Thesis (B.S.)--University of Missouri, School of Mines and Metallurgy, 1903. / The entire thesis text is included in file. Typescript. Illustrated by author. C. M. Daily determined to be Cornelius Mark Daily from "Forty-First Annual Catalogue. School of Mines and Metallurgy, University of Missouri". Title from title screen of thesis/dissertation PDF file (viewed January 29, 2009)

No description available.

published_or_final_version / abstract / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

Approved for public release; distribution is unlimited / The characteristics and application of a thyristor (a four-layer semiconductor structure) in a pulse generating circuit are explored. A thyristor device was used to create a pulse generating circuit and the pulse interval duration of this circuit was experimentally measured. The pulse interval duration was determined to be characterized by a Poisson Point Process distribution that is dependent on both temperature and applied voltage bias. The adjustable aperiodicity of the pulse intervals was a key characteristic used to design a distributed processing system of micro-robots that are capable of swarming. A micro-robotic swarm platform was simulated using finite element analysis, a JAVA-based swarm model, and three fully operational macro-scale platforms. / Outstanding Thesis

by Lee Kim-hung. / Thesis (M.Phil.)--Chinese University of Hong Kong. / Bibliography: leaf 60.

Typescript, etc. / Digitized by Kansas Correctional Industries

Lee Ming Ho. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 78-80). / Abstracts in English and Chinese. / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1. --- Background on development of AA size micro power generator --- p.1 / Chapter 1.1.1. --- Brief introduction --- p.1 / Chapter 1.1.2. --- Proposed micro power generator for wireless applications --- p.2 / Chapter 1.2. --- Literature survey --- p.3 / Chapter 1.2.1. --- Comparison of other energy sources --- p.3 / Chapter 1.2.2. --- An overview of research on electromagnetic micro power generator --- p.5 / Chapter Chapter 2 --- Principle of Micro Power Generator --- p.7 / Chapter 2.1 --- Design objective ofAA size micro power generator --- p.7 / Chapter 2.2 --- Faraday ´ةs Law of induced current --- p.9 / Chapter 2.3 --- Modal for the micro power generator system --- p.10 / Chapter 2.4 --- Design of the micro power generator --- p.13 / Chapter 2.5 --- Integrated power cell --- p.20 / Chapter Chapter 3 --- MEMS Resonator --- p.23 / Chapter 3.1. --- Design of the micro resonator --- p.23 / Chapter 3.1.1. --- Introduction to micro resonator --- p.23 / Chapter 3.1.2. --- Selection of material --- p.24 / Chapter 3.1.3. --- Different modes of vibration --- p.25 / Chapter 3.2. --- Laser Micro-machining --- p.26 / Chapter 3.3. --- MEMS Fabricated Spring --- p.28 / Chapter 3.3.1. --- Introduction of SU-8 based electroplating technique --- p.28 / Chapter 3.3.2. --- Fabrication process --- p.31 / Chapter Chapter 4 --- Characteristic of AA Size Micro Power Generator --- p.33 / Chapter 4.1. --- Experiment on a single micro power transducer --- p.36 / Chapter 4.1.1. --- Testing a single transducer without loading --- p.37 / Chapter 4.1.2. --- Testing a single transducer connected with a power management circuit --- p.38 / Chapter 4.1.3. --- Testing a single transducer with power management circuit and a 100kΩ resistor --- p.39 / Chapter 4.1.4. --- Summary of experiments on the micro power transducer --- p.40 / Chapter 4.2. --- Experiment on finding a way to increase power output --- p.41 / Chapter 4.3. --- Experiment for connecting two micro power transducers --- p.43 / Chapter 4.3.1. --- Testing on two micro power transducers connected in series --- p.44 / Chapter 4.3.2. --- Testing on combined micro power transducers with power management circuit --- p.47 / Chapter 4.4. --- Experiment on the integrated AA size micro power generator --- p.49 / Chapter 4.4.1. --- Interaction of magnetic dipole between two micro power transducers --- p.50 / Chapter 4.4.2. --- AA size micro power generator under varying input vibration frequencies --- p.52 / Chapter Chapter 5 --- Simulation and Analysis --- p.55 / Chapter 5.1. --- FEA Modeling of the MEMS Resonators --- p.55 / Chapter 5.2. --- Micro power generator system modeling --- p.57 / Chapter 5.3. --- Optimization --- p.60 / Chapter Chapter 6 --- Applications --- p.63 / Chapter 6.1. --- Wireless Temperature Sensing System --- p.64 / Chapter 6.2. --- Measurement of car vibration for noval applications --- p.70 / Chapter 6.2.1. --- Measurement of car vibration in stationary condition --- p.71 / Chapter 6.2.2. --- Measurement of car vibration traveling in The Chinese University of Hong Kong (CUHK) --- p.72 / Chapter 6.2.3. --- Measurement of car vibration traveling in rough pattern road (Tai Po Road) --- p.73 / Chapter 6.3. --- Human motion analysis --- p.74 / Chapter Chapter 7 --- Conclusion --- p.76 / Reference --- p.78 / Appendix --- p.81

Stochastic weather generators create multiple series of synthetic daily weather (precipitation, maximum temperature, etc.), and ideally these series will have statistical properties similar to those of the input historical data. The synthetic output has many applications and for example, can be used in sectors such as agriculture and hydrology. This work used a ?hybrid? weather generator which consists of a parametric Markov chain for generating precipitation occurrence and a nonparametric k-nearest neighbor method for generating values of maximum temperature, minimum temperature, and precipitation. The hybrid weather generator was implemented and validated for use at 11 different locations in the Southeastern United States. A total of 36 graphic diagnostics were used to assess the model?s performance. These diagnostics revealed that the weather generator successfully created synthetic series with most statistical properties of the historical data including extreme wet and dry spell lengths and days of first and last freeze. Climate forecasts are typically provided for seasons or months. Alternatively, process models used for risk assessment often operate at daily time scales. If climate forecasts were incorporated into the daily weather input for process models, stakeholders could then use these models to assess possible impacts on their sector of interest due to anticipated changes in climate conditions. In this work, an ?ad hoc? resampling approach was developed to create sets of daily synthetic weather series consistent with seasonal climate forecasts in the Southeastern United States. In this approach, the output of the hybrid weather generator was resampled based on forecasts in two different formats: the commonly used tercile format and a probability distribution function. This resampling approach successfully created sets of synthetic series which reflected different forecast scenarios (i.e. wetter or drier conditions). Distributions of quarterly total precipitation from the resampled synthetic series were found to be shifted with respect to the corresponding historical distributions, and in some cases, the occurrence and intensity statistics of precipitation in the new weather series had changed with respect to the historical values.

Project (M.S.)--Brigham Young University. Dept. of Statistics, 2005. / Includes bibliographical references (p. 82-85).

Thesis (Ph. D.)--University of Missouri-Columbia, 2003. / Typescript. Vita. Includes bibliographical references (leaves 140-141). Also available on the Internet.