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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
101

Inheritance of cotton fiber length and distribution

Braden, Chris Alan 30 October 2006 (has links)
Fiber quality data from five upland cotton (Gossypium hirsutum L.) genotypes, which were grown at College Station, TX during 2001 and 2002, were subjected to diallel and generation means analyses to determine the potential for improvement of fiber length and to determine the inheritance of length distribution data. Four near-long staple (NLS) upland cotton genotypes and one short-staple genotype were crossed in all combinations, excluding reciprocals. Estimates of general (GCA) and specific combining ability (SCA) for fiber length based on Griffing’s diallel Model I, Method 4 were calculated for high volume instrumentation (HVI) upper-half mean (UHM) fiber length and advance fiber information system (AFIS) mean fiber length by weight (FLw), mean fiber length by number (FLn), upper quartile length by weight (Uqlw), fiber length distribution cross entropy (using 3 different standard or check distributions - CEA, CEB, and CEC), fiber length distribution kurtosis (FLwKurt), and fiber length distribution skewness (FLwSkew) for FLw. Across environments, GCA effects were significant for fiber length measurements of UHM, FLw, FLn, Uqlw, and SFCw and distribution measurements of CEA, CEB, FLwKurt, and FLwSkew. On the basis of GCA effects, TAM 94L-25 was the best parent to be used in a cross to improve upland fiber length, while Acala 1517-99 was the parent of choice to improve distribution among the 4 parents tested. The inheritance of AFIS fiber length measurements and distribution data was estimated using parents, F1, F2, and backcross generations. The magnitude and significance of the estimates for non-allelic effects in the parental combinations suggest that epistatic gene effects are present and important in the basic mechanism of AFIS fiber length and length distribution inheritance for the populations studied. Gene effects and variances for all AFIS fiber length and distribution data measurements were inherited differently in different environments and specific parental combination, suggesting environmentally specific mechanisms. Developing genotypes with enhanced fiber length and an optimal fiber length distribution should be a priority to improve spinning performance and product quality of U.S. upland cotton.
102

On a topic of Bayesian analysis using scale mixtures distributions

Chan, Chun-man, January 2001 (has links)
Thesis (M. Phil.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 120-135).
103

The normal kernel coupler : an adaptive Markov Chain Monte Carlo method for efficiently sampling from multi-modal distributions /

Warnes, Gregory R. January 2000 (has links)
Thesis (Ph. D.)--University of Washington, 2000. / Vita. Includes bibliographical references (p. 105-112).
104

Expertise and mixture in automatic causal discovery /

Ramsey, Joseph Daniel, January 2001 (has links)
Thesis (Ph. D.)--University of California, San Diego, 2001. / Vita. Includes bibliographical references (leaves 143-146).
105

The transfer of distributions by LULU smoothers /

Butler, Pieter-Willem. January 2008 (has links)
Thesis (MSc)--University of Stellenbosch, 2008. / Bibliography. Also available via the Internet.
106

Monitoring of biomedical systems using non-stationary signal analysis

Musselman, Marcus William 18 February 2014 (has links)
Monitoring of engineered systems consists of characterizing the normal behavior of the system and tracking departures from it. Techniques to monitor a system can be split into two classes based on their use of inputs and outputs of the system. Systems-based monitoring refers to the case when both inputs and outputs of a system are available and utilized. Conversely, symptomatic monitoring refers to the case when only outputs of the system are available. This thesis extended symptomatic and systems-based monitoring of biomedical systems via the use of non-stationary signal processing and advanced monitoring methods. Monitoring of various systems of the human body is encumbered by several key hurdles. First, current biomedical knowledge may not fully comprehend the extent of inputs and outputs of a particular system. In addition, regardless of current knowledge, inputs may not be accessible and outputs may be, at best, indirect measurements of the underlying biological process. Finally, even if inputs and outputs are measurable, their relationship may be highly nonlinear and convoluted. These hurdles require the use of advanced signal processing and monitoring approaches. Regardless of the pursuit of symptomatic or system-based monitoring, the aforementioned hurdles can be partially overcome by using non-stationary signal analysis to reveal the way frequency content of biomedical signals change over time. Furthermore, the use of advanced classification and monitoring methods facilitated reliable differentiation between various conditions of the monitored system based on the information from non-stationary signal analysis. The human brain was targeted for advancement of symptomatic monitoring, as it is a system responding to a plethora internal and external stimuli. The complexity of the brain makes it unfeasible to realize system-based monitoring to utilize all the relevant inputs and outputs for the brain. Further, measurement of brain activity (outputs), in the indirect form of electroencephalogram (EEG), remains a workhorse of brain disorder diagnosis. In this thesis, advanced signal processing and pattern recognition methods are employed to devise and study an epilepsy detection and localization algorithm that outperforms those reported in literature. This thesis also extended systems-based monitoring of human biomedical systems via advanced input-output modeling and sophisticated monitoring techniques based on the information from non-stationary signal analysis. Explorations of system-based monitoring in the NMS system were driven by the fact that joint velocities and torques can be seen NMS responses to electrical inputs provided by the central nervous system (CNS) and the electromyograph (EMG) provides an indirect measurement of CNS excitations delivered to the muscles. Thus, both inputs and outputs of this system are more or less available and one can approach its monitoring via the use of system-based approaches. / text
107

Estimation with stable disturbances

Ghaffari, Novin 16 March 2015 (has links)
The family of stable distributions represents an important generalization of the Gaussian family; stable random variables obey a generalized central limit theorem where the assumption of finite variance is replaced with one of power law decay in the tails. Possessing heavy tails, asymmetry, and infinite variance, non-Gaussian stable distributions can be suitable for inference in settings featuring impulsive, possibly skewed noise. A general lack of analytical form for the densities and distributions of stable laws has prompted research into computational methods of estimation. This report introduces stable distributions through a discussion of their basic properties and definitions in chapter 1. Chapter 2 surveys applications, and chapter 3 discusses a number of procedures for inference, with particular attention to time series models in the ARMA setting. Further details and an application can be found in the appendices. / text
108

On a topic of Bayesian analysis using scale mixtures distributions

Chan, Chun-man, 陳俊文 January 2001 (has links)
published_or_final_version / Statistics and Actuarial Science / Master / Master of Philosophy
109

A novel technique for developing bimodal grain size distributions in low carbon steels

Poole, Warren J., Militzer, Matthias, Azizi-Alizamini, Hamid January 2007 (has links)
In this study a new method is introduced to produce bimodal grain structures in low carbon steels. This method is based on cold rolling of dual phase structures and appropriate annealing treatments. The difference in the recrystallization behaviour of ferrite and martensite yields a heterogeneous microstructure with a distribution of coarse and fine grains. These types of microstructures are of interest for optimizing the balance of strength and uniform elongation in ultra-fine grained low carbon steels.
110

Actuarial applications of multivariate phase-type distributions : model calibration and credibility

Hassan Zadeh, Amin January 2009 (has links)
Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

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