UNT Libraries - 102 Matching Results

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SEM Predicting Success of Student Global Software Development Teams
The extensive use of global teams to develop software has prompted researchers to investigate various factors that can enhance a team’s performance. While a significant body of research exists on global software teams, previous research has not fully explored the interrelationships and collective impact of various factors on team performance. This study explored a model that added the characteristics of a team’s culture, ability, communication frequencies, response rates, and linguistic categories to a central framework of team performance. Data was collected from two student software development projects that occurred between teams located in the United States, Panama, and Turkey. The data was obtained through online surveys and recorded postings of team activities that occurred throughout the global software development projects. Partial least squares path modeling (PLS-PM) was chosen as the analytic technique to test the model and identify the most influential factors. Individual factors associated with response rates and linguistic characteristics proved to significantly affect a team’s activity related to grade on the project, group cohesion, and the number of messages received and sent. Moreover, an examination of possible latent homogeneous segments in the model supported the existence of differences among groups based on leadership style. Teams with assigned leaders tended to have stronger relationships between linguistic characteristics and team performance factors, while teams with emergent leaders had stronger. Relationships between response rates and team performance factors. The contributions in this dissertation are three fold. 1) Novel analysis techniques using PLS-PM and clustering, 2) Use of new, quantifiable variables in analyzing team activity, 3) Identification of plausible causal indicators for team performance and analysis of the same.
An Interpreter for the Basic Programming Language
In this thesis, the first chapter provides the general description of this interpreter. The second chapter contains a formal definition of the syntax of BASIC along with an introduction to the semantics. The third chapter contains the design of data structure. The fourth chapter contains the description of algorithms along with stages for testing the interpreter and the design of debug output. The stages and actions-are represented internally to the computer in tabular forms. For statement parsing working syntax equations are established. They serve as standards for the conversion of source statements into object pseudocodes. As the statement is parsed for legal form, pseudocodes for this statement are created. For pseudocode execution, pseudocodes are represented internally to the computer in tabular forms.
Information Storage and Retrieval Systems
This thesis describes the implementation of a general purpose personal information storage and retrieval system. Chapter one contains an introduction to information storage and retrieval. Chapter two contains a description of the features a useful personal information retrieval system should contain. This description forms the basis for the implementation of the personal information storage and retrieval system described in chapter three. The system is implemented in UCSD Pascal on an Apple II microcomputer.
A Design Approach for Digital Computer Peripheral Controllers, Case Study Design and Construction
The purpose of this project was to describe a novel design approach for a digital computer peripheral controller, then design and construct a case study controller. This document consists of three chapters and an appendix. Chapter II presents the design approach chosen; a variation to a design presented by Charles R. Richards in an article published in Electronics magazine. Richards' approach consists of a finite state machine circuitry controlling all the functions of a controller. The variation to Richards' approach consists of considering the various logically independent processes which a controller carries out and assigning control of each process to a separate finite state machine. The appendix contains the documentation of the design and construction of the controller.
A Top-Down Structured Programming Technique for Mini-Computers
This paper reviews numerous theoretical results on control structures and demonstrates their practical examples. This study deals with the design of run-time support routines by using top-down structured programming technique. A number of examples are given as illustration of this method. In conclusion, structured programming has proved to be an important methodology for systematic program design and development.
FORTRAN Optimizations at the Source Code Level
This paper discusses FORTRAN optimizations that the user can perform manually at the source code level to improve object code performance. It makes use of descriptive examples within the text of the paper for explanatory purposes. The paper defines key areas in writing a FORTRAN program and recommends ways to improve efficiency in these areas.
Execution Time Analysis through Software Monitors
The analysis of an executing program and the isolation of critical code has been a problem since the first program was written. This thesis examines the process of program analysis through the use of a software monitoring system. Since there is a trend toward structured languages a subset of PL/I was developed t~o exhibit source statement monitoring and costing techniques. By filtering a PL/W program through a preorocessor which determines the cost of source statements and inserts monitoring code, a post-execution analysis of the program can be obtained. This analysis displays an estimated time cost for each source statements the number of times the statement w3s executed, and the product of these values. Additionally, a bar graph is printed in order to quickly locate very active code.
Generating Machine Code for High-Level Programming Languages
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.
A Computer Algorithm for Synthetic Seismograms
Synthetic seismograms are a computer-generated aid in the search for hydrocarbons. Heretofore the solution has been done by z-transforms. This thesis presents a solution based on the method of finite differences. The resulting algorithm is fast and compact. The method is applied to three variations of the problem, all three are reduced to the same approximating equation, which is shown to be optimal, in that grid refinement does not change it. Two types of algorithms are derived from the equation. The number of obvious multiplications, additions and subtractions of each is analyzed. Critical section of each requires one multiplication, two additions and two subtractions. Four sample synthetic seismograms are shown. Implementation of the new algorithm runs twice as fast as previous computer program.
Defensive Programming
This research explores the concepts of defensive programming as currently defined in the literature. Then these concepts are extended and more explicitly defined. The relationship between defensive programming, as presented in this research, and current programming practices is discussed and several benefits are observed. Defensive programming appears to benefit the entire software life cycle. Four identifiable phases of the software development process are defined, and the relationship between these four phases and defensive programming is shown. In this research, defensive programming is defined as writing programs in such a way that during execution the program itself produces communication allowing the programmer and the user to observe its dynamic states accurately and critically. To accomplish this end, the use of defensive programming snap shots is presented as a software development tool.
A Left-to-Right Parsing Algorithm for THIS Programming Language
The subject of this investigation is a specific set of parsers known as LR parsers. Of primary interest is a LR parsing method developed by DeRemer which specifies a translation method which can be defined by a Deterministic Push-Down Automation (DPDA). The method of investigation was to apply DeRemer's parsing technique to a specific language known as THIS Programming Language (TPL). The syntax of TPL was redefined as state diagrams and these state diagrams were, in turn, encoded into two tables--a State-Action table and a Transition table. The tables were then incorporated into a PL/l adaptation of DeRemer's algorithm and tested against various TPL statements.
Automated Testing of Interactive Systems
Computer systems which interact with human users to collect, update or provide information are growing more complex. Additionally, users are demanding more thorough testing of all computer systems. Because of the complexity and thoroughness required, automation of interactive systems testing is desirable, especially for functional testing. Many currently available testing tools, like program proving, are impractical for testing large systems. The solution presented here is the development of an automated test system which simulates human users. This system incorporates a high-level programming language, ATLIS. ATLIS programs are compiled and interpretively executed. Programs are selected for execution by operator command, and failures are reported to the operator's console. An audit trail of all activity is provided. This solution provides improved efficiency and effectiveness over conventional testing methods.
A Parallel Programming Language
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.
An Adaptive Linearization Method for a Constraint Satisfaction Problem in Semiconductor Device Design Optimization
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.
A C Navigational System
The C Navigational System (CNS) is a proposed programming environment for the C programming language. The introduction covers the major influences of programming environments and the components of a programming environment. The system is designed to support the design, coding and maintenance phases of software development. CNS provides multiple views to both the source and documentation for a programming project. User-defined and system-defined links allow the source and documentation to be hierarchically searched. CNS also creates a history list and function interface for each function in a module. The final chapter compares CNS and several other programming environments (Microscope, Rn, Cedar, PECAN, and Marvel).
Computer Graphics Primitives and the Scan-Line Algorithm
This paper presents the scan-line algorithm which has been implemented on the Lisp Machine. The scan-line algorithm resides beneath a library of primitive software routines which draw more fundamental objects: lines, triangles and rectangles. This routine, implemented in microcode, applies the A(BC)*D approach to word boundary alignments in order to create an extremely fast, efficient, and general purpose drawing primitive. The scan-line algorithm improves on previous methodologies by limiting the number of CPU intensive instructions and by minimizing the number of words referenced. This paper will describe how to draw scan-lines and the constraints imposed upon the scan-line algorithm by the Lisp Machine's hardware and software.
DRVBLD: a UNIX Device Driver Builder
New peripheral devices are being developed at an ever increasing rate. Before such accessories can be used in the UNIX environment (UNIX is a trademark of Bell Laboratories), they must be able to communicate with the operating system. This involves writing a device driver for each device. In order to do this, very detailed knowledge is required of both the device to be integrated and the version of UNIX to which it will be attached. The process is long, detailed and prone to subtle problems and errors. This paper presents a menu-driven utility designed to simplify and accelerate the design and implementation of UNIX device drivers by freeing developers from many of the implementation specific low-level details.
A Neural Network Configuration Compiler Based on the Adaptrode Neuronal Model
A useful compiler has been designed that takes a high level neural network specification and constructs a low level configuration file explicitly specifying all network parameters and connections. The neural network model for which this compiler was designed is the adaptrode neuronal model, and the configuration file created can be used by the Adnet simulation engine to perform network experiments. The specification language is very flexible and provides a general framework from which almost any network wiring configuration may be created. While the compiler was created for the specialized adaptrode model, the wiring specification algorithms could also be used to specify the connections in other types of networks.
The Object-Oriented Database Editor
Because of an interest in object-oriented database systems, designers have created systems to store and manipulate specific sets of abstract data types that belong to the real world environment they represent. Unfortunately, the advantage of these systems is also a disadvantage since no single object-oriented database system can be used for all applications. This paper describes an object-oriented database management system called the Object-oriented Database Editor (ODE) which overcomes this disadvantage by allowing designers to create and execute an object-oriented database that represents any type of environment and then to store it and simulate that environment. As conditions within the environment change, the designer can use ODE to alter that environment without loss of data. ODE provides a flexible environment for the user; it is efficient; and it can run on a personal computer.
Linear Unification
Efficient unification is considered within the context of logic programming. Unification is explained in terms of equivalence classes made up of terms, where there is a constraint that no equivalence class may contain more than one function term. It is demonstrated that several well-known "efficient" but nonlinear unification algorithms continually maintain the said constraint as a consequence of their choice of data structure for representing equivalence classes. The linearity of the Paterson-Wegman unification algorithm is shown largely to be a consequence of its use of unbounded lists of pointers for representing equivalences between terms, which allows it to avoid the nonlinearity of "union-find".
Independent Quadtrees
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 ...
A Graphical, Database-Querying Interface for Casual, Naive Computer Users
This research is concerned with some aspects of the retrieval of information from database systems by casual, naive computer users. A "casual user" is defined as an individual who only wishes to execute queries perhaps once or twice a month, and a "naive user" is someone who has little or no expertise in operating a computer and, more specifically for the purposes of this study, is not practiced at querying a database. The research initially focuses on a specific group of casual, naive users, namely a group of clinicians, and analyzes their characteristics as they pertain to the retrieval of information from a computer database. The characteristics thus elicited are then used to create the requirements for a database interface that would, potentially, be acceptable to this group. An interface having the desired requirements is then proposed. This interface consists, from a user's perspective, of three basic components. A graphical model gives a picture of the database structure. Windows give the ability to view different areas of the database, physically group together items that come under one logical heading and provide the user with immediate access to the data item names used by the system. Finally, a natural language query language provides a means of entering a query in a syntax (that of ordinary English) which is familiar to the user. The graphical model is a logical abstraction of the database. Unlike other database interfaces, it is not constrained by the model (relational, hierarchical, network) underlying the database management system, with the one caveat that the graphical model should not imply any connections which cannot be supported by the management system. Versions of the interface are implemented on both eight-bit and sixteen-bit microcomputers, and testing is conducted in order to validate the acceptability of the interface and to discover the ...
Computer Realization of Human Music Cognition
This study models the human process of music cognition on the digital computer. The definition of music cognition is derived from the work in music cognition done by the researchers Carol Krumhansl and Edward Kessler, and by Mari Jones, as well as from the music theories of Heinrich Schenker. The computer implementation functions in three stages. First, it translates a musical "performance" in the form of MIDI (Musical Instrument Digital Interface) messages into LISP structures. Second, the various parameters of the performance are examined separately a la Jones's joint accent structure, quantified according to psychological findings, and adjusted to a common scale. The findings of Krumhansl and Kessler are used to evaluate the consonance of each note with respect to the key of the piece and with respect to the immediately sounding harmony. This process yields a multidimensional set of points, each of which is a cognitive evaluation of a single musical event within the context of the piece of music within which it occurred. This set of points forms a metric space in multi-dimensional Euclidean space. The third phase of the analysis maps the set of points into a topology-preserving data structure for a Schenkerian-like middleground structural analysis. This process yields a hierarchical stratification of all the musical events (notes) in a piece of music. It has been applied to several pieces of music with surprising results. In each case, the analysis obtained very closely resembles a structural analysis which would be supplied by a human theorist. The results obtained invite us to take another look at the representation of knowledge and perception from another perspective, that of a set of points in a topological space, and to ask if such a representation might not be useful in other domains. It also leads us to ask if such a ...
Semaphore Solutions for General Mutual Exclusion Problems
Automatic generation of starvation-free semaphore solutions to general mutual exclusion problems is discussed. A reduction approach is introduced for recognizing edge-solvable problems, together with an O(N^2) algorithm for graph reduction, where N is the number of nodes. An algorithm for the automatic generation of starvation-free edge-solvable solutions is presented. The solutions are proved to be very efficient. For general problems, there are two ways to generate efficient solutions. One associates a semaphore with every node, the other with every edge. They are both better than the standard monitor—like solutions. Besides strong semaphores, solutions using weak semaphores, weaker semaphores and generalized semaphores are also considered. Basic properties of semaphore solutions are also discussed. Tools describing the dynamic behavior of parallel systems, as well as performance criteria for evaluating semaphore solutions are elaborated.
A Timescale Estimating Model for Rule-Based Systems
The purpose of this study was to explore the subject of timescale estimating for rule-based systems. A model for estimating the timescale necessary to build rule-based systems was built and then tested in a controlled environment.
Inheritance Problems in Object-Oriented Database
This research is concerned with inheritance as used in object-oriented database. More specifically, partial bi-directional inheritance among classes is examined. In partial inheritance, a class can inherit a proper subset of instance variables from another class. Two subclasses of the same superclass do not need to inherit the same proper subset of instance variables from their superclass. Bi-directional partial inheritance allows a class to inherit instance variables from its subclass. The prototype of an object-oriented database that supports both full and partial bi-directional inheritance among classes was developed on top of an existing relational database management system. The prototype was tested with two database applications. One database application needs full and partial inheritance. The second database application required bi-directional inheritance. The result of this testing suggests both advantages and disadvantages of partial bi-directional inheritance. Future areas of research are also suggested.
A Unifying Version Model for Objects and Schema in Object-Oriented Database System
There have been a number of different versioning models proposed. The research in this area can be divided into two categories: object versioning and schema versioning. In this dissertation, both problem domains are considered as a single unit. This dissertation describes a unifying version model (UVM) for maintaining changes to both objects and schema. UVM handles schema versioning operations by using object versioning techniques. The result is that the UVM allows the OODBMS to be much smaller than previous systems. Also, programmers need know only one set of versioning operations; thus, reducing the learning time by half. This dissertation shows that UVM is a simple but semantically sound and powerful version model for both objects and schema.
A Machine Learning Method Suitable for Dynamic Domains
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 ...
Multiresolutional/Fractal Compression of Still and Moving Pictures
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.
Practical Cursive Script Recognition
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.
Convexity-Preserving Scattered Data Interpolation
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.
Exon/Intron Discrimination Using the Finite Induction Pattern Matching Technique
DNA sequence analysis involves precise discrimination of two of the sequence's most important components: exons and introns. Exons encode the proteins that are responsible for almost all the functions in a living organism. Introns interrupt the sequence coding for a protein and must be removed from primary RNA transcripts before translation to protein can occur. A pattern recognition technique called Finite Induction (FI) is utilized to study the language of exons and introns. FI is especially suited for analyzing and classifying large amounts of data representing sequences of interest. It requires no biological information and employs no statistical functions. Finite Induction is applied to the exon and intron components of DNA by building a collection of rules based upon what it finds in the sequences it examines. It then attempts to match the known rule patterns with new rules formed as a result of analyzing a new sequence. A high number of matches predict a probable close relationship between the two sequences; a low number of matches signifies a large amount of difference between the two. This research demonstrates FI to be a viable tool for measurement when known patterns are available for the formation of rule sets.
Automatic Speech Recognition Using Finite Inductive Sequences
This dissertation addresses the general problem of recognition of acoustic signals which may be derived from speech, sonar, or acoustic phenomena. The specific problem of recognizing speech is the main focus of this research. The intention is to design a recognition system for a definite number of discrete words. For this purpose specifically, eight isolated words from the T1MIT database are selected. Four medium length words "greasy," "dark," "wash," and "water" are used. In addition, four short words are considered "she," "had," "in," and "all." The recognition system addresses the following issues: filtering or preprocessing, training, and decision-making. The preprocessing phase uses linear predictive coding of order 12. Following the filtering process, a vector quantization method is used to further reduce the input data and generate a finite inductive sequence of symbols representative of each input signal. The sequences generated by the vector quantization process of the same word are factored, and a single ruling or reference template is generated and stored in a codebook. This system introduces a new modeling technique which relies heavily on the basic concept that all finite sequences are finitely inductive. This technique is used in the training stage. In order to accommodate the variabilities in speech, the training is performed casualty, and a large number of training speakers is used from eight different dialect regions. Hence, a speaker independent recognition system is realized. The matching process compares the incoming speech with each of the templates stored, and a closeness ration is computed. A ratio table is generated anH the matching word that corresponds to the smallest ratio (i.e. indicating that the ruling has removed most of the symbols) is selected. Promising results were obtained for isolated words, and the recognition rates ranged between 50% and 100%.
A Theoretical Network Model and the Incremental Hypercube-Based Networks
The study of multicomputer interconnection networks is an important area of research in parallel processing. We introduce vertex-symmetric Hamming-group graphs as a model to design a wide variety of network topologies including the hypercube network.
Intrinsic and Extrinsic Adaptation in a Simulated Combat Environment
Genetic algorithm and artificial life techniques are applied to the development of challenging and interesting opponents in a combat-based computer game. Computer simulations are carried out against an idealized human player to gather data on the effectiveness of the computer generated opponents.
Computational Complexity of Hopfield Networks
There are three main results in this dissertation. They are PLS-completeness of discrete Hopfield network convergence with eight different restrictions, (degree 3, bipartite and degree 3, 8-neighbor mesh, dual of the knight's graph, hypercube, butterfly, cube-connected cycles and shuffle-exchange), exponential convergence behavior of discrete Hopfield network, and simulation of Turing machines by discrete Hopfield Network.
Efficient Linked List Ranking Algorithms and Parentheses Matching as a New Strategy for Parallel Algorithm Design
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.
Using Normal Deduction Graphs in Common Sense Reasoning
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.
Symplectic Integration of Nonseparable Hamiltonian Systems
Numerical methods are usually necessary in solving Hamiltonian systems since there is often no closed-form solution. By utilizing a general property of Hamiltonians, namely the symplectic property, all of the qualities of the system may be preserved for indefinitely long integration times because all of the integral (Poincare) invariants are conserved. This allows for more reliable results and frequently leads to significantly shorter execution times as compared to conventional methods. The resonant triad Hamiltonian with one degree of freedom will be focused upon for most of the numerical tests because of its difficult nature and, moreover, analytical results exist whereby useful comparisons can be made.
A Programming Language For Concurrent Processing
This thesis is a proposed solution to the problem of including an effective interrupt mechanism in the set of concurrent- processing primitives of a block-structured programming language or system. The proposed solution is presented in the form of a programming language definition and model. The language is called TRIPLE.
Arithmetic Computations and Memory Management Using a Binary Tree Encoding af Natural Numbers
Two applications of a binary tree data type based on a simple pairing function (a bijection between natural numbers and pairs of natural numbers) are explored. First, the tree is used to encode natural numbers, and algorithms that perform basic arithmetic computations are presented along with formal proofs of their correctness. Second, using this "canonical" representation as a base type, algorithms for encoding and decoding additional isomorphic data types of other mathematical constructs (sets, sequences, etc.) are also developed. An experimental application to a memory management system is constructed and explored using these isomorphic types. A practical analysis of this system's runtime complexity and space savings are provided, along with a proof of concept framework for both applications of the binary tree type, in the Java programming language.
Evaluation of MPLS Enabled Networks
Recent developments in the Internet have inspired a wide range of business and consumer applications. The deployment of multimedia-based services has driven the demand for increased and guaranteed bandwidth requirements over the network. The diverse requirements of the wide range of users demand differentiated classes of service and quality assurance. The new technology of Multi-protocol label switching (MPLS) has emerged as a high performance and reliable option to address these challenges apart from the additional features that were not addressed before. This problem in lieu of thesis describes how the new paradigm of MPLS is advantageous over the conventional architecture. The motivation for this paradigm is discussed in the first part, followed by a detailed description of this new architecture. The information flow, the underlying protocols and the MPLS extensions to some of the traditional protocols are then discussed followed by the description of the simulation. The simulation results are used to show the advantages of the proposed technology.
Analysis of Web Services on J2EE Application Servers
The Internet became a standard way of exchanging business data between B2B and B2C applications and with this came the need for providing various services on the web instead of just static text and images. Web services are a new type of services offered via the web that aid in the creation of globally distributed applications. Web services are enhanced e-business applications that are easier to advertise and easier to discover on the Internet because of their flexibility and uniformity. In a real life scenario it is highly difficult to decide which J2EE application server to go for when deploying a enterprise web service. This thesis analyzes the various ways by which web services can be developed & deployed. Underlying protocols and crucial issues like EAI (enterprise application integration), asynchronous messaging, Registry tModel architecture etc have been considered in this research. This paper presents a report by analyzing what various J2EE application servers provide by doing a case study and by developing applications to test functionality.
Hopfield Networks as an Error Correcting Technique for Speech Recognition
I experimented with Hopfield networks in the context of a voice-based, query-answering system. Hopfield networks are used to store and retrieve patterns. I used this technique to store queries represented as natural language sentences and I evaluated the accuracy of the technique for error correction in a spoken question-answering dialog between a computer and a user. I show that the use of an auto-associative Hopfield network helps make the speech recognition system more fault tolerant. I also looked at the available encoding schemes to convert a natural language sentence into a pattern of zeroes and ones that can be stored in the Hopfield network reliably, and I suggest scalable data representations which allow storing a large number of queries.
Modeling the Impact and Intervention of a Sexually Transmitted Disease: Human Papilloma Virus
Many human papilloma virus (HPV) types are sexually transmitted and HPV DNA types 16, 18, 31, and 45 account for more than 75% if all cervical dysplasia. Candidate vaccines are successfully completing US Federal Drug Agency (FDA) phase III testing and several drug companies are in licensing arbitration. Once this vaccine become available it is unlikely that 100% vaccination coverage will be probable; hence, the need for vaccination strategies that will have the greatest reduction on the endemic prevalence of HPV. This thesis introduces two discrete-time models for evaluating the effect of demographic-biased vaccination strategies: one model incorporates temporal demographics (i.e., age) in population compartments; the other non-temporal demographics (i.e., race, ethnicity). Also presented is an intuitive Web-based interface that was developed to allow the user to evaluate the effects on prevalence of a demographic-biased intervention by tailoring the model parameters to specific demographics and geographical region.
A general purpose semantic parser using FrameNet and WordNet®.
Syntactic parsing is one of the best understood language processing applications. Since language and grammar have been formally defined, it is easy for computers to parse the syntactic structure of natural language text. Does meaning have structure as well? If it has, how can we analyze the structure? Previous systems rely on a one-to-one correspondence between syntactic rules and semantic rules. But such systems can only be applied to limited fragments of English. In this thesis, we propose a general-purpose shallow semantic parser which utilizes a semantic network (WordNet), and a frame dataset (FrameNet). Semantic relations recognized by the parser are based on how human beings represent knowledge of the world. Parsing semantic structure allows semantic units and constituents to be accessed and processed in a more meaningful way than syntactic parsing, moving the automation of understanding natural language text to a higher level.
Impact of actual interference on capacity and call admission control in a CDMA network.
An overwhelming number of models in the literature use average inter-cell interference for the calculation of capacity of a Code Division Multiple Access (CDMA) network. The advantage gained in terms of simplicity by using such models comes at the cost of rendering the exact location of a user within a cell irrelevant. We calculate the actual per-user interference and analyze the effect of user-distribution within a cell on the capacity of a CDMA network. We show that even though the capacity obtained using average interference is a good approximation to the capacity calculated using actual interference for a uniform user distribution, the deviation can be tremendously large for non-uniform user distributions. Call admission control (CAC) algorithms are responsible for efficient management of a network's resources while guaranteeing the quality of service and grade of service, i.e., accepting the maximum number of calls without affecting the quality of service of calls already present in the network. We design and implement global and local CAC algorithms, and through simulations compare their network throughput and blocking probabilities for varying mobility scenarios. We show that even though our global CAC is better at resource management, the lack of substantial gain in network throughput and exponential increase in complexity makes our optimized local CAC algorithm a much better choice for a given traffic distribution profile.
Performance comparison of data distribution management strategies in large-scale distributed simulation.
Data distribution management (DDM) is a High Level Architecture/Run-time Infrastructure (HLA/RTI) service that manages the distribution of state updates and interaction information in large-scale distributed simulations. The key to efficient DDM is to limit and control the volume of data exchanged during the simulation, to relay data to only those hosts requiring the data. This thesis focuses upon different DDM implementations and strategies. This thesis includes analysis of three DDM methods including the fixed grid-based, dynamic grid-based, and region-based methods. Also included is the use of multi-resolution modeling with various DDM strategies and analysis of the performance effects of aggregation/disaggregation with these strategies. Running numerous federation executions, I simulate four different scenarios on a cluster of workstations with a mini-RTI Kit framework and propose a set of benchmarks for a comparison of the DDM schemes. The goals of this work are to determine the most efficient model for applying each DDM scheme, discover the limitations of the scalability of the various DDM methods, evaluate the effects of aggregation/disaggregation on performance and resource usage, and present accepted benchmarks for use in future research.
An Analysis of Motivational Cues in Virtual Environments.
Guiding navigation in virtual environments (VEs) is a challenging task. A key issue in the navigation of a virtual environment is to be able to strike a balance between the user's need to explore the environment freely and the designer's need to ensure that the user experiences all the important events in the VE. This thesis reports on a study aimed at comparing the effectiveness of various navigation cues that are used to motivate users towards a specific target location. The results of this study indicate some significant differences in how users responded to the various cues.
Improved Approximation Algorithms for Geometric Packing Problems With Experimental Evaluation
Geometric packing problems are NP-complete problems that arise in VLSI design. In this thesis, we present two novel algorithms using dynamic programming to compute exactly the maximum number of k x k squares of unit size that can be packed without overlap into a given n x m grid. The first algorithm was implemented and ran successfully on problems of large input up to 1,000,000 nodes for different values. A heuristic based on the second algorithm is implemented. This heuristic is fast in practice, but may not always be giving optimal times in theory. However, over a wide range of random data this version of the algorithm is giving very good solutions very fast and runs on problems of up to 100,000,000 nodes in a grid and different ranges for the variables. It is also shown that this version of algorithm is clearly superior to the first algorithm and has shown to be very efficient in practice.