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Reliability Models For Hpc Applications And A Cloud Economic Model, Thanadech Thanakornworakij 2012 Louisiana Tech University

Reliability Models For Hpc Applications And A Cloud Economic Model, Thanadech Thanakornworakij

Doctoral Dissertations

With the enormous number of computing resources in HPC and Cloud systems, failures become a major concern. Therefore, failure behaviors such as reliability, failure rate, and mean time to failure need to be understood to manage such a large system efficiently.

This dissertation makes three major contributions in HPC and Cloud studies. First, a reliability model with correlated failures in a k-node system for HPC applications is studied. This model is extended to improve accuracy by accounting for failure correlation. Marshall-Olkin Multivariate Weibull distribution is improved by excess life, conditional Weibull, to better estimate system reliability. Also, the univariate …


Meta-Heuristics Analysis For Technologically Complex Programs: Understanding The Impact Of Total Constraints For Schedule, Quality And Cost, Henry Darrel Webb 2012 Old Dominion University

Meta-Heuristics Analysis For Technologically Complex Programs: Understanding The Impact Of Total Constraints For Schedule, Quality And Cost, Henry Darrel Webb

EMSE Doctoral Projects

Program management data associated with a technically complex radio frequency electronics base communication system has been collected and analyzed to identify heuristics which may be utilized in addition to existing processes and procedures to provide indicators that a program is trending to failure. Analysis of the collected data includes detailed schedule analysis, detailed earned value management analysis and defect analysis within the framework of a Firm Fixed Price (FFP) incentive fee contract.

This project develops heuristics and provides recommendations for analysis of complex project management efforts such as those discussed herein. The analysis of the effects of the constraints on …


Response Surface Optimization Of Electron Beam Freeform Fabrication Depositions Using Design Of Experiments, Patricia A. Quigley 2012 Old Dominion University

Response Surface Optimization Of Electron Beam Freeform Fabrication Depositions Using Design Of Experiments, Patricia A. Quigley

Engineering Management & Systems Engineering Theses & Dissertations

The Electron Beam Freeform Fabrication (EBF3 ) System is a material depositing, layer additive technique that produces three dimensional (3D) parts out of a wide range of metals in high vacuum, using an electron beam and wire feedstock. Screening deposition trials on a titanium alloy, Ti-6Al-4V, at the National Aeronautics Space Administration (NASA) revealed selective vaporization of the aluminum content of linear prototypes when subjected to chemical analysis. In this study, the aluminum content, bead height and bead width output responses were analyzed from a systematic study of the effects that the interactions of the EBF3 processing parameters …


A Statistical Model To Determine Multiple Binding Sites Of A Transcription Factor On Dna Using Chip-Seq Data, Rasika Jayatillake 2012 Old Dominion University

A Statistical Model To Determine Multiple Binding Sites Of A Transcription Factor On Dna Using Chip-Seq Data, Rasika Jayatillake

Mathematics & Statistics Theses & Dissertations

Protein-DNA interaction is vital to many biological processes in cells such as cell division, embryo development and regulating gene expression. Chromatin Immunoprecipitation followed by massively parallel sequencing (ChIP-seq) is a new technology that can reveal protein binding sites in genome with superior accuracy. Although many methods have been proposed to find binding sites for ChIP-seq data, they can find only one binding site within a short region of the genome. In this study we introduce a statistical model to identify multiple binding sites of a transcription factor within a short region of the genome using the ChIP-seq data. Mapped sequence …


Investigation Of Trends And Predictive Effectiveness Of Crash Severity Models, James E. Mooradian 2012 University of Connecticut

Investigation Of Trends And Predictive Effectiveness Of Crash Severity Models, James E. Mooradian

Master's Theses

This thesis describes analysis using ordinal logistic regression to uncover temporal patterns in the severity level (fatal, serious injury, minor injury, slight injury or no injury) for persons involved in highway crashes in Connecticut, focusing on the demographic split between senior travelers (65 years and over) and non-senior travelers. Existing state sources provide data describing the time and weather conditions for each crash and the vehicles and persons involved over the time period from 1995 to 2009 as well as the traffic volumes and the characteristics of the roads on which these crashes occurred. Findings indicate an overall increase in …


Analysing Domestic Electricity Smart Metering Data Using Self Organising Maps, Fintan McLoughlin, Aidan Duffy, Michael Conlon 2012 Technological University Dublin

Analysing Domestic Electricity Smart Metering Data Using Self Organising Maps, Fintan Mcloughlin, Aidan Duffy, Michael Conlon

Conference Papers

This paper investigates a method of classifying domestic electricity load profiles through Self Organising Maps (SOMs). Approximately four thousand customers are divided into groups based on their electricity demand patterns. Dwelling and occupant characteristics are then investigated for each group. The results show that SOMs are an effective way of classifying customers into groups in terms of their electrical load profile and that certain dwelling and occupant characteristics are significant factors in determining which group they end up in.


Analysis Of Dietary Patterns Over Freshman Year Of College, Chelsea Lofland 2012 California Polytechnic State University, San Luis Obispo

Analysis Of Dietary Patterns Over Freshman Year Of College, Chelsea Lofland

Statistics

This analysis is an investigation of changes in Cal Poly students’ eating habits over freshman year. The motivation behind this was an interest in college students’ lifestyles; college is the first time most students live on their own and it can be an important maturation period. College is stressful, exciting, liberating, and terrifying all at the same time. This distinctive life experience, along with my desire to handle big and messy data, led me to this research question.

The response variable analyzed was food consumption and the explanatory variables were: sex, race, quarter, food group, stress, exercise, BMI, sleep quality …


Improvement Of Statistical Process Control At St. Jude Medical's Cardiac Manufacturing Facility, Christopher Lance Edwards 2012 California Polytechnic State University, San Luis Obispo

Improvement Of Statistical Process Control At St. Jude Medical's Cardiac Manufacturing Facility, Christopher Lance Edwards

Master's Theses

Sig sigma is a methodology where companies strive to reproduce results ending up having a 99.9996% chance their product will be void of defects. In order for companies to reach six sigma, statistical process control (SPC) needs to be introduced. SPC has many different tools associated with it, control charts being one of them. Control charts play a vital role in managing how a process is behaving. Control charts allow users to identify special causes, or shifts, and can therefore change the process to keep producing good products, free of defects.

There are many factories and manufacturing facilities having implemented …


Analyzing Multiple Independent Spatial Point Processes, Neal Grantham 2012 California Polytechnic State University, San Luis Obispo

Analyzing Multiple Independent Spatial Point Processes, Neal Grantham

Statistics

No abstract provided.


The Impact Of Violating Factor Scaling Method Assumptions On Latent Mean Difference Testing In Structured Means Models, Dandan Wang, Tiffany A. Whittaker, S. Natasha Beretvas 2012 The University of Texas at Austin

The Impact Of Violating Factor Scaling Method Assumptions On Latent Mean Difference Testing In Structured Means Models, Dandan Wang, Tiffany A. Whittaker, S. Natasha Beretvas

Journal of Modern Applied Statistical Methods

Type I error rates and power of the likelihood ratio test and bias of the standardized effect size measure associated with the latent mean difference in structured means modeling are examined when violating the assumptions underlying the two available factor scaling methods under various conditions. Implications and recommendations are discussed.


New Approximate Bayesian Confidence Intervals For The Coefficient Of Variation Of A Gaussian Distribution, Vincent A. R. Camara 2012 Research Center for Bayesian Applications, Inc., Largo, FL

New Approximate Bayesian Confidence Intervals For The Coefficient Of Variation Of A Gaussian Distribution, Vincent A. R. Camara

Journal of Modern Applied Statistical Methods

Confidence intervals are constructed for the coefficient of variation of a Gaussian distribution. Considering the square error and the Higgins-Tsokos loss functions, approximate Bayesian models are derived and compared to a published classical model. The models are shown to have great coverage accuracy. The classical model does not always yield the best confidence intervals; the proposed models often perform better.


A Poisson Regression Model For Female Radium Dial Workers, Tze-San Lee 2012 Western Illinois University

A Poisson Regression Model For Female Radium Dial Workers, Tze-San Lee

Journal of Modern Applied Statistical Methods

A Poisson regression model with interaction terms was applied to study the dose response relationship for radium-induced skeletal cancers. The model showed that the expected frequency count of bone tumors depended not only on the logarithmic dose and the time since first exposure, but also on the interaction between the logarithmic dose and the time since first exposure, whereas the dose-response model for head tumors depended only on the logarithmic dose.


Jmasm 32: Sas Template For Single-Subject Experimental Designs, Hyewon Chung, Jiseon Kim, Ryoungsun Park 2012 Chungnam National University, Deajeon, Korea

Jmasm 32: Sas Template For Single-Subject Experimental Designs, Hyewon Chung, Jiseon Kim, Ryoungsun Park

Journal of Modern Applied Statistical Methods

Meta-analysis has been used to synthesize research findings and to evaluate the effectiveness of treatments or the accuracy of diagnostic tools. Although meta-analytic techniques were developed to synthesize the results of several studies, controversy exists as to how to quantify the results from singlesubject experimental designs (SSEDs). The most commonly used metrics are reviewed, including nonregression and regression based methods. The application of the SAS template is demonstrated through simulated data sets. The SAS templates can be modified to accommodate a more complex data structure.


The Length-Biased Lognormal Distribution And Its Application In The Analysis Of Data From Oil Field Exploration Studies, Makarand V. Ratnaparkhi, Uttara V. Naik-Nimbalkar 2012 Wright State University

The Length-Biased Lognormal Distribution And Its Application In The Analysis Of Data From Oil Field Exploration Studies, Makarand V. Ratnaparkhi, Uttara V. Naik-Nimbalkar

Journal of Modern Applied Statistical Methods

The length-biased version of the lognormal distribution and related estimation problems are considered and sized-biased data arising in the exploration of oil fields is analyzed. The properties of the estimators are studied using simulations and the use of sample mode as an estimate of the lognormal parameter is discussed.


Four Period Crossover Designs, James F. Reed III 2012 Christiana Care Hospital System, Newark, Delaware

Four Period Crossover Designs, James F. Reed Iii

Journal of Modern Applied Statistical Methods

In higher-order four period crossover designs with two treatments, sixteen possible treatment sequences can result: AAAA, AAAB, AABA, AABB, ABAA, ABAB, ABBA, ABBB and their duals. Higher-order crossover designs are useful for several reasons: they allow estimation of a treatment effect even in the presence of a carry-over effect, they provide estimates of intra-subject variability and they draw inference on the carry-over effect. The real question related to a two-treatment four-period crossover design is the real world application of these designs. This article considers four designs: Design I: ABBA and its dual; Design II: ABBA, AABB and their duals, Design …


Gamma-Pareto Distribution And Its Applications, Ayman Alzaatreh, Felix Famoye, Carl Lee 2012 Austin Peay State University, Clarksville, TN

Gamma-Pareto Distribution And Its Applications, Ayman Alzaatreh, Felix Famoye, Carl Lee

Journal of Modern Applied Statistical Methods

A new distribution, the gamma-Pareto, is defined and studied and various properties of the distribution are obtained. Results for moments, limiting behavior and entropies are provided. The method of maximum likelihood is proposed for estimating the parameters and the distribution is applied to fit three real data sets.


A Weighted Exponential Detection Function Model For Line Transect Data, Faisal Ababneh, Omar M. Eidous 2012 Al-Hussian Bin Talal University, Ma’an, Jordan

A Weighted Exponential Detection Function Model For Line Transect Data, Faisal Ababneh, Omar M. Eidous

Journal of Modern Applied Statistical Methods

A new parametric model is proposed for modeling the density function of perpendicular distances in line transects sampling. The model can be considered a weighted exponential model in the sense that it combines two exponential models with different weights. The proposed model is appealing because it is monotone decreasing with distance from transect line; in contrast to the classical exponential model, it satisfies the shoulder condition at the origin. Simulation results for a wide range of target densities show reasonable and good performances of the weighted exponential model in most considered cases compared to the classical exponential and the half-normal …


Ordinal Regression Analysis: Using Generalized Ordinal Logistic Regression Models To Estimate Educational Data, Xing Liu, Hari Koirala 2012 Eastern Connecticut State University

Ordinal Regression Analysis: Using Generalized Ordinal Logistic Regression Models To Estimate Educational Data, Xing Liu, Hari Koirala

Journal of Modern Applied Statistical Methods

The proportional odds (PO) assumption for ordinal regression analysis is often violated because it is strongly affected by sample size and the number of covariate patterns. To address this issue, the partial proportional odds (PPO) model and the generalized ordinal logit model were developed. However, these models are not typically used in research. One likely reason for this is the restriction of current statistical software packages: SPSS cannot perform the generalized ordinal logit model analysis and SAS requires data restructuring. This article illustrates the use of generalized ordinal logistic regression models to predict mathematics proficiency levels using Stata and compares …


Robust Regression Estimates In The Prediction Of Latent Variables In Structural Equation Models, Marcelo Angelo Cirillo, Lúcia Pereira Barroso 2012 Federal University of Lavras, Brazil

Robust Regression Estimates In The Prediction Of Latent Variables In Structural Equation Models, Marcelo Angelo Cirillo, Lúcia Pereira Barroso

Journal of Modern Applied Statistical Methods

The incorporation of the robust regression methods Least Median Square (LMS) and Least Trimmed Squares (LTS) is proposed in structural equation modeling. Results show that, in situations of high deviations of symmetry, the evaluated methods would be recommended for applications including smaller sample sizes.


Comparison Of Re-Sampling Methods To Generalized Linear Models And Transformations In Factorial And Fractional Factorial Designs, Maher Qumsiyeh, Gerald Shaughnessy 2012 University of Dayton

Comparison Of Re-Sampling Methods To Generalized Linear Models And Transformations In Factorial And Fractional Factorial Designs, Maher Qumsiyeh, Gerald Shaughnessy

Journal of Modern Applied Statistical Methods

Experimental situations in which observations are not normally distributed frequently occur in practice. A common situation occurs when responses are discrete in nature, for example counts. One way to analyze such experimental data is to use a transformation for the responses; another is to use a link function based on a generalized linear model (GLM) approach. Re-sampling is employed as an alternative method to analyze non-normal, discrete data. Results are compared to those obtained by the previous two methods.


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