Draper and Guttman (1997) show that for basic 2^{k-p}designs, p >= 0, k-p replicates of blocks designs of size two are needed to estimate all the usual (estimable) effects. In Chapter 1, we provide an algebraic formal proof for the two-level blocks designs results and present results applicable to the general case; that is, for the case of s^{k} factorial (p=0) or s^{k-p}ractional factorial (p>0) designs in s^{b} blocks, where 0<b<k-p, at least (k-p)/(k-p-b) replicates are needed to clear up all possible effects. Through the theoretical development presented in this work, it can provide a clearer view on why those results would hold. We will also discuss the estimation equations given in Draper and Guttman (1997). In Chapter 2, we present a methodology for analyzing the variability of the radiated emission testings of electronic, elecommunication and information technology equipment based on a modified analysis of variance (ANOVA), with polynomial regression analysis. In our study, three electronic products; modem, monitor and notebook bought from the market are tested. Through the experiment, we show that the international standard fails to provide a methodology which gives control limits for EMC when the electronic products in question are produced. We feel that an improved EMC control procedure presented here can better meet the needs of radiated emission control.

This paper discusses the approximate and the exact n-point D-optimal design problems for the common multivariate linear and quadratic polynomial regression on some convex design spaces. For the linear polynomial regression, the design space considered are q-simplex, q-ball and convex hull of a set of finite points. It is shown that the approximate and the exact n-point D-optimal designs are concentrated on the extreme points of the design space. The structure of the optimal designs on regular polygons or regular polyhedra is also discussed. For the quadratic polynomial regression, the design space considered is a q-ball. The configuration of the approximate and the exact n-point D-optimal designs for quadratic model in two variables on a disk are investigated.

While time-dependent processes are important to biological functions, methods to leverage temporal information from large data have remained computationally challenging. In temporal gene-expression data, clustering can be used to identify genes with shared function in complex processes. Algorithms like K-Means and standard Gaussian mixture-models (GMM) fail to account for variability in replicated data or repeated measures over time and require a priori cluster number assumptions, evaluating many cluster numbers to select an optimal result. An improved penalized-GMM offers a computationally-efficient algorithm to simultaneously optimize cluster number and labels. The work presented in this dissertation was motivated by mice bone-fracture models interested in determining patterns of temporal gene-expression during bone-healing progression. To solve this, an extension to the penalized-GMM was proposed to account for correlation between replicated data and repeated measures over time by introducing random-effects using a mixture of mixed-effects polynomial regression models and an entropy-penalized EM-Algorithm (EPEM). First, performance of EPEM for different mixed-effects models were assessed with simulation studies and applied to the fracture-healing study. Second, modifications to address the high computational cost of EPEM were considered that either clustered subsets of data determined by predicted polynomial-order (S-EPEM) or used modified-initialization to decrease the initial burden (I-EPEM). Each was compared to EPEM and applied to the fracture-healing study. Lastly, as varied rates of fracture-healing were observed for mice with different genetic-backgrounds (strains), a new analysis strategy was proposed to compare patterns of temporal gene-expression between different mice-strains and assessed with simulation studies. Expression-profiles for each strain were treated as separate objects to cluster in order to determine genes clustered into different groups across strain. We found that the addition of random-effects decreased accuracy of predicted cluster labels compared to K-Means, GMM, and fixed-effects EPEM. Polynomial-order optimization with BIC performed with highest accuracy, and optimization on subspaces obtained with singular-value-decomposition performed well. Computation time for S-EPEM was much reduced with a slight decrease in accuracy. I-EPEM was comparable to EPEM with similar accuracy and decrease in computation time. Application of the new analysis strategy on fracture-healing data identified several distinct temporal gene-expression patterns for the different strains. / 2021-02-27T00:00:00Z

京都大学 / 新制・課程博士 / 博士(経済学) / 甲第24375号 / 経博第662号 / 新制||経||302(附属図書館) / 京都大学大学院経済学研究科経済学専攻 / (主査)教授 西山 慶彦, 教授 江上 雅彦, 講師 柳 貴英 / 学位規則第4条第1項該当 / Doctor of Economics / Kyoto University / DFAM

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This thesis research is involved with the development of new methodologies for enhancing the experimental use of computer simulations to optimize predicted human performance in a work domain. Using a computer simulation called Computer modeling Of Human Operator System Tasks (CoHOST) to test the concepts in this research, methods are developed that are used to establish confidence limits and significance thresholds by having the computer model self report its limits. These methods, along with experimental designs that are tailored to the use of computer simulation instead of human subject based research, are used in the CoHOST simulation to investigate the U.S. Army battalion level command and control work domain during combat conditions and develop recommendations about that domain based on the experimental use of CoHOST with these methodologies. Further, with the realization that analytical results showing strictly numerical data do not always satisfy the need for understanding by those who could most benefit from the analysis, the results are further interpreted in accordance with a team performance model and the CoHOST analysis results are mapped to it according to macroergonomic and team performance concepts. The CoHOST computer simulation models were developed based on Army needs stemming from the Persian Gulf war. They examined human mental and physical performance capabilities resulting from the introduction of a new command and control vehicle with modernized digital communications systems. Literature searches and background investigations were conducted, and the CoHOST model architecture was developed that was based on a taxonomy of human performance. A computer simulation design was implemented with these taxonomic based descriptors of human performance in the military command and control domain using the commercial programming language MicroSaint™. The original CoHOST development project developed results that suggested that automation alone does not necessarily improve human performance. The CoHOST models were developed to answer questions about whether human operators could operate effectively in a specified work domain. From an analytical point of view this satisfied queries being made from the developers of that work domain. However, with these completed models available, the intriguing possibility now exists to allow an investigation of how to optimize that work domain to maximize predicted human performance. By developing an appropriate experimental design that allows evaluative conditions to be placed on the simulated human operators in the computer model rather than live human test subjects, a series of computer runs are made to establish test points for identified dependent variables against specified independent variables. With these test points a set of polynomial regression equations are developed that describe the performance characteristics according to these dependent variables of the human operator in the work domain simulated in the model. The resulting regression equations are capable of predicting any outcome the model can produce. The optimum values for the independent variables are then determined that produce the maximum predicted human performance according to the dependent variables. The conclusions from the CoHOST example in this thesis complement the results of the original CoHOST study with the prediction that the primary attentional focus of the battalion commander during combat operations is on establishing and maintaining an awareness and understanding of the situational picture of the battlefield he is operating upon. Being able to form and sustain an accurate mental model of this domain is the predicted predominant activity and drives his ability to make effective decisions and communicate those decisions to the other members of his team and to elements outside his team. The potential specific benefit of this research to the Army is twofold. First, the research demonstrates techniques and procedures that can be used without any required modifications to the existing computer simulations that allow significant predictive use to be made of the simulation beyond its original purpose and intent. Second, the use of these techniques with CoHOST is developing conclusions and recommendations from that simulation that Army force developers can use with their continuing efforts to improve and enhance the ability of commanders and other decision makers to perform as new digital communications systems and procedures are producing radical changes to the paradigm that describes the command and control work domain. The general benefits beyond the Army domain of this research fall into the two areas of methodological improvement of simulation based experimental procedures and in the actual application area of the CoHOST simulation. Tailoring the experimental controls and development of interrogation techniques for the self-reporting and analysis of simulation parameters and thresholds are topics that bode for future study. The CoHOST simulation, while used in this thesis as an example of new and tailored techniques for computer simulation based research, has nevertheless produced conclusions that deviate somewhat from prevailing thought in military command and control. Refinement of this simulation and its use in an even more thorough simulation based study could further address whether the military decision making process itself or contributing factors such as development of mental models for understanding of the situation is or should be the primary focus of team decision makers in the military command and control domain. / Master of Science

The problem in this thesis was originally motivated by problems presented with documents of Early England Data Set (DEEDS). The central problem with these medieval documents is the lack of methods to assign accurate dates to those documents which bear no date. With the problems of the DEEDS documents in mind, we present two methods to impute missing features of texts. In the first method, we suggest a new class of metrics for measuring distances between texts. We then show how to combine the distances between the texts using statistical smoothing. This method can be adapted to settings where the features of the texts are ordered or unordered categoricals (as in the case of, for example, authorship assignment problems). In the second method, we estimate the probability of occurrences of words in texts using nonparametric regression techniques of local polynomial fitting with kernel weight to generalized linear models. We combine the estimated probability of occurrences of words of a text to estimate the probability of occurrence of a text as a function of its feature -- the feature in this case being the date in which the text is written. The application and results of our methods to the DEEDS documents are presented.

Seawater intrusion (SWI) is a widespread environmental problem, particularly in arid and semi-arid coastal areas. Unplanned prolonged over-pumping of groundwater is the most important factor in SWI that could result in severe deterioration of groundwater quality. Therefore, appropriate management strategies should be implemented in coastal aquifers to control SWI with acceptable limits of economic and environmental costs. This PhD project presents the development and application of a simulation-optimization (S/O) model to assess different management methods of controlling saltwater intrusion while satisfying water demands, and with acceptable limits of economic and environmental costs, in confined and unconfined coastal aquifers. The first S/O model (FE-GA) is developed by direct linking of an FE simulation model with a multi-objective Genetic Algorithm (GA) to optimize the efficiency of a wide range of SWI management scenarios. However, in this S/O framework, several multiple calls of the simulation model by the population-based optimization model, evaluating best individual candidate solutions resulted in a considerable computational burden. To solve this problem the numerical simulation model is replaced by an Evolutionary Polynomial Regression (EPR)-based surrogate model in the next S/O model (EPR-GA). Through these S/O approaches (FE-GA and EPR-GA) the optimal coordinates and rates of the both abstraction and recharge barriers are determined in the studied management scenarios. As a result, a new combined methodology, so far called ADRTWW, is proposed to control SWI. The ADRTWW model consists of deep Abstraction of saline water near the coast followed by Desalination of the abstracted water to a potable level for public uses and simultaneously Recharging the aquifer using a more economic source of water such as treated wastewater (TWW). In accordance to the available recharge options (injection through well or infiltration from surface pond), the general performance of ADRTWW is evaluated in different hydro-geological settings of the aquifers indicating that it offers the least cost and least salinity in comparison with other scenarios. The great capabilities of both developed S/O models in identification of the best management solutions and the optimal coordinates and rates of the abstraction well and recharge well/pond are discussed. Both FE-GA and EPR-GA can be successfully employed by a robust decision support system. In the next phase of the study, the general impacts of sea level rise (SLR), associated with its transgression nature along the coastline surface on the saltwater intrusion mechanism are investigated in different hypothetical and real case studies of coastal aquifer systems. The results show that the rate and the amount of SWI are considerably greater in aquifers with flat shoreline slopes compared with those with steep slopes. The SWI process is followed by a significant depletion in quantity of freshwater resources at the end of the century. The situation is exacerbated with combined action of SLR and groundwater withdrawals. This finding is also confirmed by 3D simulation of SWI in a regional coastal aquifer (Wadi Ham aquifer) in the UAE subjected to the coupled actions of SLR and pumping.