Intricacies and Aiding Software Tools Based on Expected Characteristics
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Introduction, Structure, and Advanced Programming Techniques
APQE12-all Advanced Programming in Quantitative Economics Introduction, structure, and advanced programming techniques Charles S. Bos VU University Amsterdam [email protected] 20 { 24 August 2012, Aarhus, Denmark 1/260 APQE12-all Outline OutlineI Introduction Concepts: Data, variables, functions, actions Elements Install Example: Gauss elimination Getting started Why programming? Programming in theory Questions Blocks & names Input/output Intermezzo: Stack-loss Elements Droste 2/260 APQE12-all Outline OutlineII KISS Steps Flow Recap of main concepts Floating point numbers and rounding errors Efficiency System Algorithm Operators Loops Loops and conditionals Conditionals Memory Optimization 3/260 APQE12-all Outline Outline III Optimization pitfalls Maximize Standard deviations Standard deviations Restrictions MaxSQP Transforming parameters Fixing parameters Include packages Magic numbers Declaration files Alternative: Command line arguments OxDraw Speed 4/260 APQE12-all Outline OutlineIV Include packages SsfPack Input and output High frequency data Data selection OxDraw Speed C-Code Fortran Code 5/260 APQE12-all Outline Day 1 - Morning 9.30 Introduction I Target of course I Science, data, hypothesis, model, estimation I Bit of background I Concepts of I Data, Variables, Functions, Addresses I Programming by example I Gauss elimination I (Installation/getting started) 11.00 Tutorial: Do it yourself 12.30 Lunch 6/260 APQE12-all Introduction Target of course I Learn I structured I programming I and organisation I (in Ox or other language) Not: Just -
17H30 : Accueil 18H00 : Présentation 19H00 : Apéro / Discussions
Les Groupwares Open Source 17h30 : Accueil 18h00 : Présentation 19h00 : Apéro / Discussions RDV Techno Evolix ± Les Groupwares Open Source - 14 Avril 2011 - [email protected] - http://www.evolix.fr/ Sommaire - Présentation Evolix et Actualités - Qu'est-ce qu'un Groupware ? - Les protocoles, les standards - Les "clients" Groupware - Les Groupwares Open Source - Focus sur Zimbra - Témoignage de l'École Centrale de Marseille - Conclusion - Nouvelles offres Evolix RDV Techno Evolix ± Les Groupwares Open Source - 14 Avril 2011 - [email protected] - http://www.evolix.fr/ Présentation et Actualités 1/2 Evolix Infogérance d'infrastructures Open Source Chiffres clés : Créé en 2004 7 personnes + de 200 serveurs infogérés RCP couvrant son métier d©infogérance RDV Techno Evolix ± Les Groupwares Open Source - 14 Avril 2011 - [email protected] - http://www.evolix.fr/ Présentation et Actualités 2/2 News Evolix - Planet Evolix : http://planet.evolix.org/ - Dernières références... - WIP : infra EVOLIX-MNT, EvoLinux, Forge RDV Techno Evolix - 4ème édition - Rencontres clients/amis/prospects autour d'un sujet technique RDV Techno Evolix ± Les Groupwares Open Source - 14 Avril 2011 - [email protected] - http://www.evolix.fr/ Qu'est-ce qu'un Groupware ? Un Groupware est un logiciel favorisant le travail collaboratif. RDV Techno Evolix ± Les Groupwares Open Source - 14 Avril 2011 - [email protected] - http://www.evolix.fr/ Def. Groupware Pour mieux définir un Groupware, parlons des autres technologies que l©on retrouve dans un SI : GED (Gestion Electronique des Documents) : Alfresco, MS Project ERP (Logiciel de Gestion d©Entreprise) : OpenERP, OpenBravo, Dolibarr, SAGE, Ciel CRM (Gestion de la Relation Client) : SugarCRM, vTiger, Salesforce Project Management : Trac, Redmine, MS Project Gestion des identifiants/authentification : annuaires (LDAP,AD), SSO (CAS, Shibboleth, Kerberos) Messagerie : Postfix/Dovecot, Exchange, Lotus Notes ...de plus en plus de ces logiciels couvrent plusieurs domaines. -
A Comparison of Six Numerical Software Packages for Educational Use in the Chemical Engineering Curriculum
SESSION 2520 A COMPARISON OF SIX NUMERICAL SOFTWARE PACKAGES FOR EDUCATIONAL USE IN THE CHEMICAL ENGINEERING CURRICULUM Mordechai Shacham Department of Chemical Engineering Ben-Gurion University of the Negev P. O. Box 653 Beer Sheva 84105, Israel Tel: (972) 7-6461481 Fax: (972) 7-6472916 E-mail: [email protected] Michael B. Cutlip Department of Chemical Engineering University of Connecticut Box U-222 Storrs, CT 06269-3222 Tel: (860)486-0321 Fax: (860)486-2959 E-mail: [email protected] INTRODUCTION Until the early 1980’s, computer use in Chemical Engineering Education involved mainly FORTRAN and less frequently CSMP programming. A typical com- puter assignment in that era would require the student to carry out the following tasks: 1.) Derive the model equations for the problem at hand, 2.) Find an appropri- ate numerical method to solve the model (mostly NLE’s or ODE’s), 3.) Write and debug a FORTRAN program to solve the problem using the selected numerical algo- rithm, and 4.) Analyze the results for validity and precision. It was soon recognized that the second and third tasks of the solution were minor contributions to the learning of the subject material in most chemical engi- neering courses, but they were actually the most time consuming and frustrating parts of computer assignments. The computer indeed enabled the students to solve realistic problems, but the time spent on technical details which were of minor rele- vance to the subject matter was much too long. In order to solve this difficulty, there was a tendency to provide the students with computer programs that could solve one particular type of a problem. -
Zanetti Chini E. “Forecaster's Utility and Forecasts Coherence”
ISSN: 2281-1346 Department of Economics and Management DEM Working Paper Series Forecasters’ utility and forecast coherence Emilio Zanetti Chini (Università di Pavia) # 145 (01-18) Via San Felice, 5 I-27100 Pavia economiaweb.unipv.it Revised in: August 2018 Forecasters’ utility and forecast coherence Emilio Zanetti Chini∗ University of Pavia Department of Economics and Management Via San Felice 5 - 27100, Pavia (ITALY) e-mail: [email protected] FIRST VERSION: December, 2017 THIS VERSION: August, 2018 Abstract We introduce a new definition of probabilistic forecasts’ coherence based on the divergence between forecasters’ expected utility and their own models’ likelihood function. When the divergence is zero, this utility is said to be local. A new micro-founded forecasting environment, the “Scoring Structure”, where the forecast users interact with forecasters, allows econometricians to build a formal test for the null hypothesis of locality. The test behaves consistently with the requirements of the theoretical literature. The locality is fundamental to set dating algorithms for the assessment of the probability of recession in U.S. business cycle and central banks’ “fan” charts Keywords: Business Cycle, Fan Charts, Locality Testing, Smooth Transition Auto-Regressions, Predictive Density, Scoring Rules and Structures. JEL: C12, C22, C44, C53. ∗This paper was initiated when the author was visiting Ph.D. student at CREATES, the Center for Research in Econometric Analysis of Time Series (DNRF78), which is funded by the Danish National Research Foundation. The hospitality and the stimulating research environment provided by Niels Haldrup are gratefully acknowledged. The author is particularly grateful to Tommaso Proietti and Timo Teräsvirta for their supervision. -
Rapid Research with Computer Algebra Systems
doi: 10.21495/71-0-109 25th International Conference ENGINEERING MECHANICS 2019 Svratka, Czech Republic, 13 – 16 May 2019 RAPID RESEARCH WITH COMPUTER ALGEBRA SYSTEMS C. Fischer* Abstract: Computer algebra systems (CAS) are gaining popularity not only among young students and schol- ars but also as a tool for serious work. These highly complicated software systems, which used to just be regarded as toys for computer enthusiasts, have reached maturity. Nowadays such systems are available on a variety of computer platforms, starting from freely-available on-line services up to complex and expensive software packages. The aim of this review paper is to show some selected capabilities of CAS and point out some problems with their usage from the point of view of 25 years of experience. Keywords: Computer algebra system, Methodology, Wolfram Mathematica 1. Introduction The Wikipedia page (Wikipedia contributors, 2019a) defines CAS as a package comprising a set of algo- rithms for performing symbolic manipulations on algebraic objects, a language to implement them, and an environment in which to use the language. There are 35 different systems listed on the page, four of them discontinued. The oldest one, Reduce, was publicly released in 1968 (Hearn, 2005) and is still available as an open-source project. Maple (2019a) is among the most popular CAS. It was first publicly released in 1984 (Maple, 2019b) and is still popular, also among users in the Czech Republic. PTC Mathcad (2019) was published in 1986 in DOS as an engineering calculation solution, and gained popularity for its ability to work with typeset mathematical notation in combination with automatic computations. -
Studies and Analysis of Reference Management Software: a Literature Review
Studies and analysis of reference management software: a literature review Jesús Tramullas Ana Sánchez-Casabón {jesus,asanchez}@unizar.es Dept .of Library & Information Science, University of Zaragoza Piedad Garrido-Picazo [email protected] Dept. of Computer and Software Engineering, University of Zaragoza Abstract: Reference management software is a well-known tool for scientific research work. Since the 1980s, it has been the subject of reviews and evaluations in library and information science literature. This paper presents a systematic review of published studies that evaluate reference management software with a comparative approach. The objective is to identify the types, models, and evaluation criteria that authors have adopted, in order to determine whether the methods used provide adequate methodological rigor and useful contributions to the field of study. Keywords: reference management software, evaluation methods, bibliography. 1. Introduction and background Reference management software has been a useful tool for researchers since the 1980s. In those early years, tools were made ad-hoc, and some were based on the dBase II/III database management system (Bertrand and Bader, 1980; Kunin, 1985). In a short period of time a market was created and commercial products were developed to provide support to this type of information resources. The need of researchers to systematize scientific literature in both group and personal contexts, and to integrate mechanisms into scientific production environments in order to facilitate and expedite the process of writing and publishing research results, requires that these types of applications receive almost constant attention in specialized library and information science literature. The result of this interest is reflected, in bibliographical terms, in the publication of numerous articles almost exclusively devoted to describing, analyzing, and comparing the characteristics of several reference management software products (Norman, 2010). -
Session Siptool: the 'Signal and Image Processing Tool'
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by DigitalCommons@CalPoly Session SIPTool: The ‘Signal and Image Processing Tool’ An Engaging Learning Environment Fred DePiero1 Abstract The ‘Signal and Image Processing Tool’ is a With the SIPTool, students create an integrated system multimedia software environment for demonstrating and that includes their processing routine along with developing Signal & Image Processing techniques. It has image/signal acquisition and display. This integrated system been used at CalPoly for three years. A key feature is is a very different result than the ‘haphazard’ line-by-line extensibility via C/C++ programming. The tool has a processing steps that students may or may not successfully minimal learning curve, making it amenable for weekly stumble through in a MatLab environment, as they follow a student projects. The software distribution includes given example. The SIPTool-based implementation is much multimedia demonstrations ready for classroom or more like a complete, commercial product. laboratory use. SIPTool programming assignments strengthen the skills needed for life-long learning by A variety of learning objectives can be readily requiring students to translate mathematical expressions addressed with the SIPTool including: time/frequency into a standard programming language, to create an relationships, 1-D and 2-D Fourier transforms, convolution, integrated processing system (as opposed to simply using correlation, filtering, difference equations, and pole/zero canned processing routines). relationships [1]. Learning objectives associated with image processing can also be presented, such as: gray scale Index Terms Image Processing, Signal Processing, resolution, pixel resolution, histogram equalization, median Software Development Environment, Multimedia Teaching filtering and frequency-domain filtering [2]. -
Public Perceptions of Nigeria Police Monetary Bribery in Awka, Nigeria
Walden University ScholarWorks Walden Dissertations and Doctoral Studies Walden Dissertations and Doctoral Studies Collection 2021 Public Perceptions of Nigeria Police Monetary Bribery in Awka, Nigeria Benjamin Chukwuka Nnadozie Walden University Follow this and additional works at: https://scholarworks.waldenu.edu/dissertations Part of the Public Administration Commons This Dissertation is brought to you for free and open access by the Walden Dissertations and Doctoral Studies Collection at ScholarWorks. It has been accepted for inclusion in Walden Dissertations and Doctoral Studies by an authorized administrator of ScholarWorks. For more information, please contact [email protected]. Walden University College of Social and Behavioral Sciences This is to certify that the doctoral dissertation by Benjamin Chukwuka Nnadozie has been found to be complete and satisfactory in all respects, and that any and all revisions required by the review committee have been made. Review Committee Dr. Ernesto Escobedo, Committee Chairperson, Public Policy and Administration Faculty Dr. Raj Singh, Committee Member, Public Policy and Administration Faculty Dr. Meena Clowes, University Reviewer, Public Policy and Administration Faculty Chief Academic Officer and Provost Sue Subocz, Ph.D. Walden University 2021 Abstract Public Perceptions of Nigeria Police Monetary Bribery in Awka, Nigeria By Benjamin Chukwuka Nnadozie Dissertation Submitted in Partial Fulfullment of the Requirements for the Degree of Doctor of Philosophy Public Policy and Administration Walden University February 2021 Abstract The Nigerian police are often perceived by the Nigerian public as a very corrupt institution due to reports in the media and direct experiences of police brutality, extortion, injustice, and especially monetary bribery. The refusal to pay monetary bribes to the police has led to loss of lives and a lack of trust in the police. -
Using Outlook™ & Insightconnector™ with Mdaemon
Using Outlook™ & InsightConnector™ with MDaemon 6.0 Alt-N Technologies, Ltd 1179 Corporate Drive West, #103 Arlington, TX 76006 Tel: (817) 652-0204 © 2002 Alt-N Technologies. All rights reserved. Outlook™ is a trademark of Microsoft, Inc. InsightConnector™ is a trademark of Bynari, Inc. Other product and company names mentioned in this document may be trademarks. Contents Abstract................................................................................................................3 Outlook and Exchange Server Sharing.............................................................4 Sharing with InsightConnector™.......................................................................6 Installing, Configuring and Using InsightConnector™....................................7 Configuring MDaemon.....................................................................................7 Installing InsightConnector...............................................................................8 Configuring Outlook .........................................................................................9 Configuring InsightConnector ........................................................................10 Creating, Sharing and Synchronizing Folders................................................11 Creating....................................................................................................11 Sharing and Synchronizing.......................................................................12 InsightConnector™ 2 Alt-N Technologies Abstract -
Towards a Fully Automated Extraction and Interpretation of Tabular Data Using Machine Learning
UPTEC F 19050 Examensarbete 30 hp August 2019 Towards a fully automated extraction and interpretation of tabular data using machine learning Per Hedbrant Per Hedbrant Master Thesis in Engineering Physics Department of Engineering Sciences Uppsala University Sweden Abstract Towards a fully automated extraction and interpretation of tabular data using machine learning Per Hedbrant Teknisk- naturvetenskaplig fakultet UTH-enheten Motivation A challenge for researchers at CBCS is the ability to efficiently manage the Besöksadress: different data formats that frequently are changed. Significant amount of time is Ångströmlaboratoriet Lägerhyddsvägen 1 spent on manual pre-processing, converting from one format to another. There are Hus 4, Plan 0 currently no solutions that uses pattern recognition to locate and automatically recognise data structures in a spreadsheet. Postadress: Box 536 751 21 Uppsala Problem Definition The desired solution is to build a self-learning Software as-a-Service (SaaS) for Telefon: automated recognition and loading of data stored in arbitrary formats. The aim of 018 – 471 30 03 this study is three-folded: A) Investigate if unsupervised machine learning Telefax: methods can be used to label different types of cells in spreadsheets. B) 018 – 471 30 00 Investigate if a hypothesis-generating algorithm can be used to label different types of cells in spreadsheets. C) Advise on choices of architecture and Hemsida: technologies for the SaaS solution. http://www.teknat.uu.se/student Method A pre-processing framework is built that can read and pre-process any type of spreadsheet into a feature matrix. Different datasets are read and clustered. An investigation on the usefulness of reducing the dimensionality is also done. -
An Introduction to the SAS System
An Introduction to the SAS System Dileep K. Panda Directorate of Water Management Bhubaneswar-751023 [email protected] Introduction The SAS – Statistical Analysis System (erstwhile expansion of SAS) - is the one of the most widely used Statistical Software package by the academic circles and Industry. The SAS software was developed in late 1960s at North Carolina State University and in 1976 SAS Institute was formed. The SAS system is a collection of products, available from the SAS Institute in North Carolina. SAS software is a combination of a statistical package, a data – base management system, and a high level programming language. The SAS is an integrated system of software solutions that performs the following tasks: Data entry, retrieval, and management Report writing and graphics design Statistical and mathematical analysis Business forecasting and decision support Operations research and project management Applications development At the core of the SAS System is the Base SAS software. The Base SAS software includes a fourth-generation programming language and ready-to-use programs called procedures. These integrated procedures handle data manipulation, information storage and retrieval, statistical analysis, and report writing. Additional components offer capabilities for data entry, retrieval, and management; report writing and graphics; statistical and mathematical analysis; business planning, forecasting, and decision support; operations research and project management; quality improvement; and applications development. In general, the Base SAS software has the following capabilities A data management facility A programming language Data analysis and reporting utilities Learning to use Base SAS enables you to work with these features of SAS. It also prepares you to learn other SAS products, because all SAS products follow the same basic rules. -
Qualitative Research 1
Qualitative research 1 Dr Raqibat Idris, MBBS, DO, MPH Geneva Foundation for Medical Education and Research 28 November 2017 From Research to Practice: Training Course in Sexual and Reproductive Health Research Geneva Workshop 2017 Overview of presentation This presentation will: • Introduce qualitative research, its advantages, disadvantages and uses • Discuss the various approaches to qualitative design Introduction • Qualitative research is a study done to explain and understand the meaning or experience of a phenomenon or social process and the viewpoints of the affected individuals. • Investigates opinions, feelings and experiences. • Understands and describes social phenomena in their natural occurrence- holistic approach. • Does not test theories but can develop theories. Mason, 2002 Features of qualitative research • Exploratory • Fluid and flexible • Data-driven • Context sensitive • Direct interaction with affected individuals Mason, 2002 Advantages and disadvantages Advantages: • Richer information • Deeper understanding of the phenomenon under study Disadvantages: • Time consuming • Expensive • Less objective • Findings cannot be generalized Mason, 2002 Uses of qualitative studies Exploratory or pilot study: • Precedes a quantitative study to help refine hypothesis • Pilot study to examine the feasibility of a program/ project implementation • Designing survey questionnaires • To improve the reliability, validity and sensibility of new or existing survey instruments in a new population Green, 2013 Uses of qualitative studies To explain quantitative data findings: • Can follow a quantitative research to help provide a deeper understanding of the results. For example, the use of ethnography to explain the social context in which mortality and birth rate data are produced. • Parallel studies in a mixed qualitative and quantitative design to provide greater understanding of a phenomenon under study.