In a nuclear reactor, delayed neutrons play a critical role in sustaining a controllable chain reaction. Delayed neutron’s relative yields and decay constants are very important for modeling reactivity control and have been studied for decades. Researchers have tried different experimental and numerical methods to assess these delayed neutron parameters. The reported parameter values vary widely, much more than the small statistical errors reported with these parameters. Interestingly, the reported parameters fit their individual measurement data well in spite of these differences. This dissertation focuses on evaluation of the errors and methods of delayed neutron relative yields and decay constants for thermal fission of U-235. Various numerical methods used to extract the delayed neutron parameter from the measured data, including Matrix Inverse, Levenberg-Marquardt, and Quasi-Newton methods, were studied extensively using simulated delayed neutron data. This simulated data was Poisson distributed around Keepin’s theoretical data. The extraction methods produced totally different results for the same data set, and some of the above numerical methods could not even find solutions for some data sets. Further investigation found that ill-conditioned matrices in the objective function were the reason for the inconsistent results. To find a reasonable solution with small variation, a regularization parameter was introduced using a numerical method called Ridge Regression. The results from the Ridge Regression method, in terms of goodness of fit to the data, were good and often better than the other methods. Due to the introduction of a regularization number in the algorithm, the fitted result contains a small additional bias, but this method can guarantee convergence no matter how large the coefficient matrix condition number. Both saturation and pulse modes were simulated to focus on different groups. Some of the factors that affect the solution stability were investigated including initial count rate, sample flight time, initial guess values. Finally, because comparing reported delayed neutron parameters among different experiments is useless to determine if their data actually differs, methods are proposed that can be used to compare the delayed neutron data sets.

The second-order least squares (SLS) method in regression model proposed by Wang (2003, 2004) is based on the first two conditional moments of the response variable given the observed predictor variables. Wang and Leblanc (2008) show that the SLS estimator (SLSE) is asymptotically more efficient than the ordinary least squares estimator (OLSE) if the third moment of the random error is nonzero. We apply the SLS method to variable selection problems and propose the adaptively weighted L1 regularized SLSE (L1-SLSE). The L1-SLSE is robust against the shape of error distributions in variable selection problems. Finite sample simulation studies show that the L1-SLSE is more efficient than L1-OLSE in the case of asymmetric error distributions. A real data application with L1-SLSE is presented to demonstrate the usage of this method. / October 2015

The stability of inkjet print is influenced by a lot of factors. Mutual effects of these factors accelerate the print degradation. The surrounding environment in image stability plays an important role, when the prints degrade especially by the light. The degradation of inkjet prints is presented as a decrease of dye or multiple dyes. It is necessary to know the dye concentration for the dye decrease prediction in the time. This dissertation thesis deals with the study of kinetics and changes in electron and molecular structure of digital photography prints after accelerated ageing tests. The study of resistance of inkjet prints was realized on one type of media using three different sets of inks. Changes in printed colours were measured and evaluated in calibration (by PLS calibration and least squares method). On the basis of calibration the dye decrease prediction of real samples in receiving layer was evaluated. Changes in electron and molecular structure were analysed on KBr pellets by FTIR an UV-Vis spectroscopy.

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ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada / Compass-I system is China has built satellite navigation system. It's a kind of regional position system according to the double-star position principle. Commonly, Compass-I system need adopt active position, in the paper several passive position methods are put forward. A combination navigation mode based on GLONASS and Compass-I passive navigation is proposed in this paper. The differences of coordinates and time systems between those two navigation systems are analyzed. User position is calculated by least squares method. Combination Navigation Algorithm can improve visible satellite constellation structure and positioning precision so as to ensure the reliability and continuity of positioning result.

Neste trabalho são propostos métodos para a estimação de parâmetros de motores de indução através do método dos Mínimos Quadrados com medição apenas de tensões, correntes e resistência do estator em um ensaio de partida em vazio. São detalhados os procedimentos para o tratamento dos sinais medidos, além das estimações do fluxo magnético e da velocidade mecânica do motor. Para a estimação dos parâmetros elétricos, são propostos métodos que diferem nos requisitos e no tratamento dos parâmetros como invariantes ou variantes no tempo. Em relação a esse último caso, é empregado um método de estimação de parâmetros por janelas de dados, aplicando um modelo com parâmetros invariantes no tempo localmente em diversas partes do ensaio. São feitas simulações para validar os métodos propostos, e dados de ensaio de três motores de diferentes potências são utilizados para analisar a escala de variação paramétrica durante a partida. É feita uma comparação entre os resultados obtidos com e sem consideração de variação nos parâmetros. / In this work, methods are proposed to estimate the parameters of induction motors through the Least Squares method with the measurement of only voltages, currents and resistance of the stator in a no-load startup test. Procedures are detailed to process the measured signals, as well as to estimate magnetic flux and rotor mechanical speed. In order to estimate the electrical parameters, methods are proposed which differ in their requisites and in the treatment of parameters as time invariant or time-varying. For the latter, a methodology for parameter estimation through data windows is used, applying a model with time invariant parameters locally to different parts of the test. Simulations are made to validate the proposed methodology, and data from tests of three motors with different powers are used to analyze the scale of parameter variation during startup. A comparison is made between the results obtained with and without the consideration of variation in the parameters.

Power systems are protected by numerical relays that detect and isolate faults that may occur on power systems. The correct operation of the relay is very important to maintain the security of the power system. <p>Numerical relays that use voltage measurements from the power system provided by coupling capacitor voltage transformers (CCVT) have sometimes difficulty in correctly identifying a fault in the protected area. The fundamental frequency voltage phasor resulting from these CCVT measurements may result in a deviation from the true value and therefore may locate this phasor temporarily in the incorrect operating region. This phasor deviation is due to the CCVT behavior and the CCVT introduces spurious decaying and oscillating transient signal components on top of the original voltage received from the power system in response to sudden voltage changes produced during faults. Most of the existing methods for estimating the voltage phasor do not take advantage of the knowledge of the CCVT behavior that can be obtained from its design parameters.<p>A new least squares error method for phasor estimation is presented in this thesis, which improves the accuracy and speed of convergence of the phasors obtained, using the knowledge of the CCVT behavior. The characteristics of the transient signal components introduced by the CCVT, such as frequencies and time constants of decay, are included in the description of the curve to be fitted, which is required in a least squares fitting technique. Parameters such as window size and sampling rate for optimum results are discussed.<p>The method proposed is evaluated using typical power systems, with results that can be compared to the response if an ideal potential transformer (PT) were used instead of a CCVT. The limitations of this method are found in some specific power system scenarios, where the natural frequencies of the power system are close to that of the CCVT, but with longer time constants. The accuracy with which the CCVT parameters are known is also assessed, with results that show little impact compared to the improvements achievable.

Power systems are protected by numerical relays that detect and isolate faults that may occur on power systems. The correct operation of the relay is very important to maintain the security of the power system. <p>Numerical relays that use voltage measurements from the power system provided by coupling capacitor voltage transformers (CCVT) have sometimes difficulty in correctly identifying a fault in the protected area. The fundamental frequency voltage phasor resulting from these CCVT measurements may result in a deviation from the true value and therefore may locate this phasor temporarily in the incorrect operating region. This phasor deviation is due to the CCVT behavior and the CCVT introduces spurious decaying and oscillating transient signal components on top of the original voltage received from the power system in response to sudden voltage changes produced during faults. Most of the existing methods for estimating the voltage phasor do not take advantage of the knowledge of the CCVT behavior that can be obtained from its design parameters.<p>A new least squares error method for phasor estimation is presented in this thesis, which improves the accuracy and speed of convergence of the phasors obtained, using the knowledge of the CCVT behavior. The characteristics of the transient signal components introduced by the CCVT, such as frequencies and time constants of decay, are included in the description of the curve to be fitted, which is required in a least squares fitting technique. Parameters such as window size and sampling rate for optimum results are discussed.<p>The method proposed is evaluated using typical power systems, with results that can be compared to the response if an ideal potential transformer (PT) were used instead of a CCVT. The limitations of this method are found in some specific power system scenarios, where the natural frequencies of the power system are close to that of the CCVT, but with longer time constants. The accuracy with which the CCVT parameters are known is also assessed, with results that show little impact compared to the improvements achievable.

There exist many methods for facial recognition, such as eigenface, templates, artificial neural networks, etc., based on the given facial sample data (patterns). When an input facial image (target) involve simple geometrical transformations and illumination, the performance of these methods are not very satisfactory. In this thesis, following Li et al., we propose a new face recognition system, which can eliminate translation, rotation, scaling, and prospective transformations of facial images automatically, and can also eliminate illumination. According to facial features, we use this method to find the best transformation and the closet illumination, and then to eliminate them for identification by the best matching between a target and the patterns. Finally, we use the least squares method to recognize the target. This method is validated by numerical examples.

This article emphasizes on fitting GARCH option pricing model with Taiwan stock market. Duan¡¦s(1995) NGARCH option pricing model is adopted. Duan solved the European option by simulation, this article follow the method and extents to pricing American option. In general, simulation approach is not convenient to solve American options as well as European options. However, the least-squares method proposed by Longstaff and Schwartz is a simple and powerful tool, so this article tests the method. The NGARCH model has parameters, and base on loglikelihood function, we fit the model with empirical observations to obtain parameters. Then we can simulate the stock prices, once stock prices are simulated, the option value can be priced. Since the article simulates the option, there should be the antithetic approaches instead of simulation. In practice, the Black-Schoels model is the benchmark for pricing European option, so this article compares the simulated European options with Black-Scholes. For American option, this article compares the simulated American options which are priced by least-squares method with trinomial tree (finite difference method).