DOCSLIB.ORG

Ontology Driven Multi-Agent Systems: an Architecture for Sensor Web Applications

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Ontology Driven Multi-Agent Systems: an Architecture for Sensor Web Applications ONTOLOGY DRIVEN MULTI-AGENT SYSTEMS: AN ARCHITECTURE FOR SENSOR WEB APPLICATIONS by DESHENDRAN MOODLEY Submitted in fulfillment of the academic requirements for the degree of Doctor of Philosophy in the School of Computer Science, Faculty of Science and Agriculture, University of KwaZulu-Natal, Durban, South Africa, December 2009 As the candidate’s supervisor I have approved this dissertation for submission. Signed: Name: Date: ABSTRACT Advances in sensor technology and space science have resulted in the availability of vast quantities of high quality earth observation data. This data can be used for monitoring the earth and to enhance our understanding of natural processes. Sensor Web researchers are working on constructing a worldwide computing infrastructure that enables dynamic sharing and analysis of complex heterogeneous earth ob- servation data sets. Key challenges that are currently being investigated include data integration; service discovery, reuse and composition; semantic interoperability; and system dynamism. Two emerging tech- nologies that have shown promise in dealing with these challenges are ontologies and software agents. This research investigates how these technologies can be integrated into an Ontology Driven Multi-Agent System (ODMAS) for the Sensor Web. The research proposes an ODMAS framework and an implemented middleware platform, i.e. the Sensor Web Agent Platform (SWAP). SWAP deals with ontology construction, ontology use, and agent based design, implementation and deployment. It provides a semantic infrastructure, an abstract architec- ture, an internal agent architecture and a Multi-Agent System (MAS) middleware platform. Distinguish- ing features include: the incorporation of Bayesian Networks to represent and reason about uncertain knowledge; ontologies to describe system entities such as agent services, interaction protocols and agent workflows; and a flexible adapter based MAS platform that facilitates agent development, execution and deployment. SWAP aims to guide and ease the design, development and deployment of dynamic alerting and monitoring applications. The efficacy of SWAP is demonstrated by two satellite image processing applications, viz. wildfire detection and monitoring informal settlement. This approach can provide sig- nificant benefits to a wide range of Sensor Web users. These include: developers for deploying agents and agent based applications; end users for accessing, managing and visualising information provided by real time monitoring applications, and scientists who can use the Sensor Web as a scientific computing platform to facilitate knowledge sharing and discovery. An Ontology Driven Multi-Agent Sensor Web has the potential to forever change the way in which geospatial data and knowledge is accessed and used. This research describes this far reaching vision, identifies key challenges and provides a first step towards the vision. ii PREFACE The research work described in this dissertation was carried out in the School of Computer Science, University of KwaZulu-Natal, Durban, from March 2001 to December 2009, under the supervision of Prof. Jules R. Tapamo and Prof. Johnson D.M. Kinyua These studies represent original work by the author and have not otherwise been submitted in any form for any degree or diploma to any tertiary institution. Where use has been made of the work of others it is duly acknowledged in the text. iii DECLARATION 1 - PLAGIARISM I, Deshendran Moodley, declare that: 1. The research reported in this thesis, except where otherwise indicated, is my original research. 2. This thesis has not been submitted for any degree or examination at any other university. 3. This thesis does not contain other persons’ data, pictures, graphs or other information, unless specifically acknowledged as being sourced from other persons. 4. This thesis does not contain other persons’ writing, unless specifically acknowledged as being sourced from other researchers. Where other written sources have been quoted, then: (a) Their words have been re-written but the general information attributed to them has been referenced (b) Where their exact words have been used, then their writing has been placed in italics and inside quotation marks, and referenced. 5. This thesis does not contain text, graphics or tables copied and pasted from the Internet, unless specifically acknowledged, and the source being detailed in the thesis and in the References sec- tions. Signed: iv DECLARATION 2 - PUBLICATIONS 1.M OODLEY, D., AND KINYUA, J. A multi-agent system for electronic job markets. In Proc. 6th International conference on Business Information Systems, Colorado Springs, USA, 4-6 June 2003, published by Dept. of Management Info. Systems, The Poznan University of Economics, Poznan (2003), pp. 42–48 2.M OODLEY, D. The future of the Internet: The semantic web, web services and a multi-agent system infrastructure for the Internet. In Proc. South African Computer Lecturers Association 2004, 4-6 July Durban, 2004 (2004) 3.M OODLEY, D., AND KINYUA, J. D. M. Towards a multi-agent infrastructure for distributed In- ternet applications. In 8th Annual Conference on WWW Applications, Bloemfontein, South Africa, 5-6 September (2006) 4.M OODLEY, D., TERHORST, A., SIMONIS, I., MCFERREN, G., AND VAN DEN BERGH, F. Using the sensor web to detect and monitor the spread of wild fires. In Second International Symposium on Geo-information for Disaster Management (Gi4DM) September 25-26, Pre-Conference Sympo- sium to ISPRS TC-IV and ISRS Symposium on Geospatial Databases for Sustainable Development September 27-30, at Goa, India (2006) 5.M OODLEY, D., AND SIMONIS, I. A new architecture for the sensor web: the SWAP-framework. In Semantic Sensor Networks Workshop, A workshop of the 5th International Semantic Web Con- ference ISWC 2006, November 5-9, Athens, Georgia, USA (2006) 6.T ERHORST, A., SIMONIS, I., AND MOODLEY, D. A service-oriented multi-agent systems archi- tecture for the sensor web. In SAEON Summit, Centurion, South Africa (2006) 7.M OODLEY, D., VAHED, A., SIMONIS, I., MCFERREN, G., AND ZYL, T. V. Enabling a new era of earth observation research: scientific workflows for the sensor web. Ecological Circuits 1 (2008), 20–23 8.T ERHORST, A., MOODLEY, D., SIMONIS, I., FROST, P., MCFERREN, G., ROOS, S., AND VAN DEN BERGH, F. Geosensor Networks, Lecture Notes in Computer Science, Volume 4540/2008. Springer-Verlag, 2008, ch. Using the Sensor Web to Detect and Monitor the Spread of Vegetation Fires in Southern Africa, pp. 239–251 Signed: v ACKNOWLEDGEMENTS Many people have supported me through this endeavour. I am deeply grateful to my wife for her patience, understanding, support and for allowing the PhD to permeate our lives over the past few years. I wish to express sincere gratitude to my supervisor Jules Tapamo for his support and guidance, and to my co-supervisor Johnson Kinyua for his support and guidance through the early stages. I would like to thank my parents, my family and my dear friends who have supported me. A special thank you to Anban Pillay for being a dear friend, and for willing to sacrifice many hours for proof reading. I wish to also acknowledge and thank: Chetna Parbhoo for designing and implementing the second case study application as part of her Masters research; Pravi Moodley who assisted with the proof read- ing; members of the ICT4EO and KSG groups at the Meraka Institute, CSIR, Pretoria, specifically Ingo Simonis and Tommie Meyer. I also acknowledge the financial support provided by the National Research Foundation and the German Academic Exchange Service (DAAD) . vi TABLE OF CONTENTS Preface ................................................ iii Declarations ............................................. iv Acknowledgements ......................................... vi Table of Contents .......................................... vii List of Figures ............................................ xii List of Tables ............................................. xviii List of Abbreviations ........................................ xix Chapter 1 Introduction .................................... 1 1.1 Background . .1 1.2 Problem statement . .3 1.3 Expected impact . .3 1.4 The SWAP framework . .4 1.4.1 Semantic infrastructure . .4 1.4.2 MASII: An Internet Wide Multi Agent System middleware . .5 1.4.3 Framework for designing and developing Sensor Web agents and applications . .5 1.4.4 Application case studies . .6 1.5 Organisation of the thesis . .6 Chapter 2 Literature review .................................. 8 2.1 The Sensor Web . .8 2.1.1 Our vision of the Sensor Web . 10 2.1.2 OGC Sensor Web Enablement . 12 2.1.3 GeoSwift . 13 vii 2.2 Software agents and multiagent systems for Internet Computing . 14 2.2.1 Agent operation . 15 2.2.2 MAS infrastructure models and platforms . 18 2.2.3 Challenges for building an Internet Wide MAS (IWMAS) . 20 2.3 Ontologies and the Semantic Web . 22 2.3.1 Ontology Representation languages . 25 2.3.2 Ontology development and management . 29 2.3.3 Ontology based systems . 32 2.3.4 Agents and the Semantic Web . 33 2.4 Agents and ontologies on the Sensor Web . 34 2.4.1 Agent based approaches . 34 2.4.2 Ontology based Sensor Web approaches . 36 2.5 Summary . 39 Chapter 3 Design of an Internet Wide Multi-Agent System Infrastructure ........ 40 3.1 Requirements for a single global multi-agent infrastructure . 40 3.2 The Multi-Agent Infrastructure for the Internet . 42 3.2.1 An abstract architecture for a IWMAS . 42 3.3 MASII design and operation . 45 3.3.1 Registry Agent (RA) . 46 3.3.2 Adapter agent (AA) . 46 3.3.3 Platform implementation . 47 3.3.4 Application development . 48 3.4 Application deployment . 49 3.5 Discussion . 49 Chapter 4 Design of the Sensor Web Agent Platform .................... 51 4.1 Our vision of the Sensor Web . 51 4.2 The SWAP Abstract Architecture . 52 4.2.1 Sensor Layer . 52 4.2.2 Knowledge Layer . 54 viii 4.2.3 Application Layer . 54 4.2.4 Incorporating OGC services . 55 4.3 Overview of the SWAP Ontological Infrastructure . 55 4.3.1 Rationale behind the SWAP ontology . 55 4.3.2 Swap rules . 57 4.4 The SWAP conceptual ontologies . 59 4.4.1 Thematic representation and reasoning .
Load more

Recommended publications
  • Use Style: Paper Title
    IJRECE VOL. 6 ISSUE 2 APR.-JUNE 2018 ISSN: 2393-9028 (PRINT) | ISSN: 2348-2281 (ONLINE) A Review on Reasoning System, Types and Tools and Need for Hybrid Reasoning Goutami M.K1, Mrs. Rashmi S R2, Bharath V3 1M.Tech, Computer Network Engineering, Dept. of Computer Science and Engineering, Dayananda Sagar college of Engineering, Bangalore. (Email: [email protected]) 2Asst. Professor, Dept. of Computer Science and Engineering, Dayananda Sagar college of Engineering , Bangalore. (Email: [email protected]) 3Dept. of Computer Science and Engineering, Dayananda Sagar college of Engineering, Bangalore Abstract— Expert system is a programming system which knowledge base then we require a programming system that utilizes the information of expert knowledge of the specific will facilitate us to access the knowledge for reasoning purpose domain to make decisions. These frameworks are intended to and helps in decision making and problem solving. Inference tackle complex issues by thinking through the learning process engine is an element of the system that applies logical rules to called as reasoning. The knowledge used for reasoning is the knowledge base to deduce new information. User interface represented mainly as if-then rules. Expert system forms a is one through which the user can communicate with the expert significant part in day-to-day life nowadays as it emulates the system. expert’s behavior in analyzing the information and concludes “A reasoning system is a software system that uses available knowledge, applies logical techniques to generate decision. This paper primarily centers on the reasoning system conclusions”. It uses logical techniques such as deduction which plays the fundamental part in field of artificial approach and induction approach.
    [Show full text]
  • AAAI Proceedings Template
    Rules versus Scripts in Games Artificial Intelligence Nathan Combs, Jean-Louis Ardoint BBN Technologies, ILOG S.A. [email protected] [email protected] Abstract indicate where they should move, e.g. pathways. The Most game behavior is written using scripts instead of rules. developer can coordinate objects and events graphically as Rules are declarative representations that, given variables in well as embed logic with the objects - behavior is added to the game, encode relationships and facts about the game. the objects by “drilling in” and associating scripts and/or From these facts one can reason about truth in the game changing property values. world. Scripts are imperative representations: they provide a set of instructions that are used to process game variables While details differ across individual games and genres, and compute some conclusion. Scripting is more intuitive the pattern is similar. For example, Operation Flashpoint for game designers and developers to work with. It is easier to conceptualize and write a script that says: "go right, go (Codemasters) provides a graphical mission editor, left, turn around twice, go straight, then fire your gun..." whereas, Unreal Tournament uses a more complex CAD then it is to formulate a set of rules that could shape an level-editor. This design pattern is an “environment- entities movement to the same effect. based programming” style that has its roots in early game systems (e.g., RuthMOO’s “Programming the While scripting allows developers to construct sophisticated Environment”) – where both the content and programming behaviors, typically these behaviors are brittle outside of the are intermingled.
    [Show full text]
  • Semantic Technologies IV Rules: Ruleml, Prova
    Arbeitsgruppe Semantic Business Process Management Lectuer 8 – Semantic Technologies IV Rules: RuleML, Prova Prof. Dr. Adrian Paschke Corporate Semantic Web (AG-CSW) Institute for Computer Science, Freie Universitaet Berlin [email protected] http://www.inf.fu-berlin.de/groups/ag-csw/ Overview . Overview Semantic Technologies . Ontologies . OMG Ontology Definition Metamodel . W3C Web Ontology Language . Rules . OMG SBVR . OMG PRR . W3C RIF . RuleML . Prova Semantic Computing Technologies 4. Software Agents and Web-based Services . Rule Responder, FIPA, Semantic Web Services, … 3. Rules and Event/Action Logic & Inference . RIF, SBVR, PRR, RuleML, Logic Programming Rule/Inference Engines,… 2. Ontologien . RDFS, OWL Lite|DL|Full, OWL 2, ODM, … 1. Explicit Meta-data and Terminologies . vCard, PICS, Dublin Core, RDF, RDFa, Micro Formats, FOAF, SIOC … RuleML SBVR PRR RuleML RIF OCL ILog Blaze Prova XCML IRL SRL RuleML . Rule Markup and Modeling Initiative (RuleML) (www.ruleml.org) . representatives from academia, industry and government . promotion of the modern and future generations of Web rule technology . RuleML is currently the de facto open language standard for Web Rules . W3C Rule Interchange Format in preparation . Collaborating with W3C (RIF), OMG (PRR, SBVR), OASIS, DARPA and other standards/gov'nt bodies RuleML Enables ... modelling markup UML translation RDF Rule interchange in XML execution ASCII publication archiving RuleML Language Family RuleML Derivation Rules Reaction Integrity Transformation Rules Constraints Rules
    [Show full text]
  • Reaction Ruleml
    Int. Late-Breaking News Event Reaction RuleML Nov. 9th, 2006 Athens, GA, USA at ISWC’06/RuleML‘06 Int. Late-Breaking News Event Reaction RuleML http://ibis.in.tum.de/research/ReactionRuleML Nov. 9th, 17.30 – 18.30 Athens, GA, USA at ISWC’06/RuleML’06 Adrian Paschke (Co-Chair Reaction RuleML) and Alexander Kozlenkov (Co-Chair RuleML) Reaction RuleML Technical Group Agenda 1. Reaction RuleML: Introduction + News 15 minutes 2. Reaction RuleML 0.1 5 minutes 3. Talks: ECA-LP and Prova Agent Architecture by Adrian Paschke 5 minutes and A. Kozlenkov Transaction Logics and Active Rules by Michael Kifer 5 minutes Production Rule Programs by Benjamin Grosof 5 minutes XChange by Michael Eckert 5 minutes and Paula Patrajan 3. Discussion 20 minutes 2 Reaction RuleML Paschke, A. and Kozlenkov, A. Special Event, Athens, GA, USA at RuleML’06/ISWC’06 2006-11-09 Reaction RuleML is … An open, general, practical, compact and user-friendly XML- serialization language for the family of reaction rules including: ECA rules and variants such as ECAP rules and triggers (EA rules) Production rules (CA rules) Active rules (rule execution sequences) Event notification and messaging rules including agent communications, negotiation and coordination protocol rules Temporal event / action and state/fluent processing logics Dynamic, update, transaction, process and transition logics … but not limited to, due to extensible language design 3 Reaction RuleML Paschke, A. and Kozlenkov, A. Special Event, Athens, GA, USA at RuleML’06/ISWC’06 2006-11-09 Reaction RuleML is intended for e.g., … Event Processing Networks Event Driven Architectures (EDAs) Reactive, rule-based Service-Oriented Architectures (SOAs) Active Semantic Web Applications Real-Time Enterprise (RTE) Business Activity Management (BAM) Business Performance Management (BPM) Service Level Management (SLM) with active monitoring and enforcing of Service Level Agreements (SLAs) or e-Contracts Supply Chain Event Management Policies … 4 Reaction RuleML Paschke, A.
    [Show full text]
  • VIEW-BASED USER INTERFACES for the SEMANTIC WEB Doctoral Dissertation
    TKK Dissertations 249 Espoo 2010 VIEW-BASED USER INTERFACES FOR THE SEMANTIC WEB Doctoral Dissertation Eetu Mäkelä Aalto University School of Science and Technology Faculty of Information and Natural Sciences Department of Media Technology TKK Dissertations 249 Espoo 2010 VIEW-BASED USER INTERFACES FOR THE SEMANTIC WEB Doctoral Dissertation Eetu Mäkelä Doctoral dissertation for the degree of Doctor of Science in Technology to be presented with due permission of the Faculty of Information and Natural Sciences for public examination and debate in Auditorium TU2 at the Aalto University School of Science and Technology (Espoo, Finland) on the 26th of November 2010 at 12 noon. Aalto University School of Science and Technology Faculty of Information and Natural Sciences Department of Media Technology Aalto-yliopisto Teknillinen korkeakoulu Informaatio- ja luonnontieteiden tiedekunta Mediatekniikan laitos Distribution: Aalto University School of Science and Technology Faculty of Information and Natural Sciences Department of Media Technology P.O. Box 15500 (Otaniementie 17) FI - 00076 Aalto FINLAND URL: http://www.media.tkk.fi/ Tel. +358-9-47001 E-mail: [email protected] © 2010 Eetu Mäkelä ISBN 978-952-60-3446-1 ISBN 978-952-60-3447-8 (PDF) ISSN 1795-2239 ISSN 1795-4584 (PDF) URL: http://lib.tkk.fi/Diss/2010/isbn9789526034478/ TKK-DISS-2833 Aalto-Print Helsinki 2010 ABSTRACT OF DOCTORAL DISSERTATION AALTO UNIVERSITY SCHOOL OF SCIENCE AND TECHNOLOGY P.O. BOX 11000, FI-00076 AALTO http://www.aalto.fi Author Eetu Mäkelä Name of the dissertation
    [Show full text]
  • Semantic Web Rule Engine
    Prova Network-based Information Systems WS’08/09 Prova: A Semantic Web Rule Engine Prof. Dr. Adrian Paschke Agenda . Motivation: Declarative Logic Programming . Prova – Syntax and Semantics . ContractLog Library . Prova Agent Architecture . Programming with Prova © by Adrian Paschke, 2008 2 Advantages of Logic Programming 1. Compact declarative representation of rules by . Global validity within a scope (module) . Separation of contract rules and application code . Simple extension of the rule base (without changing the interpreter) 2. Efficient, generic interpreter (LP inference engines) for automated rule changing and rule derivation 3. Automated conflict resolution . Traceable and verifiable rule sets . Integrity constraints are possible . Automated conflict resolution (e.g., by rule prioritization) © by Adrian Paschke, 2008 3 Simplified Example: Resolution . Rules: discount(Service, -5%) :- qos(Service,low). qos(Service, low) :- availability(Service, ServiceAvailability), lessequ(ServiceAvailability,98%). Fact: availability(s1, 97%). Query: :-solve(discount(s1, X)) result: X = -5% Backward Reasoning {~discount(s1,X)} {discount(Service, -5%), ~qos(Service,low)} {~qos(s1,low)} {qos(Service,low), ~availability(Service, Service- Availability), lessequ(ServiceAvailability, 98%)} {~availability(s1,ServiceAvailability), lessequ(ServiceAvailability,98%)} {availability(s1,97%)} © by Adrian Paschke, 2008 {} 4 Declarative Knowledge Representation Logic Programming Procedural Programming discount(Service, 5%) :- qos(Service,high). boolean getsDiscount(Service
    [Show full text]
  • Provalets: Component-Based Mobile Agents As Microservices for Rule-Based Data Access, Processing and Analytics
    Bus Inf Syst Eng 58(5):329–340 (2016) DOI 10.1007/s12599-016-0447-z RESEARCH PAPER Provalets: Component-Based Mobile Agents as Microservices for Rule-Based Data Access, Processing and Analytics Adrian Paschke Received: 15 November 2015 / Accepted: 21 June 2016 / Published online: 18 August 2016 Ó Springer Fachmedien Wiesbaden 2016 Abstract Provalets are mobile rule agents for rule-based (LED). While interlinking of machine interpretable Linked data access, semantic processing, and inference analytics. Data has been adopted in the Public Semantic Web as LOD They can be dynamically deployed as microservices from cloud (Schmachtenberg et al. 2014), corporate enterprises Maven repositories into standardized container environ- are still reluctant to use this approach to form their own ments such as OSGi, where they can be used via simple private Linked Enterprise Web of Data for, e.g., semantic REST calls. The programming model supports rapid pro- data processing, smart content enrichment2 and inference- totyping and reuse of Provalets components to build based analytics (Hu and Svensson 2010a; Wood 2010). Linked Enterprise Data applications where the sensible Reasons for this are, e.g., the lack of an easy to use and corporate data is not transmitted outside the enterprise, but understand engineering and service-oriented approach instead the Provalets providing data processing and (e.g., Service Oriented Architecture – SOA). This has lead knowledge inference capabilities are moved closer to the to, e.g., the W3C Linked Data Platform (LDP)3, which data. standardizes a REST protocol for accessing (read/write) Linked Data. While this provides a basis for SOA-based Keywords Microservices Á Linked enterprise data Á Enterprise Application Integration (EAI) (Mihindukula- Corporate semantic web Á Corporate smart content Á Rule- sooriya et al.
    [Show full text]
  • Predicate Logic (First Order Logic)
    SWAT4LS 2014 Tutorial Introduction to Rule Technologies and Systems 9-11 Dec., Berlin, Germany Prof. Dr. Adrian Paschke and Ralph Schäfermeier Arbeitsgruppe Corporate Semantic Web (AG-CSW) Institut für Informatik, Freie Universität Berlin [email protected] http://www.inf.fu-berlin/groups/ag-csw/ Agenda . Theory . Difference Rule-based Knowledge Representation and Logic Programming vs. Ontological KR and Description Logics . Example for Platform-Specific Rule System . Beyond Prolog – Prova Reactive Rule Language . Rule Markup Languages for Platform- Independent Rule Interchange . Deliberation and Reaction RuleML . W3C SWRL (+Protege SWRL) . W3C RIF Declarative Knowledge Representation . Declarative Knowledge Representation: express what is valid, the responsibility to interpret this and to decide on how to do it is delegated to an interpreter / reasoner . Logic is a discipline concerned with the principles of inference and reasoning . Logic-based languages used for declarative knowledge representation Semantic Technologies for Declarative Knowledge Representation 1. Rules bird(X) fly(X) . Goal: Derived conclusions and bird(tweety) reactions from given knowledge (rule inference / rule chaining) disjoint with 2. Ontologies Mammal Bird . Goal: Ontologies described the conceptual knowledge of a domain is a (concept semantics) Duckbill Platypus Usage of Rules 1. Rules: • Derivation rules (deliberative rules): establish / derive new knowledge. • Reaction rules that establish when certain activities should take place: • Condition-Action rules (production rules) • Event-Condition-Action (ECA) rules + varians (e.g. ECAP). • Messaging reaction rules (event message / query reaction rules) 2. Constraints on system’s structure, behavior or information: • Structural constraints. • State constraints. • Process / flow constraints. Logic Languages for Declarative KR . Predicate Logic (First Order Logic) . Expressive (variables, functions, quantifier, negation, …) .
    [Show full text]
  • Knowledge Management Applied to Software Testing: an Ontology Based Framework
    sid.inpe.br/mtc-m19/2014/01.21.12.55-TDI KNOWLEDGE MANAGEMENT APPLIED TO SOFTWARE TESTING: AN ONTOLOGY BASED FRAMEWORK Érica Ferreira de Souza Doctorate Thesis Course Graduate in Applied Computing, guided by Drs. Nandamudi Lankalapalli Vi- jaykumar, and Ricardo de Almeida Falbo, approved in February 04, 2014. URL of the original document: <http://urlib.net/8JMKD3MGP7W/3FK67N8> INPE São José dos Campos 2014 PUBLISHED BY: Instituto Nacional de Pesquisas Espaciais - INPE Gabinete do Diretor (GB) Serviço de Informação e Documentação (SID) Caixa Postal 515 - CEP 12.245-970 São José dos Campos - SP - Brasil Tel.:(012) 3208-6923/6921 Fax: (012) 3208-6919 E-mail: [email protected] BOARD OF PUBLISHING AND PRESERVATION OF INPE INTEL- LECTUAL PRODUCTION (RE/DIR-204): Chairperson: Marciana Leite Ribeiro - Serviço de Informação e Documentação (SID) Members: Dr. Antonio Fernando Bertachini de Almeida Prado - Coordenação Engenharia e Tecnologia Espacial (ETE) Dra Inez Staciarini Batista - Coordenação Ciências Espaciais e Atmosféricas (CEA) Dr. Gerald Jean Francis Banon - Coordenação Observação da Terra (OBT) Dr. Germano de Souza Kienbaum - Centro de Tecnologias Especiais (CTE) Dr. Manoel Alonso Gan - Centro de Previsão de Tempo e Estudos Climáticos (CPT) Dra Maria do Carmo de Andrade Nono - Conselho de Pós-Graduação Dr. Plínio Carlos Alvalá - Centro de Ciência do Sistema Terrestre (CST) DIGITAL LIBRARY: Dr. Gerald Jean Francis Banon - Coordenação de Observação da Terra (OBT) DOCUMENT REVIEW: Marciana Leite Ribeiro - Serviço de Informação e Documentação (SID) Yolanda Ribeiro da Silva Souza - Serviço de Informação e Documentação (SID) ELECTRONIC EDITING: Maria Tereza Smith de Brito - Serviço de Informação e Documentação (SID) André Luis Dias Fernandes - Serviço de Informação e Documentação (SID) sid.inpe.br/mtc-m19/2014/01.21.12.55-TDI KNOWLEDGE MANAGEMENT APPLIED TO SOFTWARE TESTING: AN ONTOLOGY BASED FRAMEWORK Érica Ferreira de Souza Doctorate Thesis Course Graduate in Applied Computing, guided by Drs.
    [Show full text]
  • Use Style: Paper Title
    An Analysis of Scripting Languages for Research in Applied Computing Olugbenga Oluwagbemi, Adewole Adewumi, Sanjay Misra Folakemi Majekodunmi Department of Computer Engineering Department of Computer and Information Sciences Atilim University Covenant University Ankara, Turkey Ota, Nigeria [email protected] Luis Fernandez-Sanz Department of Computer Science University of Alcala Madrid, Spain Abstract—There are several scripting languages that exist expand the use of biological, medical, behavioral or health data today. However, some are used more frequently and popular [53]. This also includes acquiring, storing, organizing, than others. This is due to certain characteristics and features archiving, analyzing and visualizing such data. Scripting that they possess. Particularly in applied computing fields like languages are crucial in this regard. In addition, scripting software engineering, bioinformatics and computational biology, languages play a vital role also in computational biology as this scripting languages are gaining popularity. This paper presents a field involves mining large pools of biological data using comparative study of ten popular scripting languages that are mathematical/computational modeling techniques [53]. used in the above mentioned fields/area. For making comparison, we have identified the factors against which these languages are Some of the problems associated with developing efficient, evaluated. Accordingly, based on selected criteria we determine effective and portable software are those related to improper their suitability in the fields of software engineering, specifications, error in the design phase, faulty implementation bioinformatics and computational biology research. This will phase, and lack of a well tested and properly refined product in serve as a guide to researchers to choose the appropriate the case of software engineering [52].
    [Show full text]
  • Rule-Based Agents for the Semantic-Pragmatic Web Paschke, Adrian; Boley, Harold
    NRC Publications Archive Archives des publications du CNRC Rule responder : rule-based agents for the semantic-pragmatic web Paschke, Adrian; Boley, Harold This publication could be one of several versions: author’s original, accepted manuscript or the publisher’s version. / La version de cette publication peut être l’une des suivantes : la version prépublication de l’auteur, la version acceptée du manuscrit ou la version de l’éditeur. For the publisher’s version, please access the DOI link below./ Pour consulter la version de l’éditeur, utilisez le lien DOI ci-dessous. Publisher’s version / Version de l'éditeur: https://doi.org/10.1142/S0218213011000528 International Journal on Artificial Intelligence Tools (IJAIT), 20, 6, pp. 1043-1081, 2011 NRC Publications Record / Notice d'Archives des publications de CNRC: https://nrc-publications.canada.ca/eng/view/object/?id=6595b500-9df5-4d69-91f7-8c54095cb082 https://publications-cnrc.canada.ca/fra/voir/objet/?id=6595b500-9df5-4d69-91f7-8c54095cb082 Access and use of this website and the material on it are subject to the Terms and Conditions set forth at https://nrc-publications.canada.ca/eng/copyright READ THESE TERMS AND CONDITIONS CAREFULLY BEFORE USING THIS WEBSITE. L’accès à ce site Web et l’utilisation de son contenu sont assujettis aux conditions présentées dans le site https://publications-cnrc.canada.ca/fra/droits LISEZ CES CONDITIONS ATTENTIVEMENT AVANT D’UTILISER CE SITE WEB. Questions? Contact the NRC Publications Archive team at [email protected]. If you wish to email the authors directly, please see the first page of the publication for their contact information.
    [Show full text]
  • ECA-LP / ECA-Ruleml: a Homogeneous Event-Condition-Action Logic Programming Language, Int
    Paschke, A.: ECA-LP / ECA-RuleML: A Homogeneous Event-Condition-Action Logic Programming Language, Int. Conf. on Rules and Rule Markup Languages for the Semantic Web (RuleML’06), Athens, Georgia, USA, Nov. 2006. Extended Abstract ECA-LP / ECA-RuleML: A Homogeneous Event-Condition-Action Logic Programming Language Adrian Paschke Internet-based Information Systems, Technische Universität München [email protected] Abstract [8] and we assume that the reader is familiar with logic programming tech- Event-driven reactive functionalities are an urgent need in nowadays distributed niques [9]. service-oriented applications and (Semantic) Web-based environments. An impor- Syntax of ECA-LP tant problem to be addressed is how to correctly and efficiently capture and process the event-based behavioral, reactive logic represented as ECA rules in combination A reactive rule in ECA-LP is formalized as an extended ECA rule, repre- with other conditional decision logic which is represented as derivation rules. In sented in the KB as a 6-ary fact with the restricted predicate name “eca”: this paper we elaborate on a homogeneous integration approach which combines eca(T,E,C,A,P,EL), where T (time), E (event), C (condition), A (action), P derivation rules, reaction rules (ECA rules) and other rule types such as integrity constraint into the general framework of logic programming. The developed ECA- (post condition), EL(se) are complex terms/functions [10]. The complex LP language provides expressive features such as ID-based updates with support terms are meta-interpreted by the ECA interpreter as (sub-) goals on further for external and self-updates of the intensional and extensional knowledge, transac- derivation rules in the KB which are used to implement the functionality of tions including integrity testing and an event algebra to define and process complex each part of an ECA rule.
    [Show full text]