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  Access Rights: Use restricted to UNT Community
  Partner: UNT Libraries
 Department: Department of Computer Science and Engineering
 Collection: UNT Theses and Dissertations
Logic Programming Tools for Dynamic Content Generation and Internet Data Mining

Logic Programming Tools for Dynamic Content Generation and Internet Data Mining

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Date: December 2000
Creator: Gupta, Anima
Description: The phenomenal growth of Information Technology requires us to elicit, store and maintain huge volumes of data. Analyzing this data for various purposes is becoming increasingly important. Data mining consists of applying data analysis and discovery algorithms that under acceptable computational efficiency limitations, produce a particular enumeration of patterns over the data. We present two techniques based on using Logic programming tools for data mining. Data mining analyzes data by extracting patterns which describe its structure and discovers co-relations in the form of rules. We distinguish analysis methods as visual and non-visual and present one application of each. We explain that our focus on the field of Logic Programming makes some of the very complex tasks related to Web based data mining and dynamic content generation, simple and easy to implement in a uniform framework.
Contributing Partner: UNT Libraries
Memory Management and Garbage Collection Algorithms for Java-Based Prolog

Memory Management and Garbage Collection Algorithms for Java-Based Prolog

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Date: August 2001
Creator: Zhou, Qinan
Description: Implementing a Prolog Runtime System in a language like Java which provides its own automatic memory management and safety features such as built--in index checking and array initialization requires a consistent approach to memory management based on a simple ultimate goal: minimizing total memory management time and extra space involved. The total memory management time for Jinni is made up of garbage collection time both for Java and Jinni itself. Extra space is usually requested at Jinni's garbage collection. This goal motivates us to find a simple and practical garbage collection algorithm and implementation for our Prolog engine. In this thesis we survey various algorithms already proposed and offer our own contribution to the study of garbage collection by improvements and optimizations for some classic algorithms. We implemented these algorithms based on the dynamic array algorithm for an all--dynamic Prolog engine (JINNI 2000). The comparisons of our implementations versus the originally proposed algorithm allow us to draw informative conclusions on their theoretical complexity model and their empirical effectiveness.
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Voting Operating System (VOS)

Voting Operating System (VOS)

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Date: December 2004
Creator: Venkatadusumelli, Kiran
Description: The electronic voting machine (EVM) plays a very important role in a country where government officials are elected into office. Throughout the world, a specific operating system that tends to the specific requirement of the EVM does not exist. Existing EVM technology depends upon the various operating systems currently available, thus ignoring the basic needs of the system. There is a compromise over the basic requirements in order to develop the systems on the basis on an already available operating system, thus having a lot of scope for error. It is necessary to know the specific details of the particular device for which the operating system is being developed. In this document, I evaluate existing EVMs and identify flaws and shortcomings. I propose a solution for a new operating system that meets the specific requirements of the EVM, calling it Voting Operating System (VOS, pronounced 'voice'). The identification technique can be simplified by using the fingerprint technology that determines the identity of a person based on two fingerprints. I also discuss the various parts of the operating system that have to be implemented that can tend to all the basic requirements of an EVM, including implementation of the memory manager, ...
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Peptide-based hidden Markov model for peptide fingerprint mapping.

Peptide-based hidden Markov model for peptide fingerprint mapping.

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Date: December 2004
Creator: Yang, Dongmei
Description: Peptide mass fingerprinting (PMF) was the first automated method for protein identification in proteomics, and it remains in common usage today because of its simplicity and the low equipment costs for generating fingerprints. However, one of the problems with PMF is its limited specificity and sensitivity in protein identification. Here I present a method that shows potential to significantly enhance the accuracy of peptide mass fingerprinting, using a machine learning approach based on a hidden Markov model (HMM). This method is applied to improve differentiation of real protein matches from those that occur by chance. The system was trained using 300 examples of combined real and false-positive protein identification results, and 10-fold cross-validation applied to assess model discrimination. The model can achieve 93% accuracy in distinguishing correct and real protein identification results versus false-positive matches. The receiver operating characteristic (ROC) curve area for the best model was 0.833.
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Procedural content creation and technologies for 3D graphics applications and games.

Procedural content creation and technologies for 3D graphics applications and games.

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Date: May 2005
Creator: Roden, Timothy E.
Description: The recent transformation of consumer graphics (CG) cards into powerful 3D rendering processors is due in large measure to the success of game developers in delivering mass market entertainment software that feature highly immersive and captivating virtual environments. Despite this success, 3D CG application development is becoming increasingly handicapped by the inability of traditional content creation methods to keep up with the demand for content. The term content is used here to refer to any data operated on by application code that is meant for viewing, including 3D models, textures, animation sequences and maps or other data-intensive descriptions of virtual environments. Traditionally, content has been handcrafted by humans. A serious problem facing the interactive graphics software development community is how to increase the rate at which content can be produced to keep up with the increasingly rapid pace at which software for interactive applications can now be developed. Research addressing this problem centers around procedural content creation systems. By moving away from purely human content creation toward systems in which humans play a substantially less time-intensive but no less creative part in the process, procedural content creation opens new doors. From a qualitative standpoint, these types of systems will not ...
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Automated defense against worm propagation.

Automated defense against worm propagation.

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Date: December 2005
Creator: Patwardhan, Sudeep
Description: Worms have caused significant destruction over the last few years. Network security elements such as firewalls, IDS, etc have been ineffective against worms. Some worms are so fast that a manual intervention is not possible. This brings in the need for a stronger security architecture which can automatically react to stop worm propagation. The method has to be signature independent so that it can stop new worms. In this thesis, an automated defense system (ADS) is developed to automate defense against worms and contain the worm to a level where manual intervention is possible. This is accomplished with a two level architecture with feedback at each level. The inner loop is based on control system theory and uses the properties of PID (proportional, integral and differential controller). The outer loop works at the network level and stops the worm to reach its spread saturation point. In our lab setup, we verified that with only inner loop active the worm was delayed, and with both loops active we were able to restrict the propagation to 10% of the targeted hosts. One concern for deployment of a worm containment mechanism was degradation of throughput for legitimate traffic. We found that with proper ...
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Using Reinforcement Learning in Partial Order Plan Space

Using Reinforcement Learning in Partial Order Plan Space

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Date: May 2006
Creator: Ceylan, Hakan
Description: Partial order planning is an important approach that solves planning problems without completely specifying the orderings between the actions in the plan. This property provides greater flexibility in executing plans; hence making the partial order planners a preferred choice over other planning methodologies. However, in order to find partially ordered plans, partial order planners perform a search in plan space rather than in space of world states and an uninformed search in plan space leads to poor efficiency. In this thesis, I discuss applying a reinforcement learning method, called First-visit Monte Carlo method, to partial order planning in order to design agents which do not need any training data or heuristics but are still able to make informed decisions in plan space based on experience. Communicating effectively with the agent is crucial in reinforcement learning. I address how this task was accomplished in plan space and the results from an evaluation of a blocks world test bed.
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Comparison and Evaluation of Existing Analog Circuit Simulator using Sigma-Delta Modulator

Comparison and Evaluation of Existing Analog Circuit Simulator using Sigma-Delta Modulator

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Date: December 2006
Creator: Ale, Anil Kumar
Description: In the world of VLSI (very large scale integration) technology, there are many different types of circuit simulators that are used to design and predict the circuit behavior before actual fabrication of the circuit. In this thesis, I compared and evaluated existing circuit simulators by considering standard benchmark circuits. The circuit simulators which I evaluated and explored are Ngspice, Tclspice, Winspice (open source) and Spectre® (commercial). I also tested standard benchmarks using these circuit simulators and compared their outputs. The simulators are evaluated using design metrics in order to quantify their performance and identify efficient circuit simulators. In addition, I designed a sigma-delta modulator and its individual components using the analog behavioral language Verilog-A. Initially, I performed simulations of individual components of the sigma-delta modulator and later of the whole system. Finally, CMOS (complementary metal-oxide semiconductor) transistor-level circuits were designed for the differential amplifier, operational amplifier and comparator of the modulator.
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A Language and Visual Interface to Specify Complex Spatial Pattern Mining

A Language and Visual Interface to Specify Complex Spatial Pattern Mining

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Date: December 2006
Creator: Li, Xiaohui
Description: The emerging interests in spatial pattern mining leads to the demand for a flexible spatial pattern mining language, on which easy to use and understand visual pattern language could be built. It is worthwhile to define a pattern mining language called LCSPM to allow users to specify complex spatial patterns. I describe a proposed pattern mining language in this paper. A visual interface which allows users to specify the patterns visually is developed. Visual pattern queries are translated into the LCSPM language by a parser and data mining process can be triggered afterwards. The visual language is based on and goes beyond the visual language proposed in literature. I implemented a prototype system based on the open source JUMP framework.
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A Multi-Variate Analysis of SMTP Paths and Relays to Restrict Spam and Phishing Attacks in Emails

A Multi-Variate Analysis of SMTP Paths and Relays to Restrict Spam and Phishing Attacks in Emails

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Date: December 2006
Creator: Palla, Srikanth
Description: The classifier discussed in this thesis considers the path traversed by an email (instead of its content) and reputation of the relays, features inaccessible to spammers. Groups of spammers and individual behaviors of a spammer in a given domain were analyzed to yield association patterns, which were then used to identify similar spammers. Unsolicited and phishing emails were successfully isolated from legitimate emails, using analysis results. Spammers and phishers are also categorized into serial spammers/phishers, recent spammers/phishers, prospective spammers/phishers, and suspects. Legitimate emails and trusted domains are classified into socially close (family members, friends), socially distinct (strangers etc), and opt-outs (resolved false positives and false negatives). Overall this classifier resulted in far less false positives when compared to current filters like SpamAssassin, achieving a 98.65% precision, which is well comparable to the precisions achieved by SPF, DNSRBL blacklists.
Contributing Partner: UNT Libraries
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