Doctor of Philosophy / Department of Industrial & Manufacturing Systems Engineering / Chih-Hang Wu / Recently, interdisciplinary (management, engineering, science, and economics) collaboration research has been growing to achieve the synergy and to reinforce the weakness of each discipline. Along this trend, this research combines three topics: mathematical programming, data mining, and supply chain management. A new pegging algorithm is developed for solving the continuous nonlinear knapsack problem. An efficient solving approach is proposed for solving the ν-support vector machine for classification problem in the field of data mining. The new pegging algorithm is used to solve the subproblem of the support vector machine problem. For the supply chain management, this research proposes an efficient integrated solving approach for the supplier selection problem. The support vector machine is applied to solve the problem of selecting potential supplies in the procedure of the integrated solving approach. In the first part of this research, a new pegging algorithm solves the continuous nonlinear knapsack problem with box constraints. The problem is to minimize a convex and differentiable nonlinear function with one equality constraint and box constraints. Pegging algorithm needs to calculate primal variables to check bounds on variables at each iteration, which frequently is a time-consuming task. The newly proposed dual bound algorithm checks the bounds of Lagrange multipliers without calculating primal variables explicitly at each iteration. In addition, the calculation of the dual solution at each iteration can be reduced by a proposed new method for updating the solution. In the second part, this research proposes several streamlined solution procedures of ν-support vector machine for the classification. The main solving procedure is the matrix splitting method. The proposed method in this research is a specified matrix splitting method combined with the gradient projection method, line search technique, and the incomplete Cholesky decomposition method. The method proposed can use a variety of methods for line search and parameter updating. Moreover, large scale problems are solved with the incomplete Cholesky decomposition and some efficient implementation techniques. To apply the research findings in real-world problems, this research developed an efficient integrated approach for supplier selection problems using the support vector machine and the mixed integer programming. Supplier selection is an essential step in the procurement processes. For companies considering maximizing their profits and reducing costs, supplier selection requires seeking satisfactory suppliers and allocating proper orders to the selected suppliers. In the early stage of supplier selection, a company can use the support vector machine classification to choose potential qualified suppliers using specific criteria. However, the company may not need to purchase from all qualified suppliers. Once the company determines the amount of raw materials and components to purchase, the company then selects final suppliers from which to order optimal order quantities at the final stage of the process. Mixed integer programming model is then used to determine final suppliers and allocates optimal orders at this stage.

Master of Science / Department of Biology / Rollie Clem / Apoptosis, or programmed cell death, is a crucial conserved process among organisms for deleting damaged unwanted cells, as well as for development and viral defense, and plays an important role in multiple diseases. Too much apoptosis may lead to Alzheimer’s disease, and too little may result in cancer. Therefore, the ability to understand this process is essential for improved medical knowledge today. Apoptosis has been explored in a number of species and pathways seem relatively conserved among most, with unique aspects contained in each, but little is known about apoptosis in mosquitoes. Improved knowledge and growing interest concerning apoptosis in mosquitoes is necessary considering the vast health effects seen across the globe as a result of diseases transferred by the mosquito vector. The Dengue virus mosquito vector Aedes aegypti was the focus here. A new player named defense repressor 1 was discovered in Drosophila melanogaster (DmDnr1), shown to play a role in apoptosis, and the homolog discovered in A. aegypti (AeDnr1). Silencing Dmdnr1 resulted in cells sensitized to apoptosis but was not enough to induce spontaneous apoptosis. In contrast, silencing Aednr1 in the A. aegypti cell line, Aag2, led to spontaneously induced apoptosis. This showed the importance of AeDnr1 as a member of the apoptotic pathway in this species. Epistasis experiments showed that apoptosis induced by silencing Aednr1 requires the initiator caspase Dronc and the effector caspase CASPS8, whereas apoptosis induced by silencing the inhibitor of apoptosis, Aeiap1, also requires Dronc but acts through the effector caspase CASPS7. Further epistasis experiments showed that apoptosis induced by silencing Aednr1 requires the IAP antagonist Mx, but not IMP. This showed for the first time a gene regulating upstream of an IAP antagonist. Biochemical studies showed that AeDnr1 regulates active CASPS8 but not CASPS7, and interacts with Mx and CASPS8 but not AeDronc, CASPS7 nor AeIAP1. Studies also showed Mx competes effectively with CASPS8 but not CASPS7 for AeIAP1 binding, and IMP competes effectively with CASPS7 but not CASPS8 for AeIAP1 binding. An improved apoptosis pathway for the mosquito A. aegypti emerged involving a potential feedback loop with explanations for the upstream IAP antagonist preference as well as the downstream effector caspase preference resulting from apoptosis induced by Aednr1 silencing. Through the discussed research, multiple unique findings resulted. Studying the mosquito model will allow us to find certain gene relations that are more difficult to uncover in the Drosophila model. Because Dnr1 is found in most systems, this improved pathway may shed light not only on a potential role of Dnr1 in apoptosis in insects but higher organisms as well.

Master of Science / Department of Statistics / Juan Du / Space and time are often vital components of research data sets. Accounting for and utilizing the space and time information in statistical models become beneficial when the response variable in question is proved to have a space and time dependence. This work focuses on the modeling and analysis of crop yield over space and time. Specifically, two different yield data sets were used. The first yield and environmental data set was collected across selected counties in Kansas from yield performance tests conducted for multiple years. The second yield data set was a survey data set collected by USDA across the US from 1900-2009. The objectives of our study were to investigate crop yield trends in space and time, quantify the variability in yield explained by genetics and space-time (environment) factors, and study how spatio-temporal information could be incorporated and also utilized in modeling and forecasting yield. Based on the format of these data sets, trend of irrigated and dryland crops was analyzed by employing time series statistical techniques. Some traditional linear regressions and smoothing techniques are first used to obtain the yield function. These models were then improved by incorporating time and space information either as explanatory variables or as auto- or cross- correlations adjusted in the residual covariance structures. In addition, a multivariate time series modeling approach was conducted to demonstrate how the space and time correlation information can be utilized to model and forecast yield and related variables. The conclusion from this research clearly emphasizes the importance of space and time components of data sets in research analysis. That is partly because they can often adjust (make up) for those underlying variables and factor effects that are not measured or not well understood.

Typescript (photocopy). / Digitized by Kansas Correctional Industries

The "global" financial crisis (GFC) emerged during 2008 and it was mainly triggered by the sub-prime mortgage crisis (SMC) in the United States of America. The main aims of this thesis is to conduct an econometric analysis of the financial crisis and household savings in South Africa and also to provide a rationale that will facilitate a policy attention on Domestic Resource Mobilisation (DRM) through household savings. The study uses quarterly time series data for the period 199401 to 201102 obtained on-line from the South African Reserve Bank (SARB). The research is based on the Keynesian saving function, which is a complement of the consumption function. The model will be estimated by using a cointegrating vector autoregressive (CVAR) framework, which allows for endogeneity of the regressors. To check robustness on the cointegration results, the study employs the second empirical technique based on Generalized Impulse Response Function (GIRF) analysis and Variance Decomposition. The regression equation of household savings is expressed as a function of household disposable income, household debt to disposable income, real GOP, interest rate, inflation rate and foreign savings. The variables are tested for the presence of a unit root by the application of the Augmented Dickey-Fuller (AOF), Phillips-Perron (PP) Kwiatkowski, Phillips, Schmidt and Shin (KPSS) tests. The findings of the study are that all variables have unit roots. The cointegration model emphasises the presence of a long run equilibrium relationship between dependent and independent variables. The CVAR reveals the short run of the dynamic household savings model. Taking this into consideration, the study concludes that household debt has a huge influence on the level of household savings. The econometric analysis also revealed that household savings in South Africa actually improved during the period associated with the GFC. It could be postulated that South African households responded to their deteriorating financial situations by reducing their average spending and increasing their savings. Variance decomposition analysis revealed that 'own shocks' constitute the predominant source of variations in household saving therefore household savings can be explained by the disturbances in macroeconomic variables in the study. The study recommends the promotion of household savings and economic growth in order to reduce the dependence of South Africa on foreign savings. DRM is therefore enhanced by a higher level of household savings, which can facilitate higher levels of investment and economic growth. / Thesis (PhD (Economics) North-West University, Mafikeng Campus, 2012

Master of Arts / Department of Economics / Lance J. Bachmeier / This thesis uses a structural VAR approach with a recursiveness assumption to examine the effects of an expansionary monetary policy shock on financial variables. We build this on the established research of the effects of monetary shocks on macro variables by measuring the expansionary shock as an increase in the money supply. We also investigate interest rate policy and test whether financial market variables matter for the determination of interest rate. We analyze four different cases in this paper using the innovations in the money supply, non-borrowed reserves, the interest rate and bond yield (including bonds with remaining maturity period close to 30- years) as a measurement for the expansionary monetary policy shock.

Le suivi de partition est défini comme étant la synchronisation sur ordinateur entre une partition musicale connue et le signal sonore de l'interprète de cette partition. Dans le cas particulier de la voix chantée, il y a encore place à l'amélioration des algorithmes existants, surtout pour le suivi de partition en temps réel. L'objectif de ce projet est donc d'arriver à mettre en oeuvre un logiciel suiveur de partition robuste et en temps-réel utilisant le signal numérisé de voix chantée et le texte des chansons. Le logiciel proposé utilise à la fois plusieurs caractéristiques de la voix chantée (énergie, correspondance avec les voyelles et nombre de passages par zéro du signal) et les met en correspondance avec la partition musicale en format MusicXML. Ces caractéristiques, extraites pour chaque trame, sont alignées aux unités phonétiques de la partition. En parallèle avec cet alignement à court terme, le système ajoute un deuxième niveau d'estimation plus fiable sur la position en associant une segmentation du signal en blocs de chant à des sections chantées en continu dans la partition. La performance du système est évaluée en présentant les alignements obtenus en différé sur 3 extraits de chansons interprétés par 2 personnes différentes, un homme et une femme, en anglais et en français.

International Telemetering Conference Proceedings / October 20-23, 2003 / Riviera Hotel and Convention Center, Las Vegas, Nevada / In this paper, we discuss a Block Adaptive Vector Quantization(BAVQ) Algorithm for Synthetic Aperture Radar(SAR). And we discuss a realization method of BAVQ algorithm for SAR raw data compressing in digital signal processor. Using the algorithm and the digital signal processor, we have compressed the SIR_C/X_SAR data.

This thesis focuses on the single-phase voltage-source inverter for use in photovoltaic (PV) electricity generating systems in both stand-alone and grid-tied applications. In many cases, developments in single-phase PV systems have followed developments in three-phase systems. Time-variant systems are more difficult to control than time-invariant systems. Nevertheless, by using suitable transformation techniques, time-variant systems can often be modelled as time-invariant systems. After the transformation, the control signals that are usually time-variant (often varying sinusoidally in time) become time-invariant at the fundamental frequency, and are hence much easier to deal with. With this approach, synchronous rotating frame control techniques have been previously proposed for high performance three-phase inverter applications. The transformation theory cannot be applied directly in single-phase systems without modification, and the d-q components would not be time-invariant in situations where harmonics, resonances or unbalance is present. Single-phase inverter controller designs based on the use of a synchronous rotating reference frame have been proposed, but such designs do not always perform as well as expected. This thesis aims to improve single-phase voltage-source inverters. The main objective is to address, in terms of cost, efficiency, power management and power quality, the problems found with single-phase designs based on a synchronous rotating frame single-phase inverter controller. Consequently, this thesis focuses on a novel controller approach in order to obtain a more reliable and flexible single-phase inverter. As the first step, this thesis investigates the single-phase inverter switching gate-drive algorithms and develops a form of space-vector pulse-width-modulation (SVPWM) in order to reduce total harmonic distortion. The results of the new SVPWM algorithm demonstrate its superior performance when compared with sinusoidal pulse-width-modulation (SPWM) which is often used with single-phase inverters. The second step, which is further reviewed and presented in this thesis, is the modelling of the single-phase inverter control based on the synchronous rotating frame. A mathematical analysis is conducted to determine the mechanism of the coupling that exists between the voltage phase and amplitude terms, and a new transformation strategy is proposed based on using the voltage phase as a reference at the Park transformation stages, and the current phase as a reference for the current at the transformation stages. The line-frequency components of the feedback signals are transformed to time-invariant components, thus eliminating the ripple and reducing the computational burden associated with the controller stage. Consequently, the inverter feedback controller stage is designed so that the coupling terms are decoupled within the controller itself. The effectiveness of the techniques proposed in this thesis are demonstrated by simulation using the MATLAB/SIMULINK environment. The proposed technique was also investigated through a practical implementation of the control system using a Digital Signal Processor (DSP) and a single-phase inverter. This practical system was tested up to 1 kW only (limited by the available inverter hardware). Nevertheless, the correlation between the simulation and the practical results is high and this gives confidence that the developed mechanism will allow the 2.5kW goal to be achieved. Practical test cases illustrate the effectiveness of the models. In addition, the comparisons between experimental and simulation results permit the system's behaviour and performance to be accurately evaluated. With the development of the new controller, small-scale single-phase renewable energy systems will become more useful in the field of power quality management through their ability to separately control the phase and amplitude of the output voltage. Consequently, incorporation of this type of generator within the national electrical distribution network, as distributed generators (DG) at low-voltage level, can assist with power quality management at the consumer side of the grid. In addition, such a generator can also operate in stand-alone mode if the grid becomes unavailable. The third step in this thesis investigates small-scale single-phase renewable energy systems operating as decentralized distributed generators within a local network. This operation is achieved by controlling the inverter side using the quantities measured at the common coupling point between the grid and the inverter, without requiring other extensive communications. Thus, the small-scale single-phase renewable energy distributed generator systems will contain only a local controller at each installation.

BACKGROUND:Interruption of vector-borne transmission of Trypanosoma cruzi remains an unrealized objective in many Latin American countries. The task of vector control is complicated by the emergence of vector insects in urban areas.METHODS:Utilizing data from a large-scale vector control program in Arequipa, Peru, we explored the spatial patterns of infestation by Triatoma infestans in an urban and peri-urban landscape. Multilevel logistic regression was utilized to assess the associations between household infestation and household- and locality-level socio-environmental measures.RESULTS:Of 37,229 households inspected for infestation, 6,982 (18.8% / 95% CI: 18.4 - 19.2%) were infested by T. infestans. Eighty clusters of infestation were identified, ranging in area from 0.1 to 68.7 hectares and containing as few as one and as many as 1,139 infested households. Spatial dependence between infested households was significant at distances up to 2,000 meters. Household T. infestans infestation was associated with household- and locality-level factors, including housing density, elevation, land surface temperature, and locality type.CONCLUSIONS:High levels of T. infestans infestation, characterized by spatial heterogeneity, were found across extensive urban and peri-urban areas prior to vector control. Several environmental and social factors, which may directly or indirectly influence the biology and behavior of T. infestans, were associated with infestation. Spatial clustering of infestation in the urban context may both challenge and inform surveillance and control of vector reemergence after insecticide intervention.