UNT Libraries - 291 Matching Results

Search Results

prev Results: 101 - 150 next
Modeling and Analysis of Next Generation 9-1-1 Emergency Medical Dispatch Protocols
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 sensors. The CPR application uses the smartphone to help administer effective CPR even if the person is not trained. The application makes the CPR process closed loop, i.e., the person who administers the CPR as well as the 9-1-1 operator receive feedback and prompt from the application about the correctness of the CPR. The breathing application analyzes the quality of breathing of the affected person and automatically sends the information to the 9-1-1 operator. In order to improve the Human Computer Interface at the caller and the operator end, I have analyzed Fitts law and extended it so that it …
The Design and Implementation of a Prolog Parser Using Javacc
Operatorless Prolog text is LL(1) in nature and any standard LL parser generator tool can be used to parse it. However, the Prolog text that conforms to the ISO Prolog standard allows the definition of dynamic operators. Since Prolog operators can be defined at run-time, operator symbols are not present in the grammar rules of the language. Unless the parser generator allows for some flexibility in the specification of the grammar rules, it is very difficult to generate a parser for such text. In this thesis we discuss the existing parsing methods and their modified versions to parse languages with dynamic operator capabilities. Implementation details of a parser using Javacc as a parser generator tool to parse standard Prolog text is provided. The output of the parser is an “Abstract Syntax Tree” that reflects the correct precedence and associativity rules among the various operators (static and dynamic) of the language. Empirical results are provided that show that a Prolog parser that is generated by the parser generator like Javacc is comparable in efficiency to a hand-coded parser.
A Comparative Analysis of Guided vs. Query-Based Intelligent Tutoring Systems (ITS) Using a Class-Entity-Relationship-Attribute (CERA) Knowledge Base
One of the greatest problems facing researchers in the sub field of Artificial Intelligence known as Intelligent Tutoring Systems (ITS) is the selection of a knowledge base designs that will facilitate the modification of the knowledge base. The Class-Entity-Relationship-Attribute (CERA), proposed by R. P. Brazile, holds certain promise as a more generic knowledge base design framework upon which can be built robust and efficient ITS. This study has a twofold purpose. The first is to demonstrate that a CERA knowledge base can be constructed for an ITS on a subset of the domain of Cretaceous paleontology and function as the "expert module" of the ITS. The second is to test the validity of the ideas that students guided through a lesson learn more factual knowledge, while those who explore the knowledge base that underlies the lesson through query at their own pace will be able to formulate their own integrative knowledge from the knowledge gained in their explorations and spend more time on the system. This study concludes that a CERA-based system can be constructed as an effective teaching tool. However, while an ITS - treatment provides for statistically significant gains in achievement test scores, the type of treatment seems not to matter as much as time spent on task. This would seem to indicate that a query-based system which allows the user to progress at their own pace would be a better type of system for the presentation of material due to the greater amount of on-line computer time exhibited by the users.
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.
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).
General Purpose Computing in Gpu - a Watermarking Case Study
The purpose of this project is to explore the GPU for general purpose computing. The GPU is a massively parallel computing device that has a high-throughput, exhibits high arithmetic intensity, has a large market presence, and with the increasing computation power being added to it each year through innovations, the GPU is a perfect candidate to complement the CPU in performing computations. The GPU follows the single instruction multiple data (SIMD) model for applying operations on its data. This model allows the GPU to be very useful for assisting the CPU in performing computations on data that is highly parallel in nature. The compute unified device architecture (CUDA) is a parallel computing and programming platform for NVIDIA GPUs. The main focus of this project is to show the power, speed, and performance of a CUDA-enabled GPU for digital video watermark insertion in the H.264 video compression domain. Digital video watermarking in general is a highly computationally intensive process that is strongly dependent on the video compression format in place. The H.264/MPEG-4 AVC video compression format has high compression efficiency at the expense of having high computational complexity and leaving little room for an imperceptible watermark to be inserted. Employing a human visual model to limit distortion and degradation of visual quality introduced by the watermark is a good choice for designing a video watermarking algorithm though this does introduce more computational complexity to the algorithm. Research is being conducted into how the CPU-GPU execution of the digital watermark application can boost the speed of the applications several times compared to running the application on a standalone CPU using NVIDIA visual profiler to optimize the application.
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.
A Netcentric Scientific Research Repository
The Internet and networks in general have become essential tools for disseminating in-formation. Search engines have become the predominant means of finding information on the Web and all other data repositories, including local resources. Domain scientists regularly acquire and analyze images generated by equipment such as microscopes and cameras, resulting in complex image files that need to be managed in a convenient manner. This type of integrated environment has been recently termed a netcentric sci-entific research repository. I developed a number of data manipulation tools that allow researchers to manage their information more effectively in a netcentric environment. The specific contributions are: (1) A unique interface for management of data including files and relational databases. A wrapper for relational databases was developed so that the data can be indexed and searched using traditional search engines. This approach allows data in databases to be searched with the same interface as other data. Fur-thermore, this approach makes it easier for scientists to work with their data if they are not familiar with SQL. (2) A Web services based architecture for integrating analysis op-erations into a repository. This technique allows the system to leverage the large num-ber of existing tools by wrapping them with a Web service and registering the service with the repository. Metadata associated with Web services was enhanced to allow this feature to be included. In addition, an improved binary to text encoding scheme was de-veloped to reduce the size overhead for sending large scientific data files via XML mes-sages used in Web services. (3) Integrated image analysis operations with SQL. This technique allows for images to be stored and managed conveniently in a relational da-tabase. SQL supplemented with map algebra operations is used to select and perform operations on sets of images.
Adaptive Planning and Prediction in Agent-Supported Distributed Collaboration.
Agents that act as user assistants will become invaluable as the number of information sources continue to proliferate. Such agents can support the work of users by learning to automate time-consuming tasks and filter information to manageable levels. Although considerable advances have been made in this area, it remains a fertile area for further development. One application of agents under careful scrutiny is the automated negotiation of conflicts between different user's needs and desires. Many techniques require explicit user models in order to function. This dissertation explores a technique for dynamically constructing user models and the impact of using them to anticipate the need for negotiation. Negotiation is reduced by including an advising aspect to the agent that can use this anticipation of conflict to adjust user behavior.
Measuring Semantic Relatedness Using Salient Encyclopedic Concepts
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 synthetic datasets for semantic relatedness as well as real world applications such as paraphrase detection and short answer grading. Our work represents a novel approach to integrate world-knowledge into current semantic models and a means to cross the language boundary for a better and more robust semantic relatedness representation, thus opening the door for an improved abstraction of meaning that carries the potential of ultimately imparting understanding of natural language to machines.
Computer Analysis of Amino Acid Chromatography
The problem with which this research was done was that of applying the IBM360 computer to the analysis of waveforms from a Beckman model 120C liquid chromatograph. Software to interpret these waveforms was written in the PLl language. For a control run, input to the computer consisted of a digital tape containing the raw results of the chromatograph run. Output consisted of several graphs and charts giving the results of the analysis. In addition, punched output was provided which gave the name of each amino acid, its elution time and color constant. These punched cards were then input to the computer as input to the experimental run, along with the raw data on the digital tape. From the known amounts of amino acids in the control run and the ratio of control to experimental peak area, the amino acids of the unknown were quantified. The resulting programs provided a complete and easy to use solution to the problem of chromatographic data analysis.
A Smooth-turn Mobility Model for Airborne Networks
In this article, I introduce a novel airborne network mobility model, called the Smooth Turn Mobility Model, that captures the correlation of acceleration for airborne vehicles across time and spatial coordinates. E?ective routing in airborne networks (ANs) relies on suitable mobility models that capture the random movement pattern of airborne vehicles. As airborne vehicles cannot make sharp turns as easily as ground vehicles do, the widely used mobility models for Mobile Ad Hoc Networks such as Random Waypoint and Random Direction models fail. Our model is realistic in capturing the tendency of airborne vehicles toward making straight trajectory and smooth turns with large radius, and whereas is simple enough for tractable connectivity analysis and routing design.
Benchmark-based Page Replacement (BBPR) Strategy: A New Web Cache Page Replacement Strategy
World Wide Web caching is widely used through today's Internet. When correctly deployed, Web caching systems can lead to significant bandwidth savings, network load reduction, server load balancing, and higher content availability. A document replacement algorithm that can lower retrieval latency and yield high hit ratio is the key to the effectiveness of proxy caches. More than twenty cache algorithms have been employed in academic studies and in corporate communities as well. But there are some drawbacks in the existing replacement algorithms. To overcome these shortcomings, we developed a new page replacement strategy named as Benchmark-Based Page Replacement (BBPR) strategy, in which a HTTP benchmark is used as a tool to evaluate the current network load and the server load. By our simulation model, the BBPR strategy shows better performance than the LRU (Least Recently Used) method, which is the most commonly used algorithm. The tradeoff is a reduced hit ratio. Slow pages benefit from BBPR.
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.
The Design and Implementation of an Intelligent Agent-Based File System
As bandwidth constraints on LAN/WAN environments decrease, the demand for distributed services will continue to increase. In particular, the proliferation of user-level applications requiring high-capacity distributed file storage systems will demand that such services be universally available. At the same time, the advent of high-speed networks have made the deployment of application and communication solutions based upon an Intelligent Mobile Agent (IMA) framework practical. Agents have proven to present an ideal development paradigm for the creation of autonomous large-scale distributed systems, and an agent-based communication scheme would facilitate the creation of independently administered distributed file services. This thesis thus outlines an architecture for such a distributed file system based upon an IMA communication framework.
Using Extended Logic Programs to Formalize Commonsense Reasoning
In this dissertation, we investigate how commonsense reasoning can be formalized by using extended logic programs. In this investigation, we first use extended logic programs to formalize inheritance hierarchies with exceptions by adopting McCarthy's simple abnormality formalism to express uncertain knowledge. In our representation, not only credulous reasoning can be performed but also the ambiguity-blocking inheritance and the ambiguity-propagating inheritance in skeptical reasoning are simulated. In response to the anomalous extension problem, we explore and discover that the intuition underlying commonsense reasoning is a kind of forward reasoning. The unidirectional nature of this reasoning is applied by many reformulations of the Yale shooting problem to exclude the undesired conclusion. We then identify defeasible conclusions in our representation based on the syntax of extended logic programs. A similar idea is also applied to other formalizations of commonsense reasoning to achieve such a purpose.
Automatic Tagging of Communication Data
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.
Case-Based Reasoning for Children Story Selection in ASP.NET
This paper describes the general architecture and function of a Case-Based Reasoning (CBR) system implemented with ASP.NET and C#. Microsoft Visual Studio .NET and XML Web Services provide a flexible, standards-based model that allows clients to access data. Web Form Pages offer a powerful programming model for Web-enabled user interface. The system provides a variety of mechanisms and services related to story retrieval and adaptation. Users may browse and search a library of text stories. More advanced CBR capabilities were also implemented, including a multi-factor distance-calculation for matching user interests with stories in the library, recommendations on optimizing search, and adaptation of stories to match user interests.
An Empirical Evaluation of Communication and Coordination Effectiveness in Autonomous Reactive Multiagent Systems
This thesis describes experiments designed to measure the effect of collaborative communication on task performance of a multiagent system. A discrete event simulation was developed to model a multi-agent system completing a task to find and collect food resources, with the ability to substitute various communication and coordination methods. Experiments were conducted to find the effects of the various communication methods on completion of the task to find and harvest the food resources. Results show that communication decreases the time required to complete the task. However, all communication methods do not fare equally well. In particular, results indicate that the communication model of the bee is a particularly effective method of agent communication and collaboration. Furthermore, results indicate that direct communication with additional information content provides better completion results. Cost-benefit models show some conflicting information, indicating that the increased performance may not offset the additional cost of achieving that performance.
Design and Implementation of a Text Editor Under Music Interactive Operating System
An interactive text editor is a computer program that allows a user to create and revise a target document such as program statements, manuscript text, and numeric data through an online terminal and the computer. It allows text to be modified and corrected many orders of magnitude faster and more easily than would manual correction. The most important characteristic of the text editor is its convenience for the user. Such convenience requires a simple, mnemonic command language which is easy to use and understand.
Computational Methods for Vulnerability Analysis and Resource Allocation in Public Health Emergencies
POD (Point of Dispensing)-based emergency response plans involving mass prophylaxis may seem feasible when considering the choice of dispensing points within a region, overall population density, and estimated traffic demands. However, the plan may fail to serve particular vulnerable sub-populations, resulting in access disparities during emergency response. Federal authorities emphasize on the need to identify sub-populations that cannot avail regular services during an emergency due to their special needs to ensure effective response. Vulnerable individuals require the targeted allocation of appropriate resources to serve their special needs. Devising schemes to address the needs of vulnerable sub-populations is essential for the effectiveness of response plans. This research focuses on data-driven computational methods to quantify and address vulnerabilities in response plans that require the allocation of targeted resources. Data-driven methods to identify and quantify vulnerabilities in response plans are developed as part of this research. Addressing vulnerabilities requires the targeted allocation of appropriate resources to PODs. The problem of resource allocation to PODs during public health emergencies is introduced and the variants of the resource allocation problem such as the spatial allocation, spatio-temporal allocation and optimal resource subset variants are formulated. Generating optimal resource allocation and scheduling solutions can be computationally hard problems. The application of metaheuristic techniques to find near-optimal solutions to the resource allocation problem in response plans is investigated. A vulnerability analysis and resource allocation framework that facilitates the demographic analysis of population data in the context of response plans, and the optimal allocation of resources with respect to the analysis are described.
A Global Stochastic Modeling Framework to Simulate and Visualize Epidemics
Epidemics have caused major human and monetary losses through the course of human civilization. It is very important that epidemiologists and public health personnel are prepared to handle an impending infectious disease outbreak. the ever-changing demographics, evolving infrastructural resources of geographic regions, emerging and re-emerging diseases, compel the use of simulation to predict disease dynamics. By the means of simulation, public health personnel and epidemiologists can predict the disease dynamics, population groups at risk and their geographic locations beforehand, so that they are prepared to respond in case of an epidemic outbreak. As a consequence of the large numbers of individuals and inter-personal interactions involved in simulating infectious disease spread in a region such as a county, sizeable amounts of data may be produced that have to be analyzed. Methods to visualize this data would be effective in facilitating people from diverse disciplines understand and analyze the simulation. This thesis proposes a framework to simulate and visualize the spread of an infectious disease in a population of a region such as a county. As real-world populations have a non-homogeneous demographic and spatial distribution, this framework models the spread of an infectious disease based on population of and geographic distance between census blocks; social behavioral parameters for demographic groups. the population is stratified into demographic groups in individual census blocks using census data. Infection spread is modeled by means of local and global contacts generated between groups of population in census blocks. the strength and likelihood of the contacts are based on population, geographic distance and social behavioral parameters of the groups involved. the disease dynamics are represented on a geographic map of the region using a heat map representation, where the intensity of infection is mapped to a color scale. This framework provides a tool for public health personnel and …
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.
Dynamic Resource Management in RSVP- Controlled Unicast Networks
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.
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.
Evaluating Stack Overflow Usability Posts in Conjunction with Usability Heuristics
This thesis explores the critical role of usability in software development and uses usability heuristics as a cost-effective and efficient method for evaluating various software functions and interfaces. With the proliferation of software development in the modern digital age, developing user-friendly interfaces that meet the needs and preferences of users has become a complex process. Usability heuristics, a set of guidelines based on principles of human-computer interaction, provide a starting point for designers to create intuitive, efficient, and easy-to-use interfaces that provide a seamless user experience. The study uses Jakob Nieson's ten usability heuristics to evaluate the usability of Stack Overflow posts, a popular Q\&A website for developers. Through the analysis of 894 posts related to usability, the study identifies common usability problems faced by users and developers, providing valuable insights into the effectiveness of usability guidelines in software development practice. The research findings emphasize the need for ongoing evaluation and improvement of software interfaces to ensure a seamless user experience. The thesis concludes by highlighting the potential of usability heuristics in guiding the design of user-friendly software interfaces and improving the overall user experience in software development.
Framework for Evaluating Dynamic Memory Allocators Including a New Equivalence Class Based Cache-conscious Allocator
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 back to source level objects. Using the traces from Gleipnir, we extended a commonly used cache simulator for generating detailed cache statistics: per function, per data object, per cache line, and identify specific data objects that are conflicting with each other. The utility of the framework is demonstrated with a new memory allocator known as equivalence class allocator. The new allocator allows users to specify cache sets, in addition to object size, where the objects should be placed. We compare this new allocator with two well-known allocators, viz., Doug Lea and Pool allocators.
Classifying Pairwise Object Interactions: A Trajectory Analytics Approach
We have a huge amount of video data from extensively available surveillance cameras and increasingly growing technology to record the motion of a moving object in the form of trajectory data. With proliferation of location-enabled devices and ongoing growth in smartphone penetration as well as advancements in exploiting image processing techniques, tracking moving objects is more flawlessly achievable. In this work, we explore some domain-independent qualitative and quantitative features in raw trajectory (spatio-temporal) data in videos captured by a fixed single wide-angle view camera sensor in outdoor areas. We study the efficacy of those features in classifying four basic high level actions by employing two supervised learning algorithms and show how each of the features affect the learning algorithms’ overall accuracy as a single factor or confounded with others.
Quality-of-Service Provisioning and Resource Reservation Mechanisms for Mobile Wireless Networks
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.
Ddos Defense Against Botnets in the Mobile Cloud
Mobile phone advancements and ubiquitous internet connectivity are resulting in ever expanding possibilities in the application of smart phones. Users of mobile phones are now capable of hosting server applications from their personal devices. Whether providing services individually or in an ad hoc network setting the devices are currently not configured for defending against distributed denial of service (DDoS) attacks. These attacks, often launched from a botnet, have existed in the space of personal computing for decades but recently have begun showing up on mobile devices. Research is done first into the required steps to develop a potential botnet on the Android platform. This includes testing for the amount of malicious traffic an Android phone would be capable of generating for a DDoS attack. On the other end of the spectrum is the need of mobile devices running networked applications to develop security against DDoS attacks. For this mobile, phones are setup, with web servers running Apache to simulate users running internet connected applications for either local ad hoc networks or serving to the internet. Testing is done for the viability of using commonly available modules developed for Apache and intended for servers as well as finding baseline capabilities of mobiles to handle higher traffic volumes. Given the unique challenge of the limited resources a mobile phone can dedicate to Apache when compared to a dedicated hosting server a new method was needed. A proposed defense algorithm is developed for mitigating DDoS attacks against the mobile server that takes into account the limited resources available on the mobile device. The algorithm is tested against TCP socket flooding for effectiveness and shown to perform better than the common Apache module installations on a mobile device.
Self-Optimizing Dynamic Finite Functions
Finite functions (also called maps) are used to describe a number of key computations and storage mechanisms used in software and hardware interpreters. Their presence spread over various memory and speed hierarchies in hardware and through various optimization processes (algorithmic and compilation based) in software, suggests encapsulating dynamic size changes and representation optimizations in a unique abstraction to be used across traditional computation mechanisms. We developed a memory allocator for testing the finite functions. We have implemented some dynamic finite functions and performed certain experiments to see the performance speed of these finite functions. We have developed some simple but powerful application programming interfaces (API) for these finite functions.
A Study on Usability of Mobile Software Targeted at Elderly People in China
With the rapid development of mobile device technology, smartphones are now not only the tool for young people but also for elderly people. However, the complicated steps of interacting with smartphones are stopping them from having a good user experience. One of the reasons is that application designers do not take consideration of the user group of elderly people. Our pilot survey shows that most elderly people lack the skills required to use a smartphone without obstacles, like typing. We also conducted an experiment with 8 participants that targeting on the usability of a daily used application, Contact List (CL), and based on a Chinese language system. We developed an android application that proposed a new method of showing the contact list according to the language usage of Chinese for this study. By asking participants to finish the same tasks on the traditional CL applications on their phones or on our application and observing their operations, we obtained useful feedback in terms of usability issues. Our experiment also tried to find out whether the method we proposed in the new application can lead to a better user experience for elderly people.
Embedded monitors for detecting and preventing intrusions in cryptographic and application protocols.
There are two main approaches for intrusion detection: signature-based and anomaly-based. Signature-based detection employs pattern matching to match attack signatures with observed data making it ideal for detecting known attacks. However, it cannot detect unknown attacks for which there is no signature available. Anomaly-based detection builds a profile of normal system behavior to detect known and unknown attacks as behavioral deviations. However, it has a drawback of a high false alarm rate. In this thesis, we describe our anomaly-based IDS designed for detecting intrusions in cryptographic and application-level protocols. Our system has several unique characteristics, such as the ability to monitor cryptographic protocols and application-level protocols embedded in encrypted sessions, a very lightweight monitoring process, and the ability to react to protocol misuse by modifying protocol response directly.
Linearly Ordered Concurrent Data Structures on Hypercubes
This thesis presents a simple method for the concurrent manipulation of linearly ordered data structures on hypercubes. The method is based on the existence of a pruned binomial search tree rooted at any arbitrary node of the binary hypercube. The tree spans any arbitrary sequence of n consecutive nodes containing the root, using a fan-out of at most [log₂ 𝑛] and a depth of [log₂ 𝑛] +1. Search trees spanning non-overlapping processor lists are formed using only local information, and can be used concurrently without contention problems. Thus, they can be used for performing broadcast and merge operations simultaneously on sets with non-uniform sizes. Extensions to generalized and faulty hypercubes and applications to image processing algorithms and for m-way search are discussed.
Cuff-less Blood Pressure Measurement Using a Smart Phone
Blood pressure is vital sign information that physicians often need as preliminary data for immediate intervention during emergency situations or for regular monitoring of people with cardiovascular diseases. Despite the availability of portable blood pressure meters in the market, they are not regularly carried by people, creating a need for an ultra-portable measurement platform or device that can be easily carried and used at all times. One such device is the smartphone which, according to comScore survey is used by 26.2% of the US adult population. the mass production of these phones with built-in sensors and high computation power has created numerous possibilities for application development in different domains including biomedical. Motivated by this capability and their extensive usage, this thesis focuses on developing a blood pressure measurement platform on smartphones. Specifically, I developed a blood pressure measurement system on a smart phone using the built-in camera and a customized external microphone. the system consists of first obtaining heart beats using the microphone and finger pulse with the camera, and finally calculating the blood pressure using the recorded data. I developed techniques for finding the best location for obtaining the data, making the system usable by all categories of people. the proposed system resulted in accuracies between 90-100%, when compared to traditional blood pressure meters. the second part of this thesis presents a new system for remote heart beat monitoring using the smart phone. with the proposed system, heart beats can be transferred live by patients and monitored by physicians remotely for diagnosis. the proposed blood pressure measurement and remote monitoring systems will be able to facilitate information acquisition and decision making by the 9-1-1 operators.
Routing Optimization in Wireless Ad Hoc and Wireless Sensor Networks
Wireless ad hoc networks are expected to play an important role in civilian and military settings where wireless access to wired backbone is either ineffective or impossible. Wireless sensor networks are effective in remote data acquisition. Congestion control and power consumption in wireless ad hoc networks have received a lot of attention in recent research. Several algorithms have been proposed to reduce congestion and power consumption in wireless ad hoc and sensor networks. In this thesis, we focus upon two schemes, which deal with congestion control and power consumption issues. This thesis consists of two parts. In the first part, we describe a randomization scheme for congestion control in dynamic source routing protocol, which we refer to as RDSR. We also study a randomization scheme for GDSR protocol, a GPS optimized variant of DSR. We discuss RDSR and RGDSR implementations and present extensive simulation experiments to study their performance. Our results indicate that both RGDSR and RDSR protocols outperform their non-randomized counterparts by decreasing the number of route query packets. Furthermore, a probabilistic congestion control scheme based on local tuning of routing protocol parameters is shown to be feasible. In the second part we present a simulation based performance study of energy aware data centric routing protocol, EAD, proposed by X. Cheng and A. Boukerche. EAD reduces power consumption by requiring only a small percentage of the network to stay awake. Our experiments show that EAD outperforms the well-known LEACH scheme.
Algorithms for Efficient Utilization of Wireless Bandwidth and to Provide Quality-of-Service in Wireless Networks
This thesis presents algorithms to utilize the wireless bandwidth efficiently and at the same time meet the quality of service (QoS) requirements of the users. In the proposed algorithms we present an adaptive frame structure based upon the airlink frame loss probability and control the admission of call requests into the system based upon the load on the system and the QoS requirements of the incoming call requests. The performance of the proposed algorithms is studied by developing analytical formulations and simulation experiments. Finally we present an admission control algorithm which uses an adaptive delay computation algorithm to compute the queuing delay for each class of traffic and adapts the service rate and the reliability in the estimates based upon the deviation in the expected and obtained performance. We study the performance of the call admission control algorithm by simulation experiments. Simulation results for the adaptive frame structure algorithm show an improvement in the number of users in the system but there is a drop in the system throughput. In spite of the lower throughput the adaptive frame structure algorithm has fewer QoS delay violations. The adaptive call admission control algorithm adapts the call dropping probability of different classes of traffic and optimizes the system performance w.r.t the number of calls dropped and the reliability in meeting the QoS promised when the call is admitted into the system.
Planning techniques for agent based 3D animations.
The design of autonomous agents capable of performing a given goal in a 3D domain continues to be a challenge for computer animated story generation systems. We present a novel prototype which consists of a 3D engine and a planner for a simple virtual world. We incorporate the 2D planner into the 3D engine to provide 3D animations. Based on the plan, the 3D world is created and the objects are positioned. Then the plan is linearized into simpler actions for object animation and rendered via the 3D engine. We use JINNI3D as the engine and WARPLAN-C as the planner for the above-mentioned prototype. The user can interact with the system using a simple natural language interface. The interface consists of a shallow parser, which is capable of identifying a set of predefined basic commands. The command given by the user is considered as the goal for the planner. The resulting plan is created and rendered in 3D. The overall system is comparable to a character based interactive story generation system except that it is limited to the predefined 3D environment.
Server load balancing.
Server load balancing technology has obtained much attention as much business proceeded towards e-commerce. The idea behind is to have set of clustered servers that share the load as against a single server to achieve better performance and throughput. In this problem in lieu of thesis, I propose and evaluate an implementation of a prototype scalable server. The prototype consists of a load-balanced cluster of hosts that collectively accept and service TCP connections. The host IP addresses are advertised using the Round Robin DNS technique, allowing any host to receive requests from any client. Once a client attempts to establish a TCP connection with one of the hosts, a decision is made as to whether or not the connection should be redirected to a different host namely, the host with the lowest number of established connections. This problem in lieu of thesis outlines the history of load balancing, various options available today and finally approach for implementing the prototype and the corresponding findings.
Rhythms of Interaction in Global Software Development Teams
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 development by defining the different time variables that can also be used to compare temporal patterns found in real-world teams. It should also inform studies about student team projects by helping instructors schedule group activities.
The Data Structure of a KSAM Key Directory
The purpose of this project is to explore the alternate data structures for a disk file which is currently a preorder binary tree. specifically, the file is the key directory for an implementation of Keyed Sequential Access Method (KSAM) in a mini-computer operating system. A new data structure will be chosen, with the reasons for that choice given, and it will be incorporated into the existing system.
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.
Modeling Alcohol Consumption Using Blog Data
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.
System and Methods for Detecting Unwanted Voice Calls
Voice over IP (VoIP) is a key enabling technology for the migration of circuit-switched PSTN architectures to packet-based IP networks. However, this migration is successful only if the present problems in IP networks are addressed before deploying VoIP infrastructure on a large scale. One of the important issues that the present VoIP networks face is the problem of unwanted calls commonly referred to as SPIT (spam over Internet telephony). Mostly, these SPIT calls are from unknown callers who broadcast unwanted calls. There may be unwanted calls from legitimate and known people too. In this case, the unwantedness depends on social proximity of the communicating parties. For detecting these unwanted calls, I propose a framework that analyzes incoming calls for unwanted behavior. The framework includes a VoIP spam detector (VSD) that analyzes incoming VoIP calls for spam behavior using trust and reputation techniques. The framework also includes a nuisance detector (ND) that proactively infers the nuisance (or reluctance of the end user) to receive incoming calls. This inference is based on past mutual behavior between the calling and the called party (i.e., caller and callee), the callee's presence (mood or state of mind) and tolerance in receiving voice calls from the caller, and the social closeness between the caller and the callee. The VSD and ND learn the behavior of callers over time and estimate the possibility of the call to be unwanted based on predetermined thresholds configured by the callee (or the filter administrators). These threshold values have to be automatically updated for integrating dynamic behavioral changes of the communicating parties. For updating these threshold values, I propose an automatic calibration mechanism using receiver operating characteristics curves (ROC). The VSD and ND use this mechanism for dynamically updating thresholds for optimizing their accuracy of detection. In addition to unwanted calls …
Influence of Underlying Random Walk Types in Population Models on Resulting Social Network Types and Epidemiological Dynamics
Epidemiologists rely on human interaction networks for determining states and dynamics of disease propagations in populations. However, such networks are empirical snapshots of the past. It will greatly benefit if human interaction networks are statistically predicted and dynamically created while an epidemic is in progress. We develop an application framework for the generation of human interaction networks and running epidemiological processes utilizing research on human mobility patterns and agent-based modeling. The interaction networks are dynamically constructed by incorporating different types of Random Walks and human rules of engagements. We explore the characteristics of the created network and compare them with the known theoretical and empirical graphs. The dependencies of epidemic dynamics and their outcomes on patterns and parameters of human motion and motives are encountered and presented through this research. This work specifically describes how the types and parameters of random walks define properties of generated graphs. We show that some configurations of the system of agents in random walk can produce network topologies with properties similar to small-world networks. Our goal is to find sets of mobility patterns that lead to empirical-like networks. The possibility of phase transitions in the graphs due to changes in the parameterization of agent walks is the focus of this research as this knowledge can lead to the possibility of disruptions to disease diffusions in populations. This research shall facilitate work of public health researchers to predict the magnitude of an epidemic and estimate resources required for mitigation.
Privacy Preserving EEG-based Authentication Using Perceptual Hashing
The use of electroencephalogram (EEG), an electrophysiological monitoring method for recording the brain activity, for authentication has attracted the interest of researchers for over a decade. In addition to exhibiting qualities of biometric-based authentication, they are revocable, impossible to mimic, and resistant to coercion attacks. However, EEG signals carry a wealth of information about an individual and can reveal private information about the user. This brings significant privacy issues to EEG-based authentication systems as they have access to raw EEG signals. This thesis proposes a privacy-preserving EEG-based authentication system that preserves the privacy of the user by not revealing the raw EEG signals while allowing the system to authenticate the user accurately. In that, perceptual hashing is utilized and instead of raw EEG signals, their perceptually hashed values are used in the authentication process. In addition to describing the authentication process, algorithms to compute the perceptual hash are developed based on two feature extraction techniques. Experimental results show that an authentication system using perceptual hashing can achieve performance comparable to a system that has access to raw EEG signals if enough EEG channels are used in the process. This thesis also presents a security analysis to show that perceptual hashing can prevent information leakage.
Automated GUI Tests Generation for Android Apps Using Q-learning
Mobile applications are growing in popularity and pose new problems in the area of software testing. In particular, mobile applications heavily depend upon user interactions and a dynamically changing environment of system events. In this thesis, we focus on user-driven events and use Q-learning, a reinforcement machine learning algorithm, to generate tests for Android applications under test (AUT). We implement a framework that automates the generation of GUI test cases by using our Q-learning approach and compare it to a uniform random (UR) implementation. A novel feature of our approach is that we generate user-driven event sequences through the GUI, without the source code or the model of the AUT. Hence, considerable amount of cost and time are saved by avoiding the need for model generation for generating the tests. Our results show that the systematic path exploration used by Q-learning results in higher average code coverage in comparison to the uniform random approach.
Ensuring Authenticity and Integrity of Critical Information Using XML Digital Signatures
It has been noticed in the past five years that the Internet use has been troubled by the lack of sufficient security and a legal framework to enable electronic commerce to flourish. Despite these shortcomings, governments, businesses and individuals are using the Internet more often as an inexpensive and ubiquitous means to disseminate and obtain information, goods and services. The Internet is insecure -- potentially millions of people have access, and "hackers" can intercept anything traveling over the wire. There is no way to make it a secure environment; it is, after all, a public network, hence the availability and affordability. In order for it to serve our purposes as a vehicle for legally binding transactions, efforts must be directed at securing the message itself, as opposed to the transport mechanism. Digital signatures have been evolved in the recent years as the best tool for ensuring the authenticity and integrity of critical information in the so called "paperless office". A model using XML digital signatures is developed and the level of security provided by this model in the real world scenario is outlined.
Field Programmable Devices and Reconfigurable Computing
The motivation behind this research has been the idea of the capability of the computing device to dynamically reconfigure itself. The goal of this work is to measure the computational power of reconfigurable machines rather in an abstract manner by proposing a model the FPGAs abstract computing machines. Modeling FPGAs in terms of Automata Theory would give a base to answer more fundamental questions about the capabilities and possible answers. If a Finite State Machine (FSM) or a Turing Machine (TM) has the capability of reconfiguring its finite control, does this ability give the abstract computing device new computational power. In other words is a reconfigurable FSM, TM or a Cellular Automata more powerful than their corresponding non-configurable versions?
The Multipath Fault-Tolerant Protocol for Routing in Packet-Switched Communication Network
In order to provide improved service quality to applications, networks need to address the need for reliability of data delivery. Reliability can be improved by incorporating fault tolerance into network routing, wherein a set of multiple routes are used for routing between a given source and destination. This thesis proposes a new fault-tolerant protocol, called the Multipath Fault Tolerant Protocol for Routing (MFTPR), to improve the reliability of network routing services. The protocol is based on a multipath discovery algorithm, the Quasi-Shortest Multipath (QSMP), and is designed to work in conjunction with the routing protocol employed by the network. MFTPR improves upon the QSMP algorithm by finding more routes than QSMP, and also provides for maintenance of these routes in the event of failure of network components. In order to evaluate the resilience of a pair of paths to failure, this thesis proposes metrics that evaluate the non-disjointness of a pair of paths and measure the probability of simultaneous failure of these paths. The performance of MFTPR to find alternate routes based on these metrics is analyzed through simulation.
Back to Top of Screen