Browsing by Author "Mallick, Bani"
Now showing items 21-40 of 42
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Tompkins, James Brandon (2016-06-17)The one megawatt TRIGA reactor at Texas A&M has various methods of irradiating samples, but one of the most unique dose positions is severely underutilized. This irradiation cell is a large space where samples may be placed ...
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Peterson, Jacob Ross (2014-04-23)An exponentially-convergent Monte Carlo (ECMC) method is analyzed using the one-group, one-dimension, slab-geometry transport equation. The method is based upon the use of a linear discontinuous finite-element trial space ...
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Spinka, Christine Marie (Texas A&M University, 2005-02-17)Gene-environment interactions are an area of increasing interest in complex hu- man diseases. The first step in any study of the interactions between genes and the environment involves identifying genes which influence ...
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Xia, Xiaoyang (2014-12-18)Reservoir simulation models are generated by petroleum engineers to optimize field operation and production, thus maximizing oil recovery. History matching methods are extensively used for reservoir model calibration and ...
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Choudhary, Ashish (Texas A&M University, 2006-10-30)In recent years Boolean Networks (BN) and Probabilistic Boolean Networks (PBN) have become popular paradigms for modeling gene regulation. A PBN is a collection of BNs in which the gene state vector transitions according ...
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Zuo, Lihua (2013-06-21)In recent decades, significant interest, based on physics and engineering applications, has developed on so-called anomalous diffusion processes that possess different spread functions with classical ones. The resulting ...
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Park, Chun Gun (Texas A&M University, 2004-09-30)Single index models are a special type of nonlinear regression model that are partially linear and play an important role in fields that employ multidimensional regression models. A wavelet series is thought of as a ...
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Kang, Seul Ki (2012-10-19)In this dissertation, we develop multiscale finite element methods and uncertainty quantification technique for Richards' equation, a mathematical model to describe fluid flow in unsaturated porous media. Both coarse-level ...
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Choi, Sujung (Texas A&M University, 2005-11-01)We discuss two-sample problems and the implementation of a new two-sample data analysis procedure. The proposed procedure is based on the concepts of mid-distribution, design of score functions, components, comparison ...
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Zheng, Weixiong (2013-12-06)The thermal neutron scattering cross sections of ZrHx are heavily affected by the solid frequency distributions, also called “phonon spectra”, of Zr and H in ZrHx. The phonon spectra are different for ZrHx with different ...
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Wang, Yanqing (2014-08-15)Motivated by a logistic regression problem involving diet and cancer, we reconsider the problem of forming a confidence interval for the ratio of two location parameters. We develop a new methodology, which we call the ...
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Roh, Soojin (2014-05-23)Ensemble Kalman filters (EnKF) is a statistical technique used to estimate the state of a nonlinear spatio-temporal dynamical system. This dissertation consists of three parts. First, we develop a methodology to make EnKF ...
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Xue, Jingnan (2017-05-30)Big data analysis and high dimensional data analysis are two popular and challenging topics in current statistical research. They bring us a lot of opportunities as well as many challenges. For big data, traditional methods ...
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Panaganti Badrinath, Kishan (2023-07-27)This research dissertation explores novel algorithms in the field of robust reinforcement learning (RL) that address the challenges of controlling dynamical systems in real-world scenarios. Classical reinforcement learning ...
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Kim, Kyong Ryun (Texas A&M University, 2007-09-17)We proposed new variance estimators for the poststratified estimator of the population total in two-stage sampling. The linearization or Taylor series variance estimator and the jackknife linearization variance estimator ...
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Dorn, Mary Frances (2017-04-24)This dissertation proposes a new semiparametric approach for binary classification that exploits the modeling flexibility of sparse graphical models. This approach is based on non-parametrically estimated densities, which ...
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Plummer, Sean C (2021-08-02)Over the past decade variational inference (VI) has surpassed Markov Chain Monte Carlo (MCMC) as the main method for performing scalable parametric Bayesian inference. Variational inference utilizes optimization to find a ...
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Li, Furong (2017-05-08)The availability of large spatial and spatial-temporal data geocoded at accurate locations has fueled increasing interest in spatial modeling and analysis. In this dissertation, we present one study concerning the inference ...
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Al Harbi, Mishal H. (Texas A&M University, 2005-08-29)Streamline-based models have shown great potential in reconciling high resolution geologic models to production data. In this work we extend the streamline-based production data integration technique to naturally fractured ...
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Prabhakar, Avinash (2010-01-16)In this work we present a novel computational framework for analyzing evolution of uncertainty in state trajectories of a hypersonic air vehicle due to uncertainty in initial conditions and other system parameters. The ...