In this thesis, we develop and test a fundamentally new linear-discontinuous least-squares (LDLS) method for spatial discretization of the one-dimensional (1-D) discrete-ordinates (SN) equations. This new scheme is based upon a least-squares method with a discontinuous trial space. We implement our new method, as well as the lineardiscontinuous Galerkin (LDG) method and the lumped linear-discontinuous Galerkin (LLDG) method. The implementation is in FORTRAN. We run a series of numerical tests to study the robustness, L2 accuracy, and the thick diffusion limit performance of the new LDLS method. By robustness we mean the resistance to negativities and rapid damping of oscillations. Computational results indicate that the LDLS method yields a uniform second-order error. It is more robust than the LDG method and more accurate than the LLDG method. However, it fails to preserve the thick diffusion limit. Consequently, it is viable for neutronics but not for radiative transfer since radiative transfer problems can be highly diffusive.

In this thesis, we study the least trimmed squares artificial neural networks (LTS-ANNs), which are generalization of the least trimmed squares (LTS) estimators frequently used in robust linear parametric regression problems to nonparametric artificial neural networks (ANNs) used for nonlinear regression problems. Two training algorithms are proposed in this thesis. The first algorithm is the incremental gradient descent algorithm. In order to speed up the convergence, the second training algorithm is proposed based on recursive least squares (RLS). Three illustrative examples are provided to test the performances of robustness against outliers for the classical ANNs and the LTS-ANNs. Simulation results show that upon proper selection of the trimming constant of the learning machines, LTS-ANNs are quite robust against outliers compared with the classical ANNs.

In recent years, the main determinants of gold price have changed worldwide due to the increasing demand of gold. Additionally, TAIFEX provided investors with anothor trading instruments by launching US Dollar-denominated Gold Futures. Therefore, Taiwan gold market and stock market might interact more closely than before. The purpose of this study was to examine the endogenous relationship between gold price and stock price, and then analyze both markets with multi-equation simulation model and two-stage least squares method. The result shows that there is endogenous relationship between these two variables. Besides, depreciation of US dollar would lead to a rise in gold price which is denominated by US dollar. Exchange rate and stock price also moved in opposite directions. Finally, the launching of gold futures truly interested the investors and boosted the gold price.

In this thesis, we investigate the CDMA (Code Division Multiple Access) multi- user detection scheme where the DD (Decorrelating Detector) is used to eliminate the multiple access interference. The DD algorithm need to compute the inverse of the matrix involves a great deal of computation, especially when the number of users is large. A recursive method with the LMS (Least-Mean-Square) algorithm, namely the decorrelating transversal filter, to detect users¡¦ signals adaptively can reduce greatly the computational complexity of a CDMA multi-user detector. In this thesis, we focus on the hardware FPGA (Fdield Programmable Gate Array) implementation of the decorrelating transversal filter. The functional system simulation of the decorrelating transversal filter is carried out by using Matlab first. Then this filter is implemented by the Xilinx FPGA and its system performance is also verified.

Structural equation model (SEM) is a general approach to analyze multivariate data. It is a relatively comprehensive model and combines useful characteristics from many statistical approaches, thus enjoys a variety of advantages when dealing complex relationships. This report gives a brief introduction to SEM, focusing especially the comparison of SEM and OLS regression. A simple tutorial of how to apply SEM is also included with the introduction and comparison. SEM can be roughly seen as OLS regression added with features such as simultaneous estimation, latent factors and autocorrelation. Therefore, SEM enjoys a variety of advantages over OLS regression. However, it is not always the case that SEM will be the optimal choice. The biggest concern is the complexity of SEM, for simpler model will be preferable for researchers when the fitness is similar. Two simulation cases, one requires special features of SEM and one satisfies assumptions of OLS regression, are applied to illustrate the choice between SEM and OLS regression. A study using data from US life insurers in the year 1994 serves as a further illustration. The conclusion is when special features of SEM is required, SEM fits better and will be the better choice, while when OLS regression assumptions are satisfied, SEM and OLS regression will fit equally well, considering the complexity of SEM, OLS regression will be the better choice. / text

The objective of the study is to analyze the effect of remittances on socio-economic conditions of rural families in Peshawar, and how remittances change the decision-making process of families. This study examines the effects of remittances on local population in three towns of Peshawar, i.e. Hayatabad, Faqir-Abad and Gulberg-area. The study is basically conducted to see how remittances bring changes in the life of the recipients. The research is quantitative, data was collected through questionnaires. For the research, a sample of 300 respondents was selected from three towns in Peshawar District. The results of the research were interpreted through statistical tools, regression model. The Ordinary least square method (OLS) was used to find out the effect of remittances on health sector and investment made by respondents in the form of purchased property and investment made in establishing their own businesses. Along with that, the simple Logit Model was also used. The result is generalized on linear model with link logit and binomial response. Findings stated that the literacy level of the emigrant’s household positively impacted on children’s probability to move to private education. The results reveals that the recipient invest 4% of their income on investment as a form of business and purchasing property while educated people appears not to be interested in investing money in businesses as they want to continue their jobs. Respondent are not using a large portion of their remittances for health perhaps mostly people are entitled to free services from the government. Remittances changed their standard of living and socio economic affairs of the remittances receiving respondents. According to my demographic information about respondents life, the remittances mostly brings changes in the physical part of people life such as Private Education, Personal transport, new houses, investment in buying properties, more electric appliances, bank balance etc., but culturally people are still conservative and believe in cultural values that have been practices by local population for centuries. Following are some main recommendations that this research has identified, Foreign remittances are improving the socio-economic conditions and decision making of rural families, however, their consumption behavior is not inclined towards investment, they rather prefer to enjoy luxurious household’s equipment. Therefore, it is recommended that these families should utilize their resources in more efficient way, and should go for short and long term investment avenues. Government must design policies in order to educate these families and create awareness among them that will enable them to look for sustainable domestic income, which would help the families in the long run. These families follow the norms and traditions, and they prefer sending their children abroad for earning purposes, which in turn is comparatively less profitable idea as compared to sending these children for higher education purpose.

published_or_final_version / abstract / toc / Physics / Master / Master of Philosophy

<p>ix, [1] s., s. 1-7: sammanfattning, s. 8-142: 6 uppsatser</p> / digitalisering@umu

Mud-pulse telemetry is a method used for measurement-while-drilling (MWD)in the oil industry. The telemetry signals are corrupted by spurious mud pump noise consisting of a large number of harmonically related sinusoids. In order to denoise the signal, the noise parameters have to be tracked accurately in real time. There are well established parametric estimation techniques for determining various parameters of independent sinusoids. The iterative methods based on the linear prediction properties of the sinusoids provide a computationally e±cient way of solving the non linear optimization problem presented by these methods. However, owing to the large number of these sinusoids, incorporating the harmonic relationship in the problem becomes important. This thesis is aimed at solving the problem of estimating parameters of harmonically related sinusoids. We examine the efficacy of IQML algorithm in estimating the parameters of the telemetry signal for varying SNRs and data lengths. The IQML algorithm proves quite robust and successfully tracks both stationary and slowly varying frequency signals. Later, we propose an algorithm for fundamental frequency estimation which relies on the initial harmonic frequency estimate. The results of tests performed on synthetic data that imitates real field data are presented. The analysis of the simulation results shows that the proposed method manages to remove noise causing sinusoids in the telemetry signal to a great extent. The low computational complexity of the algorithm also makes for an easy implementation on field where computational power is limited.

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