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Tsang Yuk Fung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 59-62). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Sequential Monte Carlo --- p.5 / Chapter 2.1 --- Recursive Bayesian estimation --- p.7 / Chapter 2.2 --- Bayesian sequential importance sampling --- p.8 / Chapter 2.3 --- Sclcction of iiiipoitance function --- p.10 / Chapter 2.4 --- Particle filter --- p.12 / Chapter 3 --- Target tracking and data association --- p.15 / Chapter 3.1 --- Target tracking and its applications --- p.16 / Chapter 3.2 --- Data association and JPDA method --- p.16 / Chapter 4 --- Particle filter using the acceptance-rejection method --- p.21 / Chapter 4.1 --- Particle Filter using the acceptance-rejection method --- p.22 / Chapter 4.2 --- Modified accoptance-rcjoction algorithm --- p.24 / Chapter 4.3 --- Examples --- p.26 / Chapter 4.3.1 --- Example 1: One dimensional non-linear case --- p.26 / Chapter 4.3.2 --- Example 2: Bearings-only tracking example --- p.27 / Chapter 4.3.3 --- Example 3: Single-target tracking --- p.31 / Chapter 4.3.4 --- Example 4: Multi-target tracking --- p.33 / Chapter 4.4 --- A new importance weight for bearings-only tracking problem --- p.34 / Chapter 5 --- Conclusion --- p.41

"This dissertation documents a study on parameter estimation methods for comprehensive pyrolysis modeling. There are four parts to this work, which are (1) evaluating effects of applying different kinetic models to pyrolysis modeling of fiberglass reinforced polymer composites; (2); evaluation of pyrolysis parameters for fiberglass reinforced polymer composites based on multi-objective optimization; (3) parameter estimation for comprehensive pyrolysis modeling: guidance and critical observations; and (4) engineering guide for estimating material pyrolysis properties for fire modeling. In the first section (Section 1), evaluation work is conducted to determine the effects of applying different kinetic models (KMs), developed based on thermal analysis using TGA data, when used in typical 1D pyrolysis models of fiberglass reinforced polymer (FRP) composites. The study shows that that increasing complexity of KMs to be used in pyrolysis modeling is unnecessary for the FRP samples investigated. Additionally, the findings from this research indicates that the basic assumption of considering thermal decomposition of each computational cell in comprehensive pyrolysis modeling as equivalent to that in a TGA experiment becomes inapplicable at depth and higher heating rates. The second part of this dissertation (Section 2) reports the results from a study conducted to investigate the ability of global, multi-objective and multi-variable optimization methods to estimate material parameters for comprehensive pyrolysis models. The research materials are two fiberglass reinforced polymer (FRP) composites that share the same fiberglass mats but with two different resin systems. One resin system is composed of a single component and the other system is composed of two components (resin and fire retardant additive). The results show that for a well-configured parameter estimation exercise using the optimization method described above, (1) estimated results are within ± 100% of the measurements in general; (2) increasing complexity of the kinetic modeling for a single component system has insignificant effect on estimated values; (3) increasing complexity of the kinetic modeling for a multiple component system with each element having different thermal characteristics has positive effect on estimated values; and (4) parameter estimation using an optimization method with appropriate level of complexity in kinetic model and optimization targets can find estimations that can be considered as effective material property values. The third part of this dissertation (Section 3) proposes a process for conducting parameter estimation for comprehensive pyrolysis models. The work describes the underlying concepts considered in the proposed process and gives discussions of its limitations. Additionally, example cases of parameter estimation exercise are shown to illustrate the application of the parameter estimation process. There are four materials considered in the example cases – thermoplastics (PMMA), corrugated cardboard, fiberglass reinforced polymer composites and plywood. In the last part (Section 4), the actual Guide, a standardized procedure for obtaining material parameters for input into a wide range of pyrolysis models is presented. This is a step-by-step process that provides a brief description of modeling approaches and assumptions; a typical mathematical formulation to identify model parameters in the equations; and methods of estimating the model parameters either by independent measurements or optimization in pair with the model. In the Guide, example cases are given to show how the process can be applied to different types of real-world materials. "

The estimation of the frequency and phase of a complex exponential in additive white Gaussian noise (AWGN) is a fundamental and well-studied problem in signal processing and communications. A variety of approaches to this problem, distinguished primarily by estimation accuracy, computational complexity, and processing latency, have been developed. One class of approaches is based on the Fast Fourier Transform (FFT) due to its connections with the maximum likelihood estimator (MLE) of frequency. This thesis compares several FFT-based approaches to the MLE in terms of their estimation accuracy and computational complexity. While FFT-based frequency estimation tends to be very accurate, the computational complexity of the FFT and the latency associated with performing these computations after the entire signal has been received can be prohibitive in some scenarios. Another class of approaches that addresses some of these shortcomings is based on linear regression of samples of the instantaneous phase of the observation. Linear- regression-based techniques have been shown to be very accurate at moderate to high signal to noise ratios and have the additional benefit of low computational complexity and low latency due to the fact that the processing can be performed as the samples arrive. These techniques, however, typically require the computation of four-quadrant arctangents, which must be approximated to retain low computational complexity. This thesis proposes a new frequency and phase estimator based on simple estimates of the zero-crossing times of the observation. An advantage of this approach is that it does not require arctangent calculations. Simulation results show that the zero-crossing frequency and phase estimator can provide high estimation accuracy, low computational complexity, and low processing latency, making it suitable for real-time applications. Accordingly, this thesis also presents a real-time implementation of the zero-crossing frequency and phase estimator in the context of a time-slotted round-trip carrier synchronization system for distributed beamforming. The experimental results show this approach can outperform a Phase Locked Loop (PLL) implementation of the same distributed beamforming system.

Typescript (photocopy). / Digitized by Kansas Correctional Industries

Age estimation is a critical component of the biological profile in forensic and bioarchaeological contexts. The majority of age estimation methods are most accurate for individuals of younger age cohorts, typically those under 40 years of age. Skeletal degeneration can vary greatly between individuals, making age estimation less accurate for adult individuals. While there are some methods that attempt to age older individuals accurately and precisely, more research must be conducted to expand the range of methods available. Falys and Prangle (2014) developed a method for estimating age in individuals over the age of 40 using three degenerative characteristics of the sternal end of the clavicle: (1) surface topography, (2) porosity, and (3) osteophyte formation. In order to test their method, a sample of 1,510 individuals of known sex and age, ranging from 20 to 101 years of age (males: n = 1112, mean = 50.57, SD = 18.015; females: n = 398, mean = 53.065, SD = 20.358), were drawn from the McCormick Collection and the William M. Bass Donated Skeletal Collection at the University of Tennessee. Due to the paucity of remains of other ancestries, only individuals of reported White ancestry were used in this study. The two estimation methods proposed in Falys and Prangle (2014), regression equation and composite score, were tested to see how well they perform when applied to a different sample population than the populations used to develop the method. When applied to the collected data, the regression equation produced age estimations that fell within the 95% confidence interval in 47.6% of the male sample and 57.4% of the female sample. Composite scores were calculated and compared to the corresponding age ranges provided in Falys and Prangle (2014). The composite scores of the male sample estimated the age of an individual more accurately than the composite scores of the female sample (male = 65.9%; female = 58.8%). The lowest estimation accuracy for both males and females was between 70-79 years of age (male = 46.0%; female = 51.4%). From 80-89 years of age, the accuracy increased for males (76.4%) and females (69.4%). The sample also included individuals under the age of 40 in order to test whether the inclusion of clavicles with recent epiphyseal union would affect the applicability of the Falys and Prangle (2014) method. Multiple regression equations were generated: (1) individuals over 20 years of age, (2) individuals over 30 years of age, and (3) individuals over 40 years of age. The results from the multiple regression analyses show comparable Pearson’s coefficients for the above mentioned equations (r = 0.690, r = 0.632, and r = 0.611, respectively). Spearman’s rank correlation coefficients indicated a correlation significant at the 0.01 level for all three components individually, as well as the composite score. Of the three components, surface topography was most strongly correlated with age for both males (r = 0.643) and females (r = 0.590). Unlike the findings of Falys and Prangle (2014), porosity was found to be the least correlated with age for both males (r = 0.474) and females (r = 0.514). In addition, when broken down into ten year intervals (40-49, 50-59, etc.), the correlation coefficients increase with advancing age. This suggests that the method becomes more accurate as the age of an individual increases. The inter-observer and intra-observer agreement tests produced very low agreement values. The low observer agreement indicates that the current scoring method is not a reliable, repeatable technique. However, when examined further, the observed trait values that differed between the tests primarily differed by one score. These results suggest that condensing the scores in order to account for more variation would likely increase the observer agreement. However, condensing the scores would result in larger age intervals, which nullifies the purpose of this method. The findings in the present study indicate that the sternal end of the clavicle has potential for use in age estimation in older individuals. Although the present study produced lower correlation coefficients than proposed by the original study in 2014, the correlations and age-at-transition test results suggest that the sternal end of the clavicle deteriorates in a predictable manner that, with more observation and understanding, could be used to accurately age older individuals more precisely than the large age intervals currently in use. Despite the correlations between the degeneration of the sternal end of the clavicle and the age-at-death, the error rates suggest it is not a reliable alternative to the current methods used.