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Articles 721 - 750 of 2694
Full-Text Articles in Computer Sciences
Ceg 4120/6120-01: Managing The Software Process, John A. Reisner
Ceg 4120/6120-01: Managing The Software Process, John A. Reisner
Computer Science & Engineering Syllabi
This course will cover some of the challenges and issues associated with software project management. Emphasis will occur on two fronts: (1) the software project manager's view (that is, what considerations and obstacles confront project managers during software development), and (2) the organizational view (that is, how organizations can foster a climate where software project management is performed effectively throughout an organization).
Ceg 416-01: Matrix Computations, Ronald F. Taylor
Ceg 416-01: Matrix Computations, Ronald F. Taylor
Computer Science & Engineering Syllabi
This course is a survey of numerical methods in linear algebra for application to problems in engineering and the sciences. Emphasis is on using modern software tools on high performance computing systems. This course covers the mathematics of linear equations, eigenvalue problems, singular value decomposition, and least squares. Material covered will be relevant to applications areas such as structural analysis, heat transfer, neural networks, mechanical vibrations, and image processing in biomedical engineering. A familiarity with MATLAB is useful, and the ability to program in languages such as CIC++ or Fortran is very important. A basic knowledge of matrix algebra is …
Ceg 260-01: Digital Computing Hardware/Switching Circuits, Meilin Liu
Ceg 260-01: Digital Computing Hardware/Switching Circuits, Meilin Liu
Computer Science & Engineering Syllabi
We will discuss and cover basic digital, combinational and sequential logic systems. Labs will be used to gain valuable practical experience in implementing elementary circuits and logic designs.
Ceg 320/520-01: Computer Organization, Michael L. Raymer
Ceg 320/520-01: Computer Organization, Michael L. Raymer
Computer Science & Engineering Syllabi
No abstract provided.
Ceg 402/602-01: Introduction To Computer Communication, Bin Wang
Ceg 402/602-01: Introduction To Computer Communication, Bin Wang
Computer Science & Engineering Syllabi
No abstract provided.
Ceg 751-01: Microprocessors Ii, Jack Jean
Ceg 751-01: Microprocessors Ii, Jack Jean
Computer Science & Engineering Syllabi
No abstract provided.
Ceg 498-01: Team Projects I And Ii, John C. Gallagher
Ceg 498-01: Team Projects I And Ii, John C. Gallagher
Computer Science & Engineering Syllabi
CEG 498 (Team Projects I and II) is a summative computer engineering design project course that builds upon previous engineering, science, mathematics and communications course work. CEG 498 projects are a minimum of two quarters in length and must be completed in groups of at least three students. Projects are selected under the guidance of the course instructor and are tailored to both student interest and formal classroom preparation. Students are evaluated both on their individual contributions as recorded in a graded engineering journals and on the quality of their collective efforts as reflected in group generated products.
Ceg 4120/6120: Managing The Software Process, John A. Reisner
Ceg 4120/6120: Managing The Software Process, John A. Reisner
Computer Science & Engineering Syllabi
This course will cover some of the challenges and issues associated with software project management. Emphasis will occur on two fronts: (1) the software manger's view (that is, what considerations and obstacles confront project managers during software development), and (2) the organizational view (that is, how organizations can foster a climate where software project management is performed effectively throughout an organization).
Ceg 233-01: Linux And Windows, Prabhaker Mateti
Ceg 233-01: Linux And Windows, Prabhaker Mateti
Computer Science & Engineering Syllabi
Introduction to Linux and Windows systems. GUI and Windowing Systems. Files and Directories, Ownership and Sharing. Programs and Processes. System calls, Libraries. Loading. Dynamic linking. Command Line Shells. Scripting languages. Regular expressions. Clients and Servers. Web browser clients and servers. Secure shell, sftp. SSUTSL. HTTPS. System Administration. 4 credit hours. 3 hours lectures, 2 hours labs.
Ceg 220-90: Introduction To C Programming For Engineers, Jay Dejongh
Ceg 220-90: Introduction To C Programming For Engineers, Jay Dejongh
Computer Science & Engineering Syllabi
This course provides a general introduction to computers as a problem-solving tool using the C programming language. Emphasis is on algorithms and techniques useful to engineers. Topics include data representation, debugging, and program verification. 4 credit hours. Prerequisite: MTH 229 (Calculus I) or EGR 101 (Engineering Mathematics). The course includes a scheduled laboratory section for which you must register.
Ceg 220-01: Introduction To C Programming For Engineers, Jay Dejongh
Ceg 220-01: Introduction To C Programming For Engineers, Jay Dejongh
Computer Science & Engineering Syllabi
This course provides a general introduction to computers as a problem-solving tool using the C programming language. Emphasis is on algorithms and techniques useful to engineers. Topics include data representation, debugging, and program verification. 4 credit hours. Prerequisite: MTH 229 (Calculus I) or EGR 101 (Engineering Mathematics). The course includes a scheduled laboratory section for which you must register.
Ceg 429/629-01: Internet Security, Prabhaker Mateti
Ceg 429/629-01: Internet Security, Prabhaker Mateti
Computer Science & Engineering Syllabi
Introduction to security issues arising primarily from computer networks. Topics include node and service authentication, address spoofing, hijacking, SYN floods, smurfing, sniffing, routing tricks, and privacy of data en route. Buffer overruns and other exploitation of software development errors. Hardening of operating systems. Intrusion detection. Firewalls. Ethics. Prerequisites: CEG 433
Ceg 726-01: Pattern Recognition, Arthur A. Goshtasby
Ceg 726-01: Pattern Recognition, Arthur A. Goshtasby
Computer Science & Engineering Syllabi
This course will cover fundamentals of Pattern Recognition, including supervised learning and clustering.
Cs 271/Bio 371: Introduction To Bioinformatics, Michael L. Raymer, Dan E. Krane
Cs 271/Bio 371: Introduction To Bioinformatics, Michael L. Raymer, Dan E. Krane
Computer Science & Engineering Syllabi
No abstract provided.
Ceg 461/661-01: Object-Oriented Programming And Design, Thomas C. Hartrum
Ceg 461/661-01: Object-Oriented Programming And Design, Thomas C. Hartrum
Computer Science & Engineering Syllabi
Study of object-oriented design and programming. Programming topics emphasize the core concepts of encapsulation, inheritance, polymorphism, and dynamic binding. Additional topics include class organization, software maintenance, and design of reusable components. There is a project to be implemented in a modem object-oriented language such as Java or C++.
Ceg 770-01: Computer Engineering Mathematics, Jack Jean
Ceg 770-01: Computer Engineering Mathematics, Jack Jean
Computer Science & Engineering Syllabi
No abstract provided.
Cs 499/699: Cloud Computing, Keke Chen
Cs 499/699: Cloud Computing, Keke Chen
Computer Science & Engineering Syllabi
This is an introductory course to cloud computing. In this course, we will explore a few aspects of cloud computing: distributed data crunching with MapReduce, cloud and datacenter filesystems, virtualization, cloud security&privacy, Amazon Web Services, and interactive web-based applications. Students are expected to read extra materials including papers and online resources, finish several mini projects, and take the final exam. Participation in the class discussion is strongly encouraged. Guest speakers might be invited for some particular topics. (3 Hours Lecture + 1 Hour lab).
Cs 399-01: Ios Programming, Erik Marlow Buck
Cs 399-01: Ios Programming, Erik Marlow Buck
Computer Science & Engineering Syllabi
No abstract provided.
Cs 415: Social Implications Of Computing, Leo Finkelstein
Cs 415: Social Implications Of Computing, Leo Finkelstein
Computer Science & Engineering Syllabi
CS 415 is a communication skills course using as its subject matter current salient issues associated with the social implications of computing. In addition to the course text, you will need to use certain reading materials in the library and elsewhere, and you will be responsible for using concepts and theories provided in class and lectures and discussions.
Cs 206-01: Computer Software Productivity Tools, John P. Herzog
Cs 206-01: Computer Software Productivity Tools, John P. Herzog
Computer Science & Engineering Syllabi
Focus on learning MS Office software applications including advanced topics in spreadsheets, database and presentation graphics, using a case study approach where critical thinking and problem solving skills are required. Computer concepts are integrated throughout the course to provide an understanding of advanced computing, the latest technological advances and how they are used in industry. Ethics and issues encountered in business are discussed to challenge students on societal impact of technology.
Cs 466/666: Introduction To Formal Languages, Guozhu Dong
Cs 466/666: Introduction To Formal Languages, Guozhu Dong
Computer Science & Engineering Syllabi
CS 466/666 is an introduction to formal language and automata theory. In this course we will examine methods for defining syntax of languages and recognizing patterns in strings/sentences: the syntax of languages can be defined using grammars and the patterns can be accepted by finite state machines. Along with presenting the fundamentals of these two topics, the course will develop and investigate the relationships between language definition mechanisms and pattern recognition devices. The text will be the third edition of Languages and Machines: An Introduction to the Theory of Computer Science, by Thomas Sudkamp.
Localized Deconvolution: Characterizing Nmr-Based Metabolomics Spectroscopic Data Using Localized High-Throughput Deconvolution, Paul E. Anderson, Ajith H. Ranabahu, Deirdre A. Mahle, Nicholas V. Reo, Michael L. Raymer, Amit P. Sheth, Nicholas J. Delraso
Localized Deconvolution: Characterizing Nmr-Based Metabolomics Spectroscopic Data Using Localized High-Throughput Deconvolution, Paul E. Anderson, Ajith H. Ranabahu, Deirdre A. Mahle, Nicholas V. Reo, Michael L. Raymer, Amit P. Sheth, Nicholas J. Delraso
Kno.e.sis Publications
The interpretation of nuclear magnetic resonance (NMR) experimental results for metabolomics studies requires intensive signal processing and multivariate data analysis techniques. Standard quantification techniques attempt to minimize effects from variations in peak positions caused by sample pH, ionic strength, and composition. These techniques fail to account for adjacent signals which can lead to drastic quantification errors. Attempts at full spectrum deconvolution have been limited in adoption and development due to the computational resources required. Herein, we develop a novel localized deconvolution algorithm for general purpose quantification of NMR-based metabolomics studies. Localized deconvolution decreases average absolute quantification error by 97% and …
Framework For The Analysis Of Coordination In Crisis Response, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John M. Flach
Framework For The Analysis Of Coordination In Crisis Response, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John M. Flach
Kno.e.sis Publications
Social Media play a critical role during crisis events, revealing a natural coordination dynamic. We propose a computational framework guided by social science principles to measure, analyze, and understand coordination among the different types of organizations and actors in crisis response. The analysis informs both the scientific account of cooperative behavior and the design of applications and protocols to support crisis management.
Discovering Fine-Grained Sentiment In Suicide Notes, Wenbo Wang, Lu Chen, Ming Tan, Shaojun Wang, Amit P. Sheth
Discovering Fine-Grained Sentiment In Suicide Notes, Wenbo Wang, Lu Chen, Ming Tan, Shaojun Wang, Amit P. Sheth
Kno.e.sis Publications
This paper presents our solution for the i2b2 sentiment classification challenge. Our hybrid system consists of machine learning and rule-based classifiers. For the machine learning classifier, we investigate a variety of lexical, syntactic and knowledge-based features, and show how much these features contribute to the performance of the classifier through experiments. For the rule-based classifier, we propose an algorithm to automatically extract effective syntactic and lexical patterns from training examples. The experimental results show that the rule-based classifier outperforms the baseline machine learning classifier using unigram features. By combining the machine learning classifier and the rule-based classifier, the hybrid system …
A Semantic Problem Solving Environment For Integrative Parasite Research: Identification Of Intervention Targets For Trypanosoma Cruzi, Priti Parikh, Todd Minning, Vinh Nguyen, Sarasi Lalithsena, Amir H. Asiaee, Satya S. Sahoo, Prashant Doshi, Rick L. Tarleton, Amit P. Sheth
A Semantic Problem Solving Environment For Integrative Parasite Research: Identification Of Intervention Targets For Trypanosoma Cruzi, Priti Parikh, Todd Minning, Vinh Nguyen, Sarasi Lalithsena, Amir H. Asiaee, Satya S. Sahoo, Prashant Doshi, Rick L. Tarleton, Amit P. Sheth
Kno.e.sis Publications
Background: Research on the biology of parasites requires a sophisticated and integrated computational platform to query and analyze large volumes of data, representing both unpublished (internal) and public (external) data sources. Effective analysis of an integrated data resource using knowledge discovery tools would significantly aid biologists in conducting their research, for example, through identifying various intervention targets in parasites, and in deciding the future direction of ongoing as well as planned projects. A key challenge in achieving this objective is the heterogeneity between the internal lab data, usually stored as flat files, Excel spreadsheets or custom-built databases, and the external …
Cognitive Approaches For The Semantic Web, Dedre Gentner, Frank Van Harmelen, Pascal Hitzler, Krzysztof Janowicz, Kai-Uwe Kuhnberger
Cognitive Approaches For The Semantic Web, Dedre Gentner, Frank Van Harmelen, Pascal Hitzler, Krzysztof Janowicz, Kai-Uwe Kuhnberger
Computer Science and Engineering Faculty Publications
A major focus in the design of Semantic Web ontology languages used to be on finding a suitable balance between the expressivity of the language and the tractability of reasoning services defined over this language. This focus mirrors the original vision of a Web composed of machine readable and understandable data. Similarly to the classical Web a few years ago, the attention is recently shifting towards a user-centric vision of the Semantic Web. Essentially, the information stored on the Web is from and for humans. This new focus is not only reflected in the fast growing Linked Data Web but …
Semantics Of Perception: Towards A Semantic Web Approach To Machine Perception, Cory Andrew Henson, Amit P. Sheth
Semantics Of Perception: Towards A Semantic Web Approach To Machine Perception, Cory Andrew Henson, Amit P. Sheth
Kno.e.sis Publications
The acts of observation and perception provide the building blocks for all human knowledge (Locke, 1690); they are the processes from which all ideas are born; and the sole bond connecting ourselves to the world around us. Now, with the advent of sensor networks capable of observation, this world may be directly accessible to machines. Missing from this vision, however, is the ability of machines to glean semantics from observation; to apprehend entities from detected qualities; to perceive. The systematic automation of this ability is the focus of machine perception -- the ability of computing machines to sense and interpret …
A Scalable Distributed Syntactic, Semantic And Lexical Language Model, Ming Tan, Wenli Zhou, Lei Zheng, Shaojun Wang
A Scalable Distributed Syntactic, Semantic And Lexical Language Model, Ming Tan, Wenli Zhou, Lei Zheng, Shaojun Wang
Kno.e.sis Publications
This paper presents an attempt at building a large scale distributed composite language model that is formed by seamlessly integrating an n-gram model, a structured language model, and probabilistic latent semantic analysis under a directed Markov random field paradigm to simultaneously account for local word lexical information, mid-range sentence syntactic structure, and long-span document semantic content. The composite language model has been trained by performing a convergent N-best list approximate EM algorithm and a follow-up EM algorithm to improve word prediction power on corpora with up to a billion tokens and stored on a supercomputer. The large scale distributed composite …
Alignment-Based Querying Of Linked Open Data, Amit Krishna Joshi, Prateek Jain, Pascal Hitzler, Peter Z. Yeh, Kunal Verma, Amit P. Sheth, Mariana Damova
Alignment-Based Querying Of Linked Open Data, Amit Krishna Joshi, Prateek Jain, Pascal Hitzler, Peter Z. Yeh, Kunal Verma, Amit P. Sheth, Mariana Damova
Kno.e.sis Publications
The Linked Open Data (LOD) cloud is rapidly becoming the largest interconnected source of structured data on diverse domains. The potential of the LOD cloud is enormous, ranging from solving challenging AI issues such as open domain question answering to automated knowledge discovery. However, due to an inherent distributed nature of LOD and a growing number of ontologies and vocabularies used in LOD datasets, querying over multiple datasets and retrieving LOD data remains a challenging task. In this paper, we propose a novel approach to querying linked data by using alignments for processing queries whose constituent data come from heterogeneous …
Extracting Diverse Sentiment Expressions With Target-Dependent Polarity From Twitter, Lu Chen, Wenbo Wang, Meenakshi Nagarajan, Shaojun Wang, Amit P. Sheth
Extracting Diverse Sentiment Expressions With Target-Dependent Polarity From Twitter, Lu Chen, Wenbo Wang, Meenakshi Nagarajan, Shaojun Wang, Amit P. Sheth
Kno.e.sis Publications
This study focuses on automatic extraction of sentiment expressions associated with given targets from Twitter. It addresses one of the key challenges in this work: Wide diversity and informal nature of sentiment expressions that cannot be trivially enumerated or captured using predefined lexical patterns.