Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 30 of 31
Full-Text Articles in Entire DC Network
Detection Algorithms For The Nano Nose, J. M. Karthikeya Udayagiri V. R.
Detection Algorithms For The Nano Nose, J. M. Karthikeya Udayagiri V. R.
UNLV Retrospective Theses & Dissertations
The Nano nose is an instrument with an array of nano sized optical sensors that produces digital patterns when exposed to radiation passing through a gaseous mixture. The digital patterns correspond to the amount of photocurrent registered on each of the sensors. The problem is to find the gas constituents in the gaseous mixture and estimate their concentrations. This thesis outlines an algorithm using a combination of a mixed gas detector and a gas concentration predictor. The mixed gas detector is an array of neural networks corresponding to the number of gases. There are two techniques outlined for the implementation …
T-Theory And Analysis Of Online Algorithms, James Oravec
T-Theory And Analysis Of Online Algorithms, James Oravec
UNLV Retrospective Theses & Dissertations
Several advancements in Online Algorithms can be credited to T-theory, a field of discrete mathematics. T-theory has aided in the development of several online algorithms for the k-server problem, although the standard notation of T-theory was not used at the time of their creation; A summary of the k-server problem, and some important concepts of T-theory, are given. A number of known k-server results are restated using the established terminology of T-theory. Included is a 3-competitiveness proof, using T-theory, for the HARMONIC algorithm for two servers, which was presented in a paper by Larmore and Oravec [71]; Previously, the Knowledge …
Study Of Document Clustering Using The K-Means Algorithm, Meghna Sharma Gummuluru
Study Of Document Clustering Using The K-Means Algorithm, Meghna Sharma Gummuluru
UNLV Retrospective Theses & Dissertations
One of the most commonly used data mining techniques is document clustering or unsupervised document classification which deals with the grouping of documents based on some document similarity function; This thesis deals with research issues associated with categorizing documents using the k-means clustering algorithm which groups objects into K number of groups based on document representations and similarities; The proposed hypothesis of this thesis is to prove that unsupervised clustering of a set of documents produces similar results to that of their supervised categorization.
An Improved Algorithm For Deinterlacing Video Streams, Christopher Weiss
An Improved Algorithm For Deinterlacing Video Streams, Christopher Weiss
UNLV Retrospective Theses & Dissertations
The MPEG-4 standard for computerized video incorporates the concept of a video object pLane While in the simplest case this can be the full rectangular frame, the standard supports a hierarchical set of arbitrary shaped planes, one for each content sensitive video object. Herein is proposed a method for extracting arbitrary planes from video that does not already contain video object plane information; Deinterlacing is the process of taking two video fields, each at half the height of the finalized image frame, and combining them into that finalized frame. As the fields are not captured simultaneously, temporal artifacts may result. …
Distributed Self-(Star) Minimum Connected Sensor Cover Algorithms, Rajesh Patel
Distributed Self-(Star) Minimum Connected Sensor Cover Algorithms, Rajesh Patel
UNLV Retrospective Theses & Dissertations
Wireless ad-hoc sensor networks are composed of a large number of tiny sensors with embedded microprocessors, that have very limited resources and yet must coordinate amongst themselves to form a connected network. Every sensor has a certain sensing radius, Rs, within which it is capable of "covering" a particular region by detecting or gathering certain data. Every sensor also has a communication radius, R c, within which it is capable of sending or receiving data; Given a query over a sensor network, the minimum connected sensor cover problem is to select a minimum, or nearly minimum, set of sensors, called …
Implementation And Analysis Of Apriori Algorithm For Data Mining, Pavankumar Bondugula
Implementation And Analysis Of Apriori Algorithm For Data Mining, Pavankumar Bondugula
UNLV Retrospective Theses & Dissertations
Data mining represents the process of extracting interesting and previously unknown knowledge from data. In this thesis we address the important data mining problem of discovering association rules. An association rule expresses the dependence of a set of attribute-value pairs, also called items, upon another set of items; We also report on various implementation techniques for the well-known Apriori Algorithm and their time complexity.
Analyzing Association Rules Produced By Applying The Apriori Algorithm To Structured Data, Darshana Gala
Analyzing Association Rules Produced By Applying The Apriori Algorithm To Structured Data, Darshana Gala
UNLV Retrospective Theses & Dissertations
In this thesis, we will use various techniques from data mining to draw interesting results from a set of structured data on personal privacy information. In particular, the well-known, Apriori Algorithm will be used to find frequent item sets and association rules in this data. This process has been shown to be effective in predicting the presence of one type of data when other data is present in other data mining applications; The thesis will also include a detailed analysis of rules generated by the algorithm and their natural interpretations.
Current Video Compression Algorithms: Comparisons, Optimizations, And Improvements, Douglas Scott Price
Current Video Compression Algorithms: Comparisons, Optimizations, And Improvements, Douglas Scott Price
UNLV Retrospective Theses & Dissertations
Compression algorithms have evolved significantly in recent years. Audio, still image, and video can be compressed significantly by taking advantage of the natural redundancies that occur within them. Video compression in particular has made significant advances. MPEG-1 and MPEG-2, two of the major video compression standards, allowed video to be compressed at very low bit rates compared to the original video. The compression ratio for video that is perceptually lossless (losses can't be visually perceived) can even be as high as 40 or 50 to 1 for certain videos. Videos with a small degradation in quality can be compressed at …
Genetic Algorithms For The Traveling Salesman Problem Using Edge Assembly Crossovers, Dwain Alan Seppala
Genetic Algorithms For The Traveling Salesman Problem Using Edge Assembly Crossovers, Dwain Alan Seppala
UNLV Retrospective Theses & Dissertations
The central issue in creating new genetic algorithms is the algorithm's crossover method. My focus is on a particular crossover known as the Edge Assembly Crossover, or EAX, by Nagata and Kobayashi. The basics of a what make up a genetic algorithm is reviewed. The traveling salesman problem is defined. The EAX as an algorithm within an algorithm is explained. The crossover's implementation is original and is listed. The use of the graphic user interface, TSP View, used to run algorithms is explained as well as the extensions to the interface that were implemented for this study. The results of …
Alternate Path Routing Algorithm For Traffic Engineering In The Internet, Shyam Subramanian
Alternate Path Routing Algorithm For Traffic Engineering In The Internet, Shyam Subramanian
UNLV Retrospective Theses & Dissertations
Data flowing through the internet continues to grow every year. Increase in traffic demands increase in bandwidth. But bandwidth1 does not grow as fast as the traffic. This leads to congestion in the network and performance degradation. One way to avoid this problem is to use efficient routing algorithm that efficiently maps the flow of data onto the network; The most often used routing algorithm in the internet is the shortest path algorithm (Dijkstra's algorithm). This algorithm is simple and easy to implement. But this algorithm leads to over-utilization of part of the network, while the other part remains under-utilized. …
Approximation Algorithms For Multi-Facility Location, Prashanth Kodela
Approximation Algorithms For Multi-Facility Location, Prashanth Kodela
UNLV Retrospective Theses & Dissertations
This thesis deals with the development and implementation of efficient algorithms to obtain acceptable solutions for the location of several facilities to serve customer sites. The general version of facility location problem is known to be NP-hard; For locating multiple facilities we use Voronoi diagram of initial facility locations to partition the customer sites into k clusters. On each Voronoi region, solutions for single facility problem is obtained by using both Weizfield's algorithm and Center of Gravity. The customer space is again partitioned by using the newly computed locations. This iteration is continued to obtain a better solution for multi-facility …
Self-Stabilizing Interval Routing Algorithm With Low Stretch Factor, Sripriya Sundaram
Self-Stabilizing Interval Routing Algorithm With Low Stretch Factor, Sripriya Sundaram
UNLV Retrospective Theses & Dissertations
A compact routing scheme is a routing strategy which suggests routing tables that are space efficient compared to traditional all-pairs shortest path routing algorithms. An Interval Routing algorithm is a compact routing algorithm which uses a routing table at every node in which a set of destination addresses that use the same output port are grouped into intervals of consecutive addresses. Self-stabilization is a property by which a system is guaranteed to reach a legitimate state in a finite number of steps starting from any arbitrary state. A self-stabilizing Pivot Interval Routing (PIR) algorithm is proposed in this work. The …
Self-Stabilizing Binary Search Tree Maintenance Algorithm, Sylvain Ronan Brigant
Self-Stabilizing Binary Search Tree Maintenance Algorithm, Sylvain Ronan Brigant
UNLV Retrospective Theses & Dissertations
Binary search tree is one of the most studied data structures. The main application of the binary search tree is in implementing efficient search operations. A binary search tree is a special binary tree which satisfies the property that for every processor p in the binary tree, the values of all the keys in the left subtree of p are smaller than that of p, and the values of all the keys in the right subtree of p are larger than that of p; We present a self-stabilizing [Dij74] algorithm to maintain a binary search tree given a binary tree …
Two New Algorithms For Classical Problems In Computer Science, John Gerard Howe
Two New Algorithms For Classical Problems In Computer Science, John Gerard Howe
UNLV Retrospective Theses & Dissertations
This thesis presents two algorithms dealing with problems in two classic algorithm areas in computer science. The first algorithm presents a simple solution to the selection problem. The sequential computing model form of this selection algorithm is presented first followed by a general parallel computing model version; The second algorithm is a relatively simple bookkeeping approximation solution to the Steiner tree problem in graphs. The problem presented deals with determining the shortest tree connecting Steiner nodes in a graph that has no direct connections between the Steiner nodes. Both algorithms are described and analyzed in detail with an appropriate running …
Fast Algorithms For Wavelet-Based Analysis Of Hyperspectral Signatures, Jiang Li
Fast Algorithms For Wavelet-Based Analysis Of Hyperspectral Signatures, Jiang Li
UNLV Retrospective Theses & Dissertations
Hyperspectral sensors promise great improvements in the quality of information gathered for remote sensing applications. However, they also present a huge challenge to data storage and computing systems. Thus there is a great need for reliable compression schemes, as well as analysis tools that can exploit the hyperspectral data in a computationally efficient manner. It has been proposed that wavelet-based methods may be superior to currently used methods for the analysis of hyperspectral signatures. In this thesis, a wavelet-based method, as well as traditional analytical methods, was implemented and applied to hyperspectral images. The computational expense of the various methods …
Self-Stabilizing Network Orientation Algorithms In Arbitrary Rooted Networks, Shivashankar Gurumurthy
Self-Stabilizing Network Orientation Algorithms In Arbitrary Rooted Networks, Shivashankar Gurumurthy
UNLV Retrospective Theses & Dissertations
Network orientation is the problem of assigning different labels to the edges at each processor, in a globally consistent manner. A self-stabilizing protocol guarantees that the system will arrive at a legitimate state in finite time, irrespective of the initial state of the system. Two deterministic distributed network orientation protocols on arbitrary rooted, asynchronous networks are proposed in this work. Both protocols set up a chordal sense of direction in the network. The protocols are self-stabilizing, meaning that starting from an arbitrary state, the protocols are guaranteed to reach a state in which every processor has a valid node label …
Genetic Algorithms Using Galib, Bradley John Hendricks
Genetic Algorithms Using Galib, Bradley John Hendricks
UNLV Retrospective Theses & Dissertations
GAlib is a C++ library of genetic algorithm objects that was recently developed at the Massachusetts Institute of Technology. This thesis is to demonstrate its functionality and versatility for implementing haploid tripartite genetic algorithms; We first built a test bed in which GAlib could be used. To achieve this, we used GAlib to solve the Traveling Salesman Problem and implemented two-opt and simulated annealing for compariSon We then examined the use of genetic algorithms for finding loop invariants. We used GAlib successfully to build a model but results remain inconclusive; In our main thrust we applied genetic algorithms to train …
Algorithms For Document Image Skew Estimation, Andrew David Bagdanov
Algorithms For Document Image Skew Estimation, Andrew David Bagdanov
UNLV Retrospective Theses & Dissertations
A new projection profile based skew estimation algorithm was developed. This algorithm extracts fiducial points representing character elements by decoding a JBIG compressed image without reconstructing the original image. These points are projected along parallel lines into an accumulator array to determine the maximum alignment and the corresponding skew angle. Methods for characterizing the performance of skew estimation techniques were also investigated. In addition to the new skew estimator, three projection based algorithms were implemented and tested using 1,246 single column text zones extracted from a sample of 460 page images. Linear regression analyses of the experimental results indicate that …
General Broadcasting Algorithms In One-Port Wormhole Routed Hypercubes, Myung Hoon Lee
General Broadcasting Algorithms In One-Port Wormhole Routed Hypercubes, Myung Hoon Lee
UNLV Retrospective Theses & Dissertations
Wormhole routing has been accepted as an efficient switching mechanism in point-to-point interconnection networks. Here the network resource, i.e. node buffers and communication channels, are effectively utilized to deliver message across the network; We consider the problem of broadcasting a message in the hypercue equipped with the wormhole switching mechanism. The model is a generalization of an earlier work and considers a broadcast path-length of {dollar}m\ (1\leq m\leq n{dollar}) in the n-cube with a single-port communication capability. In this thesis, the scheme of e-cube and a Gray code path routing and intermediate reception capability have been adopted in order to …
Self-Stabilizing Sorting Algorithms, Joseph Chacko
Self-Stabilizing Sorting Algorithms, Joseph Chacko
UNLV Retrospective Theses & Dissertations
A distributed system consists of a set of machines which do not share a global memory. Depending on the connectivity of the network, each machine gets a partial view of the global state. Transient failures in one area of the network may go unnoticed in other areas and may cause the system to go to an illegal global state. However, if the system were self-stabilizing, it would be guaranteed that regardless of the current state, the system would recover to a legal configuration in a finite number of moves; The traditional way of creating reliable systems is to make redundant …
Adaptive Sorting Algorithms For Evaluation Of Automatic Zoning, G. S Rajarathinam
Adaptive Sorting Algorithms For Evaluation Of Automatic Zoning, G. S Rajarathinam
UNLV Retrospective Theses & Dissertations
Optical Character Recognition (OCR) involves analysis of machine-printed and hand written document images. The first step in an OCR process is to locate the text to be recognized on a page. An OCR device tries to identify the characters in these text regions and outputs the characters in ASCII. To evaluate the performance of any OCR device, the ASCII output of the OCR device is compared with the ground truth text which is entered into the computer manually; Some OCR devices provide the users with automatic zoning. The output of any automatic zoning algorithm has to be corrected manually to …
Self-Stabilizing Tree Algorithms, Visalakshi Thiagarajan
Self-Stabilizing Tree Algorithms, Visalakshi Thiagarajan
UNLV Retrospective Theses & Dissertations
Designers of distributed algorithms have to contend with the problem of making the algorithms tolerant to several forms of coordination loss, primarily faulty initialization. The processes in a distributed system do not share a global memory and can only get a partial view of the global state. Transient failures in one part of the system may go unnoticed in other parts and thus cause the system to go into an illegal state. If the system were self-stabilizing, however, it is guaranteed that it will return to a legal state after a finite number of state transitions. This thesis presents and …
Self-Stabilizing Distributed Algorithms For Acyclic Graphs, Viruthagiri Natarajan
Self-Stabilizing Distributed Algorithms For Acyclic Graphs, Viruthagiri Natarajan
UNLV Retrospective Theses & Dissertations
A self-stabilizing distributed system is a network of processors, which when started from an arbitrary and possibly illegal state, always returns to a legal state in a finite number of steps. Two self-stabilizing protocols for distributed systems are presented in this thesis. The first protocol topologically sorts the processors in a distributed system of directed acyclic graph (DAG) topology and uses this information to build a shortest path routing table in each node in the system to all accessible nodes from that node. The second protocol determines the rank of the individual processors in a distributed tree network based on …
Performance Evaluation Of Distributed Mutual Exclusion Algorithms, Kenneth B Been
Performance Evaluation Of Distributed Mutual Exclusion Algorithms, Kenneth B Been
UNLV Retrospective Theses & Dissertations
In any system in which concurrent processes share resources, mutual exclusion refers to the problem of guaranteeing the integrity of those resources by restricting their use to one process at a time. Due the complex nature of distributed systems, distributed mutual exclusion algorithms are often not amenable to theoretical analysis for performance or even correctness. Experimental inquiries are therefore warranted. This thesis investigates seven well known distributed mutual exclusion algorithms in detail, and uses computer simulation to evaluate the performance and applicability of these various algorithms. Toward this end, a realistic and general model for evaluating distributed algorithms is proposed. …
Self-Stabilizing Deadlock Algorithms In Distributed Systems, Mitchell Elliott Flatebo
Self-Stabilizing Deadlock Algorithms In Distributed Systems, Mitchell Elliott Flatebo
UNLV Retrospective Theses & Dissertations
A self-stabilizing system is a network of processors, which, when started from an arbitrary (and possibly illegal) initial state, always returns to a legal state in a finite number of steps. Self-stabilization is an evolving paradigm in fault-tolerant computing. This research will be the first time self-stabilization is used in the areas of deadlock detection and prevention. Traditional deadlock detection algorithms have a process initiate a probe. If that probe travels around the system and is received by the initiator, there is a cycle in the system, and deadlock is detected. In order to prevent deadlocks, algorithms usually rank nodes …
Formal Verification Of Distributed Deadlock Detection Algorithms, Brian Matt Johnston
Formal Verification Of Distributed Deadlock Detection Algorithms, Brian Matt Johnston
UNLV Retrospective Theses & Dissertations
The problem of distributed deadlock detection has undergone extensive study. Formal verification of deadlock detection algorithms in distributed systems is an area of research that has largely been ignored. Instead, most proposed distributed deadlock detection algorithms have used informal or intuitive arguments, simulation or just neglect the entire aspect of verification of correctness; As a consequence, many of these algorithms have been shown incorrect. This research will abstract the notion of deadlock in terms of a temporal logic of actions and discuss the invariant and eventuality properties. The contributions of this research are the development of a distributed deadlock detection …
Practical Algorithms For Image Compression And Surface Estimation, Matthew Y Au
Practical Algorithms For Image Compression And Surface Estimation, Matthew Y Au
UNLV Retrospective Theses & Dissertations
Practical Algorithms for Image Compression and Surface Estimation describes three algorithms for image compression and one algorithm for surface estimation that incorporates kriging and parametric cubic splines. Two of the image compression algorithms are innovative extensions of the Run Length Encoding image compression algorithm and the third is an image compression technique based on kriging. In general the modified Run Length Encoding algorithms yield a better compression ratio by a factor of two while retaining fast decompression of the image. The algorithm based on kriging achieves a compression ratio up to 250:1 and is unique in that the compressed image …
The Use Of Synthesized Images To Evaluate The Performance Of Ocr Devices And Algorithms, Frank Robert Jenkins
The Use Of Synthesized Images To Evaluate The Performance Of Ocr Devices And Algorithms, Frank Robert Jenkins
UNLV Retrospective Theses & Dissertations
This thesis will attempt to establish if synthesized images can be used to predict the performance of Optical Character Recognition (OCR) algorithms and devices. The value of this research lies in reducing the considerable costs associated with preparing test images for OCR research. The paper reports on a series of experiments in which synthesized images of text files in nine different fonts and sizes are input to eight commercial OCR devices. The method used to create the images is explained and a detailed analysis of the character and word confusion between the output and the true text files is presented. …
Algorithms For Automatic Parallelism, Optimization, And Optimal Processor Utilization, Katharine J Macke
Algorithms For Automatic Parallelism, Optimization, And Optimal Processor Utilization, Katharine J Macke
UNLV Retrospective Theses & Dissertations
In this thesis we first investigate the reaching definitions optimization. This compiler optimization collects and stores information about where a variable is defined and how long that definition of the variable stays alive before it is redefined. We compare the old iterative solution to a new algorithm that uses the partialout concept. The partialout solution decreases execution time by eliminating the multiple passes required in the iterative solution. Currently, compilers that find a data dependence between two statements in a loop do not parallelize the loop. Next we investigate automatic parallelism for these loops by breaking the loop into a …
Distributed Mutual Exclusion Algorithms, Paul Banta
Distributed Mutual Exclusion Algorithms, Paul Banta
UNLV Retrospective Theses & Dissertations
In this thesis we present three original algorithms which solve the distributed mutual exclusion problem. Two of the three solve the problem of allowing only one site at a time into the critical section. The third solves the more difficult problem of allowing a specific number of sites (k sites) into the critical section at a time; All three algorithms are "Token Based". That is, they make use of a token and token queue in order to guarantee mutual exclusion. Only the site that currently has the token is allowed to enter its critical section in the 1 mutual exclusion …