Thesis (Ph. D.)--University of Texas at Austin, 2005. / Supervisor: Risto Miikkulainen. Vita. Includes bibliographical references.

Thesis (M.S.C.I.T.)--Regis University, Denver, Colo., 2006. / Title from PDF title page (viewed on May 24, 2006). Includes bibliographical references.

Thesis (M.S. in Computer Science)--Naval Postgraduate School, September 2009. / Thesis Advisor(s): Singh, Gurminder ; Gibson, John. "September 2009." Description based on title screen as viewed on November 6, 2009. Author(s) subject terms: Microelectromechanical systems, photovoltaic, piezoelectric, thermocouple, power harvesting, energy scavenging, thermoelectric. Includes bibliographical references (p. 59-65). Also available in print.

Thesis (Ph.D.)--Boston University / Carbon based n-conjugated materials, such as conducting polymers, fullerene, carbon nanotubes, graphene. and conjugated dendrimers have attracted wide scientific attentions in the past three decades. This work presents the first unified model Hamiltonian that can accurately capture the low-energy excitations among all these pi-conjugated systems, even with the presence of defects and heterogeneous sites. Two transferable physical parameters are incorporated into the Su-Schrieffer-Heeger Hamiltonian to model conducting polymers beyond polyacetylene: the parameter 1 scales the electronphonon coupling strength in aromatic rings and the other parameter e specifies the heterogeneous core charges. This generic Hamiltonian predicts the fundamental band gaps of polythiophene, polypyrrole, polyfuran, poly- (p-phenylene), poly-(p-phenylene vinylene), polyacenes, fullerene, carbon nanotubes, graphene, and graphene nanoribbons with an accuracy exceeding time-dependent density functional theory. Its computational costs for moderate-length polymer chains are more than eight orders of magnitude lower than first-principles approaches. The charge and energy transports along -conjugated backbones can be modeled on the adiabatic potential energy surface. The adiabatic minimum-energy path of a self-trapped topological soliton is computed for trans-polyacetylene. The frequently cited activation barrier via a ridge shift of the hyper-tangent order parameter overestimates its true value by 14 orders of magnitude. Self-trapped solitons migrate along the Goldstone mode direction with continuously adj usted amplitudes so that a small-width soliton expands and a large- width soliton shrinks when they move uphill. A soliton with the critical width may migrate without any amplitude modifications. In an open chain as solitons move from the chain center toward a chain edge, the minimum-energy path first follows a tilted washboard. Such a generic constrained Goldstone mode relaxation approach is applicable to the pinning dynamics due to the presence of structural defects and counter ions. The interchain 7r - 7r interactions are modeled using distance-dependent hopping integrals. Excellent agreements in their binding energetics and geometries with post-Hartree-Fock ab initio methods are found for the benzene dimer and the infinite 2D graphene cases. The computed photo-induced charge separated states and associated adsorption spectra agree perfectly with the experimental measurements.

<p> The goal of this research is to critically examine the nexus of risk management, decision-making, and knowledge management in an integrated framework, or triad. This research will examine this framework through the lens of managers in both human and scientific spaceflight missions at the National Aeronautics and Space Administration (NASA). It is intended to expose how coupling risk, knowledge and decision-making improve chances for mission success while potentially averting mishaps. Historical case studies of NASA Programs will be used to validate this assertion. Common risk management and knowledge management processes will be examined as enablers for risk-informed decision-making, particularly for residual risk acceptance decisions. Decision-making under normal programmatic conditions as well as during anomalous or mishap-related conditions will also be assessed. </p><p> Residual risk acceptance decision-making might be considered a special case of a requisite decision analysis model. In the context of NASA programs and projects these decisions are made throughout the lifecycle. They take on special significance however in the context of human spaceflight missions such as whether to: proceed with human-tended test and evaluation, to launch, or to respond to an off-nominal condition on-orbit. Finally, this dissertation offers a checklist for use by managers to improve residual risk acceptance decision competency within an organization.</p><p>

<p> Human error remains the highest symptomatic cause of system failure across multiple domains. Technology failure has seen a significant rate decrease through analyses and design changes, but human error causal factors have not experienced the same level of improvement. Designers and developers need improved methods to model the events leading up to and resulting in human error events. </p><p> This study examines the reported causal data of an integrated human complex system, multi-engine aircraft data, and explores methods of evaluating those data to identify the factors contributing to system failure including the human actor, technology and latent factors. The analysis methods demonstrated in this paper provide a means of assessing symptomatic failure data to provide quantitative information about the failure modes and related latent causal factors. National Transportation and Safety Board (NTSB) aviation accident data is coded using the Human Factors Analysis and Classification System (HFACS) to provide a framework for evaluating the mediating and moderating effects affecting the symptomatic and latent causal factors. We comparatively analyze these accident data for general aviation and air transport pilots to evaluate potential causal factor differences. The methodology explored leverages previous work in causal relationships to model the relationships between latent causal factors and symptomatic causal factors. </p><p> Two methods are employed to evaluate the data. Hierarchical multiple regression is used as derived from the Baron and Kenny method for statistical evaluation of moderator and mediator effects on human behavior. Multiple variable logistic regression is used to model the relationships between latent causal factors, symptomatic causal factors and accident severity. The usefulness of the framework and the possibilities for future research are discussed. </p><p> The findings first confirm the inverse relationship between pilot experience and accident rate to establish a baseline from which the quantifiable mediating and moderating effects of direct causal factors and latencies are demonstrated. Further analysis elucidates the association between the symptomatic human error initiating events and the latent failure causal factors. These data analyses are used to demonstrate the systemic relationships of the spatially and temporally disparate symptomatic and latent causal factors. </p><p> The relationship between symptomatic causal factor and latent causal factors are modeled using a causal loop and probability path diagrams. These methods identify the causal factors with the most impact to help guide users, managers and policy-makers as mitigation strategies are developed. The method is transportable to other systems based on the universality of the methods described. This research helps to enhance the ability to develop an objective systemic perspective to enable holistic solution sets. </p><p> The benefit to the systems engineering domain is the demonstration of methods that quantify and objectively link the symptomatic causal human error events initiating failures to the latent causal factors where mitigation methods can be applied. Using these methods, systems can be analyzed to better understand the disparate causal effects affecting system failure in complex socio-technical systems and actions that can be taken to mitigate the latent causal factors behind symptomatic events.</p><p>

The global mobile data traffic has increased tremendously in the last decade due to the technological advancement in smartphones. Their endless usage and bandwidth-intensive applications will saturate current 4G technologies and has motivated the need for concrete research in order to sustain the mounting data traffic demand. In this regard, the network densification has shown to be a promising direction to cope with the capacity demands in future 5G wireless networks. The basic idea is to deploy several low power radio access nodes called small cells closer to the users on the existing large radio foot print of macrocells, and this constitutes a heterogeneous network (HetNet). However, there are many challenges that operators face with the dense HetNet deployment. The mobility management becomes a challenging task due to triggering of frequent handovers when a user moves across the network coverage areas. When there are fewer users associated in certain small cells, this can lead to significant increase in the energy consumption. Intelligently switching them to low energy consumption modes or turning them off without seriously degrading user performance is desirable in order to improve the energy savings in HetNets. This dynamic power level switching in the small cells, however, may cause unnecessary handovers, and it becomes important to ensure energy savings without compromising handover performance. Finally, it is important to evaluate mobility management schemes in real network deployments, in order to find any problems affecting the quality of service (QoS) of the users. The research presented in this dissertation aims to address these challenges. First, to tackle the mobility management issue, we develop a closed form, analytical model to study the handover and ping-pong performance as a function of network parameters in the small cells, and verify its performance using simulations. Secondly, we incorporate fuzzy logic based game-theoretic framework to address and examine the energy efficiency improvements in HetNets. In addition, we design fuzzy inference rules for handover decisions and target base station selection is performed through a fuzzy ranking technique in order to enhance the mobility robustness, while also considering energy/spectral efficiency. Finally, we evaluate the mobility performance by carrying out drive test in an existing 4G long term evolution (LTE) network deployment using software defined radios (SDR). This helps to obtain network quality information in order to find any problems affecting the QoS of the users.

Thesis (MTech (Technology))--Cape Peninsula University of Technology, 2007 / Most ofMEMS sensors are based on the micro-cantilever technology, which use wide range of different design materials and structures. The benefit ofMEMS technology is in developing devices having lower cost, lower power consumption, higher performance, and integration. A free-end cantileverbeam made of magnetic material (PerrnaIloy) and a movable mass attached to the free-end has been designed using MEMS software tools. The magnetic material was used to improve the sensitivity of the cantilever-beam to an external applied magnetic field. The deflection of the cantilever was detected using capacitive sensing method. The aim of this research was to develop a non-contact current sensor based on MEMS technology by analysing the simulation of the system design of the micro cantilever when subjected to a magnetic field produced by a current-carrying conductor. When the signal, a sinusoidal current with a constant frequency is applied, the cantilever-beam exhibits a vibration motion along the vertical axis when it is placed closer to the line current. This creates corresponding capacitance changes and generates a voltage output proportional to the capacitive change in the signal processing circuitry attached to the micro cantilever. Modelling of the magnetic moment of a magnetic cantilever-beam placed in a field, the deflection of { the beam, the natural frequency of the cantilever-beam, the maximum deflection, the change in differential capacitive sensing technique, linearity of the differential capacitive, and capacitive sensitivity the circuit designed for readout was derived.

M.Ing. (Mechanical Engineering) / Micro electromechanical systems (MEMS) are presented and the application of electro discharge machining (EDM) to this scale of manufacture is discussed. A model relating input variables to output variables of micro scale EDM is developed using dimensionless groups and least squares regression. The model is used in a numeric simulation that ultimately predicts the space of a micro crater. Experimental validation is performed to check the reliability of the model by comparing the measurable experimental outputs with the outputs predicted by the model. The results and validity of the model are discussed.

M.Ing. (Electrical & Electronic Engineering) / Please refer to full text to view abstract