Human Resource Management in Emergency Situations

The dissertation examines the issues related to the human resource management in emergency situations and introduces the measures helping to solve these issues. The prime aim is to analyse complexly a human resource management, built environment resilience management life cycle and its stages for the purpose of creating an effective Human Resource Management in Emergency Situations Model and Intelligent System. This would help in accelerating resilience in every stage, managing personal stress and reducing disaster-related losses. The dissertation consists of an Introduction, three Chapters, the Conclusions, References, List of Author’s Publications and nine Appendices. The introduction discusses the research problem and the research relevance, outlines the research object, states the research aim and objectives, overviews the research methodology and the original contribution of the research, presents the practical value of the research results, and lists the defended propositions. The introduction concludes with an overview of the author’s publications and conference presentations on the topic of this dissertation. Chapter 1 introduces best practice in the field of disaster and resilience management in the built environment. It also analyses disaster and resilience management life cycle ant its stages, reviews different intelligent decision support systems, and investigates researches on application of physiological parameters and their dependence on stress. The chapter ends with conclusions and the explicit objectives of the dissertation. Chapter 2 of the dissertation introduces the conceptual model of human resource management in emergency situations. To implement multiple criteria analysis of the research object the methods of multiple criteria analysis and mahematics are proposed. They should be integrated with intelligent technologies. In Chapter 3 the model developed by the author and the methods of multiple criteria analysis are adopted by developing the Intelligent Decision Support System for a Human Resource Management in Emergency Situations consisting of four subsystems: Physiological Advisory Subsystem to Analyse a User’s Post-Disaster Stress Management; Text Analytics Subsystem; Recommender Thermometer for Measuring the Preparedness for Resilience and Subsystem of Integrated Virtual and Intelligent Technologies. The main statements of the thesis were published in eleven scientific articles: two in journals listed in the Thomson Reuters ISI Web of Science, one in a peer-reviewed scientific journal, four in peer-reviewed conference proceedings referenced in the Thomson Reuters ISI database, and three in peer-reviewed conference proceedings in Lithuania. Five presentations were given on the topic of the dissertation at conferences in Lithuania and other countries

Effect of fuel content on the human perception of engine idle irregularity

This thesis describes a digital signal processing analysis of diesel engine idle vibration in automobiles, and an analysis of the human subjective response to the idle vibration which occurs at the steering wheel. In order to quantify the variations in the diesel idle vibration that can be introduced by the engine technology, the vehicle, and the fuel type, a set of acceleration time histories were measured at the engine block and at the steering wheel for two automobiles equipped with 4-cylinder engines which had different injection systems and which operated under different fuel conditions. A combination of time domain, frequency domain and time-frequency wavelet-based analysis were used. Both the continuous wavelet transform and the discrete orthogonal wavelet transform were applied to the steering wheel acceleration time histories in order to analyse the statistical variation in terms of both instantaneous variations, and the cycle-to-cycle variations which occur across complete thermodynamic engine cycles. The combination of orthogonal wavelet transform and time-varying auto-covariance analysis, performed across a complete engine thermodynamic cycle, was identified as the most sensitive method for describing the statistical variation in diesel idle vibration. The second-order engine harmonic H2 was found to account for most of the vibrational energy at the steering wheel when at idle. Amplitude modulation of the second-order engine harmonic H2 by the half-order engine harmonic H112 has been identified as the main characteristic of the steering wheel signature of automobiles at idle. The steering wheel idle vibration produced by different engines and different fuel conditions have therefore been described in terms of the amplitude modulation depth "mil that characterises the idle waveform. Four psychophysical response tests, determined by the combination of two test protocols and two semantic descriptors, were performed. A model of the growth in the human subjective response to diesel idle vibration has been proposed in which the response scale is a function of the modulation depth parameter "mil. The model is defined over two regions of modulation depth. For values of "m" less than 0.2, humans have been found to be unable to distinguish variations in idle modulation. For values of "m" greater than 0.2, the human response grows as a power function with respect to modulation depth. Based on the current findings, suggestions for future research are also provided

Recognition of driver's fatigue expression using Local Multiresolution Derivative Pattern

To develop the human-centric driver fatigue monitoring system for automatic understanding and charactering of driver's conditions, a novel, efficient feature extraction approach, named Local Multiresolution Derivative Pattern (LMDP), is proposed to describe the driver's fatigue expression images, and the Intersection Kernel Support Vector Machines classifier is then exploited to recognize three pre-defined classes of fatigue expressions, i.e., awake expressions, moderate fatigue expressions and severe fatigue expressions. With features extracted from a fatigue expressions dataset created at Southeast University, the holdout and cross-validation experiments on fatigue expressions classification are conducted by the Intersection Kernel Support Vector Machines classifier, compared with three commonly used classification methods including the k-nearest neighbor classifier, the multilayer perception classifier and the dissimilarity-based classifier. The experimental results of holdout and cross-validation showed that LMDP offers the better performance than Local Derivative Pattern, and the second order LMDP exceeds other order LMDP. With the second order LMDP and the Intersection Kernel Support Vector Machines classifier, the classification accuracies of the severe fatigue are over 90 in the holdout and cross-validation experiments, thus demonstrating the effectiveness of the proposed feature extraction method in automatically understanding the driver's conditions towards the human-centric driver fatigue monitoring system

MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described

Generalized averaged Gaussian quadrature and applications

A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal

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

2008-2009-UNM CATALOG

Course catalog for 2008-2009https://digitalrepository.unm.edu/course_catalogs/1098/thumbnail.jp