Digital Commons Network^™

Visual Iconic Object-Oriented Programming To Advance Computer Science Education And Novice Programming, Nancy Silva Martinez

Theses and Dissertations - UTB/UTPA

Learning how to program a computer is difficult for most people. Computer programming is a cognitively challenging, time consuming, labor intensive, and frustrating endeavor. Years of formal study and training are required to learn a programming language's world of algorithms and data structures. Instructions are coded in advance before the computer demonstrates the desired behavior. Seeing all the programming steps and instruction code is complicated. There exists a tremendous gap between the representations the human brain uses when thinking about a problem and the representations used in programming a computer. Often people are much better at dealing with specific, concrete …

Autoconfiguration, Registration And Mobility Management For Pervasive Computing, Archan Misra, Subir Das, Anthony Mcauley, Sajal K. Das

Research Collection School Of Computing and Information Systems

In the vision of pervasive computing, users will exchange information and control their environments from anywhere using various wireline/wireless networks and computing devices. We believe that current protocols, such as DHCP, PPP, and Mobile IP, must be enhanced to support pervasive network access. In particular, this article identifies three fundamental functions: autoconfiguration, registration, and mobility management, that need such enhancements. Realizing that the IP autoconfiguration capabilities must be extended to configure routers and large dynamic networks, we first describe our autoconfiguration solution based on the dynamic configuration and distribution protocol (DCDP). Second, we discuss why providing user-specific services over a …

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.

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 …

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 …

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.

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.

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 …

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. …

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

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.

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.

Recent Advances In Content-Based Video Analysis, Chong-Wah Ngo, Ting-Chuen Pong, Hong-Jiang Zhang

Research Collection School Of Computing and Information Systems

In this paper, we present major issues in video parsing, abstraction, retrieval and semantic analysis. We discuss the success, the difficulties and the expectations in these areas. In addition, we identify important opened problems that can lead to more sophisticated ways of video content analysis. For video parsing, we discuss topics in video partitioning, motion characterization and object segmentation. The success in video parsing, in general, will have a great impact on video representation and retrieval. We present three levels of abstracting video content by scene, keyframe and key object representations. These representation schemes in overall serve as a good …

Development Of Atlas Based Simulation Capability For Automated Testing, Rami Hanbali

Electrical & Computer Engineering Theses & Dissertations

Computer software is emerging as a powerful tool for controlling a large number of instruments and for the testing of these instruments. The main aim of this work is to provide a software program capable of controlling a large number of engineering instruments at the touch of a button. In addition, the software is to have the capability of connecting the instruments with the desired Unit Under Test. There is great need for such software driven testing in industry, especially for large complex systems. Advantages of such an approach include: (a) automated testing in a very quick and efficient manner; …

Application-Centric Analysis Of Ip-Based Mobility Management Techniques, Archan Misra, Subir Das, Prathima Agrawal

Research Collection School Of Computing and Information Systems

This paper considers three applications—VoIP, mobile Web access and mobile server-based data transfers—and evaluates the applicability of various IP-based mobility management mechanisms. We first survey the features and characteristics of various IP mobility protocols, such as MIPv4, MIPv6, MIP-RO, SIP, CIP, HAWAII, MIP-RR and IDMP, and then evaluate their utility on an application-specific basis. The diversity in the mobility-related requirements ensures that no single mobility solution is universally applicable. We recommend a hierarchical mobility architecture. The framework uses our Dynamic Mobility Agent (DMA) architecture for managing intra-domain mobility and multiple application-based binding protocols for supporting inter-domain mobility. Thus, we recommend …

Secure And Private Distribution Of Online Video And Some Related Cryptographic Issues, Feng Bao, Robert H. Deng, Peirong Bao, Yan Guo, Hongjun Wu

Research Collection School Of Computing and Information Systems

With the rapid growth of broadband infrastructure, it is thought that the bottleneck for video-on-demand service through Internet is being cleared. However, digital video content protection and consumers privacy protection emerge as new major obstacles. In this paper we propose an online video distribution system with strong content security and privacy protection. We mainly focus on the study of security and privacy problems related to the system. Besides presenting the new system, we intensively discuss some relevant cryptographic issues, such as content protection, private information retrieval, super-speed encryption/decryption for video, and PKC with fast decryption etc. The paper can be …

Mobile Commerce: Promises, Challenges And Research Agenda, Keng Siau, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Advances in wireless technology increase the number of mobile device users and give pace to the rapid development of e-commerce using these devices. The new type of e-commerce, conducting transactions via mobile terminals, is called mobile commerce. Due to its inherent characteristics such as ubiquity, personalization, flexibility, and dissemination, mobile commerce promises businesses unprecedented market potential, great productivity, and high profitability. This paper presents an overview of mobile commerce development by examining the enabling technologies, the impact of mobile commerce on the business world, and the implications to mobile commerce providers. The paper also provides an agenda for future research …

On The Utility Of Entanglement In Quantum Neural Computing, Dan A. Ventura

Faculty Publications

Efforts in combining quantum and neural computation are briefly discussed and the concept of entanglement as it applies to this subject is addressed. Entanglement is perhaps the least understood aspect of quantum systems used for computation, yet it is apparently most responsible for their computational power. This paper argues for the importance of understanding and utilizing entanglement in quantum neural computation.

Approximation Techniques For Average Completion Time Scheduling, Chandra Chekuri, Rajeev Motwani, Balas Natarajan, Clifford Stein

Dartmouth Scholarship

We consider the problem of nonpreemptive scheduling to minimize average ( weighted) completion time, allowing for release dates, parallel machines, and precedence constraints. Recent work has led to constant-factor approximations for this problem based on solving a preemptive or linear programming relaxation and then using the solution to get an ordering on the jobs. We introduce several new techniques which generalize this basic paradigm. We use these ideas to obtain

improved approximation algorithms for one-machine scheduling to minimize average completion time with release dates. In the process, we obtain an optimal randomized on-line algorithm for the same problem that beats …

Webalps Implementation And Performance Analysis: Using Trusted Co-Servers To Enhance Privacy And Security Of Web Interactions, Shan Jiang

Dartmouth College Master’s Theses

The client-server model of the Web poses a fundamental trust issue: clients are forced to trust in secrecy and correctness of computation occurring at a remote server of unknown credibility. The current solution for this problem is to use a PKI (Public Key Infrastructure) system and SSL (Secure Sockets Layer) digital certificates to prove the claimed identity of a server and establish an authenticated, encrypted channel between the client and this server. However, this approach does not address the security risks posed by potential malicious server operators or any third parties who may penetrate the server sites. The WebALPS (Web …

Fastab: Solving The Pitch To Notation Problem, Jeremy I. Robin

Dartmouth College Undergraduate Theses

I have always been frustrated with the length of time necessary to notate a piece of music. Computers have simplified so many other aspects of our lives, it seems that they should be able to simplify this task as well. In fact, there are already two distinct ways that engineers have attempted to attack this problem. The first analyzes the waveform generated by microphone input and relies on Fourier Analysis and other similar methods. The other examines the analog signal generated by a electric guitar-like pickup placed beneath the strings. The method used by Fastab relies much less on the …

Ecomrisk.Org : A Site To Classify And Organize The Risks Of Performing Business On The Internet, Aidan Stanley Marcuss

Dartmouth College Undergraduate Theses

As the use of the Internet and other computer networks to transact business grows, there is an ever increasing need for those taking part in those transactions to understand the risks of doing so. While there are many web sites that have created valuable databases of specific vulnerabilities for certain types of hardware and software, there is a lack of focus on attempting to analyze the interaction of businesses, their systems, computer networks, and their customers and the risks that are created by either intended or unattended interactions. EcomRISK.org is a web site that presents a clear taxonomy to classify …

Tcp/Ip Implementation Within The Dartmouth Scalable Simulation Framework, Michael G. Khankin

Dartmouth College Undergraduate Theses

This paper discusses TCP/IP networking, and in particular, the DaSSF implementation of TCP/IP. The paper reviews the protocols, outlines the implementation design, and demonstrates some tests. In addition, some performance and memory usage analysis is performed. We find DaSSF TCP/IP to be a viable option to the existing SSF. DaSSF TCP/IP is faster and uses less memory so we can simulate larger, more complex, models.

Summarizing Data Sets For Classification, Christopher W. Kinzig, Krishnaprasad Thirunarayan, Gary B. Lamont, Robert E. Marmelstein

Kno.e.sis Publications

This paper describes our approach and experiences with implementing a data mining system using genetic algorithms in C++. In contrast with earlier classification algorithms that tended to “tile” the data sets using some pre-specified “shapes”, the proposed system is based on Marmelstein’s work on determining natural boundaries for class homogeneous regions. These boundaries are further refined to construct a compact set of simple data mining rules for classification.

Gravitational Acceleration In Hades, Andrew Simoson

ACMS Conference Proceedings 2001

Does acceleration due to gravity increase or decrease upon descending from Earth’s surface? The answer—as we show—depends on one’s model for Earth’s density. For our Earth, gravity increases before it collapses to zero at Earth center.

Mathematics Memory Verses: Weekly Devotionals For Math Class, Mark Colgan

ACMS Conference Proceedings 2001

Each Monday during the semester I start class with a short devotional on a verse that relates in some way to mathematics. After three weeks I choose one of the three at random for students to write out on their quiz for a possible bonus point. This encourages students to practice memorizing Scripture and it gives us the opportunity to discuss biblical principles that relate to some of the topics we are studying in the course.

I would like to share some of the Bible verses and weekly devotionals I have used in my mathematics classes. These can be organized …

Infopipes—An Abstraction For Information Flow, Jie Huang, Andrew P. Black, Jonathan Walpole, Calton Pu

Computer Science Faculty Publications and Presentations

Building Object-Oriented Distributed Systems has been facilitated by Remote Message Sending (RMS) systems like Java RMI and implementations of CORBA. However, RMS systems are designed to support request/response interactions. Streaming applications, in contrast, are characterized by high-bandwidth, long-duration communication with stringent performance requirements. Examples of streaming applications include video-on-demand, teleconferencing, on-line education, and environmental observation. These applications transfer huge amounts of data and focus on distributed information flow rather than request/response.

To simplify the task of building distributed streaming applications, we propose a new abstraction for information flow—Infopipes. Using Infopipes, information flow becomes the heart of the system, not an …

E-Docspros : Exploring Texpros Into E-Business Era, Zhenfu Cheng

Dissertations

Document processing is a critical element of office automation. TEXPROS (TEXt PROcessing System) is a knowledge-based system designed to manage personal documents. However, as the Internet and e-Business changed the way offices operate, there is a need to re-envision document processing, storage, retrieval, and sharing. In the current environment, people must be able to access documents remotely and to share those documents with others. e-DOCPROS (e-DOCument PROcessing System) is a new document processing system that takes advantage of many of TEXPROS's structures but adapts the system to this new environment. The new system is built to serve e-businesses, takes advantage …