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Full-Text Articles in Computer Sciences

Enabling Runtime Profiling To Hide And Exploit Heterogeneity Within Chip Heterogeneous Multiprocessor Systems (Chmps), Eugene Cartwright May 2016

Enabling Runtime Profiling To Hide And Exploit Heterogeneity Within Chip Heterogeneous Multiprocessor Systems (Chmps), Eugene Cartwright

Graduate Theses and Dissertations

The heterogeneity of multiprocessor systems on chip (MPSoC) has presented unique opportunities for furthering today’s diverse application needs. FPGA-based MPSoCs have the potential of bridging the gap between generality and specialization but has traditionally been limited to device experts. The flexibility of these systems can enable computation without compromise but can only be realized if this flexibility extends throughout the software stack. At the top of this stack, there has been significant effort for leveraging the heterogeneity of the architecture. However, the betterment of these abstractions are limited to what the bottom of the stack exposes: the runtime system.

The …


A Solar-Powered And Multi-Tiered Mesh Node For A Portable In Situ Emergency Response System, Adam Matthews Dec 2013

A Solar-Powered And Multi-Tiered Mesh Node For A Portable In Situ Emergency Response System, Adam Matthews

Graduate Theses and Dissertations

The aftermath of a natural disaster is typically characterized by lack of a reliable medium for dissemination of information to survivors. Current state-of-the-art emergency response systems rely on satellite radio-enabled devices, but survivors, unlike first responders, do not have access to such devices. To mitigate this problem, we present PERPETUU a solar-powered portable GIS microserver. The microserver node can be deployed in a disaster scene, and can serve maps to survivors viewable on browsers of off-the-shelf mobile systems. A key innovation in the design of the PERPETUU node is a multi-tiered hardware architecture-the system combines a low-power micro-controller, a medium-power …


High Performance Geospatial Analysis On Emerging Parallel Architectures, Seth Warn Dec 2011

High Performance Geospatial Analysis On Emerging Parallel Architectures, Seth Warn

Graduate Theses and Dissertations

Geographic information systems (GIS) are performing increasingly sophisticated analyses on growing data sets. These analyses demand high performance. At the same time, modern computing platforms increasingly derive their performance from several forms of parallelism. This dissertation explores the available parallelism in several GIS-applied algorithms: viewshed calculation, image feature transform, and feature analysis. It presents implementations of these algorithms that exploit parallel processing to reduce execution time, and analyzes the effectiveness of the implementations in their use of parallel processing.


Consolidated Study On Query Expansion, Abhishek Biruduraju Dec 2011

Consolidated Study On Query Expansion, Abhishek Biruduraju

UNLV Theses, Dissertations, Professional Papers, and Capstones

A typical day of million web users all over the world starts with a simple query. The quest for information on a particular topic drives them to search for it, and in the pursuit of their info the terms they supply for queries varies from person to person depending on the knowledge they have. With a vast collection of documents available on the web universe it is the onus of the retrieval system to return only those documents that are relevant and satisfy the user’s search requirements. The document mismatch problem is resolved by appending extra query terms to the …


Study Of Feature Selection Algorithms For Text-Categorization, Kandarp Dave Dec 2011

Study Of Feature Selection Algorithms For Text-Categorization, Kandarp Dave

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis will discuss feature selection algorithms for text-categorization. Feature selection algorithms are very important, as they can make-or-break a categorization engine. The feature selection algorithms that will be discussed in this thesis are Document Frequency, Information Gain, Chi Squared, Mutual Information, NGL (Ng-Goh-Low) coefficient, and GSS (Galavotti-Sebastiani-Simi) coefficient . The general idea of any feature selection algorithm is to determine importance of words using some measure that can keep informative words, and remove non-informative words, which can then help the text-categorization engine categorize a document, D , into some category, C . These feature selection methods are explained, implemented, …