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.

Discrete event simulation is an important tool for modeling and analysis. Some of the simulation applications such as telecommunication network performance, VLSI logic circuits design, battlefield simulation, require enormous amount of computing resources. One way to satisfy this demand for computing power is to decompose the simulation system into several logical processes (Ip) and run them concurrently. In any parallel discrete event simulation (PDES) system, the events are ordered according to their time of occurrence. In order for the simulation to be correct, this ordering has to be preserved. There are three approaches to maintain this ordering. In a conservative system, no lp executes an event unless it is certain that all events with earlier time-stamps have been executed. Such systems are prone to deadlock. In an optimistic system on the other hand, simulation progresses disregarding this ordering and saves the system states regularly. Whenever a causality violation is detected, the system rolls back to a state saved earlier and restarts processing after correcting the error. There is another approach in which all the lps participate in the computation of a safe time-window and all events with time-stamps within this window are processed concurrently. In optimistic simulation systems, there is …

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 …

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.

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.

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.

We extend the Jinni mobile agent architecture with a multicast network transport layer, an agent-to-agent delegation mechanism and a reflection based Prolog-to-Java interface. To ensure that our agent infrastructure runs efficiently, independently of router-level multicast support, we describe a blackboard based algorithm for locating a randomly roaming agent. As part of the agent-to-agent delegation mechanism, we describe an alternative to code-fetching mechanism for stronger mobility of mobile agents with less network overhead. In the context of direct and reflection based extension mechanisms for Jinni, we describe the design and the implementation of a reflection based Prolog-to-Java interface. The presence of subtyping and method overloading makes finding the most specific method corresponding to a Prolog call pattern fairly difficult. We describe a run-time algorithm which provides accurate handling of overloaded methods beyond Java's reflection package's limitations.

In this research, the application of intelligent mobile agents to the management of distributed network environments is investigated. Intelligent mobile agents are programs which can move about network systems in a deterministic manner in carrying their execution state. These agents can be considered an application of distributed artificial intelligence where the (usually small) agent code is moved to the data and executed locally. The mobile agent paradigm offers potential advantages over many conventional mechanisms which move (often large) data to the code, thereby wasting available network bandwidth. The performance of agents in network routing and knowledge acquisition has been investigated and simulated. A working mobile agent system has also been designed and implemented in JDK 1.2.

Many activities are comprised of temporally dependent events that must be executed in a specific chronological order. Supportive software applications must preserve these temporal dependencies. Whenever the processing of this type of an application includes transactions submitted to a database that is shared with other such applications, the transaction concurrency control mechanisms within the database must also preserve the temporal dependencies. A basis for preserving temporal dependencies is established by using (within the applications and databases) real-time timestamps to identify and order events and transactions. The use of optimistic approaches to transaction concurrency control can be undesirable in such situations, as they allow incorrect results for database read operations. Although the incorrectness is detected prior to transaction committal and the corresponding transaction(s) restarted, the impact on the application or entity that submitted the transaction can be too costly. Three transaction concurrency control algorithms are proposed in this dissertation. These algorithms are based on timestamp ordering, and are designed to preserve temporal dependencies existing among data-dependent transactions. The algorithms produce execution schedules that are equivalent to temporally ordered serial schedules, where the temporal order is established by the transactions' start times. The algorithms provide this equivalence while supporting currency to the …

Distributed simulation is an enabling concept to support the networked interaction of models and real world elements that are geographically distributed. This technology has brought a new set of challenging problems to solve, such as Data Distribution Management (DDM). The aim of DDM is to limit and control the volume of the data exchanged during a distributed simulation, and reduce the processing requirements of the simulation hosts by relaying events and state information only to those applications that require them. In this thesis, we propose a new DDM scheme, which we refer to as dynamic grid-based DDM. A lightweight UNT-RTI has been developed and implemented to investigate the performance of our DDM scheme. Our results clearly indicate that our scheme is scalable and it significantly reduces both the number of multicast groups used, and the message overhead, when compared to previous grid-based allocation schemes using large-scale and real-world scenarios.

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.

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.

How do the content and writing style of people who drink alcohol beverages stand out from non-drinkers? How much information can we learn about a person's alcohol consumption behavior by reading text that they have authored? This thesis attempts to extend the methods deployed in authorship attribution and authorship profiling research into the domain of automatically identifying the human action of drinking alcohol beverages. I examine how a psycholinguistics dictionary (the Linguistics Inquiry and Word Count lexicon, developed by James Pennebaker), together with Kenneth Burke's concept of words as symbols of human action, and James Wertsch's concept of mediated action provide a framework for analyzing meaningful data patterns from the content of blogs written by consumers of alcohol beverages. The contributions of this thesis to the research field are twofold. First, I show that it is possible to automatically identify blog posts that have content related to the consumption of alcohol beverages. And second, I provide a framework and tools to model human behavior through text analysis of blog data.

Computational modeling is of fundamental significance in mapping possible disease spread, and designing strategies for its mitigation. Conventional contact networks implement the simulation of interactions as random occurrences, presenting public health bodies with a difficult trade off between a realistic model granularity and robust design of intervention strategies. Recently, researchers have been investigating the use of agent-based models (ABMs) to embrace the complexity of real world interactions. At the same time, theoretical approaches provide epidemiologists with general optimization models in which demographics are intrinsically simplified. The emerging study of affiliation networks and co-affiliation networks provide an alternative to such trade off. Co-affiliation networks maintain the realism innate to ABMs while reducing the complexity of contact networks into distinctively smaller k-partite graphs, were each partition represent a dimension of the social model. This dissertation studies the optimization of intervention strategies for infectious diseases, mainly distributed in school systems. First, concepts of synthetic populations and affiliation networks are extended to propose a modified algorithm for the synthetic reconstruction of populations. Second, the definition of multi-coaffiliation networks is presented as the main social model in which risk is quantified and evaluated, thereby obtaining vulnerability indications for each school in the system. Finally, maximization …

Burrows-Wheeler compression is a three stage process in which the data is transformed with the Burrows-Wheeler Transform, then transformed with Move-To-Front, and finally encoded with an entropy coder. Move-To-Front, Transpose, and Frequency Count are some of the many algorithms used on the List Update problem. In 1985, Competitive Analysis first showed the superiority of Move-To-Front over Transpose and Frequency Count for the List Update problem with arbitrary data. Earlier studies due to Bitner assumed independent identically distributed data, and showed that while Move-To-Front adapts to a distribution faster, incurring less overwork, the asymptotic costs of Frequency Count and Transpose are less. The improvements to Burrows-Wheeler compression this work covers are increases in the amount, not speed, of compression. Best x of 2x-1 is a new family of algorithms created to improve on Move-To-Front's processing of the output of the Burrows-Wheeler Transform which is like piecewise independent identically distributed data. Other algorithms for both the middle stage of Burrows-Wheeler compression and the List Update problem for which overwork, asymptotic cost, and competitive ratios are also analyzed are several variations of Move One From Front and part of the randomized algorithm Timestamp. The Best x of 2x - 1 family includes Move-To-Front, …

As Virtual Environments (VE) become a more commonly used method of interaction and presentation, supporting users as they navigate and interact with scenarios presented in VE will be a significant issue. A key step in understanding the needs of users in these situations will be observing them perform representative tasks in a fully developed environment. In this paper, we describe the development of a test bed for interactive narrative in a virtual environment. The test bed was specifically developed to present multiple, simultaneous sequences of events (scenarios or narratives) and to support user navigation through these scenarios. These capabilities will support the development of multiple users testing scenarios, allowing us to study and better understand the needs of users of narrative VEs.

A large number of applications like multi-player games, video conferencing, chat groups and network management are presently based on multicast communication. As the group communication model is being deployed for mainstream use, it is critical to provide security mechanisms that facilitate confidentiality, authenticity and integrity in group communications. Providing security in multicast communication requires addressing the problem of scalability in group key distribution. Scalability is a concern in group communication due to group membership dynamics. Joining and leaving of members requires the distribution of a new session key to all the existing members of the group. The two approaches to key management namely centralized and distributed approaches are reviewed. A hybrid solution is then provided, which represents a improved scalable and robust approach for a secure multicast framework. This framework then is implemented in an example application of a multicast news service.

The widely used mobile phone, as well as its related technologies had opened opportunities for a complete change on how people interact and build relationship across geographic and time considerations. The convenience of instant communication by mobile phones that broke the barrier of space and time is evidently the key motivational point on why such technologies so important in people's life and daily activities. Mobile phones have become the most popular communication tools. Mobile phone technology is apparently changing our relationship to each other in our work and lives. The impact of new technologies on people's lives in social spaces gives us the chance to rethink the possibilities of technologies in social interaction. Accordingly, mobile phones are basically changing social relations in ways that are intricate to measure with any precision. In this dissertation I propose a socioscope model for social network, relationship and human behavior analysis based on mobile phone call detail records. Because of the diversities and complexities of human social behavior, one technique cannot detect different features of human social behaviors. Therefore I use multiple probability and statistical methods for quantifying social groups, relationships and communication patterns, for predicting social tie strengths and for detecting human behavior …

Researchers have speculated that global software teams have activity patterns that are dictated by work-place schedules or a client's need. Similar patterns have been suggested for individuals enrolled in distant learning projects that require students to post feedback in response to questions or assignments. Researchers tend to accept the notion that students' temporal patterns adjust to academic or social calendars and are a result of choices made within these constraints. Although there is some evidence that culture do have an impact on communication activity behavior, there is not a clear how each of these factors may relate to work done in online groups. This particular study represents a new approach to studying student-group communication activities and also pursues an alternative approach by using activity data from students participating in a global software development project to generate a variety of complex measures that capture patterns about when students work. Students work habits are also often determined by where they live and what they are working on. Moreover, students tend to work on group projects in cycles, which correspond to a start, middle, and end time period. Knowledge obtained from this study should provide insight into current empirical research on global software …

Resources are said to be fragmented in the network when they are available in non-contiguous blocks, and calls are dropped as they may not end sufficient resources. Hence, available resources may remain unutilized. In this thesis, the effect of resource fragmentation (RF) on RSVP-controlled networks was studied and new algorithms were proposed to reduce the effect of RF. In order to minimize the effect of RF, resources in the network are dynamically redistributed on different paths to make them available in contiguous blocks. Extra protocol messages are introduced to facilitate resource redistribution in the network. The Dynamic Resource Redistribution (DRR) algorithm when used in conjunction with RSVP, not only increased the number of calls accommodated into the network but also increased the overall resource utilization of the network. Issues such as how many resources need to be redistributed and of which call(s), and how these choices affect the redistribution process were investigated. Further, various simulation experiments were conducted to study the performance of the DRR algorithm on different network topologies with varying traffic characteristics.

Speech sounds generated by a simple waveform synthesizer were used to create a vector quantization codebook for use in speech recognition. Recognition was tested over the TI-20 isolated word data base using a conventional DTW matching algorithm. Input speech was band limited to 300 - 3300 Hz, then passed through the Scott Instruments Corp. Coretechs process, implemented on a VET3 speech terminal, to create the speech representation for matching. Synthesized sounds were processed in software by a VET3 signal processing emulation program. Emulation and recognition were performed on a DEC VAX 11/750. The experiments were organized in 2 series. A preliminary experiment, using no vector quantization, provided a baseline for comparison. The original codebook contained 109 vectors, all derived from 2 formant synthesized sounds. This codebook was decimated through the course of the first series of experiments, based on the number of times each vector was used in quantizing the training data for the previous experiment, in order to determine the smallest subset of vectors suitable for coding the speech data base. The second series of experiments altered several test conditions in order to evaluate the applicability of the minimal synthesized codebook to conventional codebook training. The baseline recognition rate …

Mobile agent technology presents an attractive alternative to the client-server paradigm for several network and real-time applications. However, for most applications, the lack of a viable agent security model has limited the adoption of the agent paradigm. This thesis presents a security model for mobile agents based on a security infrastructure for Computational Grids, and specifically, on X.509 Proxy Certificates. Proxy Certificates serve as credentials for Grid applications, and their primary purpose is temporary delegation of authority. Exploiting the similarity between Grid applications and mobile agent applications, this thesis motivates the use of Proxy Certificates as credentials for mobile agents. A new extension for Proxy Certificates is proposed in order to make them suited to mobile agent applications, and mechanisms are presented for agent-to-host authentication, restriction of agent privileges, and secure delegation of authority during spawning of new agents. Finally, the implementation of the proposed security mechanisms as modules within a multi-lingual and modular agent infrastructure, the Distributed Agent Delivery System, is discussed.

The presence of naturally occurring and man-made public health threats necessitate the design and implementation of mitigation strategies, such that adequate response is provided in a timely manner. Since multiple variables, such as geographic properties, resource constraints, and government mandated time-frames must be accounted for, computational methods provide the necessary tools to develop contingency response plans while respecting underlying data and assumptions. A typical response scenario involves the placement of points of dispensing (PODs) in the affected geographic region to supply vaccines or medications to the general public. Computational tools aid in the analysis of such response plans, as well as in the strategic placement of PODs, such that feasible response scenarios can be developed. Due to the sensitivity of bio-emergency response plans, geographic information, such as POD locations, must be kept confidential. The generation of synthetic geographic regions allows for the development of emergency response plans on non-sensitive data, as well as for the study of the effects of single geographic parameters. Further, synthetic representations of geographic regions allow for results to be published and evaluated by the scientific community. This dissertation presents methodology for the analysis of bio-emergency response plans, methods for plan optimization, as well as methodology …

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.