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Cause and Effect Analysis
 
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Learn about CE diagrams & how they can be used to establish the root causes of problems. Click Cc button to see subtitles in English. Next, you may want to understand computer security terms at https://youtu.be/ASxswzGt41g
Teori 16   Data Mining
 
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Video ini berisi penjelasan dan latihan soal tentang TEORI DATA MINING Dosen Pembimbing : Rengga Asmara, S.Kom, OCA.
Views: 20 Zulfan Fathoni
IEEE Control System Simulation Nonlinear system identification and control using state transition
 
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We are providing a Final year IEEE project solution & Implementation with in short time. If anyone need a Details Please Contact us Mail: [email protected] Phone: 09842339884, 09688177392 Watch this also: https://www.youtube.com/channel/UCDv0caOoT8VJjnrb4WC22aw Nonlinear system identification and control using state transition algorithm ieee projects, ieee java projects , ieee dotnet projects, ieee android projects, ieee matlab projects, ieee embedded projects,ieee robotics projects,ieee ece projects, ieee power electronics projects, ieee mtech projects, ieee btech projects, ieee be projects,ieee cse projects, ieee eee projects,ieee it projects, ieee mech projects ,ieee e&I projects, ieee IC projects, ieee VLSI projects, ieee front end projects, ieee back end projects , ieee cloud computing projects, ieee system and circuits projects, ieee data mining projects, ieee image processing projects, ieee matlab projects, ieee simulink projects, matlab projects, vlsi project, PHD projects,ieee latest MTECH title list,ieee eee title list,ieee download papers,ieee latest idea,ieee papers,ieee recent papers,ieee latest BE projects,ieee B tech projects,ieee ns2 projects,ieee ns3 projects,ieee networking projects,ieee omnet++ projects,ieee hfss antenna projects,ieee ADS antenna projects,ieee LABVIEW projects,ieee bigdata projects,ieee hadoop projects,ieee network security projects. ieee latest MTECH title list,ieee eee title list,ieee download papers,ieee latest idea,ieee papers,ieee recent papers,ieee latest BE projects, download IEEE PROJECTS,ieee B tech projects,ieee 2015 projects. Image Processing ieee projects with source code,VLSI projects source code,ieee online projects.best projects center in Chennai, best projects center in trichy, best projects center in bangalore,ieee abstract, project source code, documentation ,ppt ,UML Diagrams,Online Demo and Training Sessions., Engineering Project Consultancy, IEEE Projects for M.Tech, IEEE Projects for BE,IEEE Software Projects, IEEE Projects in Bangalore, IEEE Projects Diploma, IEEE Embedded Projects, IEEE NS2 Projects, IEEE Cloud Computing Projects, Image Processing Projects, Project Consultants in Bangalore, Project Management Consultants, Electrical Consultants, Project Report Consultants, Project Consultants For Electronics, College Project Consultants, Project Consultants For MCA, Education Consultants For PHD, Microsoft Project Consultants, Project Consultants For M Phil, Consultants Renewable Energy Project, Engineering Project Consultants, Project Consultants For M.Tech, BE Project Education Consultants, Engineering Consultants, Mechanical Engineering Project Consultants, Computer Software Project Management Consultants, Project Consultants For Electrical, Project Report Science, Project Consultants For Computer, ME Project Education Consultants, Computer Programming Consultants, Project Consultants For Bsc, Computer Consultants, Mechanical Consultants, BCA live projects institutes in Bangalore, B.Tech live projects institutes in Bangalore,MCA Live Final Year Projects Institutes in Bangalore,M.Tech Final Year Projects Institutes in Bangalore,B.E Final Year Projects ,ieee projects bangalore,ieee projects pune,Institutes in Bangalore , M.E Final Year Projects Institutes in Bangalore,Live Projects,Academic Projects, IEEE Projects, Final year Diploma, B.E, M.Tech,M.S BCA, MCA Do it yourself projects, project assistance with project report and PPT, Real time projects, Academic project guidance Bengaluru,projects at Bangalore, Bangalore at projects,Vlsi projects at Bangalore, Matlab projects at Bangalore, power electronics projects at Bangalore,ns2 projects at Bangalore,ns3 project at Bangalore, Engineering Project Consultants bangalore, Engineering projects jobs Bangalore, Academic Project Guidance for Electronics, Free Synopsis, Latest project synopsiss ,recent ieee projects ,recent engineering projects ,innovative projects. ieee matlab ac to dc projects,ieee matlab dc to dc projects,ieee matlab pid projects,ieee matlab PI projects,ieee matlab fuzzy controller projects,ieee matlab ANFIS projects,ieee fuzzy logic projects,ieee projects converters projects,ieee projects inverter projects,ieee matlab sepic converter projects,ieee matlab buck converter projects,ieee matlab cuk converter,ieee matlab fuzzy logic projects,ieee matlab multilevel converter projects,ieee matlab 14 bus projects,ieee matlab genetic algorithm projects,ieee matlab 7 bus projects,ieee matlab nine bus projects,ieee matlab switching capacitor projects,ieee matlab renewable energy projects,ieee matlab grid based projects,ieee matlab smart grid projects, ieee matlab inverter projects,ieee matlab cascaded projects,ieee matlab recent projects
The best stats you've ever seen | Hans Rosling
 
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http://www.ted.com With the drama and urgency of a sportscaster, statistics guru Hans Rosling uses an amazing new presentation tool, Gapminder, to present data that debunks several myths about world development. Rosling is professor of international health at Sweden's Karolinska Institute, and founder of Gapminder, a nonprofit that brings vital global data to life. (Recorded February 2006 in Monterey, CA.) TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes. TED stands for Technology, Entertainment, Design, and TEDTalks cover these topics as well as science, business, development and the arts. Closed captions and translated subtitles in a variety of languages are now available on TED.com, at http://www.ted.com/translate. Follow us on Twitter http://www.twitter.com/tednews Checkout our Facebook page for TED exclusives https://www.facebook.com/TED
Views: 2768775 TED
MDMap : A System for Data-Driven Layout and Exploration of Molecular Dynamics Simulations
 
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R. Patro, C.Y. Ip, S. Bista, S.S. Cho, D. Thirumalai, and A. Varshney IEEE Symposium on Biological Data Visualization , 2011 Contemporary molecular dynamics simulations result in a glut of simulation data, making analysis and discovery a difficult and burdensome task. We present MDMap, a system designed to summarize long-running molecular dynamics (MD) simulations. We represent a molecular dynamics simulation as a state transition graph over a set of intermediate (stable and semi-stable) states. The transitions amongst the states together with their frequencies represent the flow of a biomolecule through the trajectory space. MDMap automatically determines potential intermediate conformations and the transitions amongst them by analyzing the conformational space explored by the MD simulation. MDMap is an automated system to visualize MD simulations as state-transition diagrams, and can replace the current tedious manual layouts of biomolecular folding landscapes with an automated tool. The layout of the representative states and the corresponding transitions among them is presented to the user as a visual synopsis of the long-running MD simulation. We compare and contrast multiple presentations of the state transition diagrams, such as conformational embedding, and spectral, hierarchical, and force-directed graph layouts. We believe this system could provide a road-map for the visualization of other stochastic time-varying simulations in a variety of different domains.
Views: 215 GVIL UMD
Control Flow Graphs - Georgia Tech - Software Development Process
 
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Watch on Udacity: https://www.udacity.com/course/viewer#!/c-ud805/l-3670758553/m-438878582 Check out the full Advanced Operating Systems course for free at: https://www.udacity.com/course/ud805 Georgia Tech online Master's program: https://www.udacity.com/georgia-tech
Views: 51746 Udacity
STNMaker: Edition of the text into a state of a state transition network (STN) diagram
 
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STNMaker develops in Java 2D a mode-less UI application that allows to build state transition network diagrams (STN). STNMaker was developed by Daniel García Baena for his end of Computer Science Engineering project in the Jaen University. This project was scored with 10 points of a total of 10. You can ask me any questions leaving a comment or visiting my YouTube channel.
MDS Diagram Creation Tutorial
 
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How to create diagrams of use in the Multimodal Diagram System. http://tonarie.com
Views: 43 MDS APP
Introduction to BDDs
 
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Efficient representations for boolean functions, an introduction to BDDs
Views: 16038 Model Checking
Getting Started with TreeAge Pro
 
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Decision analysis with TreeAge Pro 2009. A video to help you get started with some of the essential elements of building a decision tree.
Views: 14483 carapinha711
How to: Business Model Diagram
 
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How to create a business model diagram so other people (and you) can understand it.
Privacy Preserving Event Sequence Data Visualization using a Sankey Diagram-like Representation
 
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Title: Privacy Preserving Event Sequence Data Visualization using a Sankey Diagram-like Representation Authors: Jia-Kai Chou, Yang Wang and Kwan-Liu Ma Project Page: http://vidi.cs.ucdavis.edu/People/ChouJia-Kai Abstract: Given the growing rates and richness of data being collected nowadays, it is non-trivial for data owners to determine a single best publishing granularity that presents the most value of the data while preserving its privacy. There have been extensive studies on privacy preserving algorithms in the data mining community, but relatively few have been done to provide a supervised control over the anonymization process. We present the design and evaluation of a visual interface that assists users to employ commonly used data anonymization techniques for making privacy preserving visualizations of the data. We focus on event sequence data due to its vulnerability to privacy concerns. Our visual interface is designed for data owners to examine potential privacy issues, obfuscate information as suggested by the algorithm, and fine-tune the results per their requests. Case studies using multiple datasets under different scenarios demonstrate the effectiveness of our design. These studies show that using visualization as an interface can help identify potential privacy issues, reveal underlying anonymization processes, and allow users to balance between data utility and privacy.
Views: 102 VIDI Labs
Decision Tables
 
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AS Computing - Decision Tables
Views: 25033 Comp Franklin
Where did they go?  Where did they come from?  - with narration
 
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Exploration of data visualization using provincial data for the 2007-2008 to 2010-2011 EQAO Reading Assessment Cohort. This video includes explanatory narration.
Views: 4633 ResearchChat
Transaction Management, ACID Properties in DBMS(English|Hindi)
 
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DBMS Tutorial - Transaction Management, ACID Properties in DBMS(English|Hindi) for for students of IP University Delhi and Other Universities, Engineering, MCA, BCA, B.Sc, M.Sc Colleges.
Views: 164890 Easy Engineering Classes
transaction management in dbms tutorial | DBMS
 
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DBMS transaction management -select -insert -update
Views: 12185 Education 4u
Automatic Speech Recognition - An Overview
 
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An overview of how Automatic Speech Recognition systems work and some of the challenges. See more on this video at https://www.microsoft.com/en-us/research/video/automatic-speech-recognition-overview/
Views: 26777 Microsoft Research
APSEC 2009 Checking Model Consistency using Data-Flow Testing---Part II
 
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Rafflesia Room, Bayview Beach Resort, Batu Ferringhi, Penang, Malaysia Asia-Pacific Software Engineering Conference APSEC 2009 Title: Checking Model Consistency using Data-Flow Testing Contents: - Booster * Quick Overview * Example on Declaring Bi-Directional Associations * Example on Student Management System * Example on Model Operations Described as Predicates * Booster Runtime Semantics---relations and substitutions * Example on Identifying Intra-Method Usage Patterns * Example on Composing Inter-Method Usage Patterns
Views: 246 Jackie Wang
ERPEM 2014 - Phase transitions in convex optimization problems with random data - Part 2
 
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ERPEM 2014 - 10º Encuentro Regional de Probabilidad y Estadística Matemática - High dimensional phenomena in Probability, Statistics and Signal Processing Joel Tropp - Phase transitions in convex optimization problems with random data - Part 2 Página: http://www.impa.br/opencms/en/eventos/store_old/evento_1412 Download dos vídeos: http://video.impa.br/index.php?page=erpem-2014 The Tenth Regional Meeting on Probability and Mathematical Statistics will be held at IMPA in Rio de Janeiro, Brazil, from November 10th to 14th, 2014. As with previous ERPEMs, the goal of this meeting is to promote interactions amongst among advanced students, young researchers and leading experts of the region, to encourage new collaborations and allow for active exchange of ideas through informal discussions. ERPEM 2014 will have a thematic focus on "High Dimensional Phenomena in Probability, Statistics and Signal Processing", with a five-hour minicourse and four two-hour-long invited lectures covering topics related to Empirical Processes, Compressed Sensing and High Dimensional Sparse Statistics. We hope these activities will generate enthusiasm for these areas in the region. The program is complemented by a non-thematic special lecture, contributed talks and a poster session. In addition to these activities, a week long introductory minicourse on "Randomness, Matrices and High Dimensional Problems" will be presented at IMPA on Nov 3rd-7th, 2014. This course is meant to facilitate active engagement in ERPEM, and should be accessible to all students and researchers with a solid understanding of basic measure-theoretic Probability. IMPA - Instituto Nacional de Matemática Pura e Aplicada © http://www.impa.br | http://video.impa.br
IPAM: Baron Peters - "Transition path sampling and quantitative mechanistic hypothesis testing"
 
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2014 Hands-on Summer School: Electronic Structure Theory for Materials and (Bio)molecules "Transition path sampling and quantitative mechanistic hypothesis testing" Baron Peters, University of California, Santa Barbara (UCSB) Institute for Pure and Applied Mathematics July 30, 2014 For more information: http://www.ipam.ucla.edu/abstract/?tid=11931&pcode=GSS2014
Noun Extraction
 
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Considerably speed up growing your vocabularies by extracting nouns from already articulated terms.
Views: 406 CollibraBelgium
Mining Anomalies in Network-Wide Flow Data
 
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Speakers: Mark Crovella, Boston University. Christophe Diot, Thomson Paris Research. Anukool Lakhina, Boston University Network operators are routinely confronted with a wide range of anomalies—ranging from abuse-related events (DOS attacks, worms, scans) to maintenance issues (outages, misconfigurations, etc.) to unusual customer behavior (flash crowds, shift in customer demands, etc.). To mitigate their effect, operators need to mine network-wide data for anomalies as they occur, and once detected, classify them in order to select the appropriate response. In this talk, we will present techniques to detect and classify anomalies in network-wide flow traffic data. We will then apply our methods on data collected from two backbone networks, and show that they can: 1) detect a broad set of anomalies, at a low false alarm rate, and 2) automatically classify anomalies into meaningful categories. See more at: https://www.nanog.org/meetings/nanog35/agenda
Views: 46 TeamNANOG
Rick Astley - Never Gonna Give You Up (Video)
 
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Rick Astley - Never Gonna Give You Up (Official Video) - Listen On Spotify: http://smarturl.it/AstleySpotify Learn more about the brand new album ‘Beautiful Life’: https://RickAstley.lnk.to/BeautifulLifeND Buy On iTunes: http://smarturl.it/AstleyGHiTunes Amazon: http://smarturl.it/AstleyGHAmazon Follow Rick Astley Website: http://www.rickastley.co.uk/ Twitter: https://twitter.com/rickastley Facebook: https://www.facebook.com/RickAstley/ Instagram: https://www.instagram.com/officialric... #RickAstley #NeverGonnaGiveYouUp #RickAstleyofficial #RickAstleyAlbum #RickAstleyofficialvideo #RickAstleyofficialaudio #RickAstleysongs #RickAstleyNeverGonnaGiveYouUp #WRECKITRALPH2 #RALPHBREAKSTHEINTERNET Lyrics We're no strangers to love You know the rules and so do I A full commitment's what I'm thinking of You wouldn't get this from any other guy I just wanna tell you how I'm feeling Gotta make you understand Never gonna give you up Never gonna let you down Never gonna run around and desert you Never gonna make you cry Never gonna say goodbye Never gonna tell a lie and hurt you We've known each other for so long Your heart's been aching, but You're too shy to say it Inside, we both know what's been going on We know the game and we're gonna play it And if you ask me how I'm feeling Don't tell me you're too blind to see Never gonna give you up Never gonna let you down Never gonna run around and desert you Never gonna make you cry Never gonna say goodbye Never gonna tell a lie and hurt you Never gonna give you up Never gonna let you down Never gonna run around and desert you Never gonna make you cry Never gonna say goodbye Never gonna tell a lie and hurt you (Ooh, give you up) (Ooh, give you up) Never gonna give, never gonna give (Give you up) Never gonna give, never gonna give (Give you up) We've known each other for so long Your heart's been aching, but You're too shy to say it Inside, we both know what's been going on We know the game and we're gonna play it I just wanna tell you how I'm feeling Gotta make you understand Never gonna give you up Never gonna let you down Never gonna run around and desert you Never gonna make you cry Never gonna say goodbye Never gonna tell a lie and hurt you Never gonna give you up Never gonna let you down Never gonna run around and desert you Never gonna make you cry Never gonna say goodbye Never gonna tell a lie and hurt you Never gonna give you up Never gonna let you down Never gonna run around and desert you Never gonna make you cry Never gonna say goodbye Never gonna tell a lie and hurt you"
Views: 507573551 RickAstleyVEVO
DECISION TABLE TESTING||BTECH||SOFTWARE ENGINEERING||TH SEM LECT23
 
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DECISION TABLE TESTING||BTECH||SOFTWARE ENGINEERING||TH SEM LECT23
Views: 1272 KS ACADEMY
TESTONA Tutorial - Classification Tree Method - Part 1
 
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A basic problem in software testing often is choosing a subset from the near infinite number of possible test cases. Consider the challenges of testing multiple browsers, multiple mobile devices, mobile applications, or use case paths. Testers must select test cases to design, create, and then execute to obtain sufficient coverage—all while managing the time it takes to test relative to risks. Even though test resources are limited, you still want to select the best possible set of tests. Peter Kruse, test expert from Assystem Germany, shares his experiences designing test cases with TESTONA, the most popular tool for systematic test design of classification tree-based tests. Peter shows in his tutorials the benefits of the classification tree method, gives a TESTONA tool demo and explains how to use integrate expected test outcomes and how to obtain executable test scripts directly from the test specification or user stories. If you are looking to jumpstart your systematic test design and want to avoid unnecessary tests and overhead, this series of 4 tutorial are for you! PART 1 – CLASSIFICATION TREE METHOD - Introduction PART 2 – DEMO FOR TOOL-BASED TEST DESIGN WITH TESTONA PART 3 – TEST ORACLE / EXPECTED RESULTS WITH TESTONA PART 4 – TEST SCRIPTING WITH TESTONA
Views: 1195 Assystem Germany
5-Number Summary; Boxplot
 
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This clip demonstrates a 5-Number Summary and its connection to a Boxplot.
Views: 77952 John Quinn
An Introduction to Temporal Databases
 
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In the past manipulating temporal data was rather ad hoc and in the form of simple solutions. Today organizations strongly feel the need to support temporal data in a coherent way. Consequently, there is an increasing interest in temporal data and major database vendors recently provide tools for storing and manipulating temporal data. However, these tools are far from being complete in addressing the main issues in handling temporal data. The presentation uses the relational data model in addressing the subtle issues in managing temporal data: comparing database states at two different time points, capturing the periods for concurrent events and accessing to times beyond these periods, sequential semantics, handling multi-valued attributes, temporal grouping and coalescing, temporal integrity constraints, rolling the database to a past state and restructuring temporal data, etc. It also lays the foundation in managing temporal data in NoSQL databases as well. Having ranges as a data type PostgresSQL has a solid base in implementing a temporal database that can address many of these issues successfully. About the Speaker Abdullah Uz Tansel is professor of Computer Information Systems at the Zicklin School of Business at Baruch College and Computer Science PhD program at the Graduate Center. His research interests are database management systems, temporal databases, data mining, and semantic web. Dr. Tansel published many articles in the conferences and journals of ACM and IEEE. Dr. Tansel has a pending patent application on semantic web. Currently, he is researching temporality in RDF and OWL, which are semantic web languages. Dr. Tansel served in program committees of many conferences and headed the editorial board that published the first book on temporal databases in 1993. He is also one the editors of the forth coming book titled Recommendation and Search in Social Networks to be published by Springer. He received BS, MS and PhD degrees from the Middle East Technical University, Ankara Turkey. He also completed his MBA degree in the University of Southern California. Dr. Tansel is a member of ACM and IEEE Computer Society.
Views: 568 Postgres Conference
Christos Faloutsos: NC State Computer Science "Taming the Data" talk
 
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An invited talk by Dr. Christos Faloutsos in the NC State Computer Science Department's "Taming the Data" speaker series. For a complete transcript of this video, visit http://www.ncsu.edu/youtube/transcript/faloutsos-transcript.doc.
Views: 363 NCState
5/24/18  Red Hat Linux DHCP Vulnerability | AT&T ThreatTraq
 
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Read the story at: http://go.att.com/6f7b535 Originally recorded May 22, 2018 AT&T ThreatTraq welcomes your e-mail questions and feedback at [email protected] AT&T Data Security Analysts Matt Keyser, Stan Nurilov, Murray Ortiz and Bindu Sundaresan discuss the week's top cyber security news, and share news on the current trends of malware, spam, and internet anomalies observed on the AT&T Network.
Views: 173 AT&T Tech Channel
Making Scatter Plots/Trendlines in Excel
 
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The title says it all! Check out my Channel at www.burkeyacademy.com for more videos on Statistics and Economics. If you like what I am doing, please consider supporting this effort on Patreon or buy me a cookie through PayPal! https://www.patreon.com/burkeyacademy http://paypal.me/BurkeyAcademy www.burkeyacademy.com
Views: 136741 BurkeyAcademy
Retrospective Higher-Order Markov Processes for User Trails
 
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Retrospective Higher-Order Markov Processes for User Trails Tao Wu (Purdue University) David Gleich (Purdue University) Users form trails as they browse the web, checkin with a geolocation, rate items, or consume media. A common problem is to estimate what a user might do next for the purposes of guidance, recommendation, or prefetching. First-order and higher-order Markov chains have been one of the most widely used methods to study such sequences of data. First-order Markov chains are easy to estimate, but lack accuracy when history matters. Higher-order Markov chains suffer from overfitting due to their large numbers of parameters and the sparsity in the training data. Regularized fitting only offers mild improvements to the accuracy. In this paper we propose the retrospective higher-order Markov process (RHOMP) as a low-parameter model for such sequences. This model is a special case of a higher-order Markov chain where the transitions depend retrospectively on a single history state instead of an arbitrary combination of history states. There are two immediate computational advantages: the model complexity only grows linear with the order of the Markov chains and such model scales to large state spaces. Furthermore, by providing a specific structure to the higher-order chain, RHOMPs improve the model accuracy by efficiently utilizing history states without risks of overfitting the data. We demonstrate how to estimate a RHOMP from data and we demonstrate the effectiveness of our method on various real application datasets spanning geolocation data, review sequences, and locations. The RHOMP model uniformly outperforms higher-order Markov chains, Kneser-Ney regularization, and tensor factorizations in terms of prediction accuracy. More on http://www.kdd.org/kdd2017/
Views: 218 KDD2017 video
Mobile data gathering with bounded relay in wireless sensor networks - IEEE PROJECTS 2018
 
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Mobile data gathering with bounded relay in wireless sensor networks - IEEE PROJECTS 2018 Download projects @ www.micansinfotech.com WWW.SOFTWAREPROJECTSCODE.COM https://www.facebook.com/MICANSPROJECTS Call: +91 90036 28940 ; +91 94435 11725 IEEE PROJECTS, IEEE PROJECTS IN CHENNAI,IEEE PROJECTS IN PONDICHERRY.IEEE PROJECTS 2018,IEEE PAPERS,IEEE PROJECT CODE,FINAL YEAR PROJECTS,ENGINEERING PROJECTS,PHP PROJECTS,PYTHON PROJECTS,NS2 PROJECTS,JAVA PROJECTS,DOT NET PROJECTS,IEEE PROJECTS TAMBARAM,HADOOP PROJECTS,BIG DATA PROJECTS,Signal processing,circuits system for video technology,cybernetics system,information forensic and security,remote sensing,fuzzy and intelligent system,parallel and distributed system,biomedical and health informatics,medical image processing,CLOUD COMPUTING, NETWORK AND SERVICE MANAGEMENT,SOFTWARE ENGINEERING,DATA MINING,NETWORKING ,SECURE COMPUTING,CYBERSECURITY,MOBILE COMPUTING, NETWORK SECURITY,INTELLIGENT TRANSPORTATION SYSTEMS,NEURAL NETWORK,INFORMATION AND SECURITY SYSTEM,INFORMATION FORENSICS AND SECURITY,NETWORK,SOCIAL NETWORK,BIG DATA,CONSUMER ELECTRONICS,INDUSTRIAL ELECTRONICS,PARALLEL AND DISTRIBUTED SYSTEMS,COMPUTER-BASED MEDICAL SYSTEMS (CBMS),PATTERN ANALYSIS AND MACHINE INTELLIGENCE,SOFTWARE ENGINEERING,COMPUTER GRAPHICS, INFORMATION AND COMMUNICATION SYSTEM,SERVICES COMPUTING,INTERNET OF THINGS JOURNAL,MULTIMEDIA,WIRELESS COMMUNICATIONS,IMAGE PROCESSING,IEEE SYSTEMS JOURNAL,CYBER-PHYSICAL-SOCIAL COMPUTING AND NETWORKING,DIGITAL FORENSIC,DEPENDABLE AND SECURE COMPUTING,AI - MACHINE LEARNING (ML),AI - DEEP LEARNING ,AI - NATURAL LANGUAGE PROCESSING ( NLP ),AI - VISION (IMAGE PROCESSING),mca project SOFTWARE ENGINEERING,COMPUTER GRAPHICS 1. Reviving Sequential Program Birthmarking for Multithreaded Software Plagiarism Detection 2. EVA: Visual Analytics to Identify Fraudulent Events 3. Performance Specification and Evaluation with Unified Stochastic Probes and Fluid Analysis 4. Trustrace: Mining Software Repositories to Improve the Accuracy of Requirement Traceability Links 5. Amorphous Slicing of Extended Finite State Machines 6. Test Case-Aware Combinatorial Interaction Testing 7. Using Timed Automata for Modeling Distributed Systems with Clocks: Challenges and Solutions 8. EDZL Schedulability Analysis in Real-Time Multicore Scheduling 9. Ant Colony Optimization for Software Project Scheduling and Staffing with an Event-Based Scheduler 10. Locating Need-to-Externalize Constant Strings for Software Internationalization with Generalized String-Taint Analysis 11. Systematic Elaboration of Scalability Requirements through Goal-Obstacle Analysis 12. Centroidal Voronoi Tessellations- A New Approach to Random Testing 13. Ranking and Clustering Software Cost Estimation Models through a Multiple Comparisons Algorithm 14. Pair Programming and Software Defects--A Large, Industrial Case Study 15. Automated Behavioral Testing of Refactoring Engines 16. An Empirical Evaluation of Mutation Testing for Improving the Test Quality of Safety-Critical Software 17. Self-Management of Adaptable Component-Based Applications 18. Elaborating Requirements Using Model Checking and Inductive Learning 19. Resource Management for Complex, Dynamic Environments 20. Identifying and Summarizing Systematic Code Changes via Rule Inference 21. Generating Domain-Specific Visual Language Tools from Abstract Visual Specifications 22. Toward Comprehensible Software Fault Prediction Models Using Bayesian Network Classifiers 23. On Fault Representativeness of Software Fault Injection 24. A Decentralized Self-Adaptation Mechanism for Service-Based Applications in the Cloud 25. Coverage Estimation in Model Checking with Bitstate Hashing 26. Synthesizing Modal Transition Systems from Triggered Scenarios 27. Using Dependency Structures for Prioritization of Functional Test Suites INFORMATION AND COMMUNICATION SYSTEM 1. A Data Mining based Model for Detection of Fraudulent Behaviour in Water Consumption SERVICES COMPUTING 1. SVM-DT-Based Adaptive and Collaborative Intrusion Detection (jan 2018) 2. Cloud Workflow Scheduling With Deadlines And Time Slot Availability (March-April 1 2018) 3. Secure and Sustainable Load Balancing of Edge Data Centers in Fog Computing (17 May 2018) 4. Semantic-based Compound Keyword Search over Encrypted Cloud Data 5. Quality and Profit Assured Trusted Cloud Federation Formation: Game Theory Based Approach 6. Optimizing Autonomic Resources for the Management of Large Service-Based Business Processes
NuSMV Tool Checker Demo
 
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Views: 1033 Michael Chu
Software Engineering | C5 - L5 | Use case modeling
 
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جامعة الملك خالد - عمادة التعلم الإلكتروني المقررات المفتوحة - Software Engineering EE524 Unit 5 : جامعة الملك خالد - عمادة التعلم الإلكتروني المقررات المفتوحة - Software Engineering EE524 Unit 5 : System Modeling Lecture 5 : Use case modeling Transfer-data use case Use cases in the MHC-PMS involving the role ‘Medical Receptionist’
Equivalence Partitioning
 
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Лекция: Equivalence Partitioning Курс: Осигуряване качеството на софтуера 2015 Лектор: Михаил Парванов и Димитър Гошев Дата: 16 декември 2015 Уебсайт на Академията на Телерик: http://academy.telerik.com Следете за предстоящи безплатни обучения на Академията на Телерик във Facebook: http://www.facebook.com/TelerikAcademy.
Views: 591 Telerik Academy
Understanding STAR-DELTA Starter !
 
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You might have seen that in order to start a high power rating induction motor, a starting technique called star-delta is used. In this video, we will understand why a star-delta starter is needed, and how it is accomplished practically with help of animation. We thank our patrons for making LE's educational service sustainable. Please support us at Patreon.com so that we will have the capability to release 2 videos/month. https://www.patreon.com/LearnEngineering Curious about how LE was born ?, Check out our story : https://goo.gl/otQfvD Like us on FB : https://www.facebook.com/LearnEngineering Voice-over artist : https://www.fiverr.com/mikepaine
Views: 1938946 Learn Engineering
State of the Art Tools for Signal Integrity and Power Integrity Analysis
 
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With ever increasing design complexity and link speeds, it is critical that designers have access to the fastest and most accurate simulation tools. In this webcast, we explore the latest design challenges that SI and PI engineers are facing and how our new ADS 2016 tools meet these challenges.
Views: 1681 Keysight EEsof EDA
Structured Doubly Stochastic Matrix for Graph Based Clustering
 
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Author: Xiaoqian Wang, Department of Computer Science and Engineering, University of Texas at Arlington Abstract: As one of the most significant machine learning topics, clustering has been extensively employed in various kinds of area. Its prevalent application in scientific research as well as industrial practice has drawn high attention in this day and age. A multitude of clustering methods have been developed, among which the graph based clustering method using the affinity matrix has been laid great ephasis on. Recent research work used the doubly stochastic matrix to normalize the input affinity matrix and enhance the graph based clustering models. Although the doubly stochastic matrix can improve the clustering performance, the clustering structure in the doubly stochastic matrix is not clear as expected. Thus, post-processing step is required to extract the final clustering results, which may not be optimal. To address this problem, in this paper, we propose a novel convex model to learn the structured doubly stochastic matrix by imposing low-rank constraint on the graph Laplacian matrix. Our new structured doubly stochastic matrix can explicitly uncover the clustering structure and encode the probabilities of pair-wise data points to be connected, such that the clustering results are enhanced. An efficient optimization algorithm is derived to solve our new objective. Also, we provide theoretical discussions that when the input differs, our method possesses interesting connections with K-means and spectral graph cut models respectively. We conduct experiments on both synthetic and bench-mark datasets to validate the performance of our proposed method. The empirical results demonstrate that our model provides an approach to better solving the K-mean clustering problem. By using the cluster indicator provided by our model as initialization, K-means converges to a smaller objective function value with better clustering performance. Moreover, we compare the clustering performance of our model with spectral clustering and related double stochastic model. On all datasets, our method performs equally or better than the related methods. More on http://www.kdd.org/kdd2016/ KDD2016 Conference is published on http://videolectures.net/
Views: 364 KDD2016 video
Mining Tools for Large-Scale Networks, Babis Tsourakakis
 
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Finding large near-cliques in massive networks is a notoriously hard problem of great importance to many applications, including anomaly detection in security, community detection in social networks, and mining the Web graph. How can we exploit idiosyncrasies of real-world networks in order to solve this NP-hard problem efficiently? Can we find dense subgraphs in graph streams with a single pass over the stream? Can we design near real time algorithms for time-evolving networks? In this talk I will answer these questions in the affirmative. I will also present state-of-the-art exact and approximation algorithms for extraction of large near-cliques from large-scale networks, the k-clique densest subgraph problem, which run in a few seconds on a typical laptop. I will present graph mining applications, including anomaly detection in citation networks, and planning a successful cocktail party. I will conclude my talk with some interesting research directions.
Views: 200 MMDS Foundation
OCR A'Level Use of abstraction
 
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OCR Specification Reference A Level 2.2.2e Why do we disable comments? We want to ensure these videos are always appropriate to use in the classroom. However, we value your feedback, and are happy to consider amendments due to inaccuracies. Please get in touch with us directly at: [email protected]
Views: 2255 craigndave
Structuring the Space: A Study on Enriching Node-Link Diagrams with Visual References
 
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Full Title: Structuring the Space: A Study on Enriching Node-Link Diagrams with Visual References Authors: Basak E Alper, Nathalie Henry Riche, Tobias Hollerer Abstract: Exploring large visualizations that do not fit in the screen raises orientation and navigation challenges. Structuring the space with additional visual references such as grids or contour lines provide spatial landmarks that may help viewers form a mental model of the space. However, previous studies report mixed results regarding their utility. While some evidence showed that grid and other visual embellishments improve memorability, experiments with contour lines suggest otherwise. In this work, we describe an evaluation framework to capture the impact of introducing visual references in node-link diagrams. We present the results of three controlled experiments that deepen our understanding on enriching large visualization spaces with visual structures. In particular, we provide the first tangible evidence that contour lines have significant benefits when navigating large node-link diagrams. DOI:http://doi.acm.org/10.1145/2556288.2557112
TOC - Tamil - Epsilon NFA - ε closure of a state
 
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Here I explained the process of finding ε closure of each states from ε-NFA state diagram in Tamil.
Views: 60 VKJTECH
Interpolated N-Grams for Model Based Testing
 
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Models - in particular finite state machine models - provide an invaluable source of information for the derivation of effective test cases. However, models usually approximate part of the program semantics and capture only some of the relevant dependencies and constraints. As a consequence, some of the test cases that are derived from models are infeasible. In this paper, we propose a method, based on the computation of the N-gram statistics, to increase the likelihood of deriving feasible test cases from a model. Correspondingly, the level of model coverage is also expected to increase, because infeasible test cases do not contribute to coverage. While N-grams do improve existing test case derivation methods, they show limitations when the N-gram statistics is incomplete, which is expected to necessarily occur as N increases. Interpolated N-grams overcome such limitation and show the highest performance of all test case derivation methods compared in this work.
Views: 355 Paolo Tonella
Force Field Analysis 1
 
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via YouTube Capture
Views: 401 Joan Thorvaldson
AnyLogic Statechart Transitions Types [Agent-Based Modeling for Health Policy with AnyLogic]
 
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Syllabus page with additional information is available at http://tinyurl.com/AnyLogicABM Lectures on related materials are available at http://www.cs.usask.ca/faculty/ndo885/Classes/index.html
Views: 3140 Nathaniel Osgood
Tornado Forecasting with Multiple Markov Boundaries
 
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Authors: Kui Yu, Dawei Wang, Wei Ding, Jian Pei, David L. Small, Shafiqul Islam, Xindong Wu Abstract: Reliable tornado forecasting with a long-lead time can greatly support emergency response and is of vital importance for the economy and society. The large number of meteorological variables in spatiotemporal domains and the complex relationships among variables remain the top difficulties for a long-lead tornado forecasting. Standard data mining approaches to tackle high dimensionality are usually designed to discover a single set of features without alternating options for domain scientists to select more reliable and physical interpretable variables. In this work, we provide a new solution to use the concept of multiple Markov boundaries in local causal discovery to identify multiple sets of the precursors for tornado forecasting. Specifically, our algorithm first confines the extremely large feature spaces to a small core feature space, then it mines multiple sets of the precursors from the core feature space that may equally contribute to tornado forecasting. With the multiple sets of the precursors, we are able to report to domain scientists the predictive but practical set of precursors. An extensive empirical study is conducted on eight benchmark data sets and the historical tornado data near Oklahoma City, OK in the United States. Experimental results show that the tornado precursors we identified can help to improve the reliability of long-lead time catastrophic tornado forecasting. ACM DL: http://dl.acm.org/citation.cfm?id=2788612 DOI: http://dx.doi.org/10.1145/2783258.2788612
The challenges of specifying intervals and absences in temporal queries
 
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Full Title: The challenges of specifying intervals and absences in temporal queries: a graphical language approach Authors: Megan Monroe, Rongjian Lan, Juan Morales del Olmo, Ben Shneiderman, Catherine Plaisant, Jeff Millstein Abstract: In our burgeoning world of ubiquitous sensors and affordable data storage, records of timestamped events are being produced across nearly every domain of personal and professional computing. The resulting data surge has created an overarching need to search these records for meaningful patterns of events. This paper reports on a two-part user study, as well as a series of early tests and interviews with clinical researchers, that informed the development of two temporal query interfaces: a basic, menu-based interface and an advanced, graphic-based interface. While the scope of temporal query is very broad, this work focuses on two particularly complex and critical facets of temporal event sequences: intervals (events with both a start time and an end time), and the absence of an event. We describe how users encounter a common set of difficulties when specifying such queries, and propose solutions to help overcome them. Finally, we report on two case studies with epidemiologists at the US Army Pharmacovigilance Center, illustrating how both query interfaces were used to study patterns of drug use. URL: http://dl.acm.org/citation.cfm?id=2481325 DOI: http://dx.doi.org/10.1145/2470654.2481325

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