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  Partner: UNT Libraries
 Degree Discipline: Computer Science
The Role of Intelligent Mobile Agents in Network Management and Routing

The Role of Intelligent Mobile Agents in Network Management and Routing

Date: December 2000
Creator: Balamuru, Vinay Gopal
Description: 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.
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Control Mechanisms and Recovery Techniques for Real-Time Data Transmission Over the Internet.

Control Mechanisms and Recovery Techniques for Real-Time Data Transmission Over the Internet.

Date: August 2002
Creator: Battula, Venkata Krishna Rao
Description: Streaming multimedia content with UDP has become popular over distributed systems such as an Internet. This may encounter many losses due to dropped packets or late arrivals at destination since UDP can only provide best effort delivery. Even UDP doesn't have any self-recovery mechanism from congestion collapse or bursty loss to inform sender of the data to adjust future transmission rate of data like in TCP. So there is a need to incorporate various control schemes like forward error control, interleaving, and congestion control and error concealment into real-time transmission to prevent from effect of losses. Loss can be repaired by retransmission if roundtrip delay is allowed, otherwise error concealment techniques will be used based on the type and amount of loss. This paper implements the interleaving technique with packet spacing of varying interleaver block size for protecting real-time data from loss and its effect during transformation across the Internet. The packets are interleaved and maintain some time gap between two consecutive packets before being transmitted into the Internet. Thus loss of packets can be reduced from congestion and preventing loss of consecutive packets of information when a burst of several packets are lost. Several experiments have been conducted with ...
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Multi-perspective, Multi-modal Image Registration and Fusion

Multi-perspective, Multi-modal Image Registration and Fusion

Date: August 2012
Creator: Belkhouche, Mohammed Yassine
Description: Multi-modal image fusion is an active research area with many civilian and military applications. Fusion is defined as strategic combination of information collected by various sensors from different locations or different types in order to obtain a better understanding of an observed scene or situation. Fusion of multi-modal images cannot be completed unless these two modalities are spatially aligned. In this research, I consider two important problems. Multi-modal, multi-perspective image registration and decision level fusion of multi-modal images. In particular, LiDAR and visual imagery. Multi-modal image registration is a difficult task due to the different semantic interpretation of features extracted from each modality. This problem is decoupled into three sub-problems. The first step is identification and extraction of common features. The second step is the determination of corresponding points. The third step consists of determining the registration transformation parameters. Traditional registration methods use low level features such as lines and corners. Using these features require an extensive optimization search in order to determine the corresponding points. Many methods use global positioning systems (GPS), and a calibrated camera in order to obtain an initial estimate of the camera parameters. The advantages of our work over the previous works are the following. ...
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Hopfield Networks as an Error Correcting Technique for Speech Recognition

Hopfield Networks as an Error Correcting Technique for Speech Recognition

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Date: May 2004
Creator: Bireddy, Chakradhar
Description: I experimented with Hopfield networks in the context of a voice-based, query-answering system. Hopfield networks are used to store and retrieve patterns. I used this technique to store queries represented as natural language sentences and I evaluated the accuracy of the technique for error correction in a spoken question-answering dialog between a computer and a user. I show that the use of an auto-associative Hopfield network helps make the speech recognition system more fault tolerant. I also looked at the available encoding schemes to convert a natural language sentence into a pattern of zeroes and ones that can be stored in the Hopfield network reliably, and I suggest scalable data representations which allow storing a large number of queries.
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Practical Cursive Script Recognition

Practical Cursive Script Recognition

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

Investigating the Extractive Summarization of Literary Novels

Date: December 2011
Creator: Ceylan, Hakan
Description: Abstract Due to the vast amount of information we are faced with, summarization has become a critical necessity of everyday human life. Given that a large fraction of the electronic documents available online and elsewhere consist of short texts such as Web pages, news articles, scientific reports, and others, the focus of natural language processing techniques to date has been on the automation of methods targeting short documents. We are witnessing however a change: an increasingly larger number of books become available in electronic format. This means that the need for language processing techniques able to handle very large documents such as books is becoming increasingly important. This thesis addresses the problem of summarization of novels, which are long and complex literary narratives. While there is a significant body of research that has been carried out on the task of automatic text summarization, most of this work has been concerned with the summarization of short documents, with a particular focus on news stories. However, novels are different in both length and genre, and consequently different summarization techniques are required. This thesis attempts to close this gap by analyzing a new domain for summarization, and by building unsupervised and supervised systems ...
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Using Reinforcement Learning in Partial Order Plan Space

Using Reinforcement Learning in Partial Order Plan Space

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Date: May 2006
Creator: Ceylan, Hakan
Description: Partial order planning is an important approach that solves planning problems without completely specifying the orderings between the actions in the plan. This property provides greater flexibility in executing plans; hence making the partial order planners a preferred choice over other planning methodologies. However, in order to find partially ordered plans, partial order planners perform a search in plan space rather than in space of world states and an uninformed search in plan space leads to poor efficiency. In this thesis, I discuss applying a reinforcement learning method, called First-visit Monte Carlo method, to partial order planning in order to design agents which do not need any training data or heuristics but are still able to make informed decisions in plan space based on experience. Communicating effectively with the agent is crucial in reinforcement learning. I address how this task was accomplished in plan space and the results from an evaluation of a blocks world test bed.
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Natural Language Interfaces to Databases

Natural Language Interfaces to Databases

Date: December 2006
Creator: Chandra, Yohan
Description: Natural language interfaces to databases (NLIDB) are systems that aim to bridge the gap between the languages used by humans and computers, and automatically translate natural language sentences to database queries. This thesis proposes a novel approach to NLIDB, using graph-based models. The system starts by collecting as much information as possible from existing databases and sentences, and transforms this information into a knowledge base for the system. Given a new question, the system will use this knowledge to analyze and translate the sentence into its corresponding database query statement. The graph-based NLIDB system uses English as the natural language, a relational database model, and SQL as the formal query language. In experiments performed with natural language questions ran against a large database containing information about U.S. geography, the system showed good performance compared to the state-of-the-art in the field.
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Measuring Vital Signs Using Smart Phones

Measuring Vital Signs Using Smart Phones

Date: December 2010
Creator: Chandrasekaran, Vikram
Description: Smart phones today have become increasingly popular with the general public for its diverse abilities like navigation, social networking, and multimedia facilities to name a few. These phones are equipped with high end processors, high resolution cameras, built-in sensors like accelerometer, orientation-sensor, light-sensor, and much more. According to comScore survey, 25.3% of US adults use smart phones in their daily lives. Motivated by the capability of smart phones and their extensive usage, I focused on utilizing them for bio-medical applications. In this thesis, I present a new application for a smart phone to quantify the vital signs such as heart rate, respiratory rate and blood pressure with the help of its built-in sensors. Using the camera and a microphone, I have shown how the blood pressure and heart rate can be determined for a subject. People sometimes encounter minor situations like fainting or fatal accidents like car crash at unexpected times and places. It would be useful to have a device which can measure all vital signs in such an event. The second part of this thesis demonstrates a new mode of communication for next generation 9-1-1 calls. In this new architecture, the call-taker will be able to control the ...
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Higher Compression from the Burrows-Wheeler Transform with New Algorithms for the List Update Problem

Higher Compression from the Burrows-Wheeler Transform with New Algorithms for the List Update Problem

Date: August 2001
Creator: Chapin, Brenton
Description: 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, ...
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