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Wright State University

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Articles 2011 - 2040 of 2694

Full-Text Articles in Computer Sciences

Semantics Enabled Dynamic Process Configuration, Kunal Verma, Karthik Gomadam, Jonathan Lathem, Amit P. Sheth, John A. Miller Jan 2006

Semantics Enabled Dynamic Process Configuration, Kunal Verma, Karthik Gomadam, Jonathan Lathem, Amit P. Sheth, John A. Miller

Kno.e.sis Publications

Web processes are the next generation workflows created using Web services. This paper addresses research issues in creating a framework for configuring and executing dynamic Web processes. Our approach is that of a multiparadigm constraint analysis for process configuration using quantitative and logical constraints. We also present a software architecture and an engineering approach for extending current Web service infrastructure to support dynamic Web processes. An execution environment, extending Apache Axis, one of the most popular SOAP implementations, to support dynamic process configuration is presented. Empirical evaluation of the system is performed to demonstrate the cost benefits of dynamic process …

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Data Processing In Space, Time, And Semantics Dimensions, Farshad Hakimpour, Boanerges Aleman-Meza, Matthew Perry, Amit P. Sheth Jan 2006

Data Processing In Space, Time, And Semantics Dimensions, Farshad Hakimpour, Boanerges Aleman-Meza, Matthew Perry, Amit P. Sheth

Kno.e.sis Publications

This work presents an experimental system for data processing in space, time and semantics dimensions using current Semantic Web technologies. The paper describes how we obtain geographic and event data from Internet sources and also how we integrate them into an RDF store. We briefly introduce a set of functionalities in space, time and semantics dimensions. These functionalities are implemented based on our existing technology for main-memory based RDF data processing developed in the LSDIS Lab. A number of these functionalities are exposed as REST Web services. We present two sample client side applications that are developed using a combination …

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Wright State University College Of Engineering And Computer Science Bits And Pcs Newsletter, Volume 22, Number 4, January 2006, College Of Engineering And Computer Science, Wright State University Jan 2006

Wright State University College Of Engineering And Computer Science Bits And Pcs Newsletter, Volume 22, Number 4, January 2006, College Of Engineering And Computer Science, Wright State University

BITs and PCs Newsletter

A ten page newsletter created by the Wright State University College of Engineering and Computer Science that addresses the current affairs of the college.

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Semi-Supervised Conditional Random Fields For Improved Sequence Segmentation And Labeling, Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Greiner, Dale Schuurmans Jan 2006

Semi-Supervised Conditional Random Fields For Improved Sequence Segmentation And Labeling, Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Greiner, Dale Schuurmans

Kno.e.sis Publications

We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled and unlabeled training data. Our approach is based on extending the minimum entropy regularization framework to the structured prediction case, yielding a training objective that combines unlabeled conditional entropy with labeled conditional likelihood. Although the training objective is no longer concave, it can still be used to improve an initial model (e.g. obtained from supervised training) by iterative ascent. We apply our new training algorithm to the problem of identifying gene and protein …

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An Investigation Of Codon Usage Bias Including Visualization And Quantification In Organisms Exhibiting Multiple Biases, Douglas W. Raiford, Travis E. Doom, Dan E. Krane, Michael L. Raymer Jan 2006

An Investigation Of Codon Usage Bias Including Visualization And Quantification In Organisms Exhibiting Multiple Biases, Douglas W. Raiford, Travis E. Doom, Dan E. Krane, Michael L. Raymer

Kno.e.sis Publications

Prokaryotic genomic sequence data provides a rich resource for bioinformatic analytic algorithms. Information can be extracted in many ways from the sequence data. One often overlooked process involves investigating an organism’s codon usage. Degeneracy in the genetic code leads to multiple codons coding for the same amino acids. Organism’s often preferentially utilize specific codons when coding for an amino acid. This biased codon usage can be a useful trait when predicting a gene’s expressivity or whether the gene originated from horizontal transfer. There can be multiple biases at play in a genome causing errors in the predictive process. For this …

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A Semantic Future For Ai, Rudi Studer, Anupriya Ankolekar, Pascal Hitzler Jan 2006

A Semantic Future For Ai, Rudi Studer, Anupriya Ankolekar, Pascal Hitzler

Computer Science and Engineering Faculty Publications

In our modern information society, people need to manage ever-increasing numbers of personal devices and conduct more of their work and activities online, often making use of heterogeneous services. The amount of information to be processed by each individual is constantly growing, making it increasingly difficult to control, channel, share and make constructive use of it. To mitigate this, computing needs to become much more human-centered, e.g. by presenting personalised information to users and by respecting personal preferences in controlling multiple devices or invoking various services. Appropriate representation of the semantics of the information and functionality of devices and services …

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Predicting Domain Specific Entities With Limited Background Knowledge, Christopher Thomas, Amit P. Sheth Jan 2006

Predicting Domain Specific Entities With Limited Background Knowledge, Christopher Thomas, Amit P. Sheth

Kno.e.sis Publications

This paper proposes a framework for automatic recognition of domain-specific entities from text, given limited background knowledge, e.g. in form of an ontology. The algorithm exploits several lightweight natural language processing techniques, such as tokenization and stemming, as well as statistical techniques, such as singular value decomposition (SVD) to suggest domain relatedness of unknown entities.

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Using Query-Specific Variance Estimates To Combine Bayesian Classifiers, Chi-Hoon Lee, Russell Greiner, Shaojun Wang Jan 2006

Using Query-Specific Variance Estimates To Combine Bayesian Classifiers, Chi-Hoon Lee, Russell Greiner, Shaojun Wang

Kno.e.sis Publications

Many of today's best classification results are obtained by combining the responses of a set of base classifiers to produce an answer for the query. This paper explores a novel "query specific" combination rule: After learning a set of simple belief network classifiers, we produce an answer to each query by combining their individual responses, using weights based inversely on their respective variances around their responses. These variances are based on the uncertainty of the network parameters, which in turn depend on the training datasample. In essence, this variance quantifies the base classifier's confidence of its response to this query. …

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Clustering Similarity Comparison Using Density Profiles, Eric Bae, James Bailey, Guozhu Dong Jan 2006

Clustering Similarity Comparison Using Density Profiles, Eric Bae, James Bailey, Guozhu Dong

Kno.e.sis Publications

The unsupervised nature of cluster analysis means that objects can be clustered in many ways, allowing different clustering algorithms to generate vastly different results. To address this, clustering comparison methods have traditionally been used to quantify the degree of similarity between alternative clusterings. However, existing techniques utilize only the point memberships to calculate the similarity, which can lead to unintuitive results. They also cannot be applied to analyze clusterings which only partially share points, which can be the case in stream clustering. In this paper we introduce a new measure named ADCO, which takes into account density profiles for each …

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An Online Discriminative Approach To Background Subtraction, Li Cheng, Shaojun Wang, Terry Caelli Jan 2006

An Online Discriminative Approach To Background Subtraction, Li Cheng, Shaojun Wang, Terry Caelli

Kno.e.sis Publications

We present a simple, principled approach to detecting foreground objects in video sequences in real-time. Our method is based on an on-line discriminative learning technique that is able to cope with illumination changes due to discontinuous switching, or illumination drifts caused by slower processes such as varying time of the day. Starting from a discriminative learning principle, we derive a training algorithm that, for each pixel, computes a weighted linear combination of selected past observations with time-decay. We present experimental results that show the proposed approach outperforms existing methods on both synthetic sequences and real video data.

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Formalizing Ontology Alignment And Its Operations With Category Theory, Antoine Zimmermann, Markus Krotzsch, Jerome Euzenat, Pascal Hitzler Jan 2006

Formalizing Ontology Alignment And Its Operations With Category Theory, Antoine Zimmermann, Markus Krotzsch, Jerome Euzenat, Pascal Hitzler

Computer Science and Engineering Faculty Publications

An ontology alignment is the expression of relations between different ontologies. In order to view alignments independently from the language expressing ontologies and from the techniques used for finding the alignments, we use a category-theoretical model in which ontologies are the objects. We introduce a categorical structure, called V-alignment, made of a pair of morphisms with a common domain having the ontologies as codomain. This structure serves to design an algebra that describes formally what are ontology merging, alignment composition, union and intersection using categorical constructions. This enables combining alignments of various provenance. Although the desirable properties of this algebra …

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Ceg 490/690-01: Technology-Based Ventures, Forouzan Golshani, S. Narayanan Jan 2006

Ceg 490/690-01: Technology-Based Ventures, Forouzan Golshani, S. Narayanan

Computer Science & Engineering Syllabi

No abstract provided.

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Cs 205-04,05,06: Computer Literacy And Office Automation, Terri Bauer Jan 2006

Cs 205-04,05,06: Computer Literacy And Office Automation, Terri Bauer

Computer Science & Engineering Syllabi

No abstract provided.

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Driving Deep Semantics In Middleware And Networks: What, Why And How?, Amit P. Sheth Jan 2006

Driving Deep Semantics In Middleware And Networks: What, Why And How?, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

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Knowledge Modeling And Its Application In Life Sciences: A Tale Of Two Ontologies, Satya S. Sahoo, Christopher Thomas, Amit P. Sheth, William S. York, Samir Tartir Jan 2006

Knowledge Modeling And Its Application In Life Sciences: A Tale Of Two Ontologies, Satya S. Sahoo, Christopher Thomas, Amit P. Sheth, William S. York, Samir Tartir

Kno.e.sis Publications

High throughput glycoproteomics, similar to genomics and proteomics, involves extremely large volumes of distributed, heterogeneous data as a basis for identification and quantification of a structurally diverse collection of biomolecules. The ability to share, compare, query for and most critically correlate datasets using the native biological relationships are some of the challenges being faced by glycobiology researchers. As a solution for these challenges, we are building a semantic structure, using a suite of ontologies, which supports management of data and information at each step of the experimental lifecycle. This framework will enable researchers to leverage the large scale of glycoproteomics …

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Show Me What You Mean! Exploiting Domain Semantics In Ontology Visualization, Ravi Pavagada, Christopher Thomas, Amit P. Sheth, William S. York Jan 2006

Show Me What You Mean! Exploiting Domain Semantics In Ontology Visualization, Ravi Pavagada, Christopher Thomas, Amit P. Sheth, William S. York

Kno.e.sis Publications

Ontologies build the backbone for many life-sciences applications. These ontologies, however, are represented in XML based languages that are meant for machine-consumption and hence are difficult for humans to comprehend. For a meaningful visualization of these ontologies, it is important that the display of entities and relationships captures the cognitive representation of the domain as perceived by the domain experts. In this paper we present OntoVista, an ontology visualization tool that is adaptable to the needs of different domains, especially in the life sciences. While keeping the graph structures as the predominant model, we provide a semantically enhanced graph display …

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Cs 340-01: Programming Language Workshop In Java, Ronald F. Taylor Jan 2006

Cs 340-01: Programming Language Workshop In Java, Ronald F. Taylor

Computer Science & Engineering Syllabi

This course is designed as a self-study in Java. You are expected to work independently to learn the Java language and solve a set of programming problems assigned to you using latest Java SDK available at http://java.sun.com or other software as approved by the instructor. There are no exams. We officially meet only once in a quarter. However, I will be available in the posted office hours for clarifications and general discussion of the programming assignments. Do not expect support in debugging badly documented code.

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Cs 480/680-01: Comparative Programming Languages, Michael L. Raymer Jan 2006

Cs 480/680-01: Comparative Programming Languages, Michael L. Raymer

Computer Science & Engineering Syllabi

No abstract provided.

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Cs 740-01: Algorithms, Complexity And The Theory Of Computability, Thomas Sudkamp Jan 2006

Cs 740-01: Algorithms, Complexity And The Theory Of Computability, Thomas Sudkamp

Computer Science & Engineering Syllabi

No abstract provided.

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Cs 790-01: Introduction To Parallel Algorithms, Natsuhiko Futamura Jan 2006

Cs 790-01: Introduction To Parallel Algorithms, Natsuhiko Futamura

Computer Science & Engineering Syllabi

Low-cost parallel computers such as PC clusters are becoming available, and many previously unsolvable problems can be solved using such computers. However, designing algorithms that perform well on parallel computers is often challenging. The focus of this course is on learning how to design algorithms for parallel computers and how to evaluate them.

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Cs 142-01: Computer Programming Ii, Eric Maston Jan 2006

Cs 142-01: Computer Programming Ii, Eric Maston

Computer Science & Engineering Syllabi

This course provides a continuation to the general introduction of computer programming begun in CS 141. Examples from and applications to a broad range of problems are given. The concepts covered will be applied to the Java programming language. (Students must register for both lecture and one laboratory section.)

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Cs 240-01: Introduction To Computer Science I, L. Jane Lin Jan 2006

Cs 240-01: Introduction To Computer Science I, L. Jane Lin

Computer Science & Engineering Syllabi

This course is the first in the three course sequence "Introduction to Computer Science" offered by the Computer Science department at WSU. This course presents a general introduction to C++ programming language. It introduces the fundamental capabilities of C++ language as a problem solving tool. Topics include data representation, debugging and program verification.

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Cs 242-01: Introduction To Computer Science Iii, Eric Maston Jan 2006

Cs 242-01: Introduction To Computer Science Iii, Eric Maston

Computer Science & Engineering Syllabi

This is the third and final course in the Introduction to Computer Science series. This course focuses on data structures with abstract data types, such as trees, stacks, queues, and tables.

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Cs 302-01: Client Server Databases, Karen Meyer Jan 2006

Cs 302-01: Client Server Databases, Karen Meyer

Computer Science & Engineering Syllabi

No abstract provided.

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Cs 241-01: Computer Science Ii, Mateen M. Rizki Jan 2006

Cs 241-01: Computer Science Ii, Mateen M. Rizki

Computer Science & Engineering Syllabi

No abstract provided.

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Cs 701-01: Database Systems And Design, Kenneth Melendez Jan 2006

Cs 701-01: Database Systems And Design, Kenneth Melendez

Computer Science & Engineering Syllabi

No abstract provided.

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Cs 765-01: Foundations Of Neurocomputation, Mateen M. Rizki Jan 2006

Cs 765-01: 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.

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Cs 317-01: Numerical Methods For Digital Computers - Ii, Ronald F. Taylor Jan 2006

Cs 317-01: Numerical Methods For Digital Computers - Ii, Ronald F. Taylor

Computer Science & Engineering Syllabi

Introduction to numerical methods used in the sciences. Methods for solving matrix eigenvalue problems, initial value and boundary value problem for ordinary differential equations (ODEs). Study of standard types of partial differential equations (PDEs) with applications. Solution techniques for systems of nonlinear equations. Discussion of courses of errors in numerical methods. Special topics and applications presented as schedule permits. 4 credit hours. Prerequisites: CS 316, MTH 233, 253, or 355. Programming course prerequisites: EGR 153 or CEG 220 or CS 241.

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Cs 884-01: Advanced Topics In Programming Languages, Krishnaprasad Thirunarayan Jan 2006

Cs 884-01: Advanced Topics In Programming Languages, Krishnaprasad Thirunarayan

Computer Science & Engineering Syllabi

The primary focus of this course is the design and specification of the Object-Oriented language Java.

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Cs 208-01: Computer Programming For Business I, Dennis Kellermeier Jan 2006

Cs 208-01: Computer Programming For Business I, Dennis Kellermeier

Computer Science & Engineering Syllabi

CS 208 is the first 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. This course assumes students have never written a program before.

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