Consumer's opinions and sentiments on products can reflect the performance of products in general or in various aspects. Analyzing these data is becoming feasible, considering the availability of immense data and the power of natural language processing. However, retailers have not taken full advantage of online comments. This work is dedicated to a solution for automatically analyzing and summarizing these valuable data at both product and category levels. In this research, a system was developed to retrieve and analyze extensive data from public online resources. A parallel framework was created to make this system extensible and efficient. In this framework, a star topological network was adopted in which each computing unit was assigned to retrieve a fraction of data and to assess sentiment. Finally, the preprocessed data were collected and summarized by the central machine which generates the final result that can be rendered through a web interface. The system was designed to have sound performance, robustness, manageability, extensibility, and accuracy.

Ulcerative colitis (UC) is a chronic inflammatory disease characterized by periods of relapses and remissions affecting more than 500,000 people in the United States. To achieve the therapeutic goals of UC, which are to first induce and then maintain disease remission, doctors need to evaluate the severity of UC of a patient. However, it is very difficult to evaluate the severity of UC objectively because of non-uniform nature of symptoms and large variations in their patterns. To address this, in our previous works, we developed two different approaches in which one is using the image textures, and the other is using CNN (convolutional neural network) to measure and classify objectively the severity of UC presented in optical colonoscopy video frames. But, we found that the image texture based approach could not handle larger number of variations in their patterns, and the CNN based approach could not achieve very high accuracy. In this paper, we improve our CNN based approach in two ways to provide better accuracy for the classification. We add more thorough and essential preprocessing, and generate more classes to accommodate large variations in their patterns. The experimental results show that the proposed preprocessing can improve the overall accuracy …

With an ever-growing number of publications in the biomedical domain, it becomes likely that important implicit connections between individual concepts of biomedical knowledge are overlooked. Literature based discovery (LBD) is in practice for many years to identify plausible associations between previously unrelated concepts. In this paper, we present a new, completely automatic and interactive system that creates a graph-based knowledge base to capture multifaceted complex associations among biomedical concepts. For a given pair of input concepts, our system auto-generates a list of ranked subgraphs uncovering possible previously unnoticed associations based on context information. To rank these subgraphs, we implement a novel ranking method using the context information obtained by performing random walks on the graph. In addition, we enhance the system by training a Neural Network Classifier to output the likelihood of the two concepts being likely related, which provides better insights to the end user.

Security is one of the main concerns of users who need to connect to a remote computer for various purposes, such as checking e-mails or viewing files. However in today's computer networks, privacy, transmission to intended client is not guaranteed. If data is transmitted over the Internet or a local network as plain text it may be captured and viewed by anyone with little technical knowledge. This may include sensitive data such as passwords. Big businesses use firewalls, virtual private networks and encrypt their transmissions to counter this at high costs. Secure shell protocol (SSH) provides an answer to this. SSH is a software protocol for secure communication over an insecure network. SSH not only offers authentication of hosts but also encrypts the sessions between the client and the server and is transparent to the end user. This Problem in Lieu of Thesis makes a study of SSH and creates a sample secure client and server which follows SSH and examines its performance.

With the growing popularity of e-commerce applications that use software agents, the protection of mobile agent data has become imperative. To that end, the performance of four methods that protect the data integrity of mobile agents is evaluated. The methods investigated include existing approaches known as the Partial Result Authentication Codes, Hash Chaining, and Set Authentication Code methods, and a technique of our own design, called the Modified Set Authentication Code method, which addresses the limitations of the Set Authentication Code method. The experiments were run using the DADS agent system (developed at the Network Research Laboratory at UNT), for which a Data Integrity Module was designed. The experimental results show that our Modified Set Authentication Code technique performed comparably to the Set Authentication Code method.

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.

Library information systems use different software applications and automated systems to gain access to distributed information. Rapid application development, changes made to existing software applications and development of new software on different platforms can make it difficult for library information systems to interoperate. Web services are used to offer better information access and retrieval solutions and hence make it more cost effective for libraries. This research focuses on how web services are implemented with the standard protocols like SOAP, WSDL and UDDI using different programming languages and platforms to achieve interoperability for libraries. It also shows how libraries can make use of this new technology. Since web services built on different platforms can interact with each other, libraries can access information with more efficiency and flexibility.

Geometric packing problems are NP-complete problems that arise in VLSI design. In this thesis, we present two novel algorithms using dynamic programming to compute exactly the maximum number of k x k squares of unit size that can be packed without overlap into a given n x m grid. The first algorithm was implemented and ran successfully on problems of large input up to 1,000,000 nodes for different values. A heuristic based on the second algorithm is implemented. This heuristic is fast in practice, but may not always be giving optimal times in theory. However, over a wide range of random data this version of the algorithm is giving very good solutions very fast and runs on problems of up to 100,000,000 nodes in a grid and different ranges for the variables. It is also shown that this version of algorithm is clearly superior to the first algorithm and has shown to be very efficient in practice.

Guiding navigation in virtual environments (VEs) is a challenging task. A key issue in the navigation of a virtual environment is to be able to strike a balance between the user's need to explore the environment freely and the designer's need to ensure that the user experiences all the important events in the VE. This thesis reports on a study aimed at comparing the effectiveness of various navigation cues that are used to motivate users towards a specific target location. The results of this study indicate some significant differences in how users responded to the various cues.

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 …

Worms have caused significant destruction over the last few years. Network security elements such as firewalls, IDS, etc have been ineffective against worms. Some worms are so fast that a manual intervention is not possible. This brings in the need for a stronger security architecture which can automatically react to stop worm propagation. The method has to be signature independent so that it can stop new worms. In this thesis, an automated defense system (ADS) is developed to automate defense against worms and contain the worm to a level where manual intervention is possible. This is accomplished with a two level architecture with feedback at each level. The inner loop is based on control system theory and uses the properties of PID (proportional, integral and differential controller). The outer loop works at the network level and stops the worm to reach its spread saturation point. In our lab setup, we verified that with only inner loop active the worm was delayed, and with both loops active we were able to restrict the propagation to 10% of the targeted hosts. One concern for deployment of a worm containment mechanism was degradation of throughput for legitimate traffic. We found that with proper …

The resources (memory, power and bandwidth) are limited in wireless and mobile networks. Previous research has shown that the quality of service (QoS) of the mobile client can be improved through efficient resources management. This thesis contains two areas of research that are strongly interrelated. In the first area of research, we extended the MoSync Algorithm, a network application layer media synchronization algorithm, to allow play-out of multimedia packets by the base station upon the mobile client in a First-In-First-Out (FIFO), Highest-Priority-First (PQ), Weighted Fair-Queuing (WFQ) and Round-Robin (RR) order. In the second area of research, we make modifications to the DSR and TORA routing algorithms to make them energy aware routing protocols. Our research shows that the QoS of the mobile client can be drastically improved through effective resource allocation.