Computer Sciences Commons^™

Improving Record Linkage Through Pedigrees, Burdette N. Pixton

Theses and Dissertations

Record linkage, in a genealogical context, is the process of identifying individuals from multiple sources which refer to the same real-world entity. Current solutions focus on the individuals in question and on complex rules developed by human experts. Genealogical databases are highly-structured with relationships existing between the individuals and other instances. These relationships can be utilized and human involvement greatly minimized by using a filtered structured neural network. These neural networks, using traditional back-propagation methods, are biased in a way to make the network human readable. The results show an increase in precision and recall when pedigree data is available …

Syncsql: A Language To Express Views Over Data Streams, Thanaa M. Ghanem, Per-Ake Larson, Walid G. Aref, Ahmed K. Elmagarmid

Department of Computer Science Technical Reports

No abstract provided.

Jumpstarting Phylogenetic Searches, Jesse Lewis Mecham

Theses and Dissertations

Phylogenetic analysis is a central tool in studies of comparative genomics. When a new region of DNA is isolated and sequenced, researchers are often forced to throw away months of computation on an existing phylogeny of homologous sequences in order to incorporate this new sequence. The previously constructed trees are often discarded, and the researcher begins the search again from scratch. The jumpstarting algorithm uses trees from the prior search as a starting point for a new phylogenetic search. This technique drastically decreases search time for large data sets. This kind of analysis is necessary as researchers analyze tree of …

Markov Approximations: The Characterization Of Undermodeling Errors, Lei Lei

Theses and Dissertations

This thesis is concerned with characterizing the quality of Hidden Markov modeling when learning from limited data. It introduces a new perspective on different sources of errors to describe the impact of undermodeling. Our view is that modeling errors can be decomposed into two primary sources of errors: the approximation error and the estimation error. This thesis takes a first step towards exploring the approximation error of low order HMMs that best approximate the true system of a HMM. We introduce the notion minimality and show that best approximations of the true system with complexity greater or equal to the …

Reinforcement Programming: A New Technique In Automatic Algorithm Development, Spencer Kesson White

Theses and Dissertations

Reinforcement programming is a new technique for using computers to automatically create algorithms. By using the principles of reinforcement learning and Q-learning, reinforcement programming learns programs based on example inputs and outputs. State representations and actions are provided. A transition function and rewards are defined. The system is trained until the system converges on a policy that can be directly implemented as a computer program. The efficiency of reinforcement programming is demonstrated by comparing a generalized in-place iterative sort learned through genetic programming to a sorting algorithm of the same type created using reinforcement programming. The sort learned by reinforcement …

Query-Based Multicontexts For Knowledge Base Browsing: An Evaluation, Julien Tane, Philipp Cimiano, Pascal Hitzler

Computer Science and Engineering Faculty Publications

In [7], we introduced the query-based multicontext theory, which allows to define a virtual space of views on ontological data. Each view is then materialised as a formal context. While this formal context can be visualised in a usual formal concept analysis framework such as Conexp or ToscanaJ, [7] also briefly described how the approach allowed the creation of a novel navigation framework for knowledge bases. The principle of this navigation is based on supporting the user in defining pertinent views. The purpose of this article is to discuss the benefits of the browsing interface. This discussion is performed, …

Optimal Adaptation Of Web Processes With Inter-Service Dependencies, Kunal Verma, Prashant Doshi, Karthik Gomadam, John A. Miller, Amit P. Sheth

Kno.e.sis Publications

We present methods for optimally adapting Web processes to exogenous events while preserving inter-service dependencies. For example, in a supply chain process, orders placed by the manufacturer may get delayed in arriving. In response to this event, the manufacturer has the choice of either waiting out the delay or changing the supplier. Additionally, there may be compatibility constraints between the different orders, thereby introducing the problem of coordination between them if the manufacturer chooses to change the suppliers. We present our methods within the framework of autonomic Web processes. This framework seeks to add properties of self-configuration, adaptation, and self-optimization …

When Domains Require Modeling Adaptations, Krol Kevin Mathias, Cynthia Isenhour, Alex Dekhtyar, Judy Goldsmtih, Beth Goldstein

Computer Science and Software Engineering

The project described in this paper originated with an observation by the AI group at the University of Kentucky, that, individually, stochastic planning and constraint satisfaction are well-studied topics that resulted in efficient software, but stochastic planning in the presence of constraints on the domains and actions is an open area of investigation.

We were interested in an advising scenario, and chose the US social welfare system, a.k.a. “Welfare to Work” as our test domain. This required computer scientists to learn more than expected about social science as well as the local welfare system. This paper discusses the discipline specific …

Implementation Of Microsoft's Virtual Pc In Networking Curriculum, Jim Yulga

Regis University Student Publications (comprehensive collection)

Using Microsoft's Virtual PC software product as a virtual technology in the implementation of Network Specialist curriculum allows increased versatility and considerable hardware cost savings. Rather than purchasing individual computers or removable hard drives, using boot manager programs, or simulation software (including Computer Based Training programs), for student use in learning the administration of an operating system, one computer with hard drive, sufficient processor power, and RAM can be used to implement the effective hands-on learning approach of plan, implement and test, and then review. In addition, this software allows a non-dedicated (production) computer lab to be used. This is …

Stochastic Propagation Modeling And Early Detection Of Malicious Mobile Code, Xin Xu

Doctoral Dissertations

Epidemic models are commonly used to model the propagation of malicious mobile code like a computer virus or a worm. In this dissertation, we introduce stochastic techniques to describe the propagation behavior of malicious mobile code. We propose a stochastic infection-immunization (INIM) model based on the standard Susceptible-Infected-Removed (SIR) epidemic model, and we get an explicit solution of this model using probability generating function (pgf.). Our experiments simulate the propagation of malicious mobile code with immunization. The simulation results match the theoretical results of the model, which indicates that it is reliable to use INIM model to predict the propagation …

A Relational Database Approach For Frequent Subgraph Mining, Subhesh Kumar Pradhan

Computer Science and Engineering Theses - Archive

Data mining aims at discovering interesting and previously unknown patterns from data sets. Further more, graph-based data mining represents a collection of techniques for mining the relational aspects of data represented as a graph. Complex relationships in data can be represented using graphs and hence graph mining is appropriate for analyzing data that is rich in structural relationships. Database mining of graphs, on the other hand, aims at directly mining graphs stored in a database using SQL queries. Several SQL-based mining algorithms have been developed successfully and their efficiency and scalability have been established. One of them is HDB-Subdue which …

A Novel Privacy Preserving Authentication And Access Control Scheme For Pervasive Computing Environments, K. Ren, Wenjing Lou, K. Kim, Robert H. Deng

Research Collection School Of Computing and Information Systems

Privacy and security are two important but seemingly contradictory objectives in a pervasive computing environment (PCE). On one hand, service providers want to authenticate legitimate users and make sure they are accessing their authorized services in a legal way. On the other hand, users want to maintain the necessary privacy without being tracked down for wherever they are and whatever they are doing. In this paper, a novel privacy preserving authentication and access control scheme to secure the interactions between mobile users and services in PCEs is proposed. The proposed scheme seamlessly integrates two underlying cryptographic primitives, namely blind signature …

Neural Network Based Decentralized Excitation Control Of Large Scale Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a neural network (NN) based decentralized excitation controller design for large scale power systems. The proposed controller design considers not only the dynamics of generators but also the algebraic constraints of the power flow equations. The control signals are calculated using only local signals. The transient stability and the coordination of the subsystem controllers can be guaranteed. NNs are used to approximate the unknown/imprecise dynamics of the local power system and the interconnections. All signals in the closed loop system are guaranteed to be uniformly ultimately bounded (UUB). Simulation results with a 3-machine power system demonstrate the …

A Distributed Hierarchical Energy-Efficient Scheme For Large Scale Mobile Wireless Ad Hoc Networks, Wasim El Hajj

Dissertations

In recent years, wireless networks have enjoyed tremendous development and popularity due to the technological advances of wireless radio devices. While interest in conventional wireless networks continues to evolve, new types of wireless networks, such as Mobile Ad Hoc Networks (MANET) and WirelessSensor Networks (WSN) are evolving fast and receiving much attention from academia, industry, and government.

Scalability and energy-efficiency present two of the most important challenges in Mobile Ad Hoc Networks. Scalability in MANETs can be defined as the capability of the network to provide an acceptable throughput when the network size increases. Energy-efficiency can be defined as using …

Learning As A Nonlinear Line Of Attraction For Pattern Association, Classification And Recognition, Ming-Jung Seow

Electrical & Computer Engineering Theses & Dissertations

Development of a mathematical model for learning a nonlinear line of attraction is presented in this dissertation, in contrast to the conventional recurrent neural network model in which the memory is stored in an attractive fixed point at discrete location in state space. A nonlinear line of attraction is the encapsulation of attractive fixed points scattered in state space as an attractive nonlinear line, describing patterns with similar characteristics as a family of patterns.

It is usually of prime imperative to guarantee the convergence of the dynamics of the recurrent network for associative learning and recall. We propose to alter …

An Adaptive Algorithm To Identify Ambiguous Prostate Capsule Boundary Lines For Three-Dimensional Reconstruction And Quantitation, Rania Yousry Hussein

Electrical & Computer Engineering Theses & Dissertations

Currently there are few parameters that are used to compare the efficiency of different methods of cancerous prostate surgical removal. An accurate assessment of the percentage and depth of extra-capsular soft tissue removed with the prostate by the various surgical techniques can help surgeons determine the appropriateness of surgical approaches. Additionally, an objective assessment can allow a particular surgeon to compare individual performance against a standard. In order to facilitate 3D reconstruction and objective analysis and thus provide more accurate quantitation results when analyzing specimens, it is essential to automatically identify the capsule line that separates the prostate gland tissue …

Gaussian Mixture Models And Neural Networks For Automatic Speaker Identification, Usha Gayatri Chalkapally

Electrical & Computer Engineering Theses & Dissertations

Automatic Speaker Recognition is the process of automatically recognizing who is speaking on the basis of individual information contained in speech signals. This technique of Automatic Speaker Recognition makes it possible to use the speaker's voice to verify their identity and control access to services such as voice dialing, banking by telephone, telephone shopping, database access services, information services, voice mail, security control for confidential information areas, and remote access to computers.

In this thesis, the techniques of Gaussian Mixture Models and Neural Networks for Automatic Speaker Identification are presented. Algorithms for Speaker Identification using Gaussian Mixture Models were developed, …

Dimensionality Reduction Using Non-Linear Principal Components Analysis, Tara Singh

Electrical & Computer Engineering Theses & Dissertations

Advances in data collection and storage capabilities during the past decades have led to an information overload in most sciences. Traditional statistical methods break down partly because of the increase in the number of observations, but mostly because of the increase in the number of variables associated with each observation. While certain methods can construct predictive models with high accuracy from high-dimensional data, it is still of interest in many applications to reduce the dimension of the original data prior to any modeling of the data. Patterns in the data can be hard to find in data of high dimensionality, …

Querying Formal Contexts With Answer Set Programs, Pascal Hitzler, Markus Krotzsch

Computer Science and Engineering Faculty Publications

Recent studies showed how a seamless integration of formal concept analysis (FCA), logic of domains, and answer set programming (ASP) can be achieved. Based on these results for combining hierarchical knowledge with classical rule-based formalisms, we introduce an expressive common-sense query language for formal contexts. Although this approach is conceptually based on order-theoretic paradigms, we show how it can be implemented on top of standard ASP systems. Advanced features, such as default negation and disjunctive rules, thus become practically available for processing contextual data.

Geospatial Ontology Development And Semantic Analytics, I. Budak Arpinar, Cartic Ramakrishnan, Molly Azami, Amit P. Sheth, E. Lynn Usery, Mei-Po Kwan

Kno.e.sis Publications

Geospatial ontology development and semantic knowledge discovery addresses the need for modeling, analyzing and visualizing multimodal information, and is unique in offering integrated analytics that encompasses spatial, temporal and thematic dimensions of information and knowledge. The comprehensive ability to provide integrated analysis from multiple forms of information and use of explicit knowledge make this approach unique. This also involves specification of spatiotemporal thematic ontologies and populating such ontologies with high quality knowledge. Such ontologies form the basis for defining the meaning of important relations terms, such as near or surrounded by, and enable computation of spatiotemporal thematic proximity measures we …

Cs 209: Computer Programming For Business Ii, Dennis Kellermeier

Computer Science & Engineering Syllabi

CS 209 is the second of a two quarter sequence in programming for business students. It is required for Management Information Science majors. The courses are designed to help students achieve a high degree of facility in intermediate level programming.

Cs 205-07: Computer Literacy And Office Automation, John P. Herzog

Computer Science & Engineering Syllabi

Basic computer terminology, word processing, spreadsheets, databases, and graphics.

Cs 141: Computer Programming - I, Ronald F. Taylor

Computer Science & Engineering Syllabi

This course provides a general introduction to the fundamentals of computer programming. Examples from and applications to a broad range of problems are given. No prior knowledge of programming is assumed. The concepts covered will be applied to the Java programming language. Students must register for both lecture and one laboratory section. 4 credit hours. Prerequisite: MTH 127 (College Algebra) or equivalent.

Cs 466/666: Formal Languages And Automata, Krishnaprasad Thirunarayan

Computer Science & Engineering Syllabi

This course introduces the theory of formal languages and automata. The primary focus is on the two methods of defining languages: using generators (e.g., grammars/regular expressions) and using recognizers (e.g., finite state machines). Along with presenting the fundamentals, this course will develop and examine relationships among the various specification methods for the regular languages and the context-free languages, in detail. Overall, we plan to cover the first seven chapters of the text book.

Cs 241: Computer Science Ii, Eric Maston

Computer Science & Engineering Syllabi

This course is the second in the Introduction to Computer Science (24X) series. It focuses on object oriented concepts and an introduction to data structures.

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 lectures and discussions.

Cs 765: Foundations Of Neurocomputation, Mateen M. Rizki

Computer Science & Engineering Syllabi

This course is designed to help you develop a solid understanding of neural network algorithms and architectures. At the end of this course you should be able to read and critically evaluate most neural network papers published in major journals, (e.g. IEEE Transaction on Neural Networks, Neural Networks, and Neural Computation). In addition, you should be able to implement a broad range of network architectures and learning algorithms for a variety of applications.

Ceg 460/660-01: Introduction To Software Computer Engineering, John A. Reisner

Computer Science & Engineering Syllabi

This course introduces established practices for engineering large-scale software systems. Emphasis is placed on both the technical and managerial aspects of software engineering, and the software development process. This includes techniques for requirements elicitation, analysis, design, testing, and project management. The course emphasizes object-oriented development with the Unified Modeling Language (UML). Hands-on experience is provided through individual homework problems and a partnered project.

Ceg 720-01: Computer Architecture, Jack Jean

Computer Science & Engineering Syllabi

No abstract provided.

Cs 480/680: Comparative Languages, Krishnaprasad Thirunarayan

Computer Science & Engineering Syllabi

This course will introduce fundamental concepts and paradigms underlying the design of modern programming languages. For concreteness, we study the details of an object-oriented language (e.g. Java), and a functional language (e.g., Scheme). The overall goal is to enable comparison and evaluation of existing languages. The programming assignments will be coded in Java 5 and in Scheme.