UNT Libraries - 207 Matching Results

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Multiresolutional/Fractal Compression of Still and Moving Pictures

Description: The scope of the present dissertation is a deep lossy compression of still and moving grayscale pictures while maintaining their fidelity, with a specific goal of creating a working prototype of a software system for use in low bandwidth transmission of still satellite imagery and weather briefings with the best preservation of features considered important by the end user.
Date: December 1993
Creator: Kiselyov, Oleg E.

A Multi-Time Scale Learning Mechanism for Neuromimic Processing

Description: Learning and representing and reasoning about temporal relations, particularly causal relations, is a deep problem in artificial intelligence (AI). Learning such representations in the real world is complicated by the fact that phenomena are subject to multiple time scale influences and may operate with a strange attractor dynamic. This dissertation proposes a new computational learning mechanism, the adaptrode, which, used in a neuromimic processing architecture may help to solve some of these problems. The adaptrode is shown to emulate the dynamics of real biological synapses and represents a significant departure from the classical weighted input scheme of conventional artificial neural networks. Indeed the adaptrode is shown, by analysis of the deep structure of real synapses, to have a strong structural correspondence with the latter in terms of multi-time scale biophysical processes. Simulations of an adaptrode-based neuron and a small network of neurons are shown to have the same learning capabilities as invertebrate animals in classical conditioning. Classical conditioning is considered a fundamental learning task in animals. Furthermore, it is subject to temporal ordering constraints that fulfill the criteria of causal relations in natural systems. It may offer clues to the learning of causal relations and mechanisms for causal reasoning. The adaptrode is shown to solve an advanced problem in classical conditioning that addresses the problem of real world dynamics. A network is able to learn multiple, contrary associations that separate in time domains, that is a long-term memory can co-exist with a short-term contrary memory without destroying the former. This solves the problem of how to deal with meaningful transients while maintaining long-term memories. Possible applications of adaptrode-based neural networks are explored and suggestions for future research are made.
Date: August 1994
Creator: Mobus, George E. (George Edward)

A Highly Fault-Tolerant Distributed Database System with Replicated Data

Description: Because of the high cost and impracticality of a high connectivity network, most recent research in transaction processing has focused on a distributed replicated database system. In such a system, multiple copies of a data item are created and stored at several sites in the network, so that the system is able to tolerate more crash and communication failures and attain higher data availability. However, the multiple copies also introduce a global inconsistency problem, especially in a partitioned network. In this dissertation a tree quorum algorithm is proposed to solve this problem, imposing a logical tree structure along with dynamic system reconfiguration on all the copies of each data item. The proposed algorithm can be viewed as a dynamic voting technique which, with the help of an appropriate concurrency control algorithm, exhibits the major advantages of quorum-based replica control algorithms and of the available copies algorithm, so that a single copy is read for a read operation and a quorum of copies is written for a write operation. In addition, read and write quorums are computed dynamically and independently. As a result expensive read operations, like those that require several copies of a data item to be read in most quorum schemes, are eliminated. Furthermore, the message costs of read and write operations are reduced by the use of smaller quorum sizes. Quorum sizes can be reduced to a constant in a lightly loaded system, and log n in a failure-free network, as well as [n +1/2] in a partitioned network in a heavily loaded system. On average, our algorithm requires fewer messages than the best known tree quorum algorithm, while still maintaining the same upper bound on quorum size. One-copy serializability is guaranteed with higher data availability and highest degree of fault tolerance (up to n - 1 site ...
Date: December 1994
Creator: Lin, Tsai S. (Tsai Shooumeei)

Recognition of Face Images

Description: The focus of this dissertation is a methodology that enables computer systems to classify different up-front images of human faces as belonging to one of the individuals to which the system has been exposed previously. The images can present variance in size, location of the face, orientation, facial expressions, and overall illumination. The approach to the problem taken in this dissertation can be classified as analytic as the shapes of individual features of human faces are examined separately, as opposed to holistic approaches to face recognition. The outline of the features is used to construct signature functions. These functions are then magnitude-, period-, and phase-normalized to form a translation-, size-, and rotation-invariant representation of the features. Vectors of a limited number of the Fourier decomposition coefficients of these functions are taken to form the feature vectors representing the features in the corresponding vector space. With this approach no computation is necessary to enforce the translational, size, and rotational invariance at the stage of recognition thus reducing the problem of recognition to the k-dimensional clustering problem. A recognizer is specified that can reliably classify the vectors of the feature space into object classes. The recognizer made use of the following principle: a trial vector is classified into a class with the greatest number of closest vectors (in the sense of the Euclidean distance) among all vectors representing the same feature in the database of known individuals. A system based on this methodology is implemented and tried on a set of 50 pictures of 10 individuals (5 pictures per individual). The recognition rate is comparable to that of most recent results in the area of face recognition. The methodology presented in this dissertation is also applicable to any problem of pattern recognition where patterns can be represented as a collection of black ...
Date: December 1994
Creator: Pershits, Edward

Efficient Linked List Ranking Algorithms and Parentheses Matching as a New Strategy for Parallel Algorithm Design

Description: The goal of a parallel algorithm is to solve a single problem using multiple processors working together and to do so in an efficient manner. In this regard, there is a need to categorize strategies in order to solve broad classes of problems with similar structures and requirements. In this dissertation, two parallel algorithm design strategies are considered: linked list ranking and parentheses matching.
Date: December 1993
Creator: Halverson, Ranette Hudson

Temporal Connectionist Expert Systems Using a Temporal Backpropagation Algorithm

Description: Representing time has been considered a general problem for artificial intelligence research for many years. More recently, the question of representing time has become increasingly important in representing human decision making process through connectionist expert systems. Because most human behaviors unfold over time, any attempt to represent expert performance, without considering its temporal nature, can often lead to incorrect results. A temporal feedforward neural network model that can be applied to a number of neural network application areas, including connectionist expert systems, has been introduced. The neural network model has a multi-layer structure, i.e. the number of layers is not limited. Also, the model has the flexibility of defining output nodes in any layer. This is especially important for connectionist expert system applications. A temporal backpropagation algorithm which supports the model has been developed. The model along with the temporal backpropagation algorithm makes it extremely practical to define any artificial neural network application. Also, an approach that can be followed to decrease the memory space used by weight matrix has been introduced. The algorithm was tested using a medical connectionist expert system to show how best we describe not only the disease but also the entire course of the disease. The system, first, was trained using a pattern that was encoded from the expert system knowledge base rules. Following then, series of experiments were carried out using the temporal model and the temporal backpropagation algorithm. The first series of experiments was done to determine if the training process worked as predicted. In the second series of experiments, the weight matrix in the trained system was defined as a function of time intervals before presenting the system with the learned patterns. The result of the two experiments indicate that both approaches produce correct results. The only difference between the two results ...
Date: December 1993
Creator: Civelek, Ferda N. (Ferda Nur)

A Mechanism for Facilitating Temporal Reasoning in Discrete Event Simulation

Description: This research establishes the feasibility and potential utility of a software mechanism which employs artificial intelligence techniques to enhance the capabilities of standard discrete event simulators. As background, current methods of integrating artificial intelligence with simulation and relevant research are briefly reviewed.
Date: May 1992
Creator: Legge, Gaynor W.

Using Normal Deduction Graphs in Common Sense Reasoning

Description: This investigation proposes a powerful formalization of common sense knowledge based on function-free normal deduction graphs (NDGs) which form a powerful tool for deriving Horn and non-Horn clauses without functions. Such formalization allows common sense reasoning since it has the ability to handle not only negative but also incomplete information.
Date: May 1992
Creator: Munoz, Ricardo A. (Ricardo Alberto)

Using Extended Logic Programs to Formalize Commonsense Reasoning

Description: In this dissertation, we investigate how commonsense reasoning can be formalized by using extended logic programs. In this investigation, we first use extended logic programs to formalize inheritance hierarchies with exceptions by adopting McCarthy's simple abnormality formalism to express uncertain knowledge. In our representation, not only credulous reasoning can be performed but also the ambiguity-blocking inheritance and the ambiguity-propagating inheritance in skeptical reasoning are simulated. In response to the anomalous extension problem, we explore and discover that the intuition underlying commonsense reasoning is a kind of forward reasoning. The unidirectional nature of this reasoning is applied by many reformulations of the Yale shooting problem to exclude the undesired conclusion. We then identify defeasible conclusions in our representation based on the syntax of extended logic programs. A similar idea is also applied to other formalizations of commonsense reasoning to achieve such a purpose.
Date: May 1992
Creator: Horng, Wen-Bing

An Adaptive Linearization Method for a Constraint Satisfaction Problem in Semiconductor Device Design Optimization

Description: The device optimization is a very important element in semiconductor technology advancement. Its objective is to find a design point for a semiconductor device so that the optimized design goal meets all specified constraints. As in other engineering fields, a nonlinear optimizer is often used for design optimization. One major drawback of using a nonlinear optimizer is that it can only partially explore the design space and return a local optimal solution. This dissertation provides an adaptive optimization design methodology to allow the designer to explore the design space and obtain a globally optimal solution. One key element of our method is to quickly compute the set of all feasible solutions, also called the acceptability region. We described a polytope-based representation for the acceptability region and an adaptive linearization technique for device performance model approximation. These efficiency enhancements have enabled significant speed-up in estimating acceptability regions and allow acceptability regions to be estimated for a larger class of device design tasks. Our linearization technique also provides an efficient mechanism to guarantee the global accuracy of the computed acceptability region. To visualize the acceptability region, we study the orthogonal projection of high-dimensional convex polytopes and propose an output sensitive algorithm for projecting polytopes into two dimensions.
Date: May 1999
Creator: Chang, Chih-Hui, 1967-

Independent Quadtrees

Description: This dissertation deals with the problem of manipulating and storing an image using quadtrees. A quadtree is a tree in which each node has four ordered children or is a leaf. It can be used to represent an image via hierarchical decomposition. The image is broken into four regions. A region can be a solid color (homogeneous) or a mixture of colors (heterogeneous). If a region is heterogeneous it is broken into four subregions, and the process continues recursively until all subregions are homogeneous. The traditional quadtree suffers from dependence on the underlying grid. The grid coordinate system is implicit, and therefore fixed. The fixed coordinate system implies a rigid tree. A rigid tree cannot be translated, scaled, or rotated. Instead, a new tree must be built which is the result of one of these transformations. This dissertation introduces the independent quadtree. The independent quadtree is free of any underlying coordinate system. The tree is no longer rigid and can be easily translated, scaled, or rotated. Algorithms to perform these operations axe presented. The translation and rotation algorithms take constant time. The scaling algorithm has linear time in the number nodes in the tree. The disadvantage of independent quadtrees is the longer generation and display time. This dissertation also introduces an alternate method of hierarchical decomposition. This new method finds the largest homogeneous block with respect to the corners of the image. This block defines the division point for the decomposition. If the size of the block is below some cutoff point, it is deemed to be to small to make the overhead worthwhile and the traditional method is used instead. This new method is compared to the traditional method on randomly generated rectangles, triangles, and circles. The new method is shown to use significantly less space for all three ...
Date: December 1986
Creator: Atwood, Larry D. (Larry Dale)

An Algorithm for the PLA Equivalence Problem

Description: The Programmable Logic Array (PLA) has been widely used in the design of VLSI circuits and systems because of its regularity, flexibility, and simplicity. The equivalence problem is typically to verify that the final description of a circuit is functionally equivalent to its initial description. Verifying the functional equivalence of two descriptions is equivalent to proving their logical equivalence. This problem of pure logic is essential to circuit design. The most widely used technique to solve the problem is based on Binary Decision Diagram or BDD, proposed by Bryant in 1986. Unfortunately, BDD requires too much time and space to represent moderately large circuits for equivalence testing. We design and implement a new algorithm called the Cover-Merge Algorithm for the equivalence problem based on a divide-and-conquer strategy using the concept of cover and a derivational method. We prove that the algorithm is sound and complete. Because of the NP-completeness of the problem, we emphasize simplifications to reduce the search space or to avoid redundant computations. Simplification techniques are incorporated into the algorithm as an essential part to speed up the the derivation process. Two different sets of heuristics are developed for two opposite goals: one for the proof of equivalence and the other for its disproof. Experiments on a large scale of data have shown that big speed-ups can be achieved by prioritizing the heuristics and by choosing the most favorable one at each iteration of the Algorithm. Results are compared with those for BDD on standard benchmark problems as well as on random PLAs to perform an unbiased way of testing algorithms. It has been shown that the Cover-Merge Algorithm outperforms BDD in nearly all problem instances in terms of time and space. The algorithm has demonstrated fairly stabilized and practical performances especially for big PLAs under a wide ...
Date: December 1995
Creator: Moon, Gyo Sik

Convexity-Preserving Scattered Data Interpolation

Description: Surface fitting methods play an important role in many scientific fields as well as in computer aided geometric design. The problem treated here is that of constructing a smooth surface that interpolates data values associated with scattered nodes in the plane. The data is said to be convex if there exists a convex interpolant. The problem of convexity-preserving interpolation is to determine if the data is convex, and construct a convex interpolant if it exists.
Date: December 1995
Creator: Leung, Nim Keung

Study of Parallel Algorithms Related to Subsequence Problems on the Sequent Multiprocessor System

Description: The primary purpose of this work is to study, implement and analyze the performance of parallel algorithms related to subsequence problems. The problems include string to string correction problem, to determine the longest common subsequence problem and solving the sum-range-product, 1 —D pattern matching, longest non-decreasing (non-increasing) (LNS) and maximum positive subsequence (MPS) problems. The work also includes studying the techniques and issues involved in developing parallel applications. These algorithms are implemented on the Sequent Multiprocessor System. The subsequence problems have been defined, along with performance metrics that are utilized. The sequential and parallel algorithms have been summarized. The implementation issues which arise in the process of developing parallel applications have been identified and studied.
Date: August 1994
Creator: Pothuru, Surendra

A Machine Learning Method Suitable for Dynamic Domains

Description: The efficacy of a machine learning technique is domain dependent. Some machine learning techniques work very well for certain domains but are ill-suited for other domains. One area that is of real-world concern is the flexibility with which machine learning techniques can adapt to dynamic domains. Currently, there are no known reports of any system that can learn dynamic domains, short of starting over (i.e., re-running the program). Starting over is neither time nor cost efficient for real-world production environments. This dissertation studied a method, referred to as Experience Based Learning (EBL), that attempts to deal with conditions related to learning dynamic domains. EBL is an extension of Instance Based Learning methods. The hypothesis of the study related to this research was that the EBL method would automatically adjust to domain changes and still provide classification accuracy similar to methods that require starting over. To test this hypothesis, twelve widely studied machine learning datasets were used. A dynamic domain was simulated by presenting these datasets in an uninterrupted cycle of train, test, and retrain. The order of the twelve datasets and the order of records within each dataset were randomized to control for order biases in each of ten runs. As a result, these methods provided datasets that represent extreme levels of domain change. Using the above datasets, EBL's mean classification accuracies for each dataset were compared to the published static domain results of other machine learning systems. The results indicated that the EBL's system performance was not statistically different (p>0.30) from the other machine learning methods. These results indicate that the EBL system is able to adjust to an extreme level of domain change and yet produce satisfactory results. This finding supports the use of the EBL method in real-world environments that incur rapid changes to both variables and ...
Date: July 1996
Creator: Rowe, Michael C. (Michael Charles)

Practical Cursive Script Recognition

Description: This research focused on the off-line cursive script recognition application. The problem is very large and difficult and there is much room for improvement in every aspect of the problem. Many different aspects of this problem were explored in pursuit of solutions to create a more practical and usable off-line cursive script recognizer than is currently available.
Date: August 1995
Creator: Carroll, Johnny Glen, 1953-

Quantifying Design Principles in Reusable Software Components

Description: Software reuse can occur in various places during the software development cycle. Reuse of existing source code is the most commonly practiced form of software reuse. One of the key requirements for software reuse is readability, thus the interest in the use of data abstraction, inheritance, modularity, and aspects of the visible portion of module specifications. This research analyzed the contents of software reuse libraries to answer the basic question of what makes a good reusable software component. The approach taken was to measure and analyze various software metrics as mapped to design characteristics. A related research question investigated the change in the design principles over time. This was measured by comparing sets of Ada reuse libraries categorized into two time periods. It was discovered that recently developed Ada reuse components scored better on readability than earlier developed components. A benefit of this research has been the development of a set of "design for reuse" guidelines. These guidelines address coding practices as well as design principles for an Ada implementation. C++ software reuse libraries were also analyzed to determine if design principles can be applied in a language independent fashion. This research used cyclomatic complexity metrics, software science metrics, and traditional static code metrics to measure design features. This research provides at least three original contributions. First it collects empirical data about existing reuse libraries. Second, it develops a readability measure for software libraries which can aid in comparing libraries. And third, this research developed a set of coding and design guidelines for developers of reusable software. Future research can investigate how design principles for C++ change over time. Another topic for research is the investigation of systems employing reused components to determine which libraries are more successfully used than others.
Date: December 1995
Creator: Moore, Freeman Leroy

The Design and Implementation of a Prolog Parser Using Javacc

Description: Operatorless Prolog text is LL(1) in nature and any standard LL parser generator tool can be used to parse it. However, the Prolog text that conforms to the ISO Prolog standard allows the definition of dynamic operators. Since Prolog operators can be defined at run-time, operator symbols are not present in the grammar rules of the language. Unless the parser generator allows for some flexibility in the specification of the grammar rules, it is very difficult to generate a parser for such text. In this thesis we discuss the existing parsing methods and their modified versions to parse languages with dynamic operator capabilities. Implementation details of a parser using Javacc as a parser generator tool to parse standard Prolog text is provided. The output of the parser is an “Abstract Syntax Tree” that reflects the correct precedence and associativity rules among the various operators (static and dynamic) of the language. Empirical results are provided that show that a Prolog parser that is generated by the parser generator like Javacc is comparable in efficiency to a hand-coded parser.
Date: August 2002
Creator: Gupta, Pankaj

Generating Machine Code for High-Level Programming Languages

Description: The purpose of this research was to investigate the generation of machine code from high-level programming language. The following steps were undertaken: 1) Choose a high-level programming language as the source language and a computer as the target computer. 2) Examine all stages during the compiling of a high-level programming language and all data sets involved in the compilation. 3) Discover the mechanism for generating machine code and the mechanism to generate more efficient machine code from the language. 3) Construct an algorithm for generating machine code for the target computer. The results suggest that compiler is best implemented in a high-level programming language, and that SCANNER and PARSER should be independent of target representations, if possible.
Date: December 1976
Creator: Chao, Chia-Huei

An Empirical Study of How Novice Programmers Use the Web

Description: Students often use the web as a source of help for problems that they encounter on programming assignments.In this work, we seek to understand how students use the web to search for help on their assignments.We used a mixed methods approach with 344 students who complete a survey and 41 students who participate in a focus group meetings and helped in recording data about their search habits.The survey reveals data about student reported search habits while the focus group uses a web browser plug-in to record actual search patterns.We examine the results collectively and as broken down by class year.Survey results show that at least 2/3 of the students from each class year rely on search engines to locate resources for help with their programming bugs in at least half of their assignments;search habits vary by class year;and the value of different types of resources such as tutorials and forums varies by class year.Focus group results exposes the high frequency web sites used by the students in solving their programming assignments.
Date: May 2016
Creator: Tula, Naveen

Learning from small data set for object recognition in mobile platforms.

Description: Did you stand at a door with a bunch of keys and tried to find the right one to unlock the door? Did you hold a flower and wonder the name of it? A need of object recognition could rise anytime and any where in our daily lives. With the development of mobile devices object recognition applications become possible to provide immediate assistance. However, performing complex tasks in even the most advanced mobile platforms still faces great challenges due to the limited computing resources and computing power. In this thesis, we present an object recognition system that resides and executes within a mobile device, which can efficiently extract image features and perform learning and classification. To account for the computing constraint, a novel feature extraction method that minimizes the data size and maintains data consistency is proposed. This system leverages principal component analysis method and is able to update the trained classifier when new examples become available . Our system relieves users from creating a lot of examples and makes it user friendly. The experimental results demonstrate that a learning method trained with a very small number of examples can achieve recognition accuracy above 90% in various acquisition conditions. In addition, the system is able to perform learning efficiently.
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Date: May 2016
Creator: Liu, Siyuan

A Parallel Programming Language

Description: The problem of programming a parallel processor is discussed. Previous methods of programming a parallel processor, analyzing a program for parallel paths, and special language features are discussed. Graph theory is used to define the three basic programming constructs: choice, sequence, repetition. The concept of mechanized programming is expanded to allow for total separation of control and computational sections of a program. A definition of a language is presented which provides for this separation. A method for developing the program graph is discussed. The control graph and data graph are developed separately. The two graphs illustrate control and data predecessor relationships used in determining parallel elements of a program.
Date: May 1979
Creator: Cox, Richard D.