Computer Sciences Commons^™

Two Essays On The Accounting Treatment For Information Technology Expenditures, Kimberly Swanson Church

Graduate Theses and Dissertations

The current accounting measurement and reporting system is ill-equipped to provide intangible investment information that is decision useful for stakeholders in the information economy. Potentially relevant intangible items are not reported on the balance sheet, since current standards mandate the immediate expensing of these intangible items. Presumably FASB's uncertainty with the fundamental issues of extent and timing of future benefits to the firm has led to concerns with relevance, reliability, and objectivity of capitalizing some intangibles, which results in potential long term value generating expenditures being immediately expensed on the income statement. Prior research has demonstrated extent and timing of …

Distributed Storage And Queryng Techniques For A Semantic Web Of Scientific Workflow Provenance, Jaime Alberto Navarro

Theses and Dissertations - UTB/UTPA

In scientific workflow environments, scientists depend on provenance, which records the history of an experiment. Resource Description Framework is frequently used to represent provenance based on vocabularies such as the Open Provenance Model. For complex scientific workflows that generate large amounts of RDF triples, single-machine provenance management becomes inadequate over time. In this thesis, we research how HBase capabilities can be leveraged for distributed storage and querying of provenance data represented in RDF. We architect the ProvBase system that incorporates an HBase/Hadoop backend, propose a storage schema to hold provenance triples, and design querying algorithms to evaluate SPARQL queries in …

New Algorithms For Protein Structure Comparison And Protein Structure Prediction, Zaixin Lu

Theses and Dissertations - UTB/UTPA

Proteins show a great variety of 3D conformations, which can be used to infer their evolutionary relationship and to classify them into more general groups; therefore algorithms of protein structure alignment, protein similarity search and protein structure prediction are very helpful for protein biologists. We developed new algorithms for the problems in this field. The algorithms are tested with structures from the Protein Data Bank (PDB) and SCOP, a Structure Classification of Protein Database. The experimental results show that our tools are more efficient than some well known systems for finding similar protein structures and predicting protein structures.

Algorithmic Temperature 1 Self-Assembly, Yunhui Fu

Theses and Dissertations - UTB/UTPA

We investigate the power of the Wang tile self-assembly model at temperature 1, a threshold value that permits attachment between any two tiles that share even a single bond. When restricted to deterministic assembly in the plane, no temperature 1 assembly system has been shown to build a shape with a tile complexity smaller than the diameter of the shape. Our work shows a sharp contrast in achievable tile complexity at temperature 1 if either growth into the third dimension or a small probability of error are permitted. Motivated by applications in nanotechnology and molecular computing, and the plausibility of …

Parameterized Algorithm For 3-Sat, Yi Gao

Theses and Dissertations - UTB/UTPA

The SAT problem is the classical NP-complete problem. In the past, many methods have been proposed for solving this problem. We investigated a new method for 3-SAT problem, which is a fixed parameterized algorithm proposed in this paper first. This method uses a fixed parameter k, where k is the number of true values in an assignment for checking whether the formula is satisfied or not. The complexity of our algorithm is O(3k ), which is exponentially independent of the number of variables. Theoretical analysis shows that when k is small, this method has smaller search space and higher speed.

S2st: A Relational Rdf Database Management System, Anthony T. Piazza

Theses and Dissertations - UTB/UTPA

The explosive growth of RDF data on the Semantic Web drives the need for novel database systems that can efficiently store and query large RDF datasets. To achieve good performance and scalability of query processing, most existing RDF storage systems use a relational database management system as a backend to manage RDF data. In this paper, we describe the design and implementation of a Relational RDF Database Management System. Our main research contributions are: (1) We propose a formal model of a Relational RDF Database Management System (RRDBMS), (2) We propose generic algorithms for schema, data and query mapping, (3) …

Evaluation Of Windows Servers Security Under Icmp And Tcp Denial Of Service Attacks, Hari Krishnea Vallalacheruvu

Theses and Dissertations - UTB/UTPA

Securing server from Distributed denial of service (DDoS) attacks is a challenging task for network operators. DDOS attacks are known to reduce the performance of web based applications and reduce the number of legitimate client connections. In this thesis, we evaluate performance of a Windows server 2003 under these attacks. In this thesis, we also evaluate and compare effectiveness of three different protection mechanisms, namely SYN Cache, SYN Cookie and SYN proxy protection methods, to protect against TCP SYN DDoS attacks. It is found that the SYN attack protection at the server is more effective at lower loads of SYN …

Agent Interactions In Decentralized Environments, Martin William Allen

Doctoral Dissertations 1896 - February 2014

The decentralized Markov decision process (Dec-POMDP) is a powerful formal model for studying multiagent problems where cooperative, coordinated action is optimal, but each agent acts based on local data alone. Unfortunately, it is known that Dec-POMDPs are fundamentally intractable: they are NEXP-complete in the worst case, and have been empirically observed to be beyond feasible optimal solution.

To get around these obstacles, researchers have focused on special classes of the general Dec-POMDP problem, restricting the degree to which agent actions can interact with one another. In some cases, it has been proven that these sorts of structured forms of interaction …

Image Up-Sampling Using The Discrete Wavelet Transform, Laleh Asgharian

Theses and Dissertations - UTB/UTPA

Image up-sampling is an effective technique, useful in today's digital image processing applications and rendering devices. In image up-sampling, an image is enhanced from a lower resolution to a higher resolution with the degree of enhancement depending upon application requirements. It is known that the traditional interpolation based approaches for up-sampling, such as the Bilinear or Bicubic interpolations, blur the resultant images along edges and image features. Furthermore, in color imagery, these interpolation-based up-sampling methods may have color infringing artifacts in the areas where the images contain sharp edges and fine textures. We present an interesting up-sampling algorithm based on …

An Improvement And A Generalization Of Zippel's Sparse Multivariate Polynomial Interpolation Algorithm, Michael D. Brazier

Theses and Dissertations - UTB/UTPA

The algorithm most often used for the problem of interpolating sparse multivariate polynomials from their values is Zippel's probabilistic algorithm (1988). The algorithm evaluates the function to be interpolated at a significant number of points, and for many problems of interest processing evaluations dominates the running time. This thesis presents an improvement of Zippel's algorithm, which decreases the number of evaluations needed for an interpolation by using transposed Vandermonde systems for the univariate interpolation step of Zippel's algorithm. The technique also allows a more general form of the algorithm: it becomes possible to interpolate more than one variable within a …

Improving The Performance Of Nested Loop Algorithm Using Separators, Nachiappan N. Nachiappan

Theses and Dissertations - UTB/UTPA

This thesis studies the properties of distance-based outliers and a better detection method for large multi-dimensional datasets. Outlier detection is an important task to find out the objects that deviate in a high ratio from the rest of the objects. The proposed algorithm breaks the data set into divisions and sets the area of access for each division, thus reducing the unnecessary access for a major set of elements. This algorithm reduces the run time of the existing algorithm by using separators. Datasets of varying sizes have been tested to analyze the empirical values of these procedures. Effective data structures …

Entropy-Based 2d Image Dissimilarity Measure, Meng-Hung Wu

Theses and Dissertations - UTB/UTPA

Traditional histogram or statistics based 2D image similarity/dissimilarity metrics fail to handle conjugate pair of black and white images, due to the lack of spatial information in the measurement. Recently proposed Compression-based Dissimilarity Measure (CDM) [1] based on the concept of Kolmogorov complexity has provided a different paradise for similarity measurement. However, without a clear definition how to “concatenate” two 2D images, CDM has difficulties to directly apply with 2D images. In this thesis, an entropy -based 2D image dissimilarity measure is proposed within the same Kolmogorov complexity paradise. The spatial relationship between images is embedded in our metric, and …

Naboh System: Gathering Intelligence From Traffic Patterns, Angelica M. Delgado

Theses and Dissertations - UTB/UTPA

Network traffic anomalies are important indicators of problematic traffic over a network. Network activity has patterns associated with it depending on the applications running on the local hosts connected to the network. There are traffic parameters into which network traffic of a local host can be divided: bandwidth usage, number of remote hosts that a local host is connecting to and vice versa, and number of ports used by the local host. This thesis develops a system for detecting and profiling network anomalies by analyzing traffic parameters using intelligent computational techniques. The developed system gathers intelligence by examining only the …

Empirical Performance Analysis Of Two Algorithms For Mining Intentional Knowledge Of Distance-Based Outliers, Enbamoorthy Prasanthi

Theses and Dissertations - UTB/UTPA

This thesis studies the empirical analysis of two algorithms, Uplattice and Jumplattice for mining intentional knowledge of distance-based outliers [19]. These algorithms detect strongest and weak outliers among them. Finding outliers is an important task required in major applications such as credit-card fraud detection, and the NHL statistical studies. Datasets of varying sizes have been tested to analyze the empirical values of these two algorithms. Effective data structures have been used to gain efficiency in memory-performance. The two algorithms provide intentional knowledge of the detected outliers which determines as to why an identified outlier is exceptional. This knowledge helps the …

Compensation For Automatic White Balance Correction With Histogram Equalization, David D. Kirtley

Theses and Dissertations - UTB/UTPA

Histogram equalization rather than hard scaling can be used as an effective technique to counter automatic white balance correction in video processing to facilitate motion detection in video sequences. Benefits of this method are less user interaction needed by not needing to preview the image to select a scaling area and reduction of the non-focused changes in the video caused by using a scaling area. Reduced interaction lends itself to data mining of video.

Design And Evaluation Of High-Performance Packet Switching Schemes, Taner Doganer

Theses and Dissertations - UTB/UTPA

The design of high-performance packet switches is essential to efficiently handle the exponential growth of data traffic in the next generation Internet. Shared-memory-based packet switches are known to provide the best possible delay-throughput performance and the lowest packet-loss rate compared with packet switches using other buffering strategies. However, scalability of shared-memory-based switching systems has been restricted by high memory bandwidth requirements, segregation of memory space and centralized control of switching functions that causes the switch performance to degrade as a shared-memory switch is grown in size. The new class of sliding-window based packet switches are known to overcome these problems …

Parametric Classification In Domains Of Characters, Numerals, Punctuation, Typefaces And Image Qualities, Osama Ahmed Khan

Theses and Dissertations - UTB/UTPA

This thesis contributes to the Optical Font Recognition problem (OFR), by developing a classifier system to differentiate ten typefaces using a single English character ‘e’. First, features which need to be used in the classifier system are carefully selected after a thorough typographical study of global font features and previous related experiments. These features have been modeled by multivariate normal laws in order to use parameter estimation in learning. Then, the classifier system is built up on six independent schemes, each performing typeface classification using a different method. The results have shown a remarkable performance in the field of font …

Data Analysis In The Antes System, Yavuz Tor

Theses and Dissertations - UTB/UTPA

Acanthosis nigricans is a skin condition that can be used as an indicator for the risk of developing type 2 diabetes in the future. Border Health Office, in University of Texas - Pan American, organizes screenings in schools for acanthosis nigricans. Screening results are, then, collected and evaluated in the Border Health Office. The ANTES System is a computer system that stores and manages the data collected in those screenings.

This study is on the analysis of those collected data to track the progress of data entry, to evaluate the progress on obesity and related problems, and to discover the …

Visualization Of Internet Web Pages Based On Authority And Word Frequency, David Navarro

Theses and Dissertations - UTB/UTPA

The growth, accessibility, and integration of the World Wide Web with contemporary information utilization provides a rich domain in which to explore information retrieval systems. One approach in the evolution of retrieval systems couples successful and long-standing techniques of information retrieval with new techniques, such as visualization. The system developed and reported in this thesis takes this approach. It builds upon well-known techniques of information retrieval including stemming, keyword matching, and cosine similarity. It also incorporates the new and relatively successful hubs and authority approach, which describes Web documents by their reference by other documents. Finally, it develops a new …

Machine Learning Approaches For Determining Effective Seeds For K -Means Algorithm, Kaveephong Lertwachara

Doctoral Dissertations

In this study, I investigate and conduct an experiment on two-stage clustering procedures, hybrid models in simulated environments where conditions such as collinearity problems and cluster structures are controlled, and in real-life problems where conditions are not controlled. The first hybrid model (NK) is an integration between a neural network (NN) and the k-means algorithm (KM) where NN screens seeds and passes them to KM. The second hybrid (GK) uses a genetic algorithm (GA) instead of the neural network. Both NN and GA used in this study are in their simplest-possible forms.

In the simulated data sets, I investigate two …

Modular Machine Learning Methods For Computer-Aided Diagnosis Of Breast Cancer, Mia Kathleen Markey '94

Doctoral Dissertations

The purpose of this study was to improve breast cancer diagnosis by reducing the number of benign biopsies performed. To this end, we investigated modular and ensemble systems of machine learning methods for computer-aided diagnosis (CAD) of breast cancer. A modular system partitions the input space into smaller domains, each of which is handled by a local model. An ensemble system uses multiple models for the same cases and combines the models' predictions.

Five supervised machine learning techniques (LDA, SVM, BP-ANN, CBR, CART) were trained to predict the biopsy outcome from mammographic findings (BIRADS™) and patient age based on a …

Asp -Pricing: A Black -Scholes Option Pricing Formulation, Chaitanya Singh

Doctoral Dissertations

The Applications Service Provider (ASP) arrangement has engendered a revolution in the area of corporate information technology (IT) by transforming software from a packaged off-the-shelf product to an on-line virtual service.

The focus of this study is to establish a sound mathematical foundation for evaluating software rental agreements (embedding exit flexibility) by incorporating a real options framework (based upon the Black-Scholes approach) into the traditional capital budgeting technique. The static discounted cash flow or net present value analysis may not adequately serve as a ‘barometer’ of outsourcing value due to its inherent weaknesses. On the other hand, the options approach …

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 …

The Application And Performance Of A Generic Task Routine Decision Making Algorithm To Recipe Selection In Meal Planning, Michelle M. Cox

Theses and Dissertations - UTB/UTPA

A nutritional meal planning system was implemented to test the effectiveness of a previously developed routine decision making algorithm. The combinatorics involved in ordering recipes in all possible combinations to produce variability in a meal plan and provide sufficient nutrition is conceptually intensive. Meal planning involves selection of food to eat to fulfill a person's nutritional and personal preferences. This thesis demonstrates meal planning as a decision making problem and demonstrates the utility of the routine decision making algorithm by solving this problem. Generic Tasks, identified through artificial intelligence research, provides the basis for this algorithm. It uses user preferences …

Vas (Visual Analysis System): An Information Visualization Engine To Interpret World Wide Web Structure, Tarkan Karadayi

Theses and Dissertations - UTB/UTPA

People increasingly encounter problems of interpreting and filtering mass quantities of information. The enormous growth of information systems on the World Wide Web has demonstrated that we need systems to filter, interpret, organize and present information in ways that allow users to use these large quantities of information. People need to be able to extract knowledge from this sometimes meaningful but sometimes useless mass of data in order to make informed decisions. Web users need to have some kind of information about the sort of page they might visit, such as, is it a rarely referenced or often-referenced page? This …

A Hybrid Finite Element-Finite Difference Method For Thermal Analysis In A Double-Layered Thin Film, Teng Zhu

Doctoral Dissertations

Thin film technology is of vital importance in microtechnology applications. For instance, thin films of metals, of dielectrics such as SiO2, or Si semiconductors are important components of microelectronic devices. The reduction of the device size to the microscale has the advantage of enhancing the switching speed of the device. The reduction, on the other hand, increases the rate of heat generation that leads to a high thermal load on the microdevice. Heat transfer at the microscale with an ultrafast pulsed-laser is also a very important process for thin films. Hence, studying the thermal behavior of thin films or of …

Bottom-Up Design Of Artificial Neural Network For Single-Lead Electrocardiogram Beat And Rhythm Classification, Srikanth Thiagarajan

Doctoral Dissertations

Performance improvement in computerized Electrocardiogram (ECG) classification is vital to improve reliability in this life-saving technology. The non-linearly overlapping nature of the ECG classification task prevents the statistical and the syntactic procedures from reaching the maximum performance. A new approach, a neural network-based classification scheme, has been implemented in clinical ECG problems with much success. The focus, however, has been on narrow clinical problem domains and the implementations lacked engineering precision. An optimal utilization of frequency information was missing. This dissertation attempts to improve the accuracy of neural network-based single-lead (lead-II) ECG beat and rhythm classification. A bottom-up approach defined …