Digital Commons Network^™

Ceg 360/560-01: Digital System Design, Travis E. Doom

Computer Science & Engineering Syllabi

Design of digital systems. Topics include flip-flops, registers, counters, programmable logic devices, memory devices, register-level design, and microcomputer system organization. Students must show competency in the design of digital systems. 3 hours lecture, 2 hours lab. Prerequisite: CEG 260.

Hierarchical Kohonenen Net For Anomaly Detection In Network Security, Suseela T. Sarasamma, Qiuming Zhu, Julie Huff

Computer Science Faculty Publications

A novel multilevel hierarchicalKohonen Net (K-Map) for an intrusion detection system is presented. Each level of the hierarchical map is modeled as a simple winner-take-all K-Map. One significant advantage of this multilevel hierarchical K-Map is its computational efficiency. Unlike other statistical anomaly detection methods such as nearest neighbor approach, K-means clustering or probabilistic analysis that employ distance computation in the feature space to identify the outliers, our approach does not involve costly point-to-point computation in organizing the data into clusters. Another advantage is the reduced network size. We use the classification capability of the K-Map on selected dimensions of data …

Information Technology (It) Appropriateness: The Contingency Theory Of “Fit” And It Implementation In Small And Medium Enterprises, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Publications

There is little doubt that advanced information and communication technologies (IT) arc changing the way businesses operate and conduct commerce. As the advent of a more secure Internet and new transmission standards makes it easier and cheaper for businesses to conduct inter-organizational commerce, it is incumbent upon SME managers to assess whether implementing new technologies such as Electronic Data Interchange (EDI) over the Internet, XML or web-based e-commerce is the "right thing to do" for their organizations. The key question implicit in this decision is addressed in this paper: "Under what conditions should businesses consider themselves likely candidates for (new) …

Measuring Wireless Network Usage With The Experience Sampling Method, Tristan Henderson, Denise Anthony, David Kotz

Dartmouth Scholarship

Measuring wireless local area networks has proven useful for characterizing, modeling and provisioning these networks. These measurements are typically taken passively from a vantage point on the network itself. Client devices, or users, are never actively queried. These measurements can indicate \em what is happening on the network, but it can be difficult to infer \em why a particular behavior is occurring. In this paper we use the Experience Sampling Method (ESM) to study wireless network users. We monitored 29 users remotely for one week, and signaled them to fill out a questionnaire whenever interesting wireless behavior was observed. We …

Stagger: Periodicity Mining Of Data Streams Using Expanding Sliding Windows, Mohamed G. Elfeky, Walid G. Aref, Ahmed K. Elmagarmid

Department of Computer Science Technical Reports

No abstract provided.

To Trie Or Not To Trie? Realizing Space-Partitioning Trees Inside Postgresql: Challenges, Experiences And Performance, Mohamed Y. Eltabakh, Ramy Eltarras, Walid G. Aref

Department of Computer Science Technical Reports

No abstract provided.

Translation-Based Steganography, Christian Grothoff, Krista Grothoff, Ludmila Alkhutova, Ryan Stutsman, Mikhail J. Atallah

Department of Computer Science Technical Reports

No abstract provided.

Exploiting Predicate-Window Semantics Over Data Streams, Thanaa M. Ghanem, Walid G. Aref, Ahmed K. Elmagarmid

Department of Computer Science Technical Reports

No abstract provided.

Keyword Spotting Using Normalization Of Posterior Probability Confidence Measures, Rachna Vijay Vargiya

Theses and Dissertations

Keyword spotting techniques deal with recognition of predefined vocabulary keywords from a voice stream. This research uses HMM based keyword spotting algorithms for this purpose. The three most important components of a keyword detection system are confidence measure, pruning technique and evaluation of results. We suggest that best match for a keyword would be an alignment in which all constituent states have high emission probabilities. Therefore score of even the worst subsequence must also be better than a threshold and a path can be represented by the score of its worst subsequence match. This confidence measure is called Real Fitting. …

Generalization Issues In Pattern Classification Applied To Speaker Identification, Mame C. Sall

Electrical & Computer Engineering Theses & Dissertations

This thesis is an extension of previous work on speaker identification, but with a primary focus on the generalization performance of patterns classifiers for speaker identification. The goal for all pattern classifiers is to generalize to new data, not just perform well on the training data set. The error on the training data is typically a biased estimate of the generalization error. The training set error tends to be smaller than the generalization error if the model is selected such that it minimizes the training error. Therefore, the training error alone should not be used as a good predictor of …

Applying A Simulation-Based Real-Time Decision Making Method To Mass Casualty Scenarios In Hospital Emergency Departments, Fatemah Al-Douli

Electrical & Computer Engineering Theses & Dissertations

The high possibility of having a mass casualty incident compels hospitals to plan ahead in order to sufficiently provide the healthcare needed to as many casualty victims as possible. The Emergency Rooms (ER) are usually hospitals' main entrance for many casualties. Therefore, the ER in the Children's Hospital of the King's Daughters (CHKD) was selected as the system to be examined. The ER in CHKD, the only specialized pediatric ER in the region, already struggles to handle very high patient arrival rates. Consequently, it is expected that treating a large number of patients surviving within a very short period of …

Image Compression By Vector Quantization Of Dct Coefficients Using A Self-Organizing Neural Network, Kirankumar Boyapati

Electrical & Computer Engineering Theses & Dissertations

Image compression is used to remove different types of redundancies and irrelevant information in an image so that the space required for storing the image is minimized. Conventional transform based techniques remove the redundancies between adjacent pixels and irrelevant information in the image but fail to remove the redundancies between different parts of the image. There are techniques like vector quantization, which take care of the redundant information in different parts of the image, but fail to remove the irrelevant information in the image. In this thesis a new technique for lossy digital image compression is proposed which is a …

Programmable Process Flow Networks, Filip D. Cuckov

Electrical & Computer Engineering Theses & Dissertations

A model that introduces programmability to processes occurring in a cargo terminal simulation through the use of a process language is presented in this thesis. The model provides a means for a straight-forward definition, and redefinition of changing processes, their incorporation in the simulation architecture and efficient execution. The model was built to investigate a solution for transforming the cargo terminal simulation CPortS into a process-oriented simulation without hard-coded processes. The approach taken separates the system into an architecture and a set of processes which utilize and interact with the architecture's resources and infrastructure. The processes that take place within …

Clustering And Hybrid Routing In Mobile Ad Hoc Networks, Lan Wang

Computer Science Theses & Dissertations

This dissertation focuses on clustering and hybrid routing in Mobile Ad Hoc Networks (MANET). Specifically, we study two different network-layer virtual infrastructures proposed for MANET: the explicit cluster infrastructure and the implicit zone infrastructure. In the first part of the dissertation, we propose a novel clustering scheme based on a number of properties of diameter-2 graphs to provide a general-purpose virtual infrastructure for MANET. Compared to virtual infrastructures with central nodes, our virtual infrastructure is more symmetric and stable, but still light-weight. In our clustering scheme, cluster initialization naturally blends into cluster maintenance, showing the unity between these two operations. …

Lightweight Federation Of Non-Cooperating Digital Libraries, Rong Shi

Computer Science Theses & Dissertations

This dissertation studies the challenges and issues faced in federating heterogeneous digital libraries (DLs). The objective of this research is to demonstrate the feasibility of interoperability among non-cooperating DLs by presenting a lightweight, data driven approach, or Data Centered Interoperability (DCI). We build a Lightweight Federated Digital Library (LFDL) system to provide federated search service for existing digital libraries with no prior coordination.

We describe the motivation, architecture, design and implementation of the LFDL. We develop, deploy, and evaluate key services of the federation. The major difference to existing DL interoperability approaches is one where we do not insist on …

Mems: Mobile Environmental Management System, Keith Gardiner, A Rizzini, James Carswell, Michela Bertolotto

Conference papers

This paper describes a web-based and Mobile Environmental Management System (MEMS) prototype specifically tailored to perform context-aware queries and updating of spatial datasets. Spatially enabled computing can provide situation aware assistance to both web-based and mobile users by presenting the right information at the right time, place, and situation using context-associated knowledge. Contextassociated knowledge is assembled by combining knowledge gained about information accessed in the past with the activities planned by the user, together with other situation dependencies (e.g. location) of these activities. The MEMS datasets are provided by the Canadian Department of Fisheries and Oceans (DFO) and the prototype …

Mining Social Network From Spatio-Temporal Events, Hady Wirawan Lauw, Ee Peng Lim, Teck Tim Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Knowing patterns of relationship in a social network is very useful for law enforcement agencies to investigate collaborations among criminals, for businesses to exploit relationships to sell products, or for individuals who wish to network with others. After all, it is not just what you know, but also whom you know, that matters. However, finding out who is related to whom on a large scale is a complex problem. Asking every single individual would be impractical, given the huge number of individuals and the changing dynamics of relationships. Recent advancement in technology has allowed more data about activities of individuals …

Rapid Prototyping For The Design Of Virtual Worlds, Prabhu V. Krishnan

Electrical & Computer Engineering Theses & Dissertations

Development of Virtual Reality (VR) applications is challenging where application developers are required to have expertise in the target VR technologies along with the problem domain expertise. New VR technologies impose a significant learning curve to even the most experienced VR developer. The proposed solution relies on synthesis to automate the migration of a VR application to a new unfamiliar VR platform/technology. To solve the problem, the Common Scene Definition Framework (CSDF) was developed, that serves as a superset/model representation of the target virtual world. Input modules were developed to populate the framework with the capabilities of the virtual world …

Survivable Lightpath Provisioning In Wdm Mesh Networks Under Shared Path Protection And Signal Quality Constraints, Xi Yang, Lu Shen, Byrav Ramamurthy

School of Computing: Faculty Publications

This paper addresses the problem of survivable lightpath provisioning in wavelength-division-multiplexing (WDM) mesh networks, taking into consideration optical-layer protection and some realistic optical signal quality constraints. The investigated networks use sparsely placed optical–electrical–optical (O/E/O) modules for regeneration and wavelength conversion. Given a fixed network topology with a number of sparsely placed O/E/O modules and a set of connection requests, a pair of link-disjoint lightpaths is established for each connection. Due to physical impairments and wavelength continuity, both the working and protection lightpaths need to be regenerated at some intermediate nodes to overcome signal quality degradation and wavelength contention. In the …

Walverine: A Walrasian Trading Agent, Shih-Fen Cheng, Evan Leung, Kevin M. Lochner, Kevin O'Malley, Daniel M. Reeves, Julian L. Schvartzman, Michael P. Wellman

Research Collection School Of Computing and Information Systems

TAC-02 was the third in a series of Trading Agent Competition events fostering research in automating trading strategies by showcasing alternate approaches in an open-invitation market game. TAC presents a challenging travel-shopping scenario where agents must satisfy client preferences for complementary and substitutable goods by interacting through a variety of market types. Michigan's entry, Walverine, bases its decisions on a competitive (Walrasian) analysis of the TAC travel economy. Using this Walrasian model, we construct a decision-theoretic formulation of the optimal bidding problem, which Walverine solves in each round of bidding for each good. Walverine's optimal bidding approach, as well as …

Privacy And Ownership Preserving Of Outsourced Medical Data, Elisa Bertino, Beng Chin Ooi, Yanjiang Yang, Robert H. Deng

Research Collection School Of Computing and Information Systems

The demand for the secondary use of medical data is increasing steadily to allow for the provision of better quality health care. Two important issues pertaining to this sharing of data have to be addressed: one is the privacy protection for individuals referred to in the data; the other is copyright protection over the data. In this paper, we present a unified framework that seamlessly combines techniques of binning and digital watermarking to attain the dual goals of privacy and copyright protection. Our binning method is built upon an earlier approach of generalization and suppression by allowing a broader concept …

Providing Efficient Certification Services Against Active Attacks In Ad Hoc Networks, Bo Zhu, Guilin Wang, Zhiguo Wan, Mohan S. Kankanhalli, Feng Bao, Robert H. Deng

Research Collection School Of Computing and Information Systems

Most of previous research work in key management can only resist passive attacks, such as dropping the certificate request, and are vulnerable under active attacks, such as returning a fake reply to the node requesting the certification service. In this paper, we propose two algorithms to address both security and efficiency issues of certification services in ad hoc networks. Both of the algorithms can resist active attacks. In addition, simulation results show that, compared to the previous works, our second algorithm is not only much faster in a friendly environment, but it also works well in a hostile environment in …

Integrating User Feedback Log Into Relevance Feedback By Coupled Svm For Content-Based Image Retrieval, Steven C. H. Hoi, Michael R. Lyu, Rong Jin

Research Collection School Of Computing and Information Systems

Relevance feedback has been shown as an important tool to boost the retrieval performance in content-based image retrieval. In the past decade, various algorithms have been proposed to formulate relevance feedback in contentbased image retrieval. Traditional relevance feedback techniques mainly carry out the learning tasks by focusing lowlevel visual features of image content with little consideration on log information of user feedback. However, from a long-term learning perspective, the user feedback log is one of the most important resources to bridge the semantic gap problem in image retrieval. In this paper we propose a novel technique to integrate the log …

Ais Sighci Position Paper, Dennis Galletta, Ping Zhang, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

The upcoming ACM SIGCHI Development Consortium is aimed at meeting the needs of multidisciplinary professionals that must choose among a variety of professional associations and their events. The position of AIS' (Association for Information Systems) SIGHCI is that the main problem lies in the deep chasms that separate the literatures of the related disciplines, and the solution is to provide an umbrella organization that enables a more organized federation of disciplines, groups, and associations. Problems identified include differences in terminology, competition for scarce resources, differences in how publications in various outlets are valued, and confusion about where should be the …

Proactive Caching For Spatial Queries In Mobile Environments, Haibo Hu, Jianliang Xu, Wing Sing Wong, Baihua Zheng, Dik Lun Lee, Wang-Chien Lee

Research Collection School Of Computing and Information Systems

Semantic caching enables mobile clients to answer spatial queries locally by storing the query descriptions together with the results. However, it supports only a limited number of query types, and sharing results among these types is difficult. To address these issues, we propose a proactive caching model which caches the result objects as well as the index that supports these objects as the results. The cached index enables the objects to be reused for all common types of queries. We also propose an adaptive scheme to cache such an index, which further optimizes the query response time for the best …

Predictive Neural Networks For Gene Expression Data Analysis, Ah-Hwee Tan, Hong Pan

Research Collection School Of Computing and Information Systems

Gene expression data generated by DNA microarray experiments have provided a vast resource for medical diagnosis and disease understanding. Most prior work in analyzing gene expression data, however, focuses on predictive performance but not so much on deriving human understandable knowledge. This paper presents a systematic approach for learning and extracting rule-based knowledge from gene expression data. A class of predictive self-organizing networks known as Adaptive Resonance Associative Map (ARAM) is used for modelling gene expression data, whose learned knowledge can be transformed into a set of symbolic IF-THEN rules for interpretation. For dimensionality reduction, we illustrate how the system …

Creating Software [Sic] Environments On An M-Node Beowulf Cluster To Execute Discrete-Event Simulations, Jermaine Fitz-Gerald Headley

Electrical & Computer Engineering Theses & Dissertations

This thesis describes the development of a software tool that facilitates the creation of software environments that make a simulation tool execute k replications of an application program on several nodes of an M-node Beowulf cluster. It is assumed that each cluster-node consists of p processors. The p processors that are contained in the master cluster-node are termed master processors, and the p processors that are contained in a slave cluster-node are termed slave processors. The slave processors are used to execute the replications, while the master processors are dedicated to schedule the replications and process other housekeeping chores. For …

Development Of Integrated Process Simulation System Model For Spent Fuel Treatment Facility (Sftf) Design: Quarterly Progress Report January 1-March 31, 2005, Yitung Chen, Sean Hsieh

Separations Campaign (TRP)

The Advanced Fuel Cycle Initiative (AFCI) and Transmutation Research Program-University Participation Program (TRP-UPP) supported by Department of Energy of the United States have been developing many important technologies for the transmutation of nuclear waste to address long-term disposal issues. While successfully embedding AMUSE module into a dedicated System Engineering Model (TRPSEMPro), developed by the Nevada Center for Advanced Computational Methods (NCACM) at the University of Nevada-Las Vegas collaborating with Argonne National Laboratory (ANL), ANL is interested in further simulating the Light Water Reactor (LWR) Spent Fuel Treatment Facility (SFTF) combining commercial process simulation and analysis packages and core calculation of …

Using Binary Space Subdivision To Optimize Primary Ray Processing In Ray-Tracing Algorithms, Mark Portolese '05

Honors Projects

Ray-tracing algorithms have the potential to create extremely realistic three-dimensional computer graphics. The basic idea is to trace light rays from the user through the computer screen into the hypothetical three-dimensional world. This is done to determine what objects should be displayed on the screen. Furthermore, these rays are traced back to the light sources themselves to determine shading and other photorealistic effects. However, without optimization these algorithms are slow and impractical. This paper explores the use of the classic binary space subdivision algorithm in order to speed up the process. Binary space subdivision is the use of binary trees …

Department Of Computer Science Activity 1998-2004, David Kotz

Computer Science Technical Reports

This report summarizes much of the research and teaching activity of the Department of Computer Science at Dartmouth College between late 1998 and late 2004. The material for this report was collected as part of the final report for NSF Institutional Infrastructure award EIA-9802068, which funded equipment and technical staff during that six-year period. This equipment and staff supported essentially all of the department's research activity during that period.