Digital Commons Network^™

A Multi-Agent Framework For Supporting Intelligent Fourth-Party Logistics, Hoong Chuin Lau, G. Lo

Research Collection School Of Computing and Information Systems

A distributed intelligent agent-based framework that supports fourth-party logistics optimization under a web-based e-Commerce environment has been proposed in this paper. In the framework, customer job requests come through an e-Procurement service. These requests are consolidated and pushed to the e-Market Place service periodically. The e-Market Place then serves as a broker that allows intelligent agents to bid to serve these requests optimally in real-time by solving multiple instances of underlying logistics optimization problem. The resulting system was implemented based on the Java 2 Enterprise Edition (J2EE) platform using distributed system technology for communication between objects.

Role Of Use Case Diagram In Requirement Analysis, Keng Siau, L. Lee

Research Collection School Of Computing and Information Systems

Since its debut and acceptance as a de facto standard of the object-oriented paradigm, UML has receivedcontroversial reviews. The most controversial diagramming technique in UML is undoubtedly the Use Casediagrams. Some claim that Use Case diagrams do not play a valuable role in requirement analysis. Othersargue that Use Case diagrams captured neither the static nor the dynamic aspects of the systems. The objective of this study is to investigate the role and value of Use Case diagrams in requirement analysis. We will investigate the information content of Use Case diagram and its role in requirement analysis.

An Integrated Model On Computer Abuse: A Pilot Study, S. G. Lee, Fiona Fui-Hoon Nah, S. Yoo

Research Collection School Of Computing and Information Systems

In spite of continuous organizational efforts and investments based on systematic factors, the incidence of computer abuse in organizations is still rapidly increasing. This paper proposes another perspective -- based on the general strain theory -- in preventing computer abuse. According to the general strain theory, organizational trust, which comprises organizational attachment, commitment, involvement, and norms, can prevent computer abuse by reducing insidersí computer abuse. The aim of this article is to assess the role of organizational trust from the perspectives of attachment, commitment, involvement, and norms in preventing computer abuse. The results indicate that both organizational trust and deterrent …

Real-Time Travel Time Estimation Using Macroscopic Traffic Flow Models, Pushkin Kachroo, Kaan Ozbay, Antoine G. Hobeika

Electrical & Computer Engineering Faculty Research

This paper presents the estimation of travel time on highways based on macroscopic modelling. The focus is on real-time values as compared to average or static values. The macroscopic models are used for distributed and time/space lumped settings and corresponding travel time estimation functions and algorithms are developed. The implications of these algorithms for the implementation of various incident management and traffic control strategies are also discussed.

Livelock Avoidance For Meta-Schedulers, Mark J. Clement, John Jardine, Quinn O. Snell

Faculty Publications

Meta-scheduling, a process which allows a user to schedule a job across multiple sites, has a potential for livelock. Current systems avoid livelock by locking down resources at multiple sites and allowing a metascheduler to control the resources during the lock down period or by limiting job size to that which will fit on one site. The former approach leads to poor utilization; the later poses limitations on job size. This research uses BYU's Meta-scheduler (YMS) which allows jobs to be scheduled across multiple sites without the need for locking down the nodes. YMS avoids livelock through exponential back-off This …

Analysis Of A New Vehicle Scheduling And Location Problem, Ebru K. Bish, Thin Yin Leong, Chun-Lun Li, Jonathan W. C. Ng, David Simchi-Levi

Research Collection School Of Computing and Information Systems

We consider a container terminal discharging containers from a ship and locating them in the terminal yard. Each container has a number of potential locations in the yard where it can be stored. Containers are moved from the ship to the yard using a fleet of vehicles, each of which can carry one container at a time. The problem is to assign each container to a yard location and dispatch vehicles to the containers so as to minimize the time it takes to download all the containers from the ship. We show that the problem is NP-hard and develop a …

Research Issues In Human-Computer Interaction In The Web-Based Environment, Fiona Fui-Hoon Nah, Sid Davis

Research Collection School Of Computing and Information Systems

The Internet and WWW are revolutionizing our daily lives and the way business is conducted. Since 1997, the Web has gradually evolved into a true economy and a new frontier for business. In this new Internet age, the design of a quality Web site is critical to the success of businesses. To attract and retain visitors, Web sites need to be human-centered, easy and quick to navigate, and speak the visitor’s language. User experience with the Web site is also important. The experience should be in line with the user’s goal and should feel natural to the user. Unfortunately, principles …

Video Partitioning By Temporal Slice Coherency, Chong-Wah Ngo, Ting-Chuen Pong, Roland T. Chin

Research Collection School Of Computing and Information Systems

We present a novel approach for video partitioning by detecting three essential types of camera breaks, namely cuts, wipes, and dissolves. The approach is based on the analysis of temporal slices which are extracted from the video by slicing through the sequence of video frames and collecting temporal signatures. Each of these slices contains both spatial and temporal information from which coherent regions are indicative of uninterrupted video partitions separated by camera breaks. Properties could further be extracted from the slice for both the detection and classification of camera breaks. For example, cut and wipes are detected by color-texture properties, …

The Meaning Of An Information-Centric Computer Environment, Jens G. Pohl

Collaborative Agent Design (CAD) Research Center

It is often lamented that we human beings are suffering from an information overload. This is a myth, as shown in Fig.1 there is no information overload. Instead we are suffering from a data overload. The confusion between data and information is not readily apparent and requires further explanation. Unorganized data are voluminous but of very little value. Over the past 15 years, industry and commerce have made significant efforts to rearrange this unorganized data into purposeful data, utilizing various kinds of database management systems. However, even in this organized form, we are still dealing with data and not information.

Aurora Working Group: Dsr Front End Lvcsr Evaluation — Baseline Recognition System Description, Naveen Parihar, Joseph Picone

Publications

In this document we describe the features of the baseline system to be used in the Distributed Speech Recognition (DSR) front end large vocabulary continuous speech recognition (LVCSR) evaluations being conducted by the Aurora Working Group of the European Telecommunications Standards Institute (ETSI). The objective of these evaluations is to determine the robustness of different front ends for use in client/server type telecommunications applications. As such, our experiments are designed to test the following focus conditions on the DARPA Wall Street Journal (WSJ0) corpus using a 5000-word closed-loop vocabulary and a bigram language model:

1. Additive Noise: six noise conditions …

Write Once, Move Anywhere: Toward Dynamic Interoperability Of Mobile Agent Systems, Arne Grimstrup, Robert Gray, David Kotz, Thomas Cowin, Greg Hill, Niranjan Suri, Daria Chacon, Martin Hofmann

Computer Science Technical Reports

Mobile agents are an increasingly popular paradigm, and in recent years there has been a proliferation of mobile-agent systems. These systems are, however, largely incompatible with each other. In particular, agents cannot migrate to a host that runs a different mobile-agent system. Prior approaches to interoperability have tried to force agents to use a common API, and so far none have succeeded. Our goal, summarized in the catch phrase ``Write Once, Move Anywhere,'' led to our efforts to develop mechanisms that support dynamic runtime interoperability of mobile-agent systems. This paper describes the Grid Mobile-Agent System, which allows agents to migrate …

Optimal Artificial Neural Network Architecture Selection For Bagging, Timothy L. Andersen, Tony R. Martinez, Michael E. Rimer

Faculty Publications

This paper studies the performance of standard architecture selection strategies, such as cost/performance and CV based strategies, for voting methods such as bagging. It is shown that standard architecture selection strategies are not optimal for voting methods and tend to underestimate the complexity of the optimal network architecture, since they only examine the performance of the network on an individual basis and do not consider the correlation between responses from multiple networks.

The Need For Small Learning Rates On Large Problems, Tony R. Martinez, D. Randall Wilson

Faculty Publications

In gradient descent learning algorithms such as error backpropagation, the learning rate parameter can have a significant effect on generalization accuracy. In particular, decreasing the learning rate below that which yields the fastest convergence can significantly improve generalization accuracy, especially on large, complex problems. The learning rate also directly affects training speed, but not necessarily in the way that many people expect. Many neural network practitioners currently attempt to use the largest learning rate that still allows for convergence, in order to improve training speed. However, a learning rate that is too large can be as slow as a learning …

Improving The Hopfield Network Through Beam Search, Tony R. Martinez, Xinchuan Zeng

Faculty Publications

In this paper we propose a beam search mechanism to improve the performance of the Hopfield network for solving optimization problems. The beam search readjusts the top M (M > 1) activated neurons to more similar activation levels in the early phase of relaxation, so that the network has the opportunity to explore more alternative, potentially better solutions. We evaluated this approach using a large number of simulations (20,000 for each parameter setting), based on 200 randomly generated city distributions of the 10-city traveling salesman problem. The results show that the beam search has the capability of significantly improving the network …

Speed Training: Improving The Rate Of Backpropagation Learning Through Stochastic Sample Presentation, Timothy L. Andersen, Tony R. Martinez, Michael E. Rimer

Faculty Publications

Artificial neural networks provide an effective empirical predictive model for pattern classification. However, using complex neural networks to learn very large training sets is often problematic, imposing prohibitive time constraints on the training process. We present four practical methods for dramatically decreasing training time through dynamic stochastic sample presentation, a technique we call speed training. These methods are shown to be robust to retaining generalization accuracy over a diverse collection of real world data sets. In particular, the SET technique achieves a training speedup of 4278% on a large OCR database with no detectable loss in generalization.

Improved Hopfield Networks By Training With Noisy Data, Fred Clift, Tony R. Martinez

Faculty Publications

A new approach to training a generalized Hopfield network is developed and evaluated in this work. Both the weight symmetricity constraint and the zero self-connection constraint are removed from standard Hopfield networks. Training is accomplished with Back-Propagation Through Time, using noisy versions of the memorized patterns. Training in this way is referred to as Noisy Associative Training (NAT). Performance of NAT is evaluated on both random and correlated data. NAT has been tested on several data sets, with a large number of training runs for each experiment. The data sets used include uniformly distributed random data and several data sets …

Lazy Training: Improving Backpropagation Learning Through Network Interaction, Timothy L. Andersen, Tony R. Martinez, Michael E. Rimer

Faculty Publications

Backpropagation, similar to most high-order learning algorithms, is prone to overfitting. We address this issue by introducing interactive training (IT), a logical extension to backpropagation training that employs interaction among multiple networks. This method is based on the theory that centralized control is more effective for learning in deep problem spaces in a multi-agent paradigm. IT methods allow networks to work together to form more complex systems while not restraining their individual ability to specialize. Lazy training, an implementation of IT that minimizes misclassification error, is presented. Lazy training discourages overfitting and is conducive to higher accuracy in multiclass problems …

Student Survey Of Information Technology, Wku Information Technology, Richard Kirchmeyer

Board of Regents Documents

Survey of 400 WKU students about information technology used in strategic operations planning for Information Technology. The survey attempted to determine the depth and breadth of student computer use and knowledge of a variety of hardware and software. The report was presented to the WKU Board of Regents at the August 17, 2001 meeting.

Precise Environmental Searches: Integrating Hierarchical Information Search With Envirodaemon, George Chang, Gunjan Samtani, Marcus Healey, Franz J. Kurfess, Jason Wang

Computer Science and Software Engineering

Information retrieval has evolved from searches of references, to abstracts, to documents. Search on the Web involves search engines that promise to parse full-text and other files: audio, video, and multimedia. With the indexable Web at 320 million pages and growing, difficulties with locating relevant information have become apparent. The most prevalent means for information retrieval relies on syntax-based methods: keywords or strings of characters are presented to a search engine, and it returns all the matches in the available documents. This method is satisfactory and easy to implement, but it has some inherent limitations that make it unsuitable for …

Semantic Operators And Fixed-Point Theory In Logic Programming, Anthony K. Seda, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We consider rather general operators mapping valuations to (sets of) valuations in the context of the semantics of logic programming languages. This notion generalizes several of the standard operators encountered in this subject and is inspired by earlier work of M.C. Fitting. The fixed points of such operators play a fundamental role in logic programming semantics by providing standard models of logic programs and also in determining the computability properties of these standard models. We discuss some of our recent work employing topological ideas, in conjunction with order theory, to establish methods by which one can find the fixed points …

Neural Network Approach To Causal Reasoning With Penalty Logic, Ghada Moussa Abdel Ghany Bahig

Archived Theses and Dissertations

No abstract provided.

Moving Icons, Detection And Distraction, Lyn Bartram, Colin Ware, Tom Calvert

Center for Coastal and Ocean Mapping

Simple motion has great potential for visually encoding information but there are as yet few experimentally validated guidelines for its use. Two studies were carried out to look at how efficiently simple motion cues were detected and how distracting they were in different task contexts. The results show that motion outperforms static representations and identify certain types of motions which are more distracting and irritating than others.

Web Spoofing 2001, Yougu Yuan, Eileen Zishuang Ye, Sean Smith Dartmouth College

Computer Science Technical Reports

The Web is currently the pre-eminent medium for electronic service delivery to remote users. As a consequence, authentication of servers is more important than ever. Even sophisticated users base their decision whether or not to trust a site on browser cues---such as location bar information, SSL icons, SSL warnings, certificate information, response time, etc. In their seminal work on web spoofing, Felten et al showed how a malicious server could forge some of these cues---but using approaches that are no longer reproducible. However, subsequent evolution of Web tools has not only patched security holes---it has also added new technology to …

Securing Web Servers Against Insider Attack, Shan Jiang, Sean Smith, Kazuhiro Minami Dartmouth College

Computer Science Technical Reports

Too often, ``security of Web transactions'' reduces to ``encryption of the channel''---and neglects to address what happens at the server on the other end. This oversight forces clients to trust the good intentions and competence of the server operator---but gives clients no basis for that trust. Furthermore, despite academic and industrial research in secure coprocessing, many in the computer science community still regard ``secure hardware'' as a synonym for ``cryptographic accelerator.' This oversight neglects the real potential of COTS secure coprocessing technology to establish trusted islands of computation in hostile environments---such as at web servers with risk of insider attack. …

An Information Theoretic Methodology For Prestructuring Neural Networks, Bjorn Chambless, George G. Lendaris, Martin Zwick

Complex Systems Faculty Publications and Presentations

Absence of a priori knowledge about a problem domain typically forces use of overly complex neural network structures. An information-theoretic method based on calculating information transmission is applied to training data to obtain a priori knowledge that is useful for prestructuring (reducing complexity) of neural networks. The method is applied to a continuous system, and it is shown that such prestructuring reduces training time, and enhances generalization capability.

Cost Optimal Record/Entity Matching, V. S. Verykios, Ahmed K. Elmagarmid, G. V. Moustakides

Department of Computer Science Technical Reports

No abstract provided.

Morphological And Physiological Effects Of Mechanical Trauma To The Spinal Cord, Steven Teoh, Yinlong Sun

Department of Computer Science Technical Reports

No abstract provided.

Record Matching: Past, Present And Future, M. Cochinwala, S. Dalal, Ahmed K. Elmagarmid, V. S. Verykios

Department of Computer Science Technical Reports

No abstract provided.

Broadcasting Indexed Multidimensional Data, Susanne E. Hambrusch, Chuan-Ming Liu, Walid G. Aref, Sunil Prabhakar

Department of Computer Science Technical Reports

No abstract provided.

Query Indexing And Velocity Constrained Indexing: Scalable Techniques For Continuous Queries On Moving Objects, Sunil Prabhakar, Y. Xia, D. Kalashnikov, Walid G. Aref, Susanne E. Hambrusch

Department of Computer Science Technical Reports

No abstract provided.