Interacting Effects of Climate Change Variables on Fish Aerobic Metabolism: Changing Exercise Performance in the Face of Deoxygenation, Hypercapnia, and Hyperthermia.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017

Motion compensated interpolation for subband coding of moving images

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.Includes bibliographical references (leaves 108-119).by Mark Daniel Polomski.M.S

Gaussian Process Regression for Materials and Molecules.

We provide an introduction to Gaussian process regression (GPR) machine-learning methods in computational materials science and chemistry. The focus of the present review is on the regression of atomistic properties: in particular, on the construction of interatomic potentials, or force fields, in the Gaussian Approximation Potential (GAP) framework; beyond this, we also discuss the fitting of arbitrary scalar, vectorial, and tensorial quantities. Methodological aspects of reference data generation, representation, and regression, as well as the question of how a data-driven model may be validated, are reviewed and critically discussed. A survey of applications to a variety of research questions in chemistry and materials science illustrates the rapid growth in the field. A vision is outlined for the development of the methodology in the years to come

The Sixth Annual Workshop on Space Operations Applications and Research (SOAR 1992)

This document contains papers presented at the Space Operations, Applications, and Research Symposium (SOAR) hosted by the U.S. Air Force (USAF) on 4-6 Aug. 1992 and held at the JSC Gilruth Recreation Center. The symposium was cosponsored by the Air Force Material Command and by NASA/JSC. Key technical areas covered during the symposium were robotic and telepresence, automation and intelligent systems, human factors, life sciences, and space maintenance and servicing. The SOAR differed from most other conferences in that it was concerned with Government-sponsored research and development relevant to aerospace operations. The symposium's proceedings include papers covering various disciplines presented by experts from NASA, the USAF, universities, and industry

The psychasthenia of deep space: evaluating the ‘reassertion of space in critical social theory’

The aim of this work is to question the notion of space that underlies the claimed ‘spatial turn’ in geographical and social theory. Section 1 examines this theoretical literature, drawing heavily on Soja as the self declared taxonomist of the genre, and also seeks parallels with more populist texts on cities and space, to suggest, following Williams, that there is a new ‘structure of feeling’ towards space. Section 1 introduces two foundational concepts. The first, derived from Soja’s misunderstanding of Borges’ story The Aleph, argues for an ‘alephic vision’, an imposition of a de-materialized and revelatory understanding of space. This is related to the second, an ‘ecstatic vision’, which describes the tendency, illustrated through the work of Koolhaas and recent exhibitions on the experience of cities, to treat spatial and material experience in hyperbolic and hallucinatory terms. Section 2 offers a series of theoretical reconstructions which seek to draw out parallels between the work of key theorists of what I term the ‘respatialization’ literature (Harvey, Giddens, Foucault and Lefebvre) and the work of Hillier et al in the Space Syntax school. A series of empirical studies demonstrate that the approach to the material realm offered by Space Syntax is not only theoretically compatible but can also help to explain ‘real world’ phenomena. However, the elision with wider theoretical positions points to the need for a reworking of elements of Space Syntax, and steps towards this goal are offered in section 3. In the final ‘speculative epilogue’ I reopen the philosophical debates about the nature of space, deliberately suppressed from the beginning, and suggest that perhaps the apparent theoretical and empirical versatility of Space Syntax, based upon a configurational approach to space as a complex relational system, may offer an alternative approach to these enduring metaphysical debates

ANALYSIS OF THE VOLTAGE STABILITY PROBLEM IN ELECTRIC POWER SYSTEMS USING ARTIFICIAL NEURAL NETWORKS

PhDThe voltage stability problem in electric power systems is concerned with the analysis of events and mechanisms that can lead a system into inadmissible operating conditions from the voltage viewpoint. In the worst case, total collapse of the system may result, with disastrous consequences for both electricity utilities and customers. The analysis of this problem has become an important area of research over the past decade due to some instances of voltage collapse that have occurred in electric systems throughout the world. This work addresses the voltage stability problem within the framework of artificial neural networks. Although the field of neural networks was established during the late 1940s, only in the past few years has it experienced rapid development. The neural network approach offers some potential advantages to the solution of problems for which an analytical solution is difficult. Also, efficient and accurate computation may be achieved through neural networks. The first contribution of this work refers to the development of an artificial neural network capable of computing a static voltage stability index, which provides information on the stability of a given operating state in the power system. This analytical tool was implemented as a self-contained computational system which exhibited good accuracy and extremely low processing times when applied to some study cases. Dynamic characteristics of the electrical system in the voltage stability problem are very important. Therefore, in a second stage of the present work, the scope of the research was extended so as to take into account these new aspects. Another neural network-based computational system was developed and implemented with the purpose of providing some information on the behaviour of the electrical system in the immediate future. Examples and case studies are presented throughout the thesis in order to illustrate the most relevant aspects of both artificial neural networks and the computational models developed. A general discussion summarises the main contributions of the present work and topics for further research are outlined.CNPq -Conselho Nacional de Desenvolvimento Cientffico e Tecnoldgico EPUSP -Escola Politecnica da Universidade de Sao Paul