Computer Sciences Commons^™

Factor Criteria Metric (Fcm) For Requirements Analysis Phase In The Development Of Management Information Systems, Wei Yin Chew

Student Works (2000-2009)

This project establishes a way to measure a characteristic of a product and a characteristic of a process involved in the requirements analysis phase for the development of management information systems (M!Ss) by adapting and enhancing McCall's Factor Criteria Metric (FCM) model. The two selected characteristics are the understandability of a software requirements specification (SRS) and effectiveness of a requirements gathering interview (RGI). To define the measurement for these two characteristics, a structure of factors, criteria, checklists and metrics for the characteristics of the products and processes is established based on McCall's FCM model. In addition, a software tool, FCMware, …

Development Of Object Oriented Components For Atm Network Simulation With Emphasis On Switch Architecture, Meng Kiat Gan

Student Works (2000-2009)

Asynchronous Transfer Mode (ATM) is considered to be the foundation on which B­ISON is to be built. It is the new generation of communication protocol that being deployed throughout the telecommunication industry. An important component of this communication networks is the ATM switch whose basic functions are to direct cells from input port to output port and to buffer cell destined to the same output port from different input port. Understanding an ATM switch before building it, is a challenging task as one must consider the design of switching architecture and cell buffering at the same time. As the switching …

Investigation Of Image Feature Extraction By A Genetic Algorithm, Steven P. Brumby, James P. Theiler, Simon J. Perkins, Neal R. Harvey, John J. Szymanski, Jeffrey J. Bloch, Melanie Mitchell

Computer Science Faculty Publications and Presentations

We describe the implementation and performance of a genetic algorithm which generates image feature extraction algorithms for remote sensing applications. We describe our basis set of primitive image operators and present our chromosomal representation of a complete algorithm. Our initial application has been geospatial feature extraction using publicly available multi-spectral aerial-photography data sets. We present the preliminary results of our analysis of the efficiency of the classic genetic operations of crossover and mutation for our application, and discuss our choice of evolutionary control parameters. We exhibit some of our evolved algorithms, and discuss possible avenues for future progress.

Newton Parameter Update Algorithm For Recurrent Neural Networks Applied To Adaptive System Identification And Control, Donald Allen Gates

Electrical & Computer Engineering Theses & Dissertations

This paper shows that the combination of a second-order neural network parameter update algorithm and internal network feedback can be effectively used for adaptive, nonlinear, dynamical system identification and control. Adaptive neural identification and control algorithms are typically utilized for real-time applications where the rate of adaptation is often critical. A fast, adaptive network parameter update algorithm is presented.

Simulation results show that this algorithm is capable of quickly identifying and adapting to changes in system parameters, making it feasible to use for real-time control and fault accommodation applications.

Two Approaches To Critical Path Scheduling For A Heterogeneous Environment, Guangxia Liu

Computer Science Theses & Dissertations

Advances in computing and networking technologies are making large scale distributed heterogeneous computing a reality. Multi-Disciplinary Optimization (MDO) is a class of applications that is being addressed under this paradigm. It consists of multiple heterogeneous modules interacting with each other to solve an overall design problem. An efficient implementation of such an application requires scheduling heterogeneous modules (with different computing and disk 1/0 requirements) on a heterogeneous set of resources (with different CPU, memory, disk IO specifications).

Given a set of tasks and a set of resources, an optimal schedule of the tasks on the resources is very hard to …

Computation Of Scattering From Bodies Of Revolution Using An Entire-Domain Basis Implementation Of The Moment Method, Arthur P. Ford Iv

Theses and Dissertations

Research into improved calibration targets for measurement of radar cross-section has created a need for the ability to accurately compute the scattering from perfectly conducting bodies of revolution. Common computational techniques use Moment Method codes that employ subdomain basis functions to expand the unknown current density. This approach has its shortcomings. Large numbers of basis functions are required, and increasing the number of basis functions to improve accuracy after an initial computation requires re-computation of previous results and lost processing time. This research involves using basis functions that have as their domain the entire length of the surface. Entire-domain basis …

An Efficient Gps Position Determination Algorithm, Carlos R. Colon

Theses and Dissertations

The use of detect, or closed-form solutions of the trilateration equations used to obtain the position fix in GPS receivers is investigated. The paper is concerned with the development of an efficient new position determination algorithm that uses the closed-form solution of the trilateration equations and works in the presence of pseudorange measurement noise and for an arbitrary number of satellites. in addition, an initial position guess is not required and good estimation performance is achieved even under high GDOP conditions. A two step GPS position determination algorithm which 1) entails the solution of a linear regression problem and, 2) …

Gps Signal Offset Detection And Noise Strength Estimation In A Parallel Kalman Filter Algorithm, Barry J. Vanek

Theses and Dissertations

Measurements from Global Positioning System (GPS) satellites are subject to corruption by signal interference and induced offsets. This thesis presents two independent algorithms to ensure the navigation system remains uncorrupted by these possible GPS failures. The first is a parameter estimation algorithm that estimates the measurement noise variance of each satellite. A redundant measurement differencing (RMD) technique provides direct observability of the differenced white measurement noise samples. The variance of the noise process is estimated and provided to the second algorithm, a parallel Kalman filter structure, which then adapts to changes in the real-world measurement noise strength. The parallel Kalman …

Deciding About Agent Mobility Using A Performance Cost Model, Dalia Fakher Elmansy

Archived Theses and Dissertations

No abstract provided.

An Adaptive Hierarchical Fuzzy Logic System For Modelling And Prediction Of Financial Systems, Mark Kingham

Theses: Doctorates and Masters

In this thesis, an intelligent fuzzy logic system using genetic algorithms for the prediction and modelling of interest rates is developed. The proposed system uses a Hierarchical Fuzzy Logic system in which a genetic algorithm is used as a training method for learning the fuzzy rules knowledge bases. A fuzzy logic system is developed to model and predict three month quarterly interest rate fluctuations. The system is further trained to model and predict interest rates for six month and one year periods. The proposed system is developed with first two, three, then four and finally five hierarchical knowledge bases to …

Development Of A Model For Smart Card Based Access Control In Multi-User, Multi-Resource, Multi-Level Access Systems, David Shaw

Theses: Doctorates and Masters

The primary focus of this research is an examination of the issues involved in the granting of access in an environment characterised by multiple users, multiple resources and multiple levels of access permission. Increasing levels of complexity in automotive systems provides opportunities for improving the integration and efficiency of the services provided to the operator. The vehicle lease / hire environment provided a basis for evaluating conditional access to distributed, mobile assets where the principal medium for operating in this environment is the Smart Card. The application of Smart Cards to existing vehicle management systems requires control of access to …

Backtracking In Wormhole-Switched Interconnection Networks, Soha Saad Zaghloul Abdallah

Archived Theses and Dissertations

No abstract provided.

A 2d Dwt Architecture Suitable For The Embedded Zerotree Wavelet Algorithm, James Martinez

Theses : Honours

Digital Imaging has had an enormous impact on industrial applications such as the Internet and video-phone systems. However, demand for industrial applications is growing enormously. In particular, internet application users are, growing at a near exponential rate. The sharp increase in applications using digital images has caused much emphasis on the fields of image coding, storage, processing and communications. New techniques are continuously developed with the main aim of increasing efficiency. Image coding is in particular a field of great commercial interest. A digital image requires a large amount of data to be created. This large amount of data causes …

Nonlinear Constrained Optimizer And Parallel Processing For Golden Block Line Search, Duc T. Nguyen, Wilson H. Tang, Yeou K. Tung, Hakizumwami B. Runesha

Civil & Environmental Engineering Faculty Publications

Generalized exponential penalty functions are constructed for the multiplier methods in solving nonlinear programming problems. The non-smooth extreme constraint Gext is replaced by a single smooth constraint Gs by using the generalized exponential function (base a>1). The well-known K.S. function is found to be a special case of our proposed formulation. Parallel processing for Golden block line search algorithm is then summarized, which can also be integrated into our formulation. Both small and large-scale nonlinear programming problems (up to 2000 variables and 2000 nonlinear constraints) have been solved to validate the proposed algorithms.

Variability Analysis Of Discrete Cosine Transform Coefficient (Dctc) Features For Speech Processing, Bingjun Dai

Electrical & Computer Engineering Theses & Dissertations

In this research, the variability of Discrete Cosine Transform Coefficient (DCTC) features was investigated. Additionally, a new pitch-synchronous processing method was explored to increase the stability of features and to reduce window effects when compared to the regular method. The noise sources that lead to feature variability were analyzed, and different smoothing methods were tested. It was found that longer frames, frequency warping, time smoothing of the log spectrum, and DCS level time smoothing, all help reduce DCTC variability and increase classification performance. The pitch­ synchronous method was implemented with Matlab. Important processing methods, including pitch period estimation, time­ domain …

Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson

Theses and Dissertations

Modern imaging sensors produce vast amounts data, overwhelming human analysts. One such sensor is the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) hyperspectral sensor. The AVIRIS sensor simultaneously collects data in 224 spectral bands that range from 0.4µm to 2.5µm in approximately 10nm increments, producing 224 images, each representing a single spectral band. Autonomous systems are required that can fuse "important" spectral bands and then classify regions of interest if all of this data is to be exploited. This dissertation presents a comprehensive solution that consists of a new physiologically motivated fusion algorithm and a novel Bayes optimal self-architecting classifier …

Architectural Optimization Of Digital Libraries, Aileen O. Biser

Computer Science Theses & Dissertations

This work investigates performance and scaling issues relevant to large scale distributed digital libraries. Presently, performance and scaling studies focus on specific implementations of production or prototype digital libraries. Although useful information is gained to aid these designers and other researchers with insights to performance and scaling issues, the broader issues relevant to very large scale distributed libraries are not addressed. Specifically, no current studies look at the extreme or worst case possibilities in digital library implementations. A survey of digital library research issues is presented. Scaling and performance issues are mentioned frequently in the digital library literature but are …

Maximally Disjoint Solutions Of The Set Covering Problem, David J. Rader, Peter L. Hammer

Mathematical Sciences Technical Reports (MSTR)

This paper is concerned with finding two solutions of a set covering problem that have a minimum number of variables in common. We show that this problem is NP­ complete, even in the case where we are only interested in completely disjoint solutions. We describe three heuristic methods based on the standard greedy algorithm for set covering problems. Two of these algorithms find the solutions sequentially, while the third finds them simultaneously. A local search method for reducing the overlap of the two given solutions is then described. This method involves the solution of a reduced set covering problem. Finally, …

Representations, Approximations, And Algorithms For Mathematical Speech Processing, Laura R. Suzuki

Theses and Dissertations

Representing speech signals such that specific characteristics of speech are included is essential in many Air Force and DoD signal processing applications. A mathematical construct called a frame is presented which captures the important time-varying characteristic of speech. Roughly speaking, frames generalize the idea of an orthogonal basis in a Hilbert space, Specific spaces applicable to speech are L₂(R) and the Hardy spaces H_p(D) for p> 1 where D is the unit disk in the complex plane. Results are given for representations in the Hardy spaces involving Carleson's inequalities (and its extensions), …

New Algorithms For Moving-Bank Multiple Model Adaptive Estimation, Juan R. Vasquez

Theses and Dissertations

The focus of this research is to provide methods for generating precise parameter estimates in the face of potentially significant parameter variations such as system component failures. The standard Multiple Model Adaptive Estimation (MMAE) algorithm uses a bank of Kalman filters, each based on a different model of the system. A new moving-bank MMAE algorithm is developed based on exploitation of the density data available from the MMAE. The methods used to exploit this information include various measures of the density data and a decision-making logic used to move, expand, and contract the MMAE bank of filters. Parameter discretization within …

Building Lms Adaptive Filters With Register-Based Fpgas, Li Ding

Electrical & Computer Engineering Theses & Dissertations

In this thesis, an 8-bit least mean squares (LMS) adaptive digital filter with 16 coefficients is implemented on a single FPGA, using the MaxPlus+2 design environment. The system is constructed as a hierarchical structure, using four different levels of design hierarchy. Subdesigns at each level of the hierarchy project are complied, fitted and simulated to test and verify their functional correctness. The complete system is tested and verified by checking the MaxPlus+2 simulator results against fixed-point integer arithmetic simulations written in Matlab. The resulting adaptive filter is subsequently mapped to the Alters FLEX I OK20TC144-3 device, resulting in a 14,500 …

Starcraft - Maps & Benchmark Problems, Nathan R. Sturtevant, Blizzard Corp.

Moving AI Lab: 2D Maps and Benchmark Problems

Maps extracted from Starcraft from Blizzard Corp. for use and distribution as benchmark problems.

Contains 75 maps and benchmark problem sets, converted to standard format by Dave Churchill and post-processed to remove all but the largest connected component.

Parallel Probabilistic Computations On A Cluster Of Workstations, Atanas Radenski, Andrew Vann, Boyana Norris

Mathematics, Physics, and Computer Science Faculty Books and Book Chapters

Probabilistic algorithms are computationally intensive approximate methods for solving intractable problems. Probabilistic algorithms are excellent candidates for cluster computations because they require little communication and synchronization. It is possible to specify a common parallel control structure as a generic algorithm for probabilistic cluster computations. Such a generic parallel algorithm can be glued together with domain-specific sequential algorithms in order to derive approximate parallel solutions for different intractable problems.

In this paper we propose a generic algorithm for probabilistic computations on a cluster of workstations. We use this generic algorithm to derive specific parallel algorithms for two discrete optimization problems: the …

Optimal Contention-Free Unicast-Based Multicasting In Switch-Based Networks Of Workstations, Ran Libeskind-Hadas, Dominic Mazzoni '99, Ranjith Rajagopalan '99

All HMC Faculty Publications and Research

A unicast-based multicasting algorithm is presented for arbitrary interconnection networks arising in switch-based networks of workstations. The algorithm is optimal with respect tot he number of startups incurred and is provably free from depth contention. Specifically, no two constituent unicasts for the same multicast contend for a common channel, even if some unicasts are delayed due to unpredictable variations in latencies. The algorithm uses an underlying partially adaptive deadlock-free unicast routing algorithm. Simulation results indicate that the algorithm behaves as predicted by its theoretical properties and provides a promising approach to unicast-based multicasting.

Statistical Dynamics Of The Royal Road Genetic Algorithm, Erik Van Nimwegen, James P. Crutchfield, Melanie Mitchell

Computer Science Faculty Publications and Presentations

Metastability is a common phenomenon. Many evolutionary processes, both natural and artificial, alternate between periods of stasis and brief periods of rapid change in their behavior. In this paper an analytical model for the dynamics of a mutation-only genetic algorithm (GA) is introduced that identifies a new and general mechanism causing metastability in evolutionary dynamics. The GA’s population dynamics is described in terms of flows in the space of fitness distributions. The trajectories through fitness distribution space are derived in closed form in the limit of infinite populations. We then show how finite populations induce metastability, even in regions where …

Tree-Based Multicasting In Wormhole-Routed Irregular Topologies, Ran Libeskind-Hadas, Dominic Mazzoni '99, Ranjith Rajagopalan '99

All HMC Faculty Publications and Research

A deadlock-free tree-based multicast routing algorithm is presented for all direct networks, regardless of interconnection topology. The algorithm delivers a message to any number of destinations using only a single startup phase. In contrast to existing tree-based schemes, this algorithm applies to all interconnection topologies, requires only fixed-sized input buffers that are independent of maximum message length, and uses a single asynchronous flit replication mechanism. The theoretical basis of the technique used here is sufficiently general to develop other tree-based multicasting algorithms for regular and irregular topologies. Simulation results demonstrate that this tree-based algorithm provides a very promising means of …

Development And Utilization Of Parallel Generic Algorithms For Scientific Computations, Atanas Radenski, Andrew Vann, Boyana Norris

Mathematics, Physics, and Computer Science Faculty Books and Book Chapters

We develop generic parallel algorithms as extensible modules that encapsulate related classes and parallel methods. Extensible modules define common parallel structures, such as meshes, pipelines, or master-server networks in problem-independent manner. Such modules can be extended with sequential domain-specific code in order to derive particular parallel applications. In this paper, we first outline the essence of extensible modules. Then, we focus on a case study of the cellular automaton, a message-parallel generic algorithm from which we derive diverse parallel scientific applications.

Asymptotically Tight Bounds For Performing Bmmc Permutations On Parallel Disk Systems, Thomas H. Cormen, Thomas Sundquist, Leonard F. Wisniewski

Dartmouth Scholarship

This paper presents asymptotically equal lower and upper bounds for the number of parallel I/O operations required to perform bit-matrix-multiply/complement (BMMC) permutations on the Parallel Disk Model proposed by Vitter and Shriver. A BMMC permutation maps a source index to a target index by an affine transformation over GF(2), where the source and target indices are treated as bit vectors. The class of BMMC permutations includes many common permutations, such as matrix transposition (when dimensions are powers of 2), bit-reversal permutations, vector-reversal permutations, hypercube permutations, matrix reblocking, Gray-code permutations, and inverse Gray-code permutations. The upper bound improves upon the asymptotic …

Breast Cancer Mass Detection Using Difference Of Gaussians And Pulse Coupled Neural Networks, Donald A. Cournoyer

Theses and Dissertations

CAD, serving as a second reader, has been shown to improve the success of radiologists at detecting breast cancer. This thesis will develop a new algorithm to identify masses in mammograms. The system developed for this thesis will be capable of assisting a radiologist in making decisions.

Applications Of Unsupervised Clustering Algorithms To Aircraft Identification Using High Range Resolution Radar, Dzung Tri Pham

Theses and Dissertations

Identification of aircraft from high range resolution (HRR) radar range profiles requires a database of information capturing the variability of the individual range profiles as a function of viewing aspect. This database can be a collection of individual signatures or a collection of average signatures distributed over the region of viewing aspect of interest. An efficient database is one which captures the intrinsic variability of the HRR signatures without either excessive redundancy typical of single-signature databases, or without the loss of information common when averaging arbitrary groups of signatures. The identification of 'natural' clustering of similar HRR signatures provides a …