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  Partner: UNT Libraries
 Degree Discipline: Computer Science
 Collection: UNT Theses and Dissertations
Benchmark-based Page Replacement (BBPR) Strategy: A New Web Cache Page Replacement Strategy

Benchmark-based Page Replacement (BBPR) Strategy: A New Web Cache Page Replacement Strategy

Date: May 2003
Creator: He, Wei
Description: 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.
Contributing Partner: UNT Libraries
Boosting for Learning From Imbalanced, Multiclass Data Sets

Boosting for Learning From Imbalanced, Multiclass Data Sets

Access: Use of this item is restricted to the UNT Community.
Date: December 2013
Creator: Abouelenien, Mohamed
Description: In many real-world applications, it is common to have uneven number of examples among multiple classes. The data imbalance, however, usually complicates the learning process, especially for the minority classes, and results in deteriorated performance. Boosting methods were proposed to handle the imbalance problem. These methods need elongated training time and require diversity among the classifiers of the ensemble to achieve improved performance. Additionally, extending the boosting method to handle multi-class data sets is not straightforward. Examples of applications that suffer from imbalanced multi-class data can be found in face recognition, where tens of classes exist, and in capsule endoscopy, which suffers massive imbalance between the classes. This dissertation introduces RegBoost, a new boosting framework to address the imbalanced, multi-class problems. This method applies a weighted stratified sampling technique and incorporates a regularization term that accommodates multi-class data sets and automatically determines the error bound of each base classifier. The regularization parameter penalizes the classifier when it misclassifies instances that were correctly classified in the previous iteration. The parameter additionally reduces the bias towards majority classes. Experiments are conducted using 12 diverse data sets with moderate to high imbalance ratios. The results demonstrate superior performance of the proposed method compared ...
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Bounded Dynamic Source Routing in Mobile Ad Hoc Networks

Bounded Dynamic Source Routing in Mobile Ad Hoc Networks

Access: Use of this item is restricted to the UNT Community.
Date: August 2003
Creator: George, Glyco
Description: A mobile ad hoc network (MANET) is a collection of mobile platforms or nodes that come together to form a network capable of communicating with each other, without the help of a central controller. To avail the maximum potential of a MANET, it is of great importance to devise a routing scheme, which will optimize upon the performance of a MANET, given the high rate of random mobility of the nodes. In a MANET individual nodes perform the routing functions like route discovery, route maintenance and delivery of packets from one node to the other. Existing routing protocols flood the network with broadcasts of route discovery messages, while attempting to establish a route. This characteristic is instrumental in deteriorating the performance of a MANET, as resource overhead triggered by broadcasts is directly proportional to the size of the network. Bounded-dynamic source routing (B-DSR), is proposed to curb this multitude of superfluous broadcasts, thus enabling to reserve valuable resources like bandwidth and battery power. B-DSR establishes a bounded region in the network, only within which, transmissions of route discovery messages are processed and validated for establishing a route. All route discovery messages reaching outside of this bounded region are dropped, thus ...
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Building an Intelligent Filtering System Using Idea Indexing

Building an Intelligent Filtering System Using Idea Indexing

Date: August 2003
Creator: Yang, Li
Description: The widely used vector model maintains its popularity because of its simplicity, fast speed, and the appeal of using spatial proximity for semantic proximity. However, this model faces a disadvantage that is associated with the vagueness from keywords overlapping. Efforts have been made to improve the vector model. The research on improving document representation has been focused on four areas, namely, statistical co-occurrence of related items, forming term phrases, grouping of related words, and representing the content of documents. In this thesis, we propose the idea-indexing model to improve document representation for the filtering task in IR. The idea-indexing model matches document terms with the ideas they express and indexes the document with these ideas. This indexing scheme represents the document with its semantics instead of sets of independent terms. We show in this thesis that indexing with ideas leads to better performance.
Contributing Partner: UNT Libraries
Case-Based Reasoning for Children Story Selection in ASP.NET

Case-Based Reasoning for Children Story Selection in ASP.NET

Date: December 2003
Creator: Hu, Demin
Description: 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.
Contributing Partner: UNT Libraries
CLUE: A Cluster Evaluation Tool

CLUE: A Cluster Evaluation Tool

Date: December 2006
Creator: Parker, Brandon S.
Description: Modern high performance computing is dependent on parallel processing systems. Most current benchmarks reveal only the high level computational throughput metrics, which may be sufficient for single processor systems, but can lead to a misrepresentation of true system capability for parallel systems. A new benchmark is therefore proposed. CLUE (Cluster Evaluator) uses a cellular automata algorithm to evaluate the scalability of parallel processing machines. The benchmark also uses algorithmic variations to evaluate individual system components' impact on the overall serial fraction and efficiency. CLUE is not a replacement for other performance-centric benchmarks, but rather shows the scalability of a system and provides metrics to reveal where one can improve overall performance. CLUE is a new benchmark which demonstrates a better comparison among different parallel systems than existing benchmarks and can diagnose where a particular parallel system can be optimized.
Contributing Partner: UNT Libraries
A Comparison of Agent-Oriented Software Engineering Frameworks and Methodologies

A Comparison of Agent-Oriented Software Engineering Frameworks and Methodologies

Date: December 2003
Creator: Lin, Chia-En
Description: Agent-oriented software engineering (AOSE) covers issues on developing systems with software agents. There are many techniques, mostly agent-oriented and object-oriented, ready to be chosen as building blocks to create agent-based systems. There have been several AOSE methodologies proposed intending to show engineers guidelines on how these elements are constituted in having agents achieve the overall system goals. Although these solutions are promising, most of them are designed in ad-hoc manner without truly obeying software developing life-cycle fully, as well as lacking of examinations on agent-oriented features. To address these issues, we investigated state-of-the-art techniques and AOSE methodologies. By examining them in different respects, we commented on the strength and weakness of them. Toward a formal study, a comparison framework has been set up regarding four aspects, including concepts and properties, notations and modeling techniques, process, and pragmatics. Under these criteria, we conducted the comparison in both overview and detailed level. The comparison helped us with empirical and analytical study, to inspect the issues on how an ideal agent-based system will be formed.
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Computational Complexity of Hopfield Networks

Computational Complexity of Hopfield Networks

Date: August 1998
Creator: Tseng, Hung-Li
Description: There are three main results in this dissertation. They are PLS-completeness of discrete Hopfield network convergence with eight different restrictions, (degree 3, bipartite and degree 3, 8-neighbor mesh, dual of the knight's graph, hypercube, butterfly, cube-connected cycles and shuffle-exchange), exponential convergence behavior of discrete Hopfield network, and simulation of Turing machines by discrete Hopfield Network.
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Computational Epidemiology - Analyzing Exposure Risk: A Deterministic, Agent-Based Approach

Computational Epidemiology - Analyzing Exposure Risk: A Deterministic, Agent-Based Approach

Date: August 2009
Creator: O'Neill II, Martin Joseph
Description: 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 ...
Contributing Partner: UNT Libraries
Content-based image retrieval by integration of metadata encoded multimedia (image and text) features in constructing a video summarizer application.

Content-based image retrieval by integration of metadata encoded multimedia (image and text) features in constructing a video summarizer application.

Date: May 2003
Creator: Anusuri, Ramprasad
Description: Content-based image retrieval (CBIR) is the retrieval of images from a collection by means of internal feature measures of the information content of the images. In CBIR systems, text media is usually used only to retrieve exemplar images for further searching by image feature content. This research work describes a new method for integrating multimedia text and image content features to increase the retrieval performance of the system. I am exploring the content-based features of an image extracted from a video to build a storyboard for search retrieval of images. Metadata encoded multimedia features include extracting primitive features like color, shape and text from an image. Histograms are built for all the features extracted and stored in a database. Images are searched based on comparing these histogram values of the extracted image with the stored values. These histogram values are used for extraction of keyframes from a collection of images parsed from a video file. Individual shots of images are extracted from a video clip and run through processes that extract the features and build the histogram values. A keyframe extraction algorithm is run to get the keyframes from the collection of images to build a storyboard of images. In ...
Contributing Partner: UNT Libraries