Two flow reactor studies, using an electrically heated laminar flow reactor over Vanadia based (V2O5-WO3/TiO2) honeycomb catalyst, were performed at 1 atm pressure and various temperatures. The experiments were conducted using simulated exhaust gas compositions for different exhaust gases. A quartz tube was used in order to establish inert conditions inside the reactor. The experiments utilized a Fourier transform infrared (FTIR) spectrometer in order to perform both qualitative and quantitative analysis of the reaction products. Urea-water solution decomposition was investigated over V2O5-WO3/TiO2 catalyst over the entire SCR temperature range using the temperature controlled flow reactor. The solution was preheated and then injected into pure nitrogen (N2) stream. The decomposition experiments were conducted with a number of oxygen (O2) compositions (0, 1, 10, and 15%) over the temperature range of 227oC to 477oC. The study showed ammonia (NH3), carbon-dioxide (CO2) and nitric oxide (NO) as the major products of decomposition along with other products such as nitrous oxide (N2O) and nitrogen dioxide (NO2). The selective catalytic reduction (SCR) of nitric oxide (NO) with urea-water solution over V2O5-WO3/TiO2 catalyst using a laboratory laminar-flow reactor was investigated. Urea-water solution was injected at a temperature higher than the vaporization temperature of water and the flow reactor temperature was varied from 127oC to 477oC. A FTIR spectrometer was used to determine the concentrations of the product species. The major products of SCR reduction were NH3, NO and CO2 along with the presence of other minor products NO2 and N2O. NO removal of up to 87% was observed. The aim of the urea-water decomposition experiments was to study the decomposition process as close to the SCR configuration as possible. The aim of the SCR experiments was to delineate the effect of various parameters including reaction temperature and O2 concentration on the reduction process. The SCR investigation showed that changing parameter values significantly affected the NO removal, the residual NH3 concentration, the temperature of the maximum NO reduction, and the temperature of complete NH3 conversion. In the presence of O2, the reaction temperature for maximum NO reduction was 377?C for ratio of 1.0.

Ultrasonic guided waves having the ability to inspect long distance pipeline is one of the non-destructive testing methods. The reflected echoes as well as mode conversion phenomena indicate the presence of defect or other features on the pipe. To study the feasibility of guided wave quantification of sludge inside pipes, this thesis applies the transient simulation by finite element method to analyze the scattering of the guided T(0,1) mode by non-axisymmetry layer inside a pipe. Both the Two-dimensional Fourier transform and Wavelet transform were used to process the signals to understand the scattering behavior. The numerical analyses revealed the following phenomena. First, partial energy of the T(0,1) mode will leaky into the asymmetric layer when T(0,1) mode propagates along the pipe and impinge onto the asymmetric layer inside a pipe named a composite pipe. The T(0,1) mode will convert to the propagating modes of the composite pipe model. Secondly, the composite pipe will reflect the T(0,1) and modes of higher circumferential order. The percentage of asymmetric layer inside a pipe is one of the parameter controlling the reflection spectrum response. To sum up, in this study, the reflection spectrum response could used to predict the quantified accumulation of sludge by wavelet transform through time-frequency analysis.

A circuit design of Fast Fourier Transform for DVB-H system is presented in this thesis. This circuit is based on SDF (single path delay feedback) pipeline architecture with radix-2 computation element. We propose a novel method of timing scheduling that can share one complex multiplier for couple of stage and promote the utilization of complex multiplier to 100%, so we can improve the implementation with radix-2 computation. The number of bits is carefully selected by system simulation to meetthe requirements of DVB-H system. In addition, a memory table permutation deletion method for memory scheduling, which can reduce the size of memory storing twiddle factors tables. The circuit is carried out by CMOS 0.18£gm 1P6M process with core area 2.08 x 2.076 mm2. In the gate level simulation, the output data rate of this circuit is above 50MHz, so the circuit can meet the requirement of DVB-H system.

<p>In this dissertation a novel approach to protein-ligand docking is presented. First an existing method to predict putative active sites is employed. These predictions are then used to cut down the search space of an algorithm that uses the fast Fourier transform to calculate the geometrical and electrostatic complementarity between a protein and a small organic ligand. A simplified hydrophobicity score is also calculated for each active site. The docking method could be applied either to dock ligands in a known active site or to rank several putative active sites according to their biological feasibility. The method was evaluated on a set of 310 protein-ligand complexes. The results show that with respect to docking the method with its initial parameter settings is too coarse grained. The results also show that with respect to ranking of putative active sites the method works quite well.</p>

Invariant object recognition is maybe the most basic and fundamental property of our visual system. It is the basis of many other cognitive tasks, like motor actions and social interactions. Hence, the theoretical understanding and modeling of invariant object recognition is one of the central problems in computational neuroscience. Indeed, object recognition consists of two different tasks: classification and identification. The focus of this thesis is on object identification under the basic geometrical transformations shift, scaling, and rotation. The visual system can perform shift, size, and rotation invariant object identification. This thesis consists of two parts. In the first part, we present and investigate the VisNet model proposed by Rolls. The generalization problems of VisNet triggered our development of a new neural network model for invariant object identification. Starting point for an improved generalization behavior is the search for an operation that extracts images features that are invariant under shifts, rotations, and scalings. Extracting invariant features guarantees that an object seen once in a specific pose can be identified in any pose. We present and investigate our model in the second part of this thesis.

Thesis (Ph. D.)--University of Missouri-Columbia, 2000. / Typescript. Vita. Includes bibliographical references (leaves 132-137). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 1998. / Typescript. Vita. Includes bibliographical references (leaves 134-139). Also available on the Internet.

Thesis (M.Sc.-Res.)--University of Wollongong, 2009. / Typescript. Includes bibliographical references: leaf 91-95.

Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references. Available also in a digital version from Dissertation Abstracts.

Thesis (M.S.)--Mechanical Engineering, Georgia Institute of Technology, 2004. / Fedorov, Andrei, Committee Member ; Mahan, J. Robert, Committee Member ; Zhang, Zhuomin, Committee Chair. Includes bibliographical references (leaves 80-82).