logic vulnerabilities that do not require the specification of the web application behavior to be available. Our intuition is that often the application code contains “clues” about the behavior that the developer intended to enforce. These “clues” are expressed in the form of constraints on the values of variables and on the order of the operations performed by the application, we developed two novel techniques to identify which derived invariants reflect real (or “true”) program specifications. The first one uses the presence of explicit program checks, involving the variable(s) constrained by an invariant, as a clue that the invariant is indeed relevant to the behavior of the web application. The second one is based on the idea that certain types of invariants are intrinsically more likely to reflect the intent of the programmer. In particular, we focus on invariants that relate external inputs to the contents of user sessions and the back-end database. The use of these techniques to filter the derived invariants allows for a more effective extraction of specification of a web application’s behavior, when compared to previously-proposed approaches that accept all generated likely invariants as correctly reflecting the behavior of a program. In this approach, we use an initial dynamic step where we monitor the execution of a web application when it operates on a number of normal inputs. In this step, it is important to exercise the application functionality in a way that is consistent with the intentions of the developer, i.e., by following the provided links and submitting reasonable input. Note that the information about a web

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 62 Jagruti S.Wankhade et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.61-70 application’s “normal” behavior cannot be gathered using automatic-crawling tools, as these tools usually do not interact with an application following the workflow intended by the developer or using inputs that reflect normal operational patterns. In this work, as the result of the dynamic analysis step, we infer partial program specifications in the form of likely invariants. These invariants capture constraints on the values of variables at different program points, as well as relationships between variables. For example, we might infer that the Boolean variable is Admin must be true whenever a certain (privileged) function is invoked. As another example, the analysis might determine that the variable free Shipping is true only when the number of items in the shopping cart is greater than 5. We believe that these invariants provide a good base for the detection of logic flaws because they often capture application-specific constraints that the programmer had in mind when developing the web application. Of course, it is unlikely that the set of inferred invariants represents a complete (or precise) specification of web application’s functionality. Nevertheless, it provides a good, initial step to obtain a model of the intended behavior of a program and can be used to guide further, more elaborate program analysis. 3. IMPLEMENTATION TECHNIQUE: Here we are going to use servlet-based web applications which is written in java written in .Servlets are frequently used for implementing web applications. In addition, there are a number of existing tools available for Java that can be used for program analysis. In this,we find the tools , the extensions, and the challenges which needs to overcome. A typical servlet-based web application consists of servlets[24], static documents, client-side code, and descriptive information. A servlet is a Java-based web component whose methods are executed on the server in response to certain web requests. Servlets are managed by a servlet container, which is an extension of a web server that loads/manages servlets and provides services via a well defined API.These services include receiving and mapping requests to servlets, sending responses, caching, enforcing security restrictions, etc. executed, Waler checks the truth value of provided likely invariants, analyzes the applications code for “clues,” and reports possible logic errors. In this section, we describe the architecture and execution model of Waler. 3.2.1 SYSTEM DESIGN Waler is implemented on top of the Java PathFinder (JPF) framework [19, 35], and its general architecture is shown Figure 2. In this figure, dark gray boxes represent new modules that we implemented, while dotted (light gray) boxes represent parts of JPF that we had to extend. Figure 2:

Figure 2: Walers architecture. JPF overview: JPF is an open-source, explicit-state model checker that implements a JVM. It systematically explores an applications state space by executing its bytecode. JPF consists of a number of configurable components. For example, the specific way in which an applications state © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 63 Jagruti S.Wankhade et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.61-70 space is explored depends on a chosen Search Strategy – JPF core distribution includes a number of basic strategies. The State Serializer component defines how an application state is stored, matched against others, and restored. JPF also comes with a number of interfaces that allow for its functionality to be extended and modified in arbitrary ways. In general, JPF is capable of executing any Java class file that does not depend on platform-specific native code, and many of the Java standard library classes can run on top of JPF unmodified. However, in JPF, some of the Java library classes are replaced with their model versions to reduce the complexity of their real implementations and/or to enable additional features. For example, Java classes that have native method calls (such as file I/O) have to be replaced by their models, which either emulate the required functionality or delegate the native calls to the actual JVM on top of which JPF is executed. The JPF-SE Extension: The JPF-SE extension for JPF Enables symbolic execution of programs over unbounded input when using explicit-state model checking [2]. With this extension, the Java bytecode of an application needs to be transformed so that all concrete basic types, such as integers, floats, and strings, are replaced with the corresponding symbolic types. Similarly, concrete operations need to be replaced with the equivalent operations on symbolic values. For example, all objects of type int are replaced with objects of type Expression. An addition of two integers is replaced with a call to the plus method of the Expression class. Following the standard symbolic execution approach, all newly- generated constraints are added to the path condition (PC) over the current execution path. The generation of constraints is done in the methods of symbolic classes, and it is transparent to the application. Whenever the PC is updated, it is checked for satisfiability with a constraint solver, and infeasible paths are pruned from execution. Unfortunately, we found that JPF-SE was missing a considerable amount of functionality that needed to be added to make the system suitable for real- world applications. For example, the classes implementing symbolic string objects were missing a significant number of symbolic methods with respect to the java.lang.String API,which is used extensively in web applications. Also, in order to execute an arbitrary application using JPF-SE, symbolic versions of many standard Java libraries are required. These libraries were not provided with the extension. Finally, a tool to perform the necessary transformations of Java byte code was not publicly available, and, therefore, we implemented our own transformer by leveraging ASM [25], a Java byte code engineering library. Waler overview.: In order to execute servlet-based web applications and analyze them for logic errors, we had to extend JPF in a number of ways. As shown in Figure 2, we implemented from scratch four main components: the Application Controller (AC), the Vulnerability Analysis Strategies (VAS), the Program Checks Analyzer (PCA), and the Likely Invariants Analyzer (LIA). The AC component is responsible for loading, mapping, and systematically initiating execution of servlets in a servlet-based application. As the analyzed application itself, it runs on top of the JVM implemented by core-JPF and uses symbolic versions of Java libraries. The other three components are internal to JPF, i.e., they are not visible to web applications and do not rely on model classes. The LIA component is responsible for parsing Daikon-generated invariants and checking their truth value as a program executes. The PCA component keeps track of all the program checks performed by an application on an execution path. Finally, the VAS component provides various strategies for vulnerability detection based on the information provided by LIA and PCA. We provide more details on how these modules work in the following sections. In addition, we had to extend a number of existing JPF components to address the needs of our analysis. In particular, we modified existing search strategies, state information tracking, and implemented some missing parts of JPF-SE. Due to space limitations, we will not explain all of the changes unless they are significant for understanding our approach. Finally, we extended JPF with a set of 40 model classes that provide the servlet API and related interfaces (such as the JSP API). These classes implement the standard functionality of a servlet container, but instead of reading and writing actual data from/to the network, they operate on symbolic values. Our implementation is based on the real implementation of the servlet container for Tomcat. State Space Management Similar to other model checkers, Waler faces the state explosion problem. Thus, to make Waler scale to real world web applications, we had to take a number of steps to manage (limit) the exponential © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 64 Jagruti S.Wankhade et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.61-70 growth of the application’s state space. In particular, after careful analysis of several servlet-based applications, we found that JPF often fails to identify equivalent states. The two main reasons for that are: (1) the constraints added to the symbolic PC are never removed from it due to the design of JPF- SE1, and (2), without domain-specific knowledge, JPF is not able to identify “logically equivalent” states. Here we present three techniques that we implemented to overcome these problems. States in JPF. JPF comes with some mechanisms to identify equivalent states. A state in JPF is a snapshot of the current execution status of a thread, and it consists of the content of the stack, heap, and static variables storage. This snapshot is created when a sequence of executed instructions reaches a choice point, i.e., a point where there is more than one way to proceed from the current instruction. Choice points are thread-scheduling instructions, branching instructions that operate on symbolic values, or instructions where a new application entry point needs to be chosen. Whenever JPF finds a choice point, a snapshot of the current state is created. Then, the serialized version of the state is compared to hashes of previously-seen states. The execution path is terminated when the same state has been seen before. States in Waler. In Waler, we extend the concept of JPF state to a “logical state” using the domain- specific knowledge that Waler has about web applications. In particular, we observe that the only information that is preserved between two user requests in a servlet-based application are the content of user sessions, applicationlevel contexts, the symbolic PC (which stores constraints on symbolic variables stored in sessions), and data on persistent storage. Since we do not model persistent storage in Waler and always return a new symbolic value when it is accessed, we ignore this information in our analysis. Thus, the logical state of servlet-based application is defined as the content of user sessions and application contexts, and the PC. This is the only information that should be considered when comparing states after execution of a user request is finished. State space reduction. Given the design of JPF and using our concept of logical state, we implemented three solutions to reduce the state space of a web application. First of all, we implemented an additional analysis step to remove a constraint from the PC when it includes at least one variable that is no longer live2. This is especially important when the execution of a user request is finished, because, in a web application, input received by one servlet is independent from input received by another servlet, and, unless parts of it are stored in a persistent storage, any constraints on previous input are unrelated. to the new one. The implemented solution is safe (it does not affect the soundness of the analysis) and allows our system to identify many states that are equivalent. The second solution to reduce an application state space is to prune many “irrelevant” paths from state exploration. State space reduction Given the design of JPF and using our concept of logical state, we implemented three solutions to reduce the state space of a web application. First of all, we implemented an additional analysis step to remove a constraint from the PC when it includes at least one variable that is no longer live2. This is especially important when the execution of a user request is finished, because, in a web application, input received by one servlet is independent from input received by another servlet, and, unless parts of it are stored in a persistent storage, any constraints on previous input are unrelated to the new one. The implemented solution is safe (it does not affect the soundness of the analysis) and allows our system to identify many states that are equivalent. Public void _jspService(HttpServletRequest req, HttpServletResponse res) { User user = (User) session.getAttribute(“User”); if(user==null) { User.adminLogin(request,response); return; } ... if(request.getMethod().equalsIgnoreCase(“post”)) { result = website.variables. insert(new Variable(req)); } } © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 65 Jagruti S.Wankhade et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.61-70 public void _jspService(HttpServletRequest req, HttpServletResponse res) { User user = (User) session.getAttribute(“User”); if(user==null) { User.adminLogin(request,response); return; } ... if(request.getMethod().equalsIgnoreCase(“post”)) { result = website.variables. insert(new Variable(req)); } } Figure 3: Simplified version of an unauthorized access vulnerability in the JspCart application. A third technique to limit the state space explosion problem is to identify irrelevant entry points, so that the servlets mapped to these URLs do not need to be executed. 3.2.2 Vulnerabilities Detection As described in the previous section, Waler uses model checking to systematically explore the state space of an application. During the model checking process, the system checks whether the likely invariants generated by Daikon for a program point hold whenever that point is reached. In our current implementation, we only consider likely invariants that are generated for exit points of methods (note that we differentiate between different exit points). The reason is that methods often check their parameters inside the function body (rather than in the caller). As a result, entry invariants are typically less significant. To see an example of invariants that can be produced by our system, consider the code in Figure 3, which shows a vulnerability thatWaler found in the Jsp Cart application The left listing shows the code of the /admin/variables/Add.jsp servlet, which is a privileged servlet that should only be invoked by an administrator. This is reflected by the set of likely invariants that are generated for the exit point on Line 14 for Add.jsp3: (1) session.User != null (2) session.User.isAdmin == true (3) session.User.txtUsername == “[email protected]” It can be seen that the first two invariants are part of the “true” program specification, while the third invariantis spurious (an artifact of the limited test coverage). As a side note, the invariant for the exit point at Add.jsp: Line 7 would be session.User == null. Supported Invarients The first technique to identify real invariants is based on the insight that many vulnerabilities are due to developer oversights. That is, a developer introduces checks that enforce the correct behavior on most program paths, but misses an unexpected case where the correct behavior can be violated. To capture this intuition, we defined a technique that keeps track of which paths contain checks that support an invariant and which paths are lacking such checks. More precisely, an execution path on which a likely invariant holds and it is supported by a set of checks on that path is added to the set of supporting paths for this invariant. That is, along a supporting path, the program contains checks that ensure that an invariant is true. A path on which a likely invariant can fail is added to the set of violating paths. When a likely invariant holds on all program paths to a given program point, then we know that it holds for all executions and there is no bug. When all paths can possibly violate a likely invariant, then we assume that the programmer did not intend this invariant to be part of the actual program specification, and it is likely an artifact of the limited test coverage. An application logic error is only reported byWaler if at least one supporting path and at least one violating path are found for an invariant at a program point. Public void _jspService(HttpServletRequest req, HttpServletResponse res) { if(req.getMethod() == “GET”) { out.println(“

”); } if(req.getMethod() == “POST”) { stmt = conn.prepareStatement(“UPDATE users SET” + “ password = ?, name = ? WHERE username = ?”); stmt.setString(1, req.getParameter(“password”)); stmt.setString(2, req.getParameter(“name”)); stmt.setString(3, req.getParameter(“username”)); stmt.executeUpdate(); } } Figure 4: Simplified user profile editing vulnerability public void doPost(HttpServletRequest req, HttpServletResponse res) {sess = request.getSession(true); if(action.equals(“/editpost”)){ s = conn.prepareStatement(“UPDATE posts SET” + “ author= ?, title = ?, entry = ?” + “ WHERE id = ?”); s.setString(1, (String)sess.getAttribute(“auth”)); s.setString(2, req.getParameter(“title”)); s.setString(3, req.getParameter(“entry”)); s.setString(4, req.getParameter(“id”)); s.executeUpdate(); } } Figure 5: Simplified post editing vulnerability Vulnerability Invarients For each detected bug, Waler generates a vulnerability report. This report contains the likely invariant that was violated, the program point where this invariant belongs to, and the path on which the invariant was violated (given as a sequence of servlets and corresponding methods that were invoked). This information makes it quite easy for a developer or analyst to verify vulnerabilities. Currently, vulnerabilities are simply grouped by program points. Given the low number of false positives, this allows for an effective analysis of all reports. However, not every alert generated by Waler currently maps directly to a vulnerability or a false positive. We found several situations where several invariant violations referred to the same vulnerabilities (or a false positives) in application code.

Limitations First, the types of vulnerabilities that can be identified by Waler are limited by the set of currently-implemented heuristics.Another limitation stems from the fact that we need a tool to derive approximations of program specifications. As a result, the detection rate of Waler is bounded by the capabilities of such a tool. In the current implementation, we chose to use Daikon. While Daikon is able to derive a wide variety of complex relationships between program variables, it has a limited support for some complex data structures. Another issue that we faced when working with Daikon was scalability: in its current implementation, Daikon creates a huge data structure in main memory when processing an execution trace. As a result, using Daikon on a larger application requires a large amount of RAM. We worked around this limitation by partitioning the application into subsets of classes and by performing the likely invariant generation on each subset separately. A more import limitation of Daikon is that invariants generated by the tool cannot capture all possible relations. Another, more general, limitation of the first step of our analysis is the fact that we need to exercise the application in a © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 67 Jagruti S.Wankhade et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.61-70 “normal” way (i.e., not deviating from the developer’s intended behavior). This part cannot be fully automated and needs human assistance. Nevertheless, many tools exist to ease the task of recording and scripting browsing user activity, such as Selenium [31]. Finally, the state explosion problem is one of the main limitations of the chosen model checking approach. We have already described several heuristics that help Waler limiting the state space of an application, and currently, we are working on implementing a combination of concrete and symbolic execution techniques to further improve scalability 4. VULNURABILITIES: Easy JSP Forum: The first application that we analyzed is the Easy JSP Forum application, a community forum written in JSP. Using Waler, we found that any authenticated user can edit or delete any post in a forum. To enforce access control, the Forum application does not show a “delete” or “edit link” for a post if the current user does not have moderator’s privileges for the current forum but fails to check these privileges when a delete or an edit request is received. Thus, if a user forges a delete/edit request to the application using a valid post id (all ids can be obtained from the source code of web pages accessible by all users), a post will be deleted/modified. GIMS: The second application that we analyzed is the Global Internship Management System (GIMS) web application, a human resource management software. Using Waler, we found that many of the pages in the application do not have sufficient protection from unauthorized access. In particular, our tool correctly identified servlets that can be accessed by an unauthenticated user (a user that is not logged in at all). Most of these pages do contain a check that ensures that there is some user data in a session (which is only true for authenticated users). When a check fails, the application generates output that redirects the client’s browser to a login page. JaCoB: The third application is JaCoB, a community message board application that supports posting and viewing of messages by registered users. For this program, our tool neither found any vulnerabilities nor did it generate any false alert. However, closer analysis of the application revealed two security flaws, which could not be identified with the techniques used by Waler. For example, when a user registers with the message board or logs in, she is expected to provide a username and a password. Unfortunately, when this information is processed by the application, the password is simply ignored. Also, in this application, a list of all its users and their private information is publicly available. These two problems represent serious security issues; however, they cannot be detected by Waler because the program specification that can be inferred from the applications behavior does not contain any discrepancies with respect to the applications code. JspCart: The fourth test application is JspCart, which is a typical online store. Waler identified a number of pages in its administrative interface that can be accessed by unauthorized users. In JspCart, all pages available to an admin user are protected by checks that examine the User object in the session. More precisely, the application verifies that a user is authenticated and that the user has administrative privileges. However, Waler found that four out of 45 pages are missing the second check. Therefore, any user that has a regular account with the store can access administrative pages and add, modify, or delete settings Jebbo: We analyzed a set of eight Jebbo applications that were written by senior-level undergraduate students as a class project. Jebbo is a message board application that,allows its users to open accounts, post public messages, and update their own messages and personal information.Some of the applications also implement a message rating functionality. For this project, all students were provided with a description of the application to implement along with a set of rules (including security constraints) that were expected to be enforced by the application. 5. RELATED WORK Our work is related to several areas of active research, such as deriving application specifications, using specifications for bug finding, and vulnerability analysis of web applications. our approach is related to a number of approaches that combine dynamically-generated invariants with static analysis. The main goal of this research is to show the feasibility of the proposed approach rather than to find bugs. The main goal of this system is to decrease the false positives rate of a static bug-finding tool for stand-alone Java applications. Dynamically-generated invariants are used by the CnC tool (also based on ESC/Java) as assumptions on methods arguments and return values to narrow the domain searched by the static analyzer. Introducing our two additional techniques to differentiate © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 68 Jagruti S.Wankhade et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.61-70 between real and spurious invariants allows us to avoid many of the false positives due to limitations of the dynamic analysis step. Our work is also related to the research on using an application’s code to infer application-specific properties that can be used for guided bug finding. To the best of our knowledge, one of the first techniques that uses inferred specifications to search for application- specific errors is the work by Engler et al. [10]. Their goal is similar to ours in the sense that both works are trying to identify violations of likely invariants in applications. The way it is achieved, though, is very different in the two approaches. There is also recent work that uses statistical analysis and program code to learn certain properties of the application, with the goal of searching for application-specific bugs. Another direction of research deals with protection of web service components against malicious and/or compromised clients. Finally, our work is related to a large corpus of work, such as [16, 5, 7, 17, 18, 22, 26, 30, 33, 36, 23, 29], in the area of vulnerability analysis of web applications. However, most of this research works focus on the detection of or the protection against input-validation attacks, which do not require any knowledge of application specific rules. Our work is also related to the QED tool presented in [23]. QED uses concrete model checking (with a set of predefined concrete inputs) to identify taint-based vulnerabilities in servlet- based applications. 6.CONCLUSION In this paper, we have presented a novel approach to the identification of a class of application logic vulnerabilities, in the context of web applications. Our approach uses a composition of dynamic analysis and symbolic model checking to identify invariants that are a part of the “intended” program specification, but are not enforced on all paths in the code of a web application We implemented the proposed approaches in a tool, called Waler, that analyzes servlet-based web applications. We used Waler to identify a number of previously unknown application logic vulnerabilities in several real world applications and in a number of senior undergraduate projects. To the best of our knowledge, Waler is the first tool that is able to automatically detect complex web application logic flaws without the need for a substantial human (annotation) effort or the use of ad hoc, manuallyspecified heuristics. Future work will focus on extending the class of application logic vulnerabilities that we can identify. In addition, we plan to extend Waler to deal with a number of frameworks, such as Struts and Faces. This will require creating “symbolic” versions of the libraries included in these frameworks. This initial development effort will allow us to apply our tool to a much larger set of web applications, since most large-scale, servlet-based web applications rely on one of these popular frameworks, and the lack of their support in Waler was a serious limiting factor when choosing real-world applications for the evaluation described in this paper. REFERENCES [1] AMMONS, G., BOD´I K, R., AND LARUS, J. Mining specifications. In Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages (2002), ACM, pp. 4– 16. [2] ANAND, S., PASAREANU, C., AND VISSER, W. JPF-SE: A Symbolic Execution Extension to Java PathFinder. In Proceedings of the International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS) (2007), Springer. [3] ANLEY, C. Advanced SQL Injection in SQL Server Applications. Tech. rep. Next Generation Security Software, Ltd, 2002. [4] BALIGA, A., GANAPATHY, V., AND IFTODE, L. Automatic Inference and Enforcement of Kernel Data Structure Invariants. In Computer Security Applications Conference, 2008. ACSAC 2008. Annual (2008), pp. 77–86. [5] BALZAROTTI, D., COVA, M., FELMETSGER, V., AND VIGNA, G. Multi-module Vulnerability Analysis of Web-based Applications. In Proceedings of the ACM conference on Computer and Communications Security (CCS) (2007), pp. 25–35. [6] BOND, M., SRIVASTAVA, V., MCKINLEY, K., AND SHMATIKOV, V. Efficient, Context-Sensitive Detection of Semantic Attacks. Tech. Rep. TR-09-14, UT Austin Computer Sciences,2009. [7] COVA, M., BALZAROTTI, D., FELMETSGER, V., AND VIGNA, G. Swaddler: An Approach for the Anomaly-based Detection of State Violations inWeb Applications. In Proceedings of the International Symposium on Recent Advances in Intrusion Detection (RAID) (2007), pp. 63–86. © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 69 Jagruti S.Wankhade et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.61-70 [8] CSALLNER, C., SMARAGDAKIS, Y., AND XIE, T. Article 8 (37 pages)-DSD-Crasher: A Hybrid Analysis Tool for Bug Finding. In ACM Transactions on Software Engineering and Methodology (TOSEM) (April 2008). [9] The Daikon invariant detector. http://groups.csail. mit.edu/pag/daikon/. [10] ENGLER, D., CHEN, D., HALLEM, S., CHOU, A., AND CHELF, B. Bugs as deviant behavior: a general approach to inferring errors in systems code. ACM SIGOPS Operating Systems Review 35, 5 (2001), 57–72. [11] ERNST, M., PERKINS, J., GUO, P., MCCAMANT, S., PACHECO, C., TSCHANTZ, M., AND XIAO, C. The DaikonnSystem for Dynamic Detection of Likely Invariants. Science of Computer Programming 69, 1–3 (Dec. 2007), 35–45. [12] FOSSI, M. Symantec Global Internet Security Threat Report. Tech. rep., Symantec, April 2009. Volume XIV. [13] FOUNDATION, T. A. S. Apache Tomcat. http://tomcat. apache.org/. [14] GROSSMAN, J. Seven Business Logic Flaws That Put Your Website at Risk. http://www.whitehatsec.com/home/assets/WP bizlogic092407.pdf, September 2007. [15] GUHA, A., KRISHNAMURTHI, S., AND JIM, T. Using static analysis for Ajax intrusion detection. In Proceedings of the 18th international conference on World wide web (2009), ACM New York, NY, USA, pp. 561–570.

AUTHOR’S BRIEF BIOGRAPHY:

Ms. Jagruti S. Wankhade Master of Engineering in Information Technology, Assistant Professor in Jawaharlal Darda Institute Of Engineering & Technology, Yavatmal,Maharashtra,India.

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 70 Dr. Mrs. H. V. Sanghani. / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.71-75

An Activity- Based Approach in Learning “Polymer Chemistry”

Dr. Mrs. Heena V Sanghani Assistant Professor in Applied Science Dr. Babasaheb Ambedkar College of Engineering and Research Nagpur, India [email protected]

Abstract This paper reports the experience of activity based learning conducted in chemistry in first year engineering. It was taken into consideration for students’ observation, understanding of basics of chemistry relating to day today life. “Polymer Chemistry” unit was taught using questionnaire, quiz, posters and mini Comparative chart activity. It was observed that 80% students agreed that comparative-application activity chart was mentoring collaborative learning strategy. The students found the activity learning helpful for achieving learning outcomes. The results were also very remarkable for teacher who is open to use new activity based methods or activities in their teaching.

Keywords: Activity based learning, effective learning, student- centered learning, chemistry.

1. INTRODUCTION:

Applied Chemistry is an important subject in Engineering since it plays an important role in day- today life. It develops students’ way of thinking and scientific attitude. This gained scientific way of thinking is used by the student in day today problems in life.

DIFFERENT TEACHING METHODS AND TECHNIQUES IN TEACHING:

LECTURE METHOD: Lecture is a classic instructional method where most obvious shortcoming is the lack of interactivity and the difficulty to capture continuous attention of the learners (Wessels et al., 2007; Edwards et al 2001)1 .Despite the shortcomings; lecture is still a very common approach in teaching. Over past decade, the shortcomings have been improved with various innovative methods as audio- visual technology.

POSTER METHOD: Poster is often used to convey some specific knowledge; this instructional method requires a great deal of self-motivation to learn. It was revealed in a study that audience with higher age group and higher education qualification would be more responsive to poster [Saha et al. 2005)2

Various teaching methods and techniques are used in chemistry teaching to facilitate students’ learning and understanding several chemistry topics. Recently, because of tendency towards student- centered teaching approaches teachers are requested to employ those teaching methods and techniques that are consistent with these approaches. Students are active participants of their learning and teacher role is mainly that of facilitator in student centered teaching approaches. A key advantage of this approach is that students are exposed to academic knowledge and skill simultaneously where connection can be made to the content encouraging higher order thinking (Demirci, et al. 2010)3

71 Dr. Mrs. H. V. Sanghani. / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.71-75

2. MATERIALS AND METHODS:

This study has the design of “case study” aiming at discussing some observations regarding the use of activity based teaching in the Chemistry course. The research was undertaken by one of the author who is a chemistry faculty in a college. The study was initiated based on the author’s quest for alternative teaching methods to produce effective learning the Chemistry course and her search for them. The study reported here shows that various distinct instructional methods, techniques or strategies can safely be employed in the Chemistry course. The Chemistry course has a significant position within the engineering education programs. Since knowledge and skills gained in the course are very functional for students, effective teaching of the course will lead to effective student learning.

The author who planned and implemented this case study is Assistant Professor in Engineering Chemistry in engineering college. The activity is about the unit “Polymer Science” was carried out through question-answer Cards. Students’ contributions to the course and their achievement were observed particularly in the study. As stated earlier, the study was carried out by the author on her own students. The class was selected randomly out of ten first year engineering students in the college during the year of 2012-2013. After selecting the class, the author developed question cards for different polymeric material for “Polymer Chemistry” unit. Additionally, assignment was prepared for the same unit. One of the reasons for choosing this unit is that it is quite difficult to apply knowledge and compare their features.

DEVELOPMENT OF MINI COMPARATIVE CHARTS: Chart 1

Polypropylene Polypropylene properties · low density (weight saving) · high stiffness · heat resistance · chemical inertness · steam barrier properties (food Ropes protection) · good transparency · good impact/rigidity balance · stretch ability (film and fiber applications) · good hinge property (for example Furniture where a lid and box are made together, for DVD boxes) · high gloss (appearance) · easy to weld (design) · recyclability Door mat

CH3 CH3 n

Polypropylene CH3 CH3 CH3 CH3 CH3 CH3 CH3 Propylene

Reaction

72 Dr. Mrs. H. V. Sanghani. / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.71-75

Chart 2

Polyethylene Poly ethylene and its properties LDPE : sandwich bags, cling wrap, car covers, LDPE: squeeze bottles, liners for tanks and ponds, moisture barriers · Chemically inert, Insolvent at room temperature in most in construction solvents. · Good resistance to acids and alkalis. HDPE: · Exposure to light and oxygen results in loss of strength and freezer bags, water pipes, wire and cable loss of tear resistance. insulation, extrusion coating HDPE:

chemically inert

LDPE Sandwich bag

HDPE

wire and cable insulation

Monomer Polymer

CH3 H3C Polyethylene n Ethylene Repeat unit

Reaction

73 Dr. Mrs. H. V. Sanghani. / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.71-75

3. RESULTS AND DISCUSSION:

From the questionnaire ninety percent students agree that they enjoyed the lesson and It is believed that the knowledge can be better retained by sharing the learning experience. It is essential to inculcate a positive perception among students on chemistry as increased appreciation towards the subject would enhance the effectiveness of learning. As reported by Kunter et al. (2007)4, it is important to develop and maintain learners’ interest as it associates closely to the learning outcomes. The findings of the study clearly show that student-centered teaching approaches, specifically activity-assisted teaching, have many advantages for teaching of the chemistry topics. The study investigates the effects of the activity-assisted teaching on only one topic and class. However, it still provides some significant implications for the teaching chemistry. The students enjoyed the activity- assisted teaching and actively participated in the course. Therefore, this and similar activities seem to contribute to teaching and learning process. Since this study is a case study, only some of the significant observations are discussed in the study. It is certain that there are other subtopics that are appropriate for developing activities like “Polymer Chemistry” unit in the chemistry course. Therefore, chemistry teachers may develop activities for such subtopics in the chemistry course. In the teacher training programs, the development and use of such activities can be taught to student teachers through necessary knowledge and skills in several teacher training courses such as Special Instructional Methods or General Instructional Methods. Through such course, student teachers may be prepared to use activities in the classroom settings. However, the development and use of the activities are also important for the teachers, too. Therefore, they may be informed about these activities through in-service activities. In brief, the results of the study might be useful for the chemistry teachers who are open to use new strategies, techniques, methods or activities.

4. CONCLUSION:

This paper reveals the perception of students perceived that learning is more effective when there is a greater level of involvement; for example, the hands-on experiment of urea formaldehyde resin has educated learners on how to synthesize a polymer and at the same time they are introduced to the properties of the polymer. We also evaluated the limitations of the less favored activity i.e., poster and mini lectures, supporting the observation based on the findings of the literature. Generally, more active participation with adequate facilitation is necessary to enhance effective learning.

The findings of the study indicate some significant implications for the activity-based chemistry teaching: · The students found the course more enjoyable. · The student’s learning of the application of different polymers was of deeper and lasting. · Two or three weeks later, the students could answer correctly the questions regarding various applications of polymers indicating that they could still remember what that learned through the card activity. · The card activity positively contributed to increase the student positive attitudes and interests towards the course. · The topics taught through the card activity were more easily reinforced in contrast to those topics taught through traditional one. · The card activity increased the interaction of the students. · An increased of the active participation of the students was observed

74 Dr. Mrs. H. V. Sanghani. / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.71-75

5. ACKNOWLEDGEMENTS:

The author is thankful to the reviewers for their valuable suggestions to enhance the quality of our article.

6. REFERENCES:

1. Wessels, A., Fries, S., Horz, H., Scheele, N. & Efelsberg, W. 2007. Interactive lectures: effective teaching and learning in lectures using wireless networks. Computers in Human Behavior 23: 2524- 2537 2. Saha, A., Poddar, E. & Mankad, M. 2005. Effectiveness of different methods of health education: a comparative assessment in a scientific conference. Public Health 5 (88): 1-7. 3. Demirci, A., Kesler, T. & Kaya, H. 2010. Activity-based learning in secondary school Geography lessons in Turkey: A study from teachers’ perspective. World Applied Science Journal 11(1): 53-63. 4. Kunter, M., Baumert, J. & Koller, O. 2007. Effective classroom management and the development of subject-related interest. Learning and Instruction 17(5): 494-509.

AUTHOR’S BRIEF BIOGRAPHY:

Dr. Mrs. H. V. Sanghani: She is an assistant professor in Department of Applied Science, Dr. Babasaheb Ambedkar College of Engineering and Research, Nagpur.She is offering her services as a lecturer and Assistant Professor. Thousands of students were enriched with her knowledge. She has nearly 12 years experience in teaching. Her paper was published in reputable International Journals.

75 K.R.Sobha / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.76-79

Profit Maximization of Fuzzy Assignment Problem

K.R.Sobha, Assistant Professor, Department of Mathematics, Sree Ayyappa College For Women, Chunkankadai, Nagercoil,Tamil Nadu,India. [email protected]

Abstract

The objective of this paper is to find out the optimum assignment(maximum sales) of the fuzzy assignment problem. In this paper first consider a balanced assignment problem and it is formulated to the crisp assignment problem in the linear programming problem form and solved by using Hungarian method. Using Yager’s Ranking Method fuzzy quantities are transformed in to crisp quantities. Finally a numerical illustration is given to check the validity of the proposal.

KEY WORDS: Fuzzy sets, fuzzy assignment problem, Triangular fuzzy number, Yager’s ranking method.

INTRODUCTION The assignment problem is a special type of linear programming problem in which our objective is to assign number of salesman’s to number of districts at a minimum cost(time) or maximum sales. The mathematical formulation of the problem suggests that this is a 0-1 programming problem and is highly degenerate all the algorithms developed to find optimal solution of transportation problem are applicable to assignment problem. However, due to its highly degeneracy nature a specially designed algorithm. Widely known as Hungarian method proposed by Kuhn (1) is used for its solution.

In this paper, we investigate more realistic problem and namely the assignment problem, with fuzzy costs . Since the objectives are to minimize the total cost (or) to maximize the total profit, subject to some crisp constraints, the objective function is considered also as a fuzzy number. The methods are to rank the fuzzy objective values of the objective function by some ranking method for fuzzy number to find the best alternative. On the basic of idea the Yager’s ranking methods(6) has been adopted to transform the fuzzy assignment problem to a crisp one.

PRELIMINARIES Zadeh [7] in 1965 first introduced Fuzzy set as a mathematical way of representing impreciseness or vagueness in everyday life. FUZZY SET A fuzzy set is characterized by a membership function mapping elements of a domain, space, or universe of discourse X to the unit interval [0,1].(ie) A = {(x,m A (x);x Î X},here mA : X ® [0,1]is a mapping called the degree of membership function of the fuzzy set A and mA (x) is called the membership value of x in the fuzzy set A.These membership grades are often represented by real numbers ranging from [0,1].

TRIANGULAR FUZZY NUMBER For a triangular fuzzy number A(x) ,it can be represented by A(a,b,c,;1) with membership function m A (x) given by © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 76 K.R.Sobha / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.76-79 ìx - a ,a £ x £ b ïb - a ï ï1, x = b m A (x) = í c - x ï , b £ x £ c ïc - b ï î0,otherwise. a - cut

The a - cut of a fuzzy number A(x) is defined as A(x) = {x /m(x) ³ a,a Î[0,1]}

DEFUZZIFICATION

Defuzzification is the process of finding singleton value (crisp value) which represents the average value of the TFNs. Here use Yager’s ranking to defuzzify the TFNs because of its simplicity and accuracy.

YAGER’S RANKING TECHNIQUE

Yager’s ranking technique [6] which satisfy compensation,linarity, additively properties and provides results which consists of human intuition. If a is a fuzzy number then the Yager’s ranking is defined by

1 R(a) = (0.5)(a L ,a U )da ò a a 0 L U where (a a ,a a ) = {(b - a)a + a,c - (c - b)a}.

NUMERICAL EXAMPLE

Let us consider a fuzzy assignment problem with rows representing 5 sales men and the columns sales districts. The problem is to find the assignment of sales man to districts that will result in maximum sales.

Table 1

(22,32,42) (28,38,48) (30,40,50) (18,28,38) (30,40,50) (30,40,50) (14,24,34) (18,28,38) (11,21,31) (5,6,7) (31,41,51) (17,27,37) (23,33,43) (20,30,40) (27,37,47) (12,22,32) (28,38,48) (31,41,51) (26,36,46) (26,36,46) (19,29,39) (23,33,43) (30,40,50) (25,35,45) (29,39,49)

The given problem is a balanced Assignment problem.

In conformation to model, the fuzzy assignment problem can be formulated in the following mathematical programming form for

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 77 K.R.Sobha / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.76-79

MaxZ = R(22,32,42)x11+R(28,38,48) x12+ R(30,40,50)x13+R(18,28,38)x14+R(30,40,50)x15+ R(30,40,50)x21+R(14,24,34)x22+R(18,28,38)x23+R(11,21,31)x24+R(5,6,7)x25+R(31,41,51)x31 +R(17,27,37)x32+R(23,33,43)x33+R(20,30,40)x34+ R(27,37,47)x35+ R(12,22,32)x41+ R42+ R(28,38,48)x42+R(31,41,51)x43+R(26,36,46)x44+R(26,36,46)x45+ R(19,29,39)x51+R(23,33,43) x52+ R(30,40,50) x53+R(25,35,45)x54+ R(29,39,49)x55

Applying Yager’s ranking indices for the fuzzy costs

1 R(a) = (0.5)(a L ,a U )da ò a a 0 L U where (a a , a a ) = {(b - a)a + a, c - (c - b)a}

1 R(22,32,42) = ò (0.5)(10a + 22,42 -10a)da 0 1 R(22,32,42) = ò (0.5)(64)da = 32 0

Similarly

R(28,38,48)=38,R(30,40,50)=40,R(18,28,38)=28,R(30,40,50)=40,R(30,40,50)=40, R(14,24,34)=24,R(18,28,38)=28,R(11,21,31)x24=21,R(5,6,7)=6,R(31,41,51)=41, R(17,27,37)=27,R(23,33,43)=33,R(20,30,40)=30,R(27,37,47)=37,R(12,22,32)=22, R(28,38,48)=38,R(31,41,51)=41,R(26,36,46)=36,,R(23,33,43)=33,R(30,40,50) =40,R(25,35,45)=35, R(29,39,49)=39.

Substitute the values in fuzzy assignment problem we get the crisp assignment problem (profit matrix) ,which is the following table.

Table 2 32 38 40 28 40 40 24 28 21 6 41 27 33 30 37 22 38 41 36 36 29 33 40 35 39

Since the problem is a maximization problem ,convert it in to minimization one by subtracting each element from the maximum element [41] ,we have the following table

Table 3 9 3 1 13 1 1 17 13 20 35 0 14 8 11 4 19 3 0 5 5 12 8 1 6 2

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 78 K.R.Sobha / International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.76-79 Using Hungarian method this problem can be solved as

Table 4 D1 D2 D3 D4 D5 S1 12 0 0 7 0 S2 0 10 8 10 30 S3 0 8 4 2 0 S4 20 1 0 0 5 S5 15 5 0 0 1

The optimal assignment is S1 ® D 2 ,S2 ® D1 ,S3 ® D 5 ,S4 ® D 4 ,S5 ® D 3 . The maximum profit cost = 38+40+37+36+40 = Rs.191.

CONCLUSION TTttthTT.ijerCccccoa.com , In this article ,the assignment costs are considered as imprecise number described by fuzzy numbers which are more realistic and general in nature.More over the fuzzy assignment problem has been transformed in to crisp assignment problem using Yager’s ranking indices. Numerical example shows that by this method we can have optimal assignment (maximum) as well as the crisp and fuzzy optimal total cost.This technique can also can be used in solving unbalanced assignment problems,balanced/unbalanced transportation problems. REFERENCE

[1] H.W.Kuhn, the Hungarian Method for the assignment problem, Naval Research Logistic Quartely Vol.02.1995 PP.83-97 [2] M.Sakaw, I.Nishizaki, Y.Uemura, Interactive fuzzy programming for two level linear and linear fractional production and assignment problems, a case study. European J.Oer.Res.135 (2001) 142-157. [3] Chi-Jen Lin, Ue-Pyng Wen, A Labelling algorithm for the fuzzy assignment problem, fuzzy sets and system 142 (2004) 373-391. [4] M.S.Chen, on a fuzzy assignment problem, Tamkang.J, fuzzy sets and systems 98 (1998) 291-29822 (1985) 407-411. [5] X.Wang, fuzzy Optimal assignment problem, fuzzy math 3 (1987) 101-108. [6] R.R.Yager,: “ A procedure for ordering fuzzy subsets of the unit interval”, Information Sciences, 24, 143-161 (1981). [7] Zadeh, L. A: “Fuzzy sets, Information and Control”, 8, pp 338–353 (1965).

AUTHOR’S BRIEF BIOGRAPHY:

Dr.K.R.Sobha is a Assistant professor in Department of Mathematics ,Sree Ayyappa College for women,Chunkankadai, Nagercoil,India.She received her Ph.D degree in Mathematics from Manonmaniam Sundarnar University,Tirunelveli,Tamilnadu,India. She has sixteen years of graduate/Post Graduate teaching experience in Engineering/arts colleges.Her research fields include perishable inventory queueing system .She has published papers in Perishable inventory system, fuzzy numbers, fuzzy transportation problems, etc. in national/ international journals.

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 79 Gifty K Baby et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.80-87

Review on thermal challenges in embedded system

GIFTY K BABY1 GNANA SHEELA K2 Electronics and Communication Department, Electronics and Communication Department, Toc H Institute of Science and Technology, Kerala, India. Toc H Institute of Science and Technology, Kerala, India. Email:[email protected] Email:[email protected]

Abstract Embedded systems are used in safety critical areas such as automotive electronics and medical applications. These safety critical applications impose strict requirements on reliability, performance, low power and testability of the underlying VLSI circuits. The VLSI circuits operate very often at high temperature, which has negative impact on reliability, performance, power-efficiency and testability with silicon technology scaling. Several thermal impacts on VLSI circuits and their related challenges are discussed. This paper presents also a few emerging techniques that take temperature into account in the design and test processes. There are number of embedded computers controlling virtually all devices and systems in a huge spectrum of application areas including aerospace, manufacturing, chemical processes, healthcare care, automotive, transportation, telecommunication, and consumer appliances. Many of these systems are safety-critical, such as automotive electronics and medical equipment, with stringent reliability and real time requirements. At the same time, with silicon technology scaling, VLSI circuits used to implement the computational components of these systems are built with smaller transistors, operate at higher clock frequency, run at lower voltage levels, and operate very often at higher temperature. Consequently, they are subject to more faults and interferences.

Keywords-Dynamic Thermal Management; Burn-in; Principal Orthogonal Decomposition; Model-Based Design

1.INTRODUCTION Recently embedded system encountered many constraints such as power, energy, reliability, and temperature. Among these challenging issues, temperature related issues have become especially important within the past several years. This paper summarizes recent thermal management techniques for embedded system. Temperature monitoring, requirement for Dynamic Thermal Management (DTM), includes temperature estimation and sensor placement techniques for accurate temperature measurement or estimation. Micro architectural techniques include both static and dynamic thermal management techniques that control hardware structures. Floor planning covers a range of thermal-aware floor planning techniques for 2D and 3D microprocessors. OS/ compiler techniques include thermal-aware task scheduling and instruction scheduling techniques. Liquid cooling techniques are higher capacity alternatives to conventional air cooling techniques. Thermal reliability/security issues cover temperature-dependent reliability modeling, Dynamic Reliability Management (DRM), and malicious codes that specifically cause overheating. Temperature-related issues will only become more challenging as process technology continues to evolve and transistor densities scale up faster than power per transistor scales down. © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 80 Gifty K Baby et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.80-87 I.1 Three Modes of Heat Transfer A. Conduction Thermal conduction is the process in which thermal energy transfers through matter, from a region of higher temperature to lower temperature and acts to equalize the temperature difference. It can also be described as the heat energy transferred from one material to another by direct contact. Fourier’s Law of Conduction states that the rate of heat flow equals the product of the area normal to the heat flow path, the temperature gradient along the path and the thermal conductivity of the medium. Heat flux, “q” is the rate of heat transfer per unit area and it depends on the direction. Consider a one dimensional block with one side at a constant T1 and the others B. Convection Convection is the transfer of thermal energy between two surfaces as a consequence of a relative velocity between them. The most practical application is where one surface is a solid and the other is a fluid.ide at a constant T2, where T1 > T2. On a basic level, the convective heat transfer can be improved with higher airflow and more surface area. However, it is not always possible to make the thermal solution larger or increase the airflow, due the constraints of embedded form factors. Therefore, the thermal solution designer must factor in all the boundary conditions in order to develop a suitable solution. Convective heat transfer plays a very important role in electronics cooling. This mode of heat transfer will allow higher power processors to be cooled in most applications. C. Radiation Radiation cooling is the transfer of heat by electromagnetic emission, primarily in the infrared wavelengths. While the transfer of energy by conduction and convection requires the presence of a material medium, radiation does not. In fact, radiation transfer occurs most effectively in a vacuum. Graphically represents the radiation heat transfer between two surfaces at different temperatures. For the majority of embedded applications, radiation will result in a very small percentage of the total heat transfer. The only applications where it will have significant impact are in fan less designs. 2. LITERATURE SURVEY Oleg Semenov et al (2003) presented burn-in which is performed at elevated temperature, which is achieved by special equipment .This approach will not be able to achieve the specified temperature gradients, especially those with large magnitudes. Burn-in is a quality improvement procedure challenged by the high leakage currents that are rapidly increasing with IC technology scaling. These currents are expected to increase even more under the new burn-in environments leading to higher junction temperatures, possible thermal runaway, and yield loss during burn-in. It can be estimate the increase in junction temperature with technology scaling. It shows that under normal operating conditions, the junction temperature is increasing 1.45 /generation. The increase in junction temperature under the burn-in condition was found to be exponential. The range of optimal burn-in voltage and temperature is reduced significantly with technology scaling.

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 81 Gifty K Baby et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.80-87 Dettori M et al (2003) formulated the principal Orthogonal decomposition (POD) used to develop a low- order nonlinear model which simulation results for tracking a ramp with rate 50 C/sec with a controller scheme that includes feedback, feed forward and pre filter and investigates the application of model-based control design techniques to distributed temperature control systems. Multivariable controllers are an essential part of the modern-day rapid thermal processing (RTP) systems. This paper considers all aspects of the control problem beginning with a physics-based model and concluding with implementation of the real-time embedded controller. The thermal system used as an example throughout the paper is a RTP chamber that is widely used in semiconductor wafer processing. With its exceptionally stringent performance requirements of wafer temperature, high temperature ramp rates, RTP temperature control is a challenging distributed temperature control problem. Additionally, it is an important problem in the semiconductor industry because of the progressively smaller “thermal budget” resulting from ever decreasing integrated circuit dimensions. Jon L. E et al (2003)formulated model-based control system design which has excellent temperature control on both the low-order and the full nonlinear simulations and need for addition of run-to-run control to deal with system nonlinearities. Model-Based Design (MBD) is a mathematical and visual method of addressing problems associated with designing complex control, signal processing and communication systems. It is used in many motion controls, industrial equipment, aerospace, and automotive applications. Model-based design is a methodology applied in designing embedded software. MBD provides an efficient approach for establishing a common framework for communication throughout the design process while supporting the development cycle . In model-based design of control systems, development is manifested in these four steps: 1) modeling a plant, 2) analyzing and synthesizing a controller for the plant, 3) simulating the plant and controller, and 4) integrating all these phases by deploying the controller. Jayanth Srinivasan et al (2004) formulated RAMP industrial strength model which has high correlation between application power and temperature. The relentless scaling of CMOS technology has provided a steady increase in processor performance for the past three decades. However, increased power densities and other scaling effects have an adverse impact on long term processor lifetime reliability. This paper represents a first attempt at quantifying the impact of scaling on lifetime reliability due to intrinsic hard errors, taking workload characteristics into consideration. For our quantitative evaluation, we use RAMP previously proposed industrial strength model that provides reliability estimates for a workload, but for a given technology. Chen F et al(2004) has developed the methodology of effective thermal conductivity which allows quick evaluation of various Cullow-k campasite interconnect structures advancement in thermal properties of low-k dielectrics and better chip cooling designs could be critical to future technologies. Demonstrated that interconnect Joule heating and low thermal conductivity of low-k dielectric materials can have a large impact on chip reliability and performance.

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 82 Gifty K Baby et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.80-87 Liao w et al (2006) formulated genetic algorithm to solve problems with multiple solutions .The advantage is that it solves problems with multiple solutions but it cannot assure constant optimization response times. The value of average current becomes stable when the circuit is in the computer science field of. This heuristic (also so artificial intelligence, a genetic algorithm is a search heuristic that mimics the process of natural selection sometimes called a meta heuristic) is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms(EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover. Genetic algorithms find application in bioinformatics, phylogenetics, computational science, engineering, economics, chemistry, manufacturing, mathematics, physics, pharma cometrics and other fields. Lio.Y et al (2007) presented thermal-constrained energy optimization procedure to minimize system energy consumption under a constraint on peak temperature which optimizes energy under a constraint on peak temperature. If the bound is too loose, the system may operate at an unnecessary-high temperature average which results in 11 °C temperature reduction with 8.3% energy overhead are designed using the small cell library. .Flament et al (2009) formulated ALARA (As Low As Reasonably Achievable)low as reasonably practicable. IC modeling using fault injection and simulation techniques could be performed to evaluate mitigation efficiency. The implementation of equipments with embedded electronic to monitor, control, measure and operate future large facilities dedicated to high energy physics or nuclear fusion are necessary. Reliable operation of these equipments will be achieved through availability and reliability analysis. In several cases, the equipment selection or development approach has to be done by considering a harsh environment in terms of radiations. In order to implement these systems in such environments shielding, location and distance from the source must be considered to reduce, to protect and to avoid radiation effects. People in charge of the choice of the equipments have to take into account and mitigate radiation effects from subsystem to system level. This requires an approach integrating tradeoff between performance and reliability, between the use of the state of the art of technologies and robust and well known devices. Experience and knowledge from previous programs should be considered to build approach and strategy that may be necessary to overcome difficulties. In the present paper, we will review the main challenges faced by designers for systems implementation with embedded electronics in future facilities dedicated to international physics programs. Zebo Peng et al (2010) time-redundancy based fault-tolerance techniques handle transient faults and the hardware/ software trade-offs related to fault detection and fault tolerance with the increased silicon area, additional design effort, lower production quantities, excessive power consumption, and protection mechanisms against radiation (such as shields). It deals with the design of embedded systems for safety-critical applications,

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 83 Gifty K Baby et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.80-87 where both fault tolerance and real-time requirements should be taken into account at the same time. With silicon technology scaling, integrated circuits are implemented with smaller transistors, operate at higher clock frequency, and run at lower voltage levels. As a result, they are subject to more faults, in particular, transient faults. Additionally, in nano-scale technology, physics-based random variations play an important role in many device performance metrics, and have led to many new defects. It describes several key challenges and presents several emerging solutions to the design and optimization of such systems. In particular, it discusses the advantages of using time-redundancy based fault-tolerance techniques that are triggered by fault occurrences to handle transient faults and the hardware/ software trade-offs related to fault detection and fault tolerance. Nima Aghaee et al (2014) formulated an algorithm such as Burn in which has an advantage such as low cost in a reasonably short time and the disadvantage is that it do not sufficiently speed up the formation of the defects that depend on large temperature gradients and consequently such early-life defects will go undetected. Burn-in is usually carried out with high temperature and elevated voltage. Since some of the early-life failures depend not only on high temperature but also on temperature gradients, simply rising up the temperature of an IC is not sufficient to detect them. This is especially true for 3D stacked ICs, since they have usually very large temperature gradients. The efficient detection of these early-life failures requires that specific temperature gradients are enforced as a part of the burn-in process. This paper presents an efficient method to do so by applying high power stimuli to the cores of the IC under burn-in through the test access mechanism. Therefore, no external heating equipment is required. The scheduling of the heating and cooling intervals to achieve the required temperature gradients is based on thermal simulations and is guided by functions derived from a set of thermal equations. Peng.z et al (2014) formulated electro migration and time-dependent dielectric breakdown which is efficient but Time consuming which results in amplitude and frequency of temperature oscillation has a huge impact on the overall lifetime of a chip. More and more embedded systems are used in safety-critical areas such as automotive electronics and medical applications. These safety critical applications impose stringent requirements on reliability, performance, low power and testability of the underlying VLSI circuits. With silicon technology scaling, VLSI circuits operate very often at high temperature, which has negative impact on reliability, performance, power-efficiency and testability. This paper discusses several thermal impacts on VLSI circuits and their related challenges. It presents few emerging techniques that take temperature into account in the design and testprocesses

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 84 Gifty K Baby et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.80-87 3. COMPARATIVE ANALYSIS TABLE 1.COMPARATIVE ANALYSIS

Author Year Algorithm Advantages Disadvantages Results Peng.z et al 2014 .electro-migration and efficient Time consuming Amplitude & frequency time-dependent scillation─ has huge impact dielectric breakdown on the overall lifetime

Nima 2014 Burn in low cost in a reasonably short does not sufficiently speed up the Aghaee et al time formation of the defects that depend on large temperature gradients and consequently such early-life defects will go undetected. Zebo Peng et 2010 time-redundancy handle transient faults and increased silicon area, lower production al based fault-tolerance hardware/software trade-offs quantities, excessive power consumption, & techniques related to fault detection and protection mechanisms against radiation fault tolerance Lio.y et al 2007 thermal-constrained optimize energy under a If the bound is too loose, the system may average 11 °C temperature energy optimization constraint on peak temperature. operate at an unnecessary-high reduction with 8.3% energy procedure to minimize temperature overhead system. Weiping 2006 Genetic algorithm It solves problems with multiple cannot assure constant optimisation The value of average current Liao et al solutions. response times. become stable when the circuits are designed Jayanth 2004 RAMP [industrial High correlation between Srinivasan et stenght model] application power and al temperature F. Chen et al 2004 effective thermal allows quick evaluation of advancement in thermal interconnect conductivity various Cullow-k campasite properties of low-k dielectrics and better Joule heating and low interwnnect structures chip cooling designs could thermal conductivity of low-k be critical to future technologies. dielectric materials can have a large impact on chip reliability and performance Oleg 2003 performed at elevated not able to achieve the specified Semenov et burn-in temperature, which is achieved temperature gradients, especially those al by special equipment with large magnitudes. Dettori.m et 2003 1.principal used to develop a low-order . simulation results for al Orthogonal nonlinear tracking ramp with rate 50 decomposition (POD) model. C/sec scheme that includes feedback, feedforward

Jon L. E et al 2003 model-based control excellent need for addition of run-to-run control to system design temperature control on both the deal with system low-order and the full nonlinear nonlinearities simulations. © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 85 Gifty K Baby et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.80-87 4. CONCLUSION Embedded systems for safety-critical applications have put stringent requirements on reliability, performance, power-efficiency and testability of the underlying VLSI circuits. These different requirements are all impacted by the temperature the chip. This survey paper has discussed several of these thermal impacts and their related challenges. It has also presented briefly several emerging techniques that take temperature into account in the design and test processes of embedded systems, especially at the system level. The issues are discussed in this paper such as the influence of temperature on reliability, power consumption, and testability, are not new, taken individually. However, the interplay of these issues and their increased impacts has led to many great challenges. In particular, there are still many open problems in how to develop efficient global optimization techniques to consider the different thermal impacts and other design requirements at the same time, so that it can build highly reliable and predictable embedded systems in an efficient manner. This paper provides an overview of the reliability modeling for embedded system and a perspective of the different system level design techniques for lifetime optimization. 5. REFERENCES 1. R. Dennard.Design of Ion-Implanted MOSFET’s with Very Small Physical Dimensions. IEEE Journal of Solid-State Circuits, vol. 9, no. 5, pp. 0256–268, 1974. 2. K. Mistry.A 45nm Logic Technology with High-k+Metal Gate Transistors, Strained Silicon, 9 Cu Interconnect Layers, 193nm Dry Patterning, and 100Packaging. in IEEE International Electron Devices Meeting (IEDM), 2007, pp. 247–250. 3. M. Bohr.A 30 Year Retrospective on Dennard’s MOSFET Scaling Paper. IEEE Solid-State Circuits Society Newsletter, vol. 12, no. 1, pp. 11–13, 2007. 4. W. Liao.Temperature-Aware Performance and Power Modeling.Tech. Report, UCLA, Engr. 04-250, 2004. 5. H. Esmaeilzadeh.Power Challenges May End the Multicore Era. Communications of the ACM, vol. 56, no. 2, pp. 93–102, 2013 6. F. Reynolds.Thermally Accelerated Aging of Semiconductor ComponentsProceedings of the IEEE, vol. 62, no. 2, pp. 212– 222, 1974. 7. Semenov .O .Effect of CMOS Technology Scaling on Thermal Management During Burn-In , IEEE, 8. T. Brozek, Y. D. Cha.Temperature Accelerated Gate Oxide Degradation Under Plasma-Induced Charging.IEEE Electron Device Letters, vol. 17, no. 6, pp. 288– 290, 1996. 9. S. Kumar.Adaptive Techniques for Overcoming Performance Degradation Due to Aging in CMOS Circuits.IEEE Transactions on Very Large Scale Integration Systems (TVLSI), vol. 19, no. 4, pp. 603–614, 2011. 10. S. Ramey.Intrinsic Transistor Reliability Improvements from 22nm Tri-Gate Technology.in IEEE International Reliability Physics Symposium (IRPS), 2013, pp. 4C.5.1–4C.5.5. 11. Y. Leblebici .Design considerations for cmos digital circuits with improved hot-carrier reliability .IEEE Journal of Solid- State Circuits, vol. 31, no. 7, pp. 1014–1024, 1996. 12. V. Huard. CMOS Device Design-in Reliability Approach in Advanced Nodes,in IEEE International Reliability Physics Symposium, 2009, pp. 624–633. 13. A. Tiwari .Facelift: Hiding and Slowing Down Aging in Multicores. in Proceedings of the IEEE/ACM International Symposium on Microarchitecture (MICRO). IEEE Computer Society, 2008, pp. 129–140. 14. F. Oboril. Reducing NBTI-induced Processor Wearout by Exploiting the Timing Slack of Instructions .in Proceedings of the Conference on Hardware/ Software Codesign and System Synthesis,vol.10, 2012, pp. 443–452. 15. F. Ahmed.Wearout- Aware Compiler-Directed Register Assignment for Embedded Systems.in Proceedings of the International Symposium on Quality Electronic Design (ISQED), 2012, pp. 33–40. 16. J. Srinivasan .The Impact of Technology Scaling on Lifetime Reliability.Proc. DSN, 2004. 17. W. Huang.HotSpot: A Compact Thermal Modeling Methodology for Early-Stage VLSI Design. IEEE Trans. On VLSI Systems, 2006. 18. I Ukhov .Steady-State Dynamic Temperature Analysis and Reliability Optimization for Embedded Multiprocessor Systems. Proc. DAC, 2012 © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 86 Gifty K Baby et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.80-87 19. M. Bao . Temperature-Aware Idle Time Distribution for Leakage Energy Optimization,. IEEE Trans. on VLSI Systems, 2012. 20. N. Aghaee. An Efficient Temperature-Gradient Based Burn-In Technique ,or 3D Stacked ICs. Proc. DATE, 2014 21. F. Hawki[2] W. Huang, et al.HotSpot: A Compact Thermal Modeling Methodology for Early-Stage VLSI Design. IEEE Trans. On VLSI Systems, 2006.

AUTHOR’S BRIEF BIOGRAPHY:

Gifty K Baby: She completed her B.Tech in the Department of Electronics & Communication Engineering under CUSAT, Kerala. Currently she is pursuing M.Tech in the specialization of VLSI and Embedded System of CUSAT, Kerala.

K.Gnana Sheela: She received her Ph D in Electronics & Communication from Anna University, Chennai. Presently she is an Associate Professor in TIST. She has published 18 international journal papers. She is life member of ISTE.

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Biodiesel extracted from citrus limetta seed oil as a blend with diesel oil as alternate fuel for diesel engine

M.Mohamed Musthafa School of Mechanical Engineering SASTRA University Thanjavur, India. Email:[email protected]

Abstract Biodiesel from vegetable oils are proposed to be promising alternative fuel for the substitute of diesel fuel either partially or completely. The use of edible vegetable oils for biodiesel production is not feasible, as the demand for edible vegetable oils is tremendously increasing. Prime importance is given to alternative biodiesel feedstock like non- conventional seed oils. This study is devoted to extract the oil from citrus limetta seeds and the potential of oil extracted from these seeds for biodiesel production. Transestrification of citrus limetta seed oil was carried out using methanol and potassium hydroxide as a catalyst. Physicochemical properties of citrus limetta oil and citrus limetta biodiesel are determined. The concentration of citrus limetta biodiesel used in the test was ranged from B10, B15 and B20. Experimental results showed that the brake thermal efficiency increased as the load was increased, and the brake specific fuel consumption was slightly higher than the diesel fuel. The higher content of citrus limetta biodiesel significantly reduces the emission of CO, HC and smoke. However, NOx emissions of the blends were found to be increased significantly than diesel as blend ratio increased.

Keywords: Biodiesel, diesel, citrus limetta seed oil, Transestrification, diesel engine and emission.

1. INTRODUCTION: The conventional sources of energy such as petroleum-derived fuels, coal and natural gas are depleting and will be exhausted in the near future. The worldwide energy consumption is increasing due to rapid population growth and economic development. Because of the limited reserves of fossil fuels, increasing prices of crude oils and environmental concerns, biodiesel from vegetable oil is a viable alternative for diesel engines. [1, 2] Vegetable oil is receiving more and more attention recently because it is renewable, biodegradable, non-toxic and environment-friendly. [3,4] Direct use of vegetable oils as fuel can cause numerous engine problems like poor fuel atomization, incomplete combustion, carbon deposition, engine fouling and lubrication oil contamination, which is due to higher viscosity. Hence the viscosity of vegetable oils can be reduced by several methods which include blending of oils, micro emulsification, cracking / pyrolysis and transesterification [5]. Among this, transesterification is widely used for industrial biodiesel production [6-8]. The biodiesel is quite similar to conventional diesel fuel in its physical characteristics and can be used alone or mixed in any ratio with petroleum based diesel fuel in the existing diesel engines with no modification. Biodiesel as a neat can be used as a direct substitute for petro diesel and is technically called B100. The preferred ratio of mixture ranges between 5% (B5) and 20% (B20). The blending ratio has been investigated by various authors on CI engines. Up to 20% blending of biodiesel with diesel has shown no problems in engine parts [9-11]. Currently, more than 95% of the biodiesel is made from edible oils or conventional sources. (Soybean, rapeseed, sunflower, palm etc.,) Continuous and large-scale production of biodiesel from edible oils may cause negative impact to the world such as depletion of food supply leading to economic imbalance.[12, 13] Taking these factors into consideration, non- conventional and non-edible oils definitely have the advantage over edible oils as biodiesel feed stocks. Therefore, exploring alternative biodiesel feed stocks like non-edible vegetable oils should be an important objective for biodiesel industries in near future. There is no information in the literature on the use of oil obtained from waste seeds of citrus limetta. Citrus limetta grows tropical and subtropical climates. It begins bearing fruit at 5 to 7 years old, with peak production at 10 to 20 years. They produce about 300-1000 fruits per year. In © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 88 M.Mohamed Musthafa /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.88-97 India, it is available during the months of July and August and also from November to March. They can be used only for extracting juice and their seed not to be used. But these seeds contain 30-40% of oil. Therefore this study identifies viability of biodiesel production from citrus limetta seeds oil by transesterification method with methanol using alkali catalyst. Citrus limetta biodiesel was blended with diesel at the proportion of 10%, 15% and 20% by volume and experimentally investigated the performance and emission characteristics of diesel engine. 2. MATERIALS AND METHODS

2.1 Materials

The materials were used as methyl alcohol of 99.9% purity and KOH pellets of 98.2% purity. Oil was extracted from seeds in goyum 1500 model oil expeller. Citrus limetta fruits and seeds are shown in figure 1.

Figure1. Photographic view of citrus limetta fruits and seeds

2.2 Transesterification process

One litre of citrus limetta oil is taken in a three necked flask which is heated till temperature reaches to 650C on magnetic stirrer. The potassium hydroxide and methanol was prepared in order to maintain the molar ratio of 6:1 [14-18]. The prepared methanolic solution was added slowly and heated for one and half hour. After the reaction, the oil was transferred to a separating funnel for glycerol separation. The upper layer was the biodiesel and the bottom layer was glycerin. The upper layer of ester was separated out. The separated ester was washed with warm water (around 10% volume of ester) to remove the catalyst present in the ester and then the washed biodiesel was heated to 1100C for removal of moisture. By this process, 92% yield of biodiesel was obtained. The properties of prepared biodiesel fuel were tested in our research laboratory as per ASTM standards [19-22]. The kinematic viscosity of the fuel blends at 400C was measured using a viscometer as per ASTM D445 standards. ASTM D1298 standard was employed using digital density meter to determine the density. Flash and re point testers (ASTM D93) were used to determine the ash and re points of the fuel. The caloric value of the fuel was determined by bomb calorimeter (ASTM D420) and is listed in Table 1.

Table 1. Physicochemical properties of diesel, citrus limetta seed oil and biodiesel from citrus limetta seed oil. Biodiesel from Citrus limetta Properties Diesel citrus limetta seed seed Oil oil Density (kg/m3) 857 964 844 Viscosity @40oC (cSt) 2.95 39.4 4.3 Calorific Value (MJ/kg) 42.96 37.2 39.7 Flash point (o C) 66 187 136 Fire point (o C) 79 225 149

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2.3. Experimental setup

Experiments were carried out in a single cylinder, four stroke, constant speed, water cooled direct injection diesel engine and the detailed engine specications are given in the Table 2. The photographic view of experimental setup is shown in figure 2. The engine was coupled with an eddy current dynamometer to apply different engine loads. Chromel Alumel (k-type) thermo-couples were installed to measure gas temperature at inlet and outlet ducts. The fuel consumption was measured by the use of a 50 cc graduated burette and stop watch. The smoke intensity was measured by an AVL 437 smoke meter. Nitrous oxides (NOx), Carbon monoxide (CO), Hydrocarbon (HC) and Carbon dioxide (CO2) were measured by AVL 444 Di gas analyzers. Then the fuel consumption, exhaust gas temperature and exhaust emissions such as NOx, CO, HC, CO2 and smoke were measured and recorded for different loads. The engine was rst started by manual cranking with diesel as a fuel and it was allowed to reach its steady state (for about 30 min). The test fuels included a conventional diesel fuel and three different citrus limetta biodiesel blends (B10, B15 and B20).

Table 2. Engine specifications

Make Kirloskar-TV1 Number of cylinder One Bore 87.5mm Stroke 110mm Compression ratio 17.5:1 Dynamo meter arm length 195mm Rated speed 1500 rpm Rated output 5.2kW Engine loading device Eddy current dynamo meter Injection pressure 205bar Fuel injection timing 23-bTDC

Figure 2. Photographic view of experimental setup © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 90 M.Mohamed Musthafa /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.88-97 3. RESULTS AND DISCUSSION

3.1 Performance Analysis

Engine performance characteristics are the major criterion that governs the suitability of a fuel [23-25]. This study is concerned with the evaluation of brake specific energy consumption (BSEC) and brake thermal efficiency (BTE) of the biodiesel-diesel blends. The performance test was carried out in a single cylinder diesel engine and graphs are plotted between brake power and above parameters respectively. Figure 3&4 gives a comparison of four different samples with BTE and BSEC plotted against the brake power individually. The four samples are pure diesel, B10, B15 and B20. From the graphs it is concluded that B15 and B20 blends exhibited better and the same performance nearly. Brake thermal efficiency is the ratio of brake power to the energy released during the combustion process. Figure 3 shows the variations of brake thermal efficiency of biodiesel blends with respect to diesel fuel. It was found that BTE of citrus limetta biodiesel blends is slightly higher than that of diesel fuel. The maximum BTE of B20 fuel is 30% and those of diesel is 27%. This might be due to the improved combustion which is caused by greater oxygen content of biodiesel molecule and better ignition quality of biodiesel blends. Similar results were also reported in the literature [26].

Figure 4 shows the variation of BSEC with respect to brake power for various citrus limetta biodiesel blends and petroleum diesel. When fuels with different heating value are tested, it is better to compare the brake specific energy consumption instead of specific fuel consumption. It is observed that, as the load increases, BSEC of all fuels decreases. At full load condition, the difference in BSEC of all biodiesel blends and diesel was found to be marginal. This might be attributed to the combined effect of lower heating value, higher density and viscosity. The brake specific energy consumption is high when compared with the normal diesel. However, the brake thermal efficiency proved to be slightly high when compared with the normal diesel.

B20 30 B15 B10 DIESEL

20 Brake Thermal Efficiency (%) 15

10 0 1 2 3 4 5 Brake Power( KW)

Figure 3. Comparison of brake thermal efficiency of test fuels at different loads

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DIESEL B10 25 B15 B20

15 Brake specific energy consumption (MJ/KWh) consumption energy specific Brake

10 0 1 2 3 4 5 6 Brake power(KW)

Figure 4. Comparison of BSEC of test fuels at different loads

3.2 Engine Emissions

This study compares the emissions of major pollutants like oxides of nitrogen, carbon monoxide, unburned hydrocarbon and smoke of citrus limetta biodiesel blends with diesel and pure diesel. Figure 5-8 shows the comparison of exhaust gas variations for four different samples with respect to the brake power. The blended fuel results tend to give absolutely positive results in compared with diesel fuel.

3.2.1 Exhaust gas Temperature

Figure 5 shows the exhaust gas temperature variations for test fuels with load. It is observed that the exhaust gas temperature increases with load because more fuel is burnt at higher loads to meet the power requirement. It is also observed that the exhaust gas temperature increases with B10; B15 &B20 test fuel for all the loads. This may be due to the higher oxygen content of the biodiesel, which improves combustion and thus may increase the exhaust gas temperature.

400

DIESEL B10 B15 C)

0 300 B20

200 Exhaust gas temperature (

100

0 1 2 3 4 5 6 Brake power (KW) Figure 5. Comparison of exhaust gas temperature of test fuels at different loads

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3.2.2 Nitrogen Oxides (NOX) emission

The variation of Oxides of Nitrogen (NOX) concentration with load for biodiesel blends and diesel is shown in Figure 6. NOX increase may be associated with the oxygen content of the citrus limetta biodiesel, since the oxygen present in the fuel may provide additional oxygen for NOX formation. Another factor causing the increase in NOX could be the possibility of higher combustion flame temperatures (evidenced in higher exhaust temperature) arising from improved combustion. It has to be noted that a larger part of the combustion is completed before TDC for citrus limetta biodiesel and its blends compared to diesel due to their lower ignition delay. So it is highly possible that higher peak cycle temperatures are reached for citrus limetta biodiesel blends compared to diesel. However NOX can be controlled by adopting exhaust gas recirculation and by employing suitable catalytic converters.

1000

DIESEL B10 800 B15 B20

600

400 Oxides of Nitrogen (ppm) of Nitrogen Oxides 200

0 0 1 2 3 4 5 6 Brake power (KW)

Figure 6. Comparison of NOX emission of test fuels at different loads

3.2.3 Carbon Monoxide (CO) emission

Figure 7 gives the comparison of the carbon monoxide (CO) emission of biodiesel blends with conventional diesel. CO is one of the intermediate compounds formed during the intermediate combustion stage of hydrocarbon fuels. CO formation depends on air fuel equivalence ratio, fuel type, combustion chamber design, starting of injection timing, injection pressure and speed. Experimental results reveal that the emission of CO is reduced by 15% & 20% for B15 andB20 test fuel when compared to diesel at rated load condition. The results for the CO emissions are in-line with most of the literature [27, 28]. This is due to the oxygen content in biodiesel which allows more carbon molecules to oxidize when compared with diesel fuel. The presences of lower CO indicate the chemical energy of the fuel which is completely utilized during combustion process.

3.2.4 Hydrocarbon (HC) emission

The unburnt hydrocarbons (UBHC) emissions with B10, B15 &B20 test fuels are compared with diesel is shown in Figure 8. HC emissions are reduced over the entire range of loads for blended test fuel. It decreases with increase in percentage of biodiesel in the blend. Since the citrus limetta seed oil biodiesel is an oxygenated fuel, it promotes better combustion and results in reduction in UBHC emissions. A 37% reduction of UBHC was observed in the case of B20 as compared to diesel.

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1.0

0.8 B20 B15 B10 DIESEL 0.6

0.4 CO(% by volume) CO(%

0.2

0.0 0 1 2 3 4 5 6 brake power (KW)

Figure 7.Comparison of CO emission of test fuels at different loads

DIESEL 70 B10 B15 B20 60

HC(ppm) 40

10 0 1 2 3 4 5 6 Brakepower (KW) Figure 8. Comparison of hydro carbon emission of test fuels at different loads

3.2.5 Smoke density

The comparison of smoke density between citrus limetta seed oil biodiesel blends and diesel is given in Figure 9. As seen in the figure 9, blended test fuel significantly reduces smoke. Smoke or soot primarily comprises of carbon particles. The improved combustion characteristics of biodiesel may lead to fewer unburnt fuel particles impinging on cylinder walls (wall quenching). A vast reduction in smoke intensity is observed with increase in percentage of biodiesel in the blend, especially at high loads.

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100

DIESEL B10 90 B20 B15

60 Smoke density (HSU) density Smoke

40 0 1 2 3 4 5 6 Brake power (KW)

Figure 9. Comparison of smoke density of test fuels at different loads

4. CONCLUSION

In the present investigation, the performance and emission characteristics of a direct injection compression ignition engine fueled with citrus limetta biodiesel blends with diesel (B10, B15& B20) have been discussed and compared with diesel fuel. Results of the present work are summarized as follows: Brake specific energy consumption increases with increase in percentage of CLSO biodiesel in the fuel due to the lower calorific value of it. It was 9.52% higher for B20 fuel than that of diesel at rated load condition. The brake thermal efficiency increases with increase in percentage of citrus limetta biodiesel in the fuel. It was 2% higher for B20 fuel than that of diesel at rated load condition. It is also observed that there is significant reduction in CO, UBHC and smoke emissions for biodiesel blends compared to diesel fuel. However, NOX emission of biodiesel is marginally higher than petroleum diesel. The waste citrus limetta seed as potential feedstock for future biodiesel production and reduces the production cost. Citrus limetta biodiesel and their blends satisfy the important fuel properties as per ASTM specification and improve the performance and emission characteristics of engine significantly. Finally, it was concluded that biodiesel blend of 20 percent by volume in the diesel may be used successfully as an alternative fuels in diesel engines.

REFERENCE

[1] D.C Deka, and S. Basumatary, “High quality biodiesel from yellow oleander (Thevetia peruviana ) seed oil”, Biomass Bio energy,vol.35, pp. 1797-1803,2011. [2] S. Basumatary, “Non-Conventional Seed Oils as Potential Feed stocks for Future Biodiesel Industries- A Brief Review”, Research Journal of Chemical Sciences,vol.3(5), pp.99-103, 2013. [3] M.M. Gui, K.T.Lee, and S. Bhatia, “Feasibility of edible oil vs. non-edible oil vs. waste edible oil as biodiesel feedstock”, Energy, vol.33, pp,1646-1653, 2008.

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 95 M.Mohamed Musthafa /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.88-97 [4] S. Chattopadhyay, A. Karemore, S. Das, A. Deysarkar, and R. Sen, “Biocatalytic Production of Biodiesel from Cottonseed Oil: Standardization of Process Parameters and Comparison of Fuel Characteristics”, Applied Energy, vol. 88, pp. 1251-1256, 2011. [5] Shailendra Sinha, Avinash Kumar Agarwal, and Sanjeev Garg, “Biodiesel development from rice bran oil: Transesterification process optimization and fuel characterization”,Energy Conversion and Management, vol.49, pp.1248-1257, 2008. [6] D.Y.C. Leung, X. Wu, and M.K.H. Leung, “A review on biodiesel production using catalyzed Transesterification”, Applied Energy, vol.87, pp. 1083-1095, 2010. [7] S. Basumatary, “Non-Edible Oils of Assam as Potential Feed stocks for Biodiesel Production: A Review”, Journal of Chem. Bio. Phy. Science, vol.3(1), pp.551-558, 2013. [8] S.R. Mishra, M.K. Mohanty, S.P. Das, and A.K. Pattanaik, “Production of biodiesel (methyl ester) from simarouba glauca oil”, Res. J. Chem. Science, vol.2(5), pp. 66- 71, 2012. [9] S. Sinha, A.K. Agarwal, and S. Garg, “Biodiesel development from rice bran oil: transesterification process optimization and fuel characterization”, Energy Conversion and Management, vol.49, pp. 1248-1257. 2008. [10] Q. Shu, J. Gao, Z. Nawaz, Y. Liao, D. Wang, and J. Wang, “Synthesis of Biodiesel From Waste Vegetable Oil with Large Amounts of Free Fatty Acids using A Carbon- based Solid Acid Catalyst”, Applied Energy, vol.87, pp.2589-2596, 2010. [11] B. Tesfa, R. Mishra, F. Gu, and N. Powles, “Prediction Models for Density and Viscosity of Biodiesel and their Effects on Fuel Supply System in CI Engines” Renewable Energy, vol.35, pp.2752-2760, 2010. [12] B.R. Moser, and S.F. Vaughn, “Coriander seed oil methyl esters as biodiesel fuel: Unique fatty acid composition and excellent oxidative stability”, Biomass Bio energy, vol.34, pp.550-558, 2010. [13] F. Saloua, C. Saber, and Z. Hedi, “Methyl ester of [Maclura pomifera (Rafin.) Schneider] seed oil: Biodiesel production and characterization”, Bio resource Technology, vol.101, pp.3091-3096, 2010. [14] A.K. Agarwal, and L.M. Das, “Biodiesel development and characterization for use as a fuel in compression ignition engines”, A.S.M.E J Eng, Gas Turbines Power,vol.123, pp.440-447, 2000. [15] P.K. Sahoo, L.M. Das, and S.N. Naik, “Biodiesel development from high acid value polanga seed oil and performance evaluation in a CI engine” Fuel, vol.86, pp.448- 454, 2007. [16] Alok Kumar Tiwari, Akhilesh Kumar, and Hifjur Raheman, “Biodiesel production from jatropha oil (Jatropha curcas) with high free fatty acids: An optimized process”, Biomass and Bio energy, vol.31, pp.569-575, 2007. [17] S.K. Karmee, and A. Chadha, “Preparation of biodiesel from crude oil of Pongamia pinnata”, BioResource Technology, vol.96, pp.1425-1429, 2005. [18] E. Alptekin, and M. Cnakc, “Determination of the Density and the Viscosities of Biodiesel-Diesel Fuel Blends”, Renewable Energy,vol.33, pp.2623-2630, 2008. [19] P. Benjumea, J. Agudelo, and A. Agudelo, “Basic Properties of Palm Oil Biodiesel- Diesel Blends”, Fuel, vol.87, pp. 2069-2075, 2008. [20] F. Karaosmanoglu, M. Tuter, E. Gollu, S. Yanmaz, and E. Altintig, “Fuel Properties of Cottonseed Oil”, Energy Sources, vol.21(9), pp.821-828, 1999. [21] Z. Al-Hamamre, and A. Al-Salaymeh, “ Physical Properties of (Jojoba Oil+Biodiesel), (Jojoba Oil+Diesel) and (Biodiesel+Diesel) Blends” Fuel, vol.123, pp.175-188, 2014. [22] H. Raheman, and S.V. Ghadge, “Performance of compression ignition engine with mahua (Madhuca indica) biodiesel”, Fuel, vol.86(16), pp.2568-2573, 2007. [23] T.C. Herchel, Machacon, S. Seiichi, K. Takao, and N. Hisao, “Performance and emission characteristics of a diesel engine fueled with coconut oil-diesel fuel blend”, Biomass and Bio energy, vol.20, pp.63-69, 2001. © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 96 M.Mohamed Musthafa /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.88-97 [24] M.J. Haa, K.M. Scott, T.L. Alleman, and R.L. McCormick, “Engine performance of biodiesel fuel prepared from soybean soap stock: a high quality renewable fuel produced from a waste feedstock Energy”, Fuel, vol. 15, pp. 1207-1212, 2001. [25] M. Mohamed Musthafa, S.P. Sivapirakasam, and M. Udayakumar, “Comparative studies on fly ash coated low heat rejection diesel engine on performance and emission characteristics fueled by rice bran and pongamia methyl ester and their blend with diesel”, Energy, vol.36, pp.2343-2351, 2011. [26] A.N. Ozsezen, M. Canakci, A. Turkcan, and C. Sayin, “Performance and combustion characteristics of a DI diesel engine fueled with waste palm oil and canola oil methyl esters”, Fuel, vol.88, pp.629-636. 2009. [27] M. Canakci, “Combustion characteristics of a turbocharged DI compression ignition engine fueled with petroleum diesel fuels and biodiesel”, Bio resource Technology , vol.98, pp.1167-1175, 2007. [28] G.L.N. Rao, S. Sampath, and K. Rajagopal, “Experimental studies on the combustion and emission characteristics of a diesel engine fueled with used cooking oil methyl ester and its diesel blends”, Int.Journal of Engineering Applied Science, vol.4, pp.64- 70, 2008. [29] N. Nabi, and M. Rahman Akhter, “Biodiesel from cotton seed oil and its effect on engine performance and exhaust emissions”, Applied Thermal Engineering, vol.87, pp.714-722, 2009. [30] P.K. Sahoo, and L.M. Das, “Combustion analysis of Jatropha, Karanja and Polanga based biodiesel as fuel in a diesel engine”, Fuel, vol.88, pp.994-999, 2009.

AUTHOR’S BRIEF BIOGRAPHY

Dr. M. Mohamed Musthafa: He is presently working as a senior Assistant professor in school of Mechanical Engineering, SASTRA University, Thanjavur, Tamilnadu. He has a vast teaching experience of two decade at undergraduate level in different reputed institution. He has large number of research paper to his credit. His area of interest includes alternate fuels, Low heat rejection engine, heat transfer and solar energy.

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An Innovative Algorithm to Enhance Security

V. S. S. K. Anand V. Sai Supreetha 4/4 B.Tech (Information Technology) 4/4 B.Tech (Information Technology) Bapatla Engineering College Bapatla Engineering College Bapatla, India Bapatla, India [email protected] [email protected]

Abstract The m ain aim of this paper is to propose an innovative algorithm for secure data exchange between the sender and receiver. The innovative algorithm boosts of a stronger cipher than its classical counterparts. A cipher, produced as a result of encryption, is said to be strong if it has more confusion and diffusion[1], which makes it very difficult to crack by third parties or hackers. This novel hybrid cipher is obtained by combining the classical ciphers like Hill[4] and Vigenere cipher[8] with diffusion and confusion properties. This paper analyses the avalanche effects[9] between the aforementioned classical ciphers.

Keywords: Cryptography, Encryption, Decryption, Random Matrix, Keys Exchange, Ciphertext, Avalanche Effect

1. INTRODUCTION:

In today’s world of ubiquitous computing security has become a major criterion to ensure safe data exchange between sender and receiver. This involves encryption, which is done at sender’s side, and decryption done at the receiver’s side. The main aim of encryption is to convert the message which is in plain form to unintelligible form called as cipher. This cipher so obtained need to be strong enough that it won’t be used to get back the original message easily. Usually encryption involves a key and an encryption algorithm which when applied on original message gives the cipher. The strength of the cipher depends on both the strength of the key and the algorithm.

Speaking of keys, cryptography is divided largely into two types based on them– Symmetric key cryptography and Asymmetric key cryptography. As the name itself gives the idea, symmetric key cryptography deals with same key being used for both encryption and decryption. Asymmetric key uses different keys for encryption and decryption. Also, we can classify cryptography based on the techniques used - conventional or public key. In conventional cryptography only one key is used on both sender and receiver side, either same or different. In public key cryptography there are two keys – public and private – for both sender and receiver.

Key Key

Unintelligible form

Encryption Decryption

Cipher text Plaintext Plaintext

Figure 1 : Process of encryption and decryption in cryptography

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Classical cipher algorithms like Caesar cipher, Vigenere cipher, Hill cipher, Playfair cipher, Mono alphabetic cipher have been proved to be less efficient in providing enough security to the plaintext. They basically are failing to the modern cryptanalysis attacks and hence are proved to be less secure and easy to crack. While they don’t work out individually, combining them with some additional properties might do the trick of making them more secure which is basically the premise of this paper. Here comparison in avalanche effects [2] of individual ciphers and the proposed combination is being made to justify the result. Avalanche effect is the number of changed bits from original cipher to the cipher obtained by small variation in plaintext. The reason for using this property to determine the strength of the cipher is it determines the degree of randomness and hence the difficulty in getting back the original message.

2. Algorithm:

As discussed earlier the proposed algorithm is an amalgamation[3] of Hill cipher and Vigenere cipher. In classical cryptography, the Hill cipher is a polygraphic substitution cipher based on linear algebra. Coming to Vigenere, it is a simple form of polyalphabetic substitution.

Hill Cipher :

In Hill a n x n matrix is taken as key and the plaintext is taken as a vectors of length n and multiplied with key matrix to generate cipher text and inverse matrix multiplication is performed to generate plaintext back. An illustration of Hill cipher algorithm is given below:

Encryption Process in Hill Cipher algorithm:

4 5 K1 = [ ] K2 = 2 (since 2 x 2 matrix) 3 6

Plaint text = WALK

WALK  W = 22, A = 0, L = 11, K = 10

푊 퐿 22 11  [ ] 퐴 퐾 0 10

4 5 22 88 10 퐾 [ ] x [ ] = [ ]  [ ] (mod 26)  [ ] 3 6 0 66 14 푂

4 5 11 94 16 푄 [ ] x [ ] = [ ]  [ ] (mod 26)  [ ] 3 6 10 93 15 푃

W A L K  K O Q P

Decryption Process in Hill Cipher algorithm:

4 5 Now using K1 = [ ] Perform Hill cipher decryption. 3 6

Here inverse of K1 matrix exist and when the product of K1 is done with its inverse we get Identity matrix. © IJMSET-Advanced Scientific Research Forum (ASRF),All Rights Reserved “ASRF promotes research nature, Research nature enriches the world’s future”

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-1 -1 6 −5 K1 = 9 *[ ] (mod 26) −3 4

6 21 18 63 18 11 3 * [ ] [ ] (mod 26)  [ ] 23 4 69 12 17 12

K = 10 C = 16 O = 14 P = 15

18 11 10 22 [ ] x [ ] (mod 26)  [ ] 17 12 14 0

18 11 16 11 [ ] x [ ] (mod 26)  [ ] 17 12 15 10

22  W, 0  A, 11  L, 10  K

Vigenere Cipher:

For both Encryption and Decryption we will be using Vigenere Square. Here in Vigenere cipher only uppercase is used and lowercase letter are converted to uppercase and then encryption and decryption is done. An illustration of Vigenere cipher algorithm is given below:

Encryption Process in Vigenere Cipher algorithm:

Plaintext = WALK and Key = OMG

Using Vigenere Square we map

W * O  K A * M  M L * G  R K * O  Y

Final cipher text = KMRY

Decryption Process in Vigenere Cipher algorithm:

Cipher text = KMRY and Key = OMG

Using Vigenere Square we map

O * K  W M *M  A G * R  L O * Y  K

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Now the let us see about how encryption and decryption are done using the proposed algorithm.

Encryption process of proposed method:

1. A square matrix K1 is taken (as key in hill cipher). 2. Value of number of rows / columns is taken as K2. 3. The plaintext which we want to encrypt is taken and each letter is represented with its corresponding value in alphabet (A = 0, B = 1, C=2, D=3… Z = 25) not considering the case. 4. To encrypt a message, each block of letters of length ‘n’ is considered as an n- component vector and is multiplied by K1 which is an n × n matrix. 5. The matrix K1, which is used in encryption, should be chosen randomly from the set of invertible n × n matrices (modulo 26). 6. To decrypt the message, each block is multiplied by the inverse of the matrix used for encryption. 7. Take another key K3 to use for Vigenere cipher encryption. 8. Now Vigenere cipher operation is done on the output obtained after performing Hill cipher on plaintext. 9. Now the output obtained after Vigenere operation is taken and first letter of the cipher text is XORed with the K2 and the output of this is again XORed with the next letter of the cipher text and continued this way for all letters to increase complexity.

Decryption process of proposed method:

1. Keys K1, K2, K3 are used at decryption side since we used a symmetric key cryptography. 2. First take the final cipher text generated during the encryption phase. Now take key K2 and do XOR between K2 and first letter of ciphertext and XOR between second letter and first letter and so on until all the letters are covered. 3. Now perform Vigenere cipher operation on the output obtained in step 2 using K3. 4. The result obtained in step 3 is decrypted using Hill cipher decryption mechanism.

3. RESULTS AND DISCUSSION:

The main beauty of this algorithm is that the final cipher generated is stronger and also may have special characters making it difficult to various kinds of plaintext attacks. Another important thing here is to transfer all the keys securely and secretly and for that we take the help of existing techniques [7] To understand the algorithm even better see the below example:

Encryption Process:

4 5 K1 = [ ] K2 = 2 (since 2 x 2 matrix) 3 6

Plaint text = WALK

WALK  W = 22, A = 0, L = 11, K = 10

푊 퐿 22 11  [ ] 퐴 퐾 0 10

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4 5 22 88 10 퐾 [ ] x [ ] = [ ]  [ ] (mod 26)  [ ] 3 6 0 66 14 푂

4 5 11 94 16 푄 [ ] x [ ] = [ ]  [ ] (mod 26)  [ ] 3 6 10 93 15 푃

W A L K  K O Q P

Now Vigenere operation is performed on K O Q P using K3 = OMG

K O Q P * O M G  Y A W D (Using Vigenere table)

Now take K2 = 2 and convert it into its binary from its ASCII equivalent = 00110010

Now take binary equivalents of ASCII values of Y A W D

Y = 01011001 A = 01000001 W = 01010111 D = 01000100

2 ⊕ Y  00110010 ⊕ 01011001  01101011  k (Binary to ASCII Conversion) k ⊕ A  01101011 ⊕ 01000001  00101010  * * ⊕ W  00101010 ⊕ 01010111  01111101  } } ⊕ D  01111101 ⊕ 01000100  00111001  9

Final cipher text = k * } 9.

Since we are using XOR operations there is a chance of occurrence of special characters like +, &, *, . For example in the above case instead of c ⊕ D if we take any other case like t ⊕ R we get 100110 whose ASCII equivalent is ‘&’. Now let us see how the decryption is done.

Decryption Process:

Now the cipher text we have is k * } 9.

Keys used in the encryption process are used here also. Hence keys we have are

4 5 K1 = [ ] K2 = 2 (since 2 x 2 matrix) K3 = OMG 3 6

Now do X-OR operation for 2 and k

2 ⊕ k  00110010 ⊕ 01101011  01011001  Y ( Binary to ASCII Conversion ) k ⊕ *  01101011 ⊕ 00101010  01000001  A * ⊕ }  00101010 ⊕ 01111101  01010111  W } ⊕ 9  01111101 ⊕ 00111001  01000100  D

102

V.S.S.K.Anand et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.98-104 Now we have Y R M D and using K3 = O M G perform Vigenere decryption.

O * Y  K M * A  O G * W  Q O * D  P

4 5 Now using K1 = [ ] Perform Hill cipher decryption. 3 6 Here inverse of K1 matrix exist and when the product of K1 is done with its inverse we get Identity matrix.

-1 -1 6 −5 K1 = 9 *[ ] (mod 26) −3 4

6 21 18 63 18 11 3 * [ ] [ ] (mod 26)  [ ] 23 4 69 12 17 12

K = 10 C = 16 O = 14 P = 15

18 11 10 22 [ ] x [ ]  [ ] 17 12 14 0

18 11 16 11 [ ] x [ ]  [ ] 17 12 15 10

22  W, 0  A, 11  L, 10  K

As it can be seen from the above result that the decryption is a piece of cake when we know the keys being used. Here it is imperative that a random key generation algorithm is used to generate the matrix in Hill Cipher. This is important because the core cipher being used is susceptible to plaintext attack and is proved so already.

Comparison of avalanche effects in Hill, Vigenere and proposed Hybrid Cipher algorithms.

Cipher used Plaintext Changed Cipher Cipher Number Avalanche (case 1) Plaintext generated generated Of bits effect (case 2) (in case 1) (in case 2) changed (in %)

Hill WALK WCLK KOQP UAQP 7 21.8% Cipher Vigenere WALK WCLK KMRY KORY 1 3% Cipher Hybrid WALK WCLK k*}9 {6a% 10 31.25% Cipher

4. CONCLUSION:

It is observed that the avalanche effect, is relatively higher than the Hill cipher and Vigenere cipher taken individually. It is also observed that this effect is more pronounced when the input size is significantly larger. Therefore the bigger the message is and correspondingly bigger the © IJMSET-Advanced Scientific Research Forum (ASRF),All Rights Reserved “ASRF promotes research nature, Research nature enriches the world’s future”

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V.S.S.K.Anand et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.98-104 random matrix used for Hill Cipher[5][6], the more secure the obtained cipher.

The future scope of this work would be to extend this cipher with few other modern techniques where there are more rounds in encryption and decryption process. It is to be noted that if a small input with single round could produce this variation in the avalanche effect, then it would be an interesting work as a future scope to combine this with techniques like DES or AES and analyze the result.

5. ACKNOWLEDGEMETNS: Extremely thankful to the reviewers for their valuable suggestions which helped to enhance the quality of this paper.

6. REFERENCES:

[1] Cryptography and Network Security, Fifth Edition. by William Stallings. [2] Comparing Classical Encryption with Modern Techniques by Mohit Kumar, Reena Mishra, Rakesh Kumar Pandey and Poonam Singh. [3] Developing a Modified Hybrid Caesar Cipher and Vigenere Cipher for Secure Data Communication O.E. Omolara, A.I. Oludare and S.E. Abdulahi. [4] Hill cipher from Wikipedia. [5] Novel Methods of Generating Self-Invertible Matrix for Hill Cipher Algorithm. by Bibhudendra Acharya, Girija Sankar Rath, Sarat Kumar Patra, and Saroj Kumar Panigrahy [6] On the Keyspace of the Hill Cipher Jerey Overbey, William Traves and Jerzy Wojdylo. [7] Secret Key Exchange : http://technet.microsoft.com/en-us/library/cc962035.aspx [8] Vigenere Cipher - Wikipedia. [9] Wikipedia – Avalanche Effect

AUTHOR’S BRIEF BIOGRAPHY:

V.S.S.K Anand: He is currently pursuing his B.Tech in the field of Information Technology at Bapatla Engineering College, Bapatla. He is a Microsoft Student Associate and Firefox Student Ambassador. He is also a Microsoft Specialist, VM Ware certified associate, Webmaker mentor for Mozilla, had organized webinars for 600+ women students as part of Microsoft Women In Tech initiative. Some of his achievements include being winner of Windows 8 App Update Challenge, Winner of Google Mapathon 2013. He aspires to get into one of the top universities for his higher studies in Computer Science.

. V.S.Supreetha: She is currently pursuing her B.Tech in the field of Information Technology at Bapatla Engineering College, Bapatla. She is a VMWare certified associate in Cloud, Data Center Virtualization and Work Force Mobility. She is a member of Student Network Team, IEEE Hyderabad

Section. She is an avid Competitive Programmer and a MOOC enthusiast. She aspires to become a Data scientist by pursuing higher studies in Computer Science.

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CONCEPTS ON TERNARY SEMIRINGS

1 2 Dr.D. Madhusudana Rao . G SrinivasaRao , Lecturer and Head, Asst. Professor, Department of Mathematics, Department of Mathematics, VSR & NVR College, Tenali, A.P. Tirumala Engineering College, [email protected], Narasarao Pet, A.P. [email protected] [email protected]

Abstract In this paper we study the properties of ternary semiring satisfying the identities. Mathematics Subject Classification : 16Y30, 16Y99. Key Words: Ternary semi ring, E-inverse, additive identity, multiplicative identiry.

1.INTRODUCTION: Algebraic structures play a prominent role in mathematics with wide ranging applications in many disciplines such as theoretical physics, computer sciences, control engineering, information sciences, coding theory, topological spaces, and the like. The theory of ternary algebraic systems was introduced by D. H. Lehmer [9]. He investigated certain ternary algebraic systems called triplexes which turn out to be commutative ternary groups. D. MadhusudhanaRao[11] characterized the primary ideals in ternary semigroups. about T. K. Dutta and S. Kar [6] introduced and studied some properties of ternary semirings which is a generalization of ternary rings. Our main purpose in this paper is to introduce the notion of some concepts of ternary semirings.

2.PRELIMINARIES : Definition2.1 : A nonempty set T together with a binary operation called addition and a ternary multiplication denoted by [ ] is said to be a ternary semiring if T is an additive commutative semigroup satisfying the following conditions : i) [[abc]de] = [a[bcd]e] = [ab[cde]], ii) [(a + b)cd] = [acd] + [bcd], iii) [a(b + c)d] = [abd] + [acd], iv) [ab(c + d)] = [abc] + [abd] for all a; b; c; d; e T. Throughout Twill denote a ternary semiring unless otherwise stated. ∈ Note2.2 : For the convenience we write xxx123 instead of [xxx123] Note2.3 : Let T be a ternary semiring. If A,B and C are three subsets of T , we shall denote the set ABC = {Sabc:,, a ÎÎÎ A b B c C} . Note2.4 : Let T be a ternary semiring. If A,B are two subsets of T , we shall denote the set A + B = {abaAbB+ÎÎ:,} . Note2.5 : Any semiring can be reduced to a ternary semiring. Example2.6 :Let T be an semigroup of all m × n matrices over the set of all non negative rational numbers. Then T is a ternary semiring with matrix multiplication as the ternary operation. Example2.7 :Let S = {...,−2i, −i, 0, i, 2i, ...} be a ternary semiring withrespect to addition and complex triple multiplication.

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 105 Dr.D. Madhusudana Rao et.al./ International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.105-110 Example 2.8 :The set T consisting of a single element 0 with binary operation defined by 0 + 0 = 0 and ternary operation defined by 0.0.0 = 0 is a ternary semiring. This ternary semiring is called the null ternary semiring or the zero ternary semiring. Example2.9 : The set Q of all rational numbers with respect to ordinary addition and ternary multiplication [ ] defined by [abc] = abc for all a, b, c Q is a ternary semiring. Example2.10 :The set T = { 0, 1, 2, 3, 4 } is a ternary semiring with respect to addition modulo 5 and multiplication modulo 5 as ternary operation is defined∈ as follows : +5 0 1 2 3 4 ×5 0 1 2 3 4 0 0 1 2 3 5 0 0 0 0 0 0 1 1 2 3 4 0 1 0 1 2 3 4 2 2 3 4 0 1 2 0 2 4 1 3 3 3 4 0 1 2 3 0 3 1 4 2 4 4 0 1 2 3 4 0 4 3 2 1 Definition2.11: A ternary semiring T is said to be commutativeternary semiring provided abc = bca = cab = bac = cba = acbfor all a,b,cÎ T. Example2.12 : (Z0, +, .) is a ternary semiring of infinite order which is commutative. Example2.13 :The set 2I of all evern integers is a commutative ternary semiring with respect to ordinary addition and ternary multiplication [ ] defined by [abc] = abc for all a, b, c T. Note 2.14 :The set M of all n×n matrices with their elements as real numbers (rational numbers, complex numbers, integers) is a non-commutative ternary semiring, with respect∈ to addition and ternary multiplication of matrices as the two ternary semiring compositions. Definition 2.15 : A ternary semigroup ( T , . ) is said to be left regular , if it satisfies the identity a = a3xy " a , x , y T. Definition 2.16 : A ternary semigroup ( T , . ) is said to be right regular , if it satisfies the identity a = xya3 " a , x , y ∈ T Definition2.17 : A ternary semigroup ( T , . ) is said to be lateral regular, if it satisfies the identify a = xa3y " a , x , y ∈ T Definition2.18 : A ternary semigroup ( T , . ) is said to betwo sided regular, if it left as well as right regular. ∈ Definition2.19 : A ternary semigroup ( T , . ) is said to beregular , it is left, lateral and right regular.

3. STRUCTURE OF CERTAIN CLASSES OF TERNARY SEMIRINGS: Definition3.1 :A ternary semigroup ( T , [ ] ) is said to be left singular, if it satisfies the identity ab2 = a " a , b T. Definition 3.2 :A ternary semigroup ( T , [ ] ) is said to belateral singular, if it satisfies the identity bab = ∈a " a , b T. Definition 3.3 :A ternary semigroup ( T , [ ] ) is said to beright singular, if it satisfies the identity b2a = a " a , b T. ∈ Definition 3.4: A ternary semigroup ( T, [ ] ) is said to betwo sided singular, if it is both left and right singular. ∈ Definition 3.5 :A ternary semigroup ( T , [ ] ) is said to besingular, if it is left, lateral and right singular. Definition 3.6 : An element a of a ternary multiplicative semigroup T‘ is called an E-inverse if there exist an element x such that (axa)(axa)(axa) = axa , i.e., axa E (.), where E(.) is the set of all ternary multiplicative idempotent elements of T. Definition3.7 : A ternary semigroup T‘is called an E-inverse ternary∈ semigroup if every element of T is an E-inverse. Definition 3.8 : An element a of an additive semigroup T is called an E-inverse if there is an element x in T such that axa + axa= axa i.e. axa E (+), where E (+) is the set of all additive idempotent elements of T . ∈ © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 106 Dr.D. Madhusudana Rao et.al./ International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.105-110 Definition3.9 : A semigroup T is called an E-inverse semigroup if every element of T is an E-inverse. Theorem 3.10: Let (T, +, .) be a ternary semiring satisfying the identity ababa+ a = a , , ÎT. If (T, .) is a regular ternary semigroup, then (T, +) is a E-inverse semigroup. Proof. : By hypothesis, (T, .) is a left regular ternary semigroup. i.e., a = ababa Consider∀ ababa+ a = a , ÎT. Þ (ababa + a ) . ba = a.ba Þ ababa.ba + a.ba = a∀.ba Þ aba + aba = aba , , ÎT. Hence (T, +) is an E-inverse semigroup. Definition 3.11 : A ternary∀ semigroup ( T , + ) is said to satisfy quasi separative if x3 = xyx = yxy = y3implies x = y , ÎT. Theorem3.12 : Let ( T , + ) be a ternary semiring satisfying the identity aba+ a = a , ÎT. If T contains a ternary∀ multiplicative identity which is also an additive identity, then (T, .) is quasi separative. ∀ Proof : Let e be the ternary multiplicative identity is also an additive identity. By hypothesis, aba+ a = a , ÎT. To prove that (T, .) is quasi-separative i.e., a3 = aba = bab = b3 implies a = b, , ÎT. Let a3 = aba Þ a3 = a (ba +e∀ e) = aba + aee= aba + a = a( Sinceaba + a = a ) Þ a3 = a . Similarly∀ b3 = bab = b ( ab + ee) = bab + bee = bab + b = b, Þ b3 = b . If a3 = aba = bab = b3 implies a =a3 = aba = bab = b3 = bÞ a = b. Hence (T, .) is quasi-separative. Definition3.13 :An additive semigroup ( T , + ) is said to be band if a + a = a ÎT. Definition3.14 :An additive semigroup ( T , + ) is said to rectangular bandif a + b + a = a , , ÎT. ∀ Definition3.15 :A ternary semigroup (T, .) is said to be a band if a3 = a , ÎT. ∀Definition3.16 : A ternary semigroup ( T , . ) is said to be rectangular band if ababa = a, , ÎT. Definitiion3.17 : A ternary semiring (T , + , . ) is said to be mono-ternary∀ semi-ring if eithera + b = ab2 or a + b = a2b, , ÎT. ∀ Definition3.18 :A ternary semigroup (T, +) is said to be left ( right ) singular if a + b = a ( a + b = b) , , Î∀T. Theorem3.19 : A ( T , + , . ) is a ternary semiring and T contains ternary multiplicative identitywhich is also additive∀ identity.Then (T, .) is left singular if and only if a + ab2= a , ÎT. Proof :Given thata + ab2= a , ÎT and let e be a multiplicative identity as well as ∀additive identity. a + ab2= aÞ aee + ab2 = a a ( ee + b2 ) = aÞab2 = a. Therefore ( T , .) is left singular. ∀ Conversely suppose that T is left singular⇒ ab2 = a a(b2) = a a ( ee + b2 ) = a aee + ab2 = a a + ab2= a. Definition3.20 :A ternary semiring ( T , + , . ) with additive⇒ identity⇒ zero is said⇒ to be zero sum free ternary⇒ semiring ⇒if x + x = 0 ÎT. Theorem3.21 :If (T, +, .) is a ternary semiring satisfying the identity a + ab2= a , , ÎT and T contains a∀ ternary multiplicative identity which is also an additive identity , then the following are true. ∀(i) (T, +) is left singular (ii) (T, +) is a ternary mono-semiring. (iii) ( T , . ) is a band (iv) (ab2 )n + (ba2)n = a + bfor odd natural number n. Proof : (i) Consider a + ab2= a , ÎT Þ a + ab2 + b = a + b Þ a + (ab + ee) b = a + b ∀ Þ a + ab2=a + b; Þ a = a + b ® ( 1 ) Similarly b + a2b = b , ÎT , Þ b + a2b + a = b + a Þ b + (ba + ee) a = b + a Þ b + ba2 = b + aÞ∀b = b + a ® ( 2 ) © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 107 Dr.D. Madhusudana Rao et.al./ International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.105-110 From (1) and (2) (T, +) is left singular. (ii) Consider a + ab2=a , ÎT Þ a + ab2 + b = a + b Þ a (ee + b2) + b = a + b Þ ab2 + b = a + b Þ (ab∀ + ee) b = a + b Þ ab2 = a + b. Therefore ( T, .) is a mono ternary semiring. (iii) From (1) We have a + a3 = a ÎT. Þ a ( ee + a2 ) = a , Þ a3 = a ÎT. ( T, .) is a band. ∀ (iv) By the theorem 3.19, ab2 = a∀ and a2b = b Þ (ab2) + (ba2) = a + b Þ (ab2)1 + (ba2)1 = a + b Then the given statement is true for n = 1. (ab2)3 + (ba2)3 = a3 + b3 =⇒ a + b (by using condition (iii)) Then the given statement is true for n = 3. Continuing this process, we get (ab2)n + (ba2)n = a + b for odd natural number n. The following is an example for both theorems 3.19 and 3.21 Example3.22 : Let T = { e , a , b } + e a b x e a b e e a b e e a b a a a a a a a a b b b b b b b b

Theorem3.23 :Let ( T , + , . ) be a ternary semiring satisfying the identity a + a3 = a , , ÎT and PRD, then b + ba2 = b , , ÎT. Proof :By hypothesis, a + a3 = a , ÎT. ∀ 3 Consider a + a = a , Þ a ( ee∀ + a2) = aee Þ ee + a2 = ee , Þ b ( ee+ a2) = bee∀ Þ b + ba2 = b , , ÎT. Theorem3.24 : If ( T , + , . ) is a ternary semiring satisfying the identity a + a2b = a for all a, b T and ∀(T , . ) is a right singular ternary semi-group , then ( T , + ) is a left singular semigroup. Proof∈ :a + a2b = a , ÎT ® ( 1 ) Suppose (T ,. ) is a right singular ternary semigroup. We have a2b = b Þ a + a2b = a + b Þ a = a + b and hence∀ ( T, +) is a left singular semigroup. Theorem 3.25 : If (T , + , .) is a ternary semiring satisfying a + ababa= a , ÎT and (T , .) is a rectangular band, then (T , + ) is a band. Proof :Consider a +ababa= a , ÎT ® ( 1 ) ∀ Given that ( T, .) is a rectangular band implies ababa = a ® ( 2 ). From (1) and (2) we have Þ a +∀ababa = ababaÞ a + a = a a ÎT Hence (T, +) is a band. Theorem 3.26 : Let (T, +, .) be a ternary semiring satisfying ∀ a + ab2= a , ÎT. If (T, +) is commutative and (T, +) is rectangular band , then a + bn = a for n > 1 for an odd natural number n. ∀ Proof : since (T, +) is rectangular band, we have a + b + a = a® ( 1 ) 2 Considera + ab = a , ÎT ® ( 2 ) Þ a + ( a + b + a ) b2 = a ∀ Þ a + ab2 + b3 + ab2 = a Þ a + ab2 + b3 = a [Since (T , + ) is commutative ] Þ a + b3 = a ® ( 3) [Since From (2)] Therefore the result is true for n = 3. © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 108 Dr.D. Madhusudana Rao et.al./ International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.105-110 From (3) ab2 + b2 . b3 = ab2 Þ a + ab2 + b5 = a + ab2

Þ a + b5 = a ® ( 4 ) The result is true for n = 5 . Continuing this process, we get a + bn = a for n is an odd positive integer. TheoreM3.27 : Let ( T, +, .) be a ternary semiring satisfying the identity a + a3 = a , "a ÎT positive rational domain. Then b + a2b = b , ÎT. PROOF :By hypothesis, a + a3 = a"a ÎT ∀ Consider a + a3 = a Þ a( 1 + a2) = aÞ 1 + a2= 1Þ (1 + a2) b = bÞ b + a2b = b Therefore b + a2b = b "a,bÎT Theorem3.28 : Let (T, +, .) be a ternary semiring with the identity a + aba = a "a,b ÎT . Then the following hold : (i) If (T, .) is a band, then (T, +) is a band. Converse is also true if (T, +) is leftcancellative. (ii ) If (T, .) is a rectangular band and (T, +) is commutative then (T, .) is a band. Proof :( i )a + aba = a , "a,b ÎT . Taking b = a . Þ a + a3 = a , a ÎT (Since (T, .) is a band) Þ a + a = a , a ÎT . Hence (T, +) is a band. Conversely, We have to prove∀ that (T,.) is a band. Considera + aba = a "a,b ÎT . Clearly a + a3 ∀= a = a + a (Since (T , + ) is a band). By left cancellative law on addition, a = a3. Therefore (T, .)is a band. ( ii ) Suppose that (T, . ) is a rectangular band anda + aba = a Þ (a + aba)ba = aba Þ aba + ababa = aba Þ aba + a = aba. Taking a = b, then we have a3 + a = a3 ®( 1 ) Interchanging the roles of a and a3in (1), we have a + a3 = a. ®( 2 ) Since (T, +) is commutative and from (1) and (2) a = a3.Therefore (T, .)is a band. Definition3.29 :A ternary semiring T is said to be zero square ternary semiring provided a3 = 0 for all a in T. Theorem3.30 : If T is a zero square ternary semiring where 0 is the additive identity and T satisfies the identity a + ab2 = a , "a,b ÎT , then ababa = 0 and babab = 0. Proof :By hypothesis a + ab2 = a , "a,b ÎT Þ ( a + ab2).a2 = a.a2 Þ a3+ ab2.a2 = a3 Þ 0 + ababa = 0 Þ ababa = 0 "a,b ÎT . Similarlyit is easy to prove babab= 0. Theorem3.31: Let (T ,+ , .) be a ternary semiring with the identity a + ab2 = a "a,b ÎT . (i) If (T , . ) is left singular ternary semigroup and it is commutative then T is an E-inverse ternary semigroup. ( ii ) If (T , . ) is a band, then T is an E-inverse ternary semigroup. PROOF :( i ) By hypothesis, a + ab2 = a "a,b ÎT . Þ aba + ab2.ba = a.ba , Þ aba + babab = aba Þ aba + b = aba , Þ b+ aba + b = b + aba Þ ( b + ba2) + b = b + ba2 Þ b + b = b "b Î T . T is an E-inverse ternary semigroup. (ii) By hypothesis, a + ab2 = a "a,b ÎT . 2 2 Þ a .ab + ab . ab = a.ab , Þ aba + ab .ab = aba Þ aba + a.ab = aba Þ aba + aba = aba, "a,b ÎT . Therefore T is an E-inverse ternary semigroup.

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 109 Dr.D. Madhusudana Rao et.al./ International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 7, 2014, pp.105-110 4.CONCLUSION In this paper mainly we studied about some properties in ternary semirings.

REFERENCES [1].Arif Kaya and Satyanarayana M. Semirings satisfying properties of distributive type, Proceeding of the American Mathematical Society, Volume 82, Number 3, July 1981. [2].Chinaram, R., A note on quasi-ideal in ¡¡semirings, Int. Math. Forum, 3 (2008), 1253{1259. [3].Daddi. V. R and Pawar. Y. S. Ideal Theory in Commutative Ternary A-semirings, International Mathematical Forum, Vol. 7, 2012, no. 42, 2085 – 2091. [4].Dixit, V.N. and Dewan, S., A note on quasi and bi-ideals in ternary semigroups, Int. J. Math.Math.Sci. 18, no. 3 (1995), 501{508. [5].Dutta, T.K. and Kar, S., On regular ternary semirings, Advances in Algebra, Proceedings of the ICM Satellite Conference in Algebra and Related Topics, World Scienti¯c, New Jersey, 2003, 343{355. [6].Dutta, T.K. and Kar, S., A note on regular ternary semirings, Kyung-pook Math. J., 46 (2006), 357{365. [7].Jonathan S. Golan. Semirings and Affine Equations over Them: Theory and Applications, Kluwer Academic. [8].Kar, S., On quasi-ideals and bi-ideals in ternary semirings, Int. J. Math. Math.Sc., 18 (2005), 3015{3023. [9].Lehmer. D. H., A ternary analogue of abelian groups, Amer. J. Math., 59(1932), 329-338. [10].Lister, W.G., Ternary rings, Trans Amer. Math.Soc., 154 (1971), 37{55. [11].MadhusudhanaRao. D., Primary Ideals in Quasi-Commutative Ternary Semigroups International Research Journal of Pure Algebra – 3(7), 2013, 254-258.

AUTHOR’S BRIEF BIOGRAPHY:

Dr. D. MadhusudhanaRao: He completed his M.Sc. from Osmania University, Hyderabad, Telangana, India. M. Phil. from M. K. University, Madurai, Tamil Nadu, India. Ph. D. from AcharyaNagarjuna University, Andhra Pradesh, India. He joined as Lecturer in Mathematics, in the department of Mathematics, VSR & NVR College, Tenali, A. P. India in the year 1997, after that he promoted as Head, Department of Mathematics, VSR & NVR College, Tenali. He helped more than 5 Ph.D’s. At present he guided 5 Ph. D. Scalars and 3 M. Phil., Scalars in the department of Mathematics, AcharyaNagarjuna University, Nagarjuna Nagar, Guntur, A. P. A major part of his research work has been devoted to the use of semigroups, Gamma semigroups, duo gamma semigroups, partially ordered gamma semigroups and ternary semigroups, Gamma semirings and ternary semirings, Near rings ect. He acting as peer review member to the “British Journal of Mathematics & Computer Science”. He published more than 30 research papers in different International Journals in the last two academic years.

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 110 N.Srilatha et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 8, 2014, pp.111-118

Face recognition using 2D-Local Preserving Projection & 2D-Discrete Cosine Transform

N.Srilatha M.Koteswara Rao K.Veeraswamy PG Student, ECE Department Assoc. Professor, ECE Department Professor, ECE Department QIS College of Engineering & QIS College of Engineering & QIS College of Engineering & Technology ONGOLE Technology ONGOLE Technology ONGOLE [email protected] [email protected] [email protected]

Abstract We propose a new face recognition method based on two-dimensional locality preserving projections (2DLPP) in frequency domain. For this purpose, we first introduce the two-dimensional locality preserving projections. Then the 2DLPP in frequency domain is proposed for face recognition. In fact, two dimensional discrete cosine transform (2DDCT) is used as a pre-processing step and it transforms the face image signals from spatial domain into frequency domain aiming to reduce the effects of illumination and pose changes in face recognition. Then 2DLPP is applied on the upper left corner blocks of the 2DDCT transformed matrices, which represent main energy of each original image. For demonstration, the Olivetti Research Laboratory (ORL), YALE, FERET and YALE-B face datasets are used to compare the proposed approach with the conventional 2DLPP and 2DDCT approaches with the nearest neighborhood (NN) classifier. The experimental results show that the proposed 2DLPP in frequency domain is superior over the 2DLPP in spatial domain and 2DDCT itself in frequency domain

Keywords: Modern Sciences, Engineering and Technology.

1.INTRODUCTION: It has been shown in the face detection by explicit modeling of facial features has been troubled by the unpredictability of face appearance and environmental conditions. Although some of the recent feature-based attempts have improved the ability to cope with the unpredictability, most are still limited to head and shoulder and quasi-frontal faces (or are included as one of the techniques in a combined system). There is still a need for techniques that can perform in more hostile scenarios such as detecting multiple faces with clutter-intensive backgrounds. This requirement has inspired a new research area in which face detection is treated as a pattern recognition problem. By formulating the problem as one of learning to recognize a face pattern from examples, the specific application of face knowledge is avoided. This eliminates the potential of modeling error due to incomplete or inaccurate face knowledge. The basic approach in recognizing face patterns is via training procedure which classifies examples into face and non-face prototype classes. Comparison between these classes and a 2Dintensity array (hence the name image-based) extracted from an input image allows the decision of face existence to be made. The simplest image-based approaches rely on template matching [62, 114], but these approaches do not perform as well as the more complex techniques presented in the following sections. Most of the image-based approaches apply a window scanning technique for detecting faces. The window scanning algorithm is in essence just an exhaustive search of the input image for possible face locations at all scales, but there are variations in the implementation of this algorithm for almost all the image-based systems. Typically, the size of the scanning window, the sub sampling rate, the step size, and the number of iterations vary depending on the method proposed and the need for a computationally efficient system. In the following three sections we have roughly divided the image-based approaches into linear subspace methods, neural networks, and statistical approaches. In each section we give a presentation of the characteristics of some of the proposed methods, we attempt to do a comparative evaluation based on results reported on a common dataset. © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 111 N.Srilatha et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 8, 2014, pp.111-118

Basics related 2D-LPP & 2D-DCT and PCA are discussed in section II. Proposed method is discussed in section III. Experimental results are presented in section IV. Concluding remarks are discussed in section V.

2. 2D-LPP & 2D-DCT: 2D-LPP: 2D-LPP is based directly on 2-Dimensional matrix rather than 1-Dimensional vectors as conventional LPP. For algebraic procedure 2D-LPP is two methods. They are 2D-PCA & 2D-LDA. The class label of given data is not properly used by PCA. The most discriminate information in the trining set is in LDA. The class label of given data is not properly used by PCA. PCA is a useful statistical technique that has found application in fields such as face recognition and image compression, and is a common technique for finding patterns in data of high dimension. Before getting to a description of PCA, this tutorial first introduces mathematical concepts that will be used in PCA. It covers standard deviation, covariance, eigenvectors and eigenvalues. This background knowledge is meant to make the PCA section very straightforward, but can be skipped if the concepts are already familiar. The most discriminate information in the training set is in LDA. There are many possible techniques for classification of data. Principal Component Analysis (PCA) and Linear Discriminate Analysis (LDA) are two commonly used techniques for data classification and dimensionality reduction. Linear Discriminate Analysis easily handles the case where the within-class frequencies are unequal and their performance has been examined on randomly generated test data. This method maximizes the ratio of between-class variance to the within-class variance in any particular data set there by guaranteeing maximal reparability. The use of Linear Discriminate Analysis for data classification is applied to classification problem in speech recognition. We decided to implement an algorithm for LDA in hopes of providing better classification compared to Principal Components Analysis. The prime difference between LDA and PCA is that PCA does more of feature classification and LDA does data classification. In PCA, the shape and location of the original data sets changes when transformed to a different space where as LDA doesn’t change the location but only tries to provide more classes reparability and draw a decision region between the given classes. This method also helps to better understand the distribution of the feature data.

Algorithm: Constructing the NN graph: Let M denote a graph with K nodes, ith node corresponding To image Edge between nodes i and j if and are close several methods to measure close. Here are two S-NN: Nodes I and j are onnected at the edge of i.s is the nearest neighbors of j or j is s is nearest neighbors of i. · -neighborhoods: nodes I and j are connected to < .Distance between two matrix ||*|| is the Euclidean distance between their victimization representation in . Choosing the weight: An edge between nodes I and j put a similar weight in .otherwise =0.After we get a sparse symmetric (M M) similar matrix A. the similar weight can be: (a)Simple-minded: If =1 iff nodes I and j are linked by an edge.

(b) Heat kernel: if i and j are linked if = where t is the constant. If t is constant multiplied by the maximum distance of pair wise neighbor images.

Eigen map: Calculate the eigenvalues and Eigen vectors for the generalized eigenvalue problem:

. Where D is diagonal matrix with .L=D-S is the laplacian matrix.

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 112 N.Srilatha et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 8, 2014, pp.111-118

2D-DCT: 2D -DCT coefficients is obtained from horizontally and vertically neighboring blocks. 2D DCT and the results also suggest that histogram equalization pre-processing and also increase the error. The given face image is analyzed on a block by block basis. Given image block f(x,y),where x,y=0,1,2,…., (where =8).the result is an matrix C(p,q)containing 2D DCT coefficients:

Where

Fig 1:Several2D DCT basis functions for =8 p 0 1 2 3 0 1 8 4 14 q 1 12 9 7 0 2 15 2 5 6 3 13 3 11 10 Table1: Ordering of 2D DCT coefficients S(p,q) for =4

3. PROPOSED ALGORITHM: INPUT: Training sample matrices { }, r and c.

OUTPUT: Sub-optimal projection matrices L and R.

1. Let the initial = for L and set i=1.

2. While not convergent.

3. From the matrix

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 113 N.Srilatha et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 8, 2014, pp.111-118

and

One can compute the r eigenvectors = Corresponding to the minimum c eigenvalues.

4. Let =

5. from the matrix

and

One can compute the r eigenvectors = corresponding to the minimum r eigenvalues.

6. Let =

7. I=i+1

8. End while

9. ,

Neural networks:

Neural networks have become a popular technique for pattern recognition problems, including face detection. Neural networks today are much more than just the simple MLP. Modular architectures, committee–ensemble classification, complex learning algorithms, auto associative and compression networks, and networks evolved or pruned with genetic algorithms are all examples of the widespread use of neural networks in pattern recognition. For face recognition, this implies that neural approaches might be applied for all parts of the system, and this had indeed been shown in several papers. An introduction to some basic neural network methods for face detection can be found in Viennet and Fougelman Souli´e.The first neural approaches to face detection were based on MLPs, where promising results where reported on fairly simple datasets. The first advanced neural © IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved “IJMSET promotes research nature, Research nature enriches the world’s future” 114 N.Srilatha et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET) ISSN 2349-3755; Available at https://www.ijmset.com Volume 1, Issue 8, 2014, pp.111-118 approach which reported results on a large, difficult dataset was by Rowley et. Their system incorporates face knowledge in a retinal connected neural network shown. The neural network is designed to look at windows of 20 * 20 pixels (thus 400 input units). There is one hidden layer with 26 units, where 4 units look at 10 * 10 pixel sub regions, 16 look at 5 £ 5 sub regions, and 6 look at 20 * 5 pixels overlapping horizontal stripes. The input window is pre-processed through lighting correction (a best fit linear function is subtracted) and histogram equalization. This pre-processing method was adopted from Sung and Poggio’s system mentioned earlier and is shown. A problem that arises with window scanning techniques is overlapping detections. Rowley et al. deals with this problem through two heuristics:

Thresholding: the number of detections in a small neighborhood surrounding the current location is counted, and if it is above a certain threshold, a face is present at this location.

Fig 2: The pre processing method

Overlap elimination: when a region is classified as a face according to thresholding, then overlapping detections are likely to be false positives and thus are rejected. To further improve performance, they train multiple neural networks and combine the output with an arbitration strategy (AND ing, OR ing, voting, or a separate arbitration neural network). This algorithm was applied in a person tracking system and for initial face detection in the head tracking system of La Cassia. A similar system was recently proposed in [57].Recently, Rowley combined this system with a router neural network to detect faces at all angles in the image plane. They use a fully connected MLP with one hidden layer and 36 output units (one unit for each 10± angle) to decide the angle of the face. The system detects 79:6% of the faces in two large datasets with a small number of false positives.

4. EXPERIMENTAL RESULTS: The YALE dataset contains different facial expressions or lighting configurations.

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Fig 3: Browsing an input image DCT is very sensitive to illumination change. The main of dataset to evaluate the performance of proposed technique. It can be seen from the se results that 2DDCT+2DLPP is the best from both the recognition performance and computational time.

Fig 4: Matching of an image

The FERET face database contains thousands of face images We select 49 individuals that have equal or more than 10 images in gray_feret_cd 1andgray_feret_cd2 and the images are scaled down to112_92 according to the positions of eyes and noses from the original size of 640_480.

Fig 5: unmatching of an image

S.No Methods Recognition accuracy

1 2DLDA 82.7 2 2DPCA 83.6 3 2DLPP 88.3 4 2DDCT 90.6

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5 2DDCT+2DLPP 92.9 6 2DDCT+2DLPP+2DLDA 94 (Proposed)

Table 2: Recognition performance comparison on YALE

Fig 6: Comparison of 6 approaches on the YALE dataset

5. CONCLUSION For demonstration, the Olivetti Research Laboratory (ORL), YALE, FERET and YALE-B face datasets are used to compare the proposed approach with the conventional 2DLPP and 2DDCT approaches with the nearest neighborhood (NN) classifier. The experimental results show that the proposed 2DLPP in frequency domain is superior over the 2DLPP in spatial domain and 2DDCT itself in frequency domain

6. REFERENCES

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AUTHOR’S BRIEF BIOGRAPHY

N.Srilatha is currently PG Student in ECE department of QIS College of Engineering and Technology, Ongole, A.P, India. She received his B.Tech from JNTUK, Kakinada. His research interests in the area of content based image retrieval.

M.Koteswara Rao is currently working as associate professor in ECE Department, QIS College of Engineering & Technology, Ongole, A.P, India. He received his M.Tech from JNTUK, Kakinada. He has six years experience in the teaching undergraduate and post graduate students. His research interests in the area of content based image retrieval.

K.VeeraSwamy is currently Professor in ECE department and Principal of QIS College of Engineering and Technology, Ongole, A.P, India. He received his Ph.D from JNTUK, Kakinada. He has fourteen years experience in teaching under graduate and post graduate students. His research interests are in the areas of image compression, image watermarking, Face recognition, CBIR, and networking protocols.