Globally distributed software teams are widespread throughout industry. But finding reliable methods that can properly assess a team's activities is a real challenge. Methods such as surveys and manual coding of activities are too time consuming and are often unreliable. Recent advances in information retrieval and linguistics, however, suggest that automated and/or semi-automated text classification algorithms could be an effective way of finding differences in the communication patterns among individuals and groups. Communication among group members is frequent and generates a significant amount of data. Thus having a web-based tool that can automatically analyze the communication patterns among global software teams could lead to a better understanding of group performance. The goal of this thesis, therefore, is to compare automatic and semi-automatic measures of communication and evaluate their effectiveness in classifying different types of group activities that occur within a global software development project. In order to achieve this goal, we developed a web-based component that can be used to help clean and classify communication activities. The component was then used to compare different automated text classification techniques on various group activities to determine their effectiveness in correctly classifying data from a global software development team project.

This investigation dealt with locating and measuring x-ray absorption of radiographic images. The methods developed provide a fast, accurate, minicomputer control, for analysis of embedded objects. A PDP/8 computer system was interfaced with a Joyce Loebl 3CS Microdensitometer and a Leeds & Northrup Recorder. Proposed algorithms for bone location and data smoothing work on a twelve-bit minicomputer. Designs of a software control program and operational procedure are presented. The filter made wedge and limb scans monotonic from minima to maxima. It was tested for various convoluted intervals. Ability to resmooth the same data in multiple passes was tested. An interval size of fifteen works well in one pass.

Emergency Medical Dispatch Protocols are guidelines that a 9-1-1 dispatcher uses to evaluate the nature of emergency, resources to send and the nature of help provided to the 9-1-1 caller. The current Dispatch Protocols are based on voice only call. But the Next Generation 9-1-1 (NG9-1-1) architecture will allow multimedia emergency calls. In this thesis I analyze and model the Emergency Medical Dispatch Protocols for NG9-1-1 architecture. I have identified various technical aspects to improve the NG9-1-1 Dispatch Protocols. The devices (smartphone) at the caller end have advanced to a point where they can be used to send and receive video, pictures and text. There are sensors embedded in them that can be used for initial diagnosis of the injured person. There is a need to improve the human computer (smartphone) interface to take advantage of technology so that callers can easily make use of various features available to them. The dispatchers at the 9-1-1 call center can make use of these new protocols to improve the quality and the response time. They will have capability of multiple media streams to interact with the caller and the first responders.The specific contributions in this thesis include developing applications that use smartphone …

While pragmatics, through its integration of situational awareness and real world relevant knowledge, offers a high level of analysis that is suitable for real interpretation of natural dialogue, semantics, on the other end, represents a lower yet more tractable and affordable linguistic level of analysis using current technologies. Generally, the understanding of semantic meaning in literature has revolved around the famous quote ``You shall know a word by the company it keeps''. In this thesis we investigate the role of context constituents in decoding the semantic meaning of the engulfing context; specifically we probe the role of salient concepts, defined as content-bearing expressions which afford encyclopedic definitions, as a suitable source of semantic clues to an unambiguous interpretation of context. Furthermore, we integrate this world knowledge in building a new and robust unsupervised semantic model and apply it to entail semantic relatedness between textual pairs, whether they are words, sentences or paragraphs. Moreover, we explore the abstraction of semantics across languages and utilize our findings into building a novel multi-lingual semantic relatedness model exploiting information acquired from various languages. We demonstrate the effectiveness and the superiority of our mono-lingual and multi-lingual models through a comprehensive set of evaluations on specialized …

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.

This thesis describes a software implementation of the IEEE Floating-Point Standard (IEEE Task P754), which is believed to be an effective system for reliable, accurate computer arithmetic. The standard is implemented as a set of procedures written in Motorola 6809 assembly language. Source listings of the procedures are contained in appendices.

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 …

The author's primary goal is to begin research leading ot the attainment of a low cost computer/music system which will allow the composer to write polyphonic music of up to eight voices into a computer through a terminal, and have the music played back by means of computer synthesized sound or by means of a conventional synthesizer controlled by a computer via digital-to-analog converters. The goal system will allow the composer to retreat and hear his product objectively as the painter steps back to review his canvas.

Email connects 85% of the world. This paper explores the pattern of information overload encountered by majority of email users and examine what steps key email providers are taking to combat the problem. Besides fighting spam, popular email providers offer very limited tools to reduce the amount of unwanted incoming email. Rather, there has been a trend to expand storage space and aid the organization of email. Storing email is very costly and harmful to the environment. Additionally, information overload can be detrimental to productivity. We propose a simple solution that results in drastic reduction of unwanted mail, also known as graymail.

Trusted Computing capability has become ubiquitous these days, and it is being widely deployed into consumer devices as well as enterprise platforms. As the number of threats is increasing at an exponential rate, it is becoming a daunting task to secure the systems against them. In this context, the software integrity measurement at runtime with the support of trusted platforms can be a better security strategy. Trusted Computing devices like TPM secure the evidence of a breach or an attack. These devices remain tamper proof if the hardware platform is physically secured. This type of trusted security is crucial for forensic analysis in the aftermath of a breach. The advantages of trusted platforms can be further leveraged if they can be used wisely. RADIUM (Race-free on-demand Integrity Measurement Architecture) is one such architecture, which is built on the strength of TPM. RADIUM provides an asynchronous root of trust to overcome the TOC condition of DRTM. Even though the underlying architecture is trusted, attacks can still compromise applications during runtime by exploiting their vulnerabilities. I propose an application-level integrity measurement solution that fits into RADIUM, to expand the trusted computing capability to the application layer. This is based on the concept …

This project focuses on a prototype system architecture which integrates features of an event-driven gate-level simulator and features of the multiple expert system architecture, HEARSAY-II. Combining artificial intelligence and simulation techniques, a knowledge-based simulator was designed and constructed to model non-standard circuit behavior. This non-standard circuit behavior is amplified by advances in integrated circuit technology. Currently available digital circuit simulators can not simulate this behavior. Circuit designer expertise on behavioral phenomena is used in the expert system to guide the base simulator by manipulating its events to achieve the desired behavior.

Ambiguity is inherent to human language. In particular, word sense ambiguity is prevalent in all natural languages, with a large number of the words in any given language carrying more than one meaning. Word sense disambiguation is the task of automatically assigning the most appropriate meaning to a polysemous word within a given context. Generally the problem of resolving ambiguity in literature has revolved around the famous quote “you shall know the meaning of the word by the company it keeps.” In this thesis, we investigate the role of context for resolving ambiguity through three different approaches. Instead of using a predefined monolingual sense inventory such as WordNet, we use a language-independent framework where the word senses and sense-tagged data are derived automatically from Wikipedia. Using Wikipedia as a source of sense-annotations provides the much needed solution for knowledge acquisition bottleneck. In order to evaluate the viability of Wikipedia based sense-annotations, we cast the task of disambiguating polysemous nouns as a monolingual classification task and experimented on lexical samples from four different languages (viz. English, German, Italian and Spanish). The experiments confirm that the Wikipedia based sense annotations are reliable and can be used to construct accurate monolingual sense classifiers. …

The physical limitations of uniprocessors and the real-time requirements of numerous practical applications have made parallel processing an essential technology in military, industry and scientific research. In this dissertation, we investigate parallelizations of three practical applications using three parallel machine models. The algorithms are: Finitely inductive (FI) sequence processing is a pattern recognition technique used in many fields. We first propose four parallel FI algorithms on the EREW PRAM. The time complexity of the parallel factoring and following by bucket packing is O(sk^2 n/p), and they are optimal under some conditions. The parallel factoring and following by hashing requires O(sk^2 n/p) time when uniform hash functions are used and log(p) ≤ k n/p and pm ≈ n. Their speedup is proportional to the number processors used. For these results, s is the number of levels, k is the size of the antecedents and n is the length of the input sequence and p is the number of processors. We also describe algorithms for raster/vector conversion based on the scan model to handle block-like connected components of arbitrary geometrical shapes with multi-level nested dough nuts for the IES (image exploitation system). Both the parallel raster-to-vector algorithm and parallel vector-to-raster algorithm require …

In this thesis, a framework for Quality of Service provisioning in next generation wireless access networks is proposed. The framework aims at providing a differentiated service treatment to real-time (delay-sensitive) and non-real-time (delay-tolerant) multimedia traffic flows at the link layer. Novel techniques such as bandwidth compaction, channel reservation, and channel degradation are proposed. Using these techniques, we develop a call admission control algorithm and a call control block as part of the QoS framework. The performance of the framework is captured through analytical modeling and simulation experiments. By analytical modeling, the average carried traffic and the worst case buffer requirements for real-time and non-real-time calls are estimated. Simulation results show a 21% improvement in call admission probability of real-time calls, and a 17% improvement for non-real-time calls, when bandwidth compaction is employed. The channel reservation technique shows a 12% improvement in call admission probability in comparison with another proposed scheme in the literature.

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 …

Many infectious diseases are spread through interactions between susceptible and infectious individuals. Keeping track of where each exposure to the disease took place, when it took place, and which individuals were involved in the exposure can give public health officials important information that they may use to formulate their interventions. Further, knowing which individuals in the population are at the highest risk of becoming infected with the disease may prove to be a useful tool for public health officials trying to curtail the spread of the disease. Epidemiological models are needed to allow epidemiologists to study the population dynamics of transmission of infectious agents and the potential impact of infectious disease control programs. While many agent-based computational epidemiological models exist in the literature, they focus on the spread of disease rather than exposure risk. These models are designed to simulate very large populations, representing individuals as agents, and using random experiments and probabilities in an attempt to more realistically guide the course of the modeled disease outbreak. The work presented in this thesis focuses on tracking exposure risk to chickenpox in an elementary school setting. This setting is chosen due to the high level of detailed information realistically available to …

Software applications’ performance is hindered by a variety of factors, but most notably by the well-known CPU-memory speed gap (often known as the memory wall). This results in the CPU sitting idle waiting for data to be brought from memory to processor caches. The addressing used by caches cause non-uniform accesses to various cache sets. The non-uniformity is due to several reasons, including how different objects are accessed by the code and how the data objects are located in memory. Memory allocators determine where dynamically created objects are placed, thus defining addresses and their mapping to cache locations. It is important to evaluate how different allocators behave with respect to the localities of the created objects. Most allocators use a single attribute, the size, of an object in making allocation decisions. Additional attributes such as the placement with respect to other objects, or specific cache area may lead to better use of cache memories. In this dissertation, we proposed and implemented a framework that allows for the development and evaluation of new memory allocation techniques. At the root of the framework is a memory tracing tool called Gleipnir, which provides very detailed information about every memory access, and relates it …

Susceptibles-infectives-removals (SIR) and its derivatives are the classic mathematical models for the study of infectious diseases in epidemiology. In order to model and simulate epidemics of an infectious disease, a global stochastic field simulation paradigm (GSFS) is proposed, which incorporates geographic and demographic based interactions. The interaction measure between regions is a function of population density and geographical distance, and has been extended to include demographic and migratory constraints. The progression of diseases using GSFS is analyzed, and similar behavior to the SIR model is exhibited by GSFS, using the geographic information systems (GIS) gravity model for interactions. The limitations of the SIR and similar models of homogeneous population with uniform mixing are addressed by the GSFS model. The GSFS model is oriented to heterogeneous population, and can incorporate interactions based on geography, demography, environment and migration patterns. The progression of diseases can be modeled at higher levels of fidelity using the GSFS model, and facilitates optimal deployment of public health resources for prevention, control and surveillance of infectious diseases.

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.

The basis of today’s security systems is the trust and confidence that the system will behave as expected and are in a known good trusted state. The trust is built from hardware and software elements that generates a chain of trust that originates from a trusted known entity. Leveraging hardware, software and a mandatory access control policy technology is needed to create a trusted measurement environment. Employing a control layer (hypervisor or microkernel) with the ability to enforce a fine grained access control policy with hyper call granularity across multiple guest virtual domains can ensure that any malicious environment to be contained. In my research, I propose the use of radium's Asynchronous Root of Trust Measurement (ARTM) capability incorporated with a secure mandatory access control policy engine that would mitigate the limitations of the current hardware TPM solutions. By employing ARTM we can leverage asynchronous use of boot, launch, and use with the hypervisor proving its state and the integrity of the secure policy. My solution is using Radium (Race free on demand integrity architecture) architecture that will allow a more detailed measurement of applications at run time with greater semantic knowledge of the measured environments. Radium incorporation of a …

Network security is a complex field that is handled by security professionals who need certain expertise and experience to configure security systems. With the ever increasing size of the networks, managing them is going to be a daunting task. What kind of solution can be used to generate effective security configurations by both security professionals and nonprofessionals alike? In this thesis, a web tool is developed to simplify the process of configuring security systems by translating direct human language input into meaningful, working security rules. These human language inputs yield the security rules that the individual wants to implement in their network. The human language input can be as simple as, "Block Facebook to my son's PC". This tool will translate these inputs into specific security rules and install the translated rules into security equipment such as virtualized Cisco FWSM network firewall, Netfilter host-based firewall, and Snort Network Intrusion Detection. This tool is implemented and tested in both a traditional network and a cloud environment. One thousand input policies were collected from various users such as staff from UNT departments' and health science, including individuals with network security background as well as students with a non-computer science background to analyze …

One in seven people in the world use online social networking for a variety of purposes -- to keep in touch with friends and family, to share special occasions, to broadcast announcements, and more. The majority of society has been bought into this new era of communication technology, which allows everyone on the internet to share information with friends. Since social networking has rapidly become a main form of communication, holes in privacy have become apparent. It has come to the point that the whole concept of sharing information requires restructuring. No longer are online social networks simply technology available for a niche market; they are in use by all of society. Thus it is important to not forget that a sense of privacy is inherent as an evolutionary by-product of social intelligence. In any context of society, privacy needs to be a part of the system in order to help users protect themselves from others. This dissertation attempts to address the lack of privacy management in online social networks by designing models which understand the social science behind how we form social groups and share information with each other. Social relationship strength was modeled using activity patterns, vocabulary usage, …