The present work provides charge state fractions that may be used to generate TEAMS relative sensitivity factors for impurities in semiconductor materials.

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal.

This study investigates the main factors of production, their interaction and influence on cycle time efficiency for shovel-truck systems on surface mines. The main factors are truck payload, cycle time and operator proficiency. It is now routine that shoveltruck cycles are analysed using simulation methods. The Elbrond, FPC, Talpac, Arena and Machine Repair simulation models are discussed to explain how their model characteristics contribute to the differences in their reported cycle efficiency as indicated by productivity results. The Machine Repair Model based on Markov chains is adapted for shovel-truck systems and examined for calculating shovel-truck cycle times. The various probability distributions that can be use to model particular cycle time variables and some methods in selecting the “best” fit are examined. Truck cycle time variable sensitivity is examined by using the Excel® add-on program @Risk (Palisade Corp.) in determining their respective weighting or contribution within the total cycle time variability. The analysis of cycle efficiency leads ultimately to sizing of a shovel-truck system. When determining a fleet size for a particular surface operation the planning engineers will tend to use one and to a lesser extent perhaps two separate simulation models. This study calculates the productivity (tonnes per hour) for a “virtual mine” with a variable number of trucks, variable cycle distances and variable truck loading times. The study also includes a separate analysis of cycle time variables and their probability distributions for the Orapa diamond mine in Botswana, to show possible distributions for various cycle variables. The study concludes with a calculation of the truck fleet size using the Elbrond, FPC, Talpac and Arena and Machine Repair models for the Optimum Colliery coal mine and then compares the results and their correlation. The main findings are that the calculation of waiting time is different for the various models, each model yields a unique fleet sizing solution and any solution in effect represents a range of results.

Implementation of the National Water Act in South Africa requires that an ecological Reserve be determined for all significant resources. The ecological Reserve determination is the estimation of the amount of water required to maintain the system in a particular ecological condition. Because aquatic habitats are defined in terms of local hydraulic variables rather than amounts of water, hydraulic analysis provides a crucial link in relating hydrological conditions and river ecosystem integrity. Over the last decade, considerable effort has been devoted to developing hydraulics for the Reserve determination. The hydraulics needs for Reserve determination are primarily for low flow analysis, and appropriate methods still need to be developed. This thesis deals with hydraulics under low flow conditions. Its emphasis is on developing appropriate methods for describing the hydraulic characteristics of South African rivers under conditions of low discharge, and the influence of vegetation and large bed roughness. The following methods have been developed: · A new equation for prediction of overall flow resistance under large-scale roughness, and a new approach for estimation of intermediate-scale roughness resistance that distinguishes the influences of large and intermediate scale roughness components. · Prediction methods for velocity distributions with large roughness elements. Under low flows, rocks and boulders may control the local velocity and depth distributions. Distributions of velocities and depth are related to rapidly spatially varied flow caused by the boundary geometry rather than flow resistance phenomena. With increasing discharge, the multiple local controls become submerged and the flow tends towards a resistance controlled condition. Available information addressing the distinction between resistance controlled and multiple local controls conditions is limited. This thesis contributes to understanding the transformation between multiple local controls and the resistance controlled conditions. · Practical conveyance prediction methods for three situations pertaining to the occurrence of vegetation in rivers and wetlands. In-channel and riparian vegetation makes an important contribution to the creation of physical habitats for aquatic animals, but also has significant effects on flow resistances that need to be predicted.

A simulação de dados que seguem distribuição de Poisson é essencial em muitas aplicações reais de várias áreas, tais como saúde, marketing, ciências agronômicas, entre outras em que os dados são contagens multivariadas. Métodos de simulação atuais sofrem de limitações computacionais e restrições à estrutura de correlação e, portanto, são raramente usados. Neste trabalho propôs-se uma modificação do método NORTA para gerar dados com distribuição Poisson multivariada a partir de uma distribuição normal multivariada com matriz de correlações e vetor de médias pré estabelecidos. Como as distribuições Normal multivariada e univariada e a distribuição Poisson univariada já estão implementadas em softwares estatísticos, inclusive no R, implementou-se algumas linhas de código. Mostrou-se que o método funciona bem e é altamente preciso na geração de dados multivariados com distribuição marginais de Poisson, para diferentes estruturas de correlações (negativas e positivas e variando os valores) e para altos e baixos valores de médias. Mostrou-se as vantagens práticas da simulação de dados de Poisson multivariada sobre a normal multivariada na detecção da taxa de falsos alertas de super populações de percevejos, evidenciando que simulações inadequadas podem levar a excesso de falsos alertas. Uma vez que os dados seguem distribuição Poisson multivariada, a taxa de falsos alertas pode ser maior do que a imaginada. Essa taxa pode ser estimada por um modelo ajustado. A mesma técnica pode ser aplicada em diversos problemas de várias áreas do conhecimento. / The simulation data that follow a Poisson distribution is essential in many real applications in various areas such as healthcare, marketing, agronomic sciences, among others that the data are multivariate counts. Current simulation methods suffer from limitations and constraints on computing correlation structure and are therefore seldom used. This paper proposed a modification of the NORTA method for generating data with multivariate Poisson distribution from a multivariate normal distribution with correlation matrix and vector of predetermined average. As the multivariate and univariate Normal distribution and univariate Poisson distribution are already implemented in statistical software, including R, was implemented just a few lines of code. It was shown that the method works well and is highly accurate in generating multivariate data with marginal Poisson distribution structures for different correlations (negative and positive values) and for high and low ?. Proved the practical benefits of the simulation data on the multivariate Poisson multivariate normal in the detection of super bugs populations, inadequate simulations can lead to excessive false alerts. Once the data are multivariate Poisson distribution, the rate of false alarms can be greater than the imagined. This rate can be estimated by an adjusted model. The same technique can be applied to many problems in various fields of knowledge.

Thesis. 1976. Ph.D.--Massachusetts Institute of Technology. Dept. of Mathematics. / Microfiche copy available in Archives and Science. / Vita. / Includes bibliographical references. / by Robert R. Reitano. / Ph.D.

Um modelo matemático foi desenvolvido, para avaliar o perfil Compton produzido por diferentes distribuições de momento do elétron. Estas distribuições de momento são avaliadas a partir das funções de onda dos elétrons orbitais. Perfis Compton para cinco elementos (Pb POT. 82 , W POT. 74 , Ag POT. 47, Cu POT. 29 e Al POT. 13) e para três ângulos de espalhamento (30º ,15º , 10º) foram calculados usando funções hidrogenóides e Hartree-Fock relativísticas. Experimentalmente usando um de 662 Kev de energia mediu-se, com um detetor GeLi, o perfil Compton desses elementos nas condições geométricas acima, observando-se boa concordância com as distribuições de momento relativístico, calculadas por Biggs, Mendelsohn e Mann. Este acordo, entretanto só foi conseguido quanto utilizamos as correções propostas for Ribberford, que permitem associar o conceito de perfil Compton para qualquer ângulo de espalhamento. Isto mostra que é possível associar univocamente o perfil Compton às distribuições de momento para qualquer ângulo de espalhamento ao contrário do que tradicionalmente se aceitava (apenas 180º). O modelo matemático foi estendido para cálculos de perfis Compton com feixes incidentes e emergentes polarizados. / .

Juesheng Fu. / "April 2003." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (p. 124-132). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web.

To complete an online world Flora by 2020 rapid progress is required towards understanding the taxonomy and distributions of the world's plants. This ambitious target set by the Global Strategy for Plant Conservation is hampered by two facts; first, many species of seed plant remain poorly known and second, the process of improving taxonomy and discovering species is not well understood. Here I investigate in detail the taxonomy and process of species discovery in a genus of tropical plants, Aframomum by examining specimens, taxonomic literature and authors of specimen determinations. I demonstrate that >50% of Aframomum specimens did not have the correct name prior to a recent comprehensive revision, that the number of specimens in herbaria doubled between 1970 and 2000, and that these results are also found in other taxa. I deconstruct the process of ‘species discovery' by identifying four key events: Initial collection, publication, conservation assessment, and distribution mapping. The time lags between the initial collection and completion of a) an accurate conservation assessment (101 years) and b) a comprehensive distribution map (115 years) demonstrate that many seed plant species published in the last 100 years are not fully understood. This is partly due to the fact that most species protologues (>90%) cite too few specimens at publication to produce an accurate conservation assessment. Furthermore, I explore variation in species' distribution patterns over time, taking account of specimen misidentification. Taken together the thesis identifies the lack of taxonomic capacity to efficiently deal with the tremendous influx of specimens since 1970, the poor current state of taxonomic knowledge of many taxa, and three significant time lags in the process of species discovery. Focused taxonomic effort is required for the successful completion of a world online Flora with conservation assessments to meet the 2020 GSPC target.

by Yiu Ming Cheung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (leaves 92-99). / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.1.1 --- Bayesian YING-YANG Learning Theory and Number Selec- tion Criterion --- p.5 / Chapter 1.2 --- General Motivation --- p.6 / Chapter 1.3 --- Contributions of the Thesis --- p.6 / Chapter 1.4 --- Other Related Contributions --- p.7 / Chapter 1.4.1 --- A Fast Number Detection Approach --- p.7 / Chapter 1.4.2 --- Application of RPCL to Prediction Models for Time Series Forecasting --- p.7 / Chapter 1.4.3 --- Publications --- p.8 / Chapter 1.5 --- Outline of the Thesis --- p.8 / Chapter 2 --- Open Problem: How Many Clusters? --- p.11 / Chapter 3 --- Bayesian YING-YANG Learning Theory: Review and Experiments --- p.17 / Chapter 3.1 --- Briefly Review of Bayesian YING-YANG Learning Theory --- p.18 / Chapter 3.2 --- Number Selection Criterion --- p.20 / Chapter 3.3 --- Experiments --- p.23 / Chapter 3.3.1 --- Experimental Purposes and Data Sets --- p.23 / Chapter 3.3.2 --- Experimental Results --- p.23 / Chapter 4 --- Conditions of Number Selection Criterion --- p.39 / Chapter 4.1 --- Alternative Condition of Number Selection Criterion --- p.40 / Chapter 4.2 --- Conditions of Special Hard-cut Criterion --- p.45 / Chapter 4.2.1 --- Criterion Conditions in Two-Gaussian Case --- p.45 / Chapter 4.2.2 --- Criterion Conditions in k*-Gaussian Case --- p.59 / Chapter 4.3 --- Experimental Results --- p.60 / Chapter 4.3.1 --- Purpose and Data Sets --- p.60 / Chapter 4.3.2 --- Experimental Results --- p.63 / Chapter 4.4 --- Discussion --- p.63 / Chapter 5 --- Application of Number Selection Criterion to Data Classification --- p.80 / Chapter 5.1 --- Unsupervised Classification --- p.80 / Chapter 5.1.1 --- Experiments --- p.81 / Chapter 5.2 --- Supervised Classification --- p.82 / Chapter 5.2.1 --- RBF Network --- p.85 / Chapter 5.2.2 --- Experiments --- p.86 / Chapter 6 --- Conclusion and Future Work --- p.89 / Chapter 6.1 --- Conclusion --- p.89 / Chapter 6.2 --- Future Work --- p.90 / Bibliography --- p.92 / Chapter A --- A Number Detection Approach for Equal-and-Isotropic Variance Clusters --- p.100 / Chapter A.1 --- Number Detection Approach --- p.100 / Chapter A.2 --- Demonstration Experiments --- p.102 / Chapter A.3 --- Remarks --- p.105 / Chapter B --- RBF Network with RPCL Approach --- p.106 / Chapter B.l --- Introduction --- p.106 / Chapter B.2 --- Normalized RBF net and Extended Normalized RBF Net --- p.108 / Chapter B.3 --- Demonstration --- p.110 / Chapter B.4 --- Remarks --- p.113 / Chapter C --- Adaptive RPCL-CLP Model for Financial Forecasting --- p.114 / Chapter C.1 --- Introduction --- p.114 / Chapter C.2 --- Extraction of Input Patterns and Outputs --- p.115 / Chapter C.3 --- RPCL-CLP Model --- p.116 / Chapter C.3.1 --- RPCL-CLP Architecture --- p.116 / Chapter C.3.2 --- Training Stage of RPCL-CLP --- p.117 / Chapter C.3.3 --- Prediction Stage of RPCL-CLP --- p.122 / Chapter C.4 --- Adaptive RPCL-CLP Model --- p.122 / Chapter C.4.1 --- Data Pre-and-Post Processing --- p.122 / Chapter C.4.2 --- Architecture and Implementation --- p.122 / Chapter C.5 --- Computer Experiments --- p.125 / Chapter C.5.1 --- Data Sets and Experimental Purpose --- p.125 / Chapter C.5.2 --- Experimental Results --- p.126 / Chapter C.6 --- Conclusion --- p.134 / Chapter D --- Publication List --- p.135 / Chapter D.1 --- Publication List --- p.135