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Full-Text Articles in Physical Sciences and Mathematics
A Hierarchical Approach To Improve The Ant Colony Optimization Algorithm, Bryan J. Fischer
A Hierarchical Approach To Improve The Ant Colony Optimization Algorithm, Bryan J. Fischer
EWU Masters Thesis Collection
The ant colony optimization algorithm (ACO) is a fast heuristic-based method for finding favorable solutions to the traveling salesman problem (TSP). When the data set reaches larger values however, the ACO runtime increases dramatically. As a result, clustering nodes into groups is an effective way to reduce the size of the problem while leveraging the advantages of the ACO algorithm. The method for recombining groups of nodes is explored by treating the graph as a hierarchy of clusters, and modifying the original ACO heuristic to operate on a hypergraph. This method of using hierarchical clustering is significantly faster than the …
Comparison Of The Tally Numbering System To Traditional Arithmetic Systems In Field Programmable Gate Arrays, Robert Paul Shredow
Comparison Of The Tally Numbering System To Traditional Arithmetic Systems In Field Programmable Gate Arrays, Robert Paul Shredow
EWU Masters Thesis Collection
This research explores the use of heterogeneous computing platforms for use in machine learning as well as different neural network architectures. These platforms and architectures can be used to accelerate the complex operations that are required for machine learning, more specifically neural networks. The use of different architectures, implementing different types of numbering and mathematics systems is explored in hopes of accelerating mathematical functions. The heterogeneous computing platform explored in this thesis is a Field Programmable Gate Arrays (FPGA), specifically a SoC/FPGA which is a ARM CPU and a FPGA in the same chip. FPGAs are unique because they are …
Glyph Based Segmentation Of Chinese Calligraphy Characters In The "Collected Characters" Stele., David A. Mcinnis
Glyph Based Segmentation Of Chinese Calligraphy Characters In The "Collected Characters" Stele., David A. Mcinnis
EWU Masters Thesis Collection
Text character segmentation is the process of detecting the bounding box position of individual characters within a written text document image. The character segmentation problem remains extremely difficult for ancient Chinese calligraphy documents. This paper examines a glyph-based segmentation technique for segmenting Chinese Calligraphy characters in the "Collected Characters". The glyph-based character segmentation pipeline utilizes a combination of well-understood image processing techniques in a novel pipeline which is able to detect Chinese calligraphy characters from ink-blots with a good reliability.
A Practical And Efficient Algorithm For The K-Mismatch Shortest Unique Substring Finding Problem, Daniel Robert Allen
A Practical And Efficient Algorithm For The K-Mismatch Shortest Unique Substring Finding Problem, Daniel Robert Allen
EWU Masters Thesis Collection
This thesis revisits the k-mismatch shortest unique substring (SUS) finding problem and demonstrates that a technique recently presented in the context of solving the k-mismatch average common substring problem can be adapted and combined with parts of the existing solution, resulting in a new algorithm which has expected time complexity of O(n logk n), while maintaining a practical space complexity at O(kn), where n is the string length. When k > 0, which is the hard case, the new proposal significantly improves the any-case O(n2) time complexity of the prior best method for k-mismatch SUS finding. Experimental study …
Gpu Accelerated Risk Quantification, Forrest L. Ireland
Gpu Accelerated Risk Quantification, Forrest L. Ireland
EWU Masters Thesis Collection
Factor Analysis of Information Risk (FAIR) is a standard model for quantitatively estimating cybersecurity risks and has been implemented as a sequential Monte Carlo simulation in the RiskLens and FAIR-U applications. Monte Carlo simulations employ random sampling techniques to model certain systems through the course of many iterations. Due to their sequential nature, FAIR simulations in these applications are limited in the number of iterations they can perform in a reasonable amount of time. One method that has been extensively used to speed up Monte Carlo simulations is to implement them to take advantage of the massive parallelization available when …
Evaluating A Cluster Of Low-Power Arm64 Single-Board Computers With Mapreduce, Daniel Mcdermott
Evaluating A Cluster Of Low-Power Arm64 Single-Board Computers With Mapreduce, Daniel Mcdermott
EWU Masters Thesis Collection
With the meteoric rise of enormous data collection in science, industry, and the cloud, methods for processing massive datasets have become more crucial than ever. MapReduce is a restricted programing model for expressing parallel computations as simple serial functions, and an execution framework for distributing those computations over large datasets residing on clusters of commodity hardware. MapReduce abstracts away the challenging low-level synchronization and scalability details which parallel and distributed computing often necessitate, reducing the concept burden on programmers and scientists who require data processing at-scale. Typically, MapReduce clusters are implemented using inexpensive commodity hardware, emphasizing quantity over quality due …