This thesis considers the subject of crowd safety and investigates how the application of risk assessment can provide support for decision making in crowd safety management and planning. The focus is on major public venues and events where large crowds arc a normal part of the operation. Conventional methods of assessment tend to be ad hoc, reactive and rely on individual experiences. The risk assessment approach, which is comprehensive, systematic and pro-active, can help to overcome these shortfalls. Risk assessments have already been successfully applied in many workplaces, ranging from high hazard industrial plants to the office environment. However, this thesis argues that for it to be of benefit, the risk assessment must be appropriate to the nature of the operation and the nature and the extent of the hazards involved. The existing risk assessments are inappropriate to crowd safety in this respect and a more suitable methodology is required. In order to identify the methods and tools that could provide the potential solutions to the problems of assessing crowd and behaviour related hazards, a review of other risk assessments was conducted. It has highlighted a number of techniques and tools that could be applied to assess crowd safety risks. Based on the criteria mentioned above and the findings of this review, a prototype crowd safety risk assessment methodology was developed. A series of trials were conducted to evaluate the validity and usability of the prototype. Revisions were made accordingly to produce the final draft. Experiments and a questionnaire survey were then carried out on the final draft to test and verify the methodology. In general, they show that the methodology has led to an improvement in most aspects of crowd safety risk assessment. In the experiments that compared the methodology against methods representing the existing risk assessments and the conventional way of assessing crowd safety, subjects using the methodology tend to perform better in most areas. More hazards were identified. In the evaluation of risks, better consistency was achieved between individuals using the methodology. However, their judgements appeared to be less consistent over time. The use of a larger rating scheme with more choices available in the methodology could have an impact on consistency in risk evaluation. Another key factor could be that the subjects who took part in the experiments were all novice assessors. Possible learning effect may have occurred in between experiments, which could have resulted in a change of mind over time. If this is the case, this result could be an indication that the methodology is more sensitive to changes in risks or risk perception. It will be interesting to find out if experienced assessors can achieve better consistency. By and large, the experiments and questionnaire survey have served to verify, at least in part, the arguments that risk assessment is better than the conventional assessment method and that there are more benefits to be gained when the risk assessment is more appropriate to the nature and the extent of the crowd safety hazards that could arise in major public venues. Nevertheless, it is important to recognise that the research work presented in this thesis is merely the first step towards a crowd safety risk assessment methodology. There are outstanding issues yet to be resolved, not least the issue of the apparent lack of consistency over time in risk evaluation. This thesis has identified the research and development work that is required to resolve these issues and to further the benefits that risk assessment could bring to crowd safety.

M.A. / The discipline of political risk analysis has often been criticised as a ‘soft science’. As the title of this study suggest, the major challenge of this study is set out to provide an empirical analysis of political risk and to prove that political risk can indeed be measured. The aim of this study is to provide an empirical analysis of political risk by testing the reliability of current risk assessment approaches to accurately forecast political risk. There have not been many attempts to test the reliability of political risk assessment models. However, Howell & Chaddick (1994) tested the reliability of three (EIU, PRS and BERI) political risk assessment models to accurately forecast risk projections in the period 1982-1994. This study will revisit the test done by Howell & Chaddick (1994) in order to determine the reliability of three forecast models. In order for forecasts to be reliable, forecasts must be justified and defended by applying practical logic. Practical logic implies that theory be tested against real world experience. Hence, a reliable analysis will require that actual losses be tested against theory. Therefore, in addressing the connection between theory and actual losses, this study will correlate losses incurred in the period 1994- 2004 with theory. Due to the nominal nature of the concept political risk, there has been a lack of consensus in the field on what constitute political risk. This study will provide a conceptual clarification of political risk. A brief discussion of the underlying theoretical background in political risk is required in order to understand the concept of political risk and terms thereof. Hence, this study will establish a theoretical base of political risk analysis. This study argue that low political risk encourage foreign direct investment. The relationship between political risk and foreign direct investment will be analysed in this study. It is hoped that in light of this study’s findings, a case can be putt III forth that multi-national corporations can use political risk analysis to minimise exposure to losses and as an extension of political risk analysis, multi-national corporations can use political risk insurance to hedge against political risks. The outcomes of this study aim to prove that political risk can be empirically tested and measured and that the analysis of political risk is essential to successfully manage political risks.

Este trabalho estabeleceu cenários típicos para o Estado de São Paulo, a partir de dados de investigações ambientais de empreendimentos que armazenam, manipulam ou comercializam combustíveis derivados de petróleo (posto de combustíveis, TRR - transportador retalhista e revendedor, garagem e bases). As plumas de contaminação em fase dissolvida foram caracterizadas a partir de dados levantados em campo e dos resultados obtidos com o modelamento das plumas, usando o modelo Domenico. Desse modo, foi possível comparar as características das plumas reais com as calculadas e posteriormente discutir sobre os perímetros de proteção de poços de abastecimento (PPP). Uma das conclusões é de que não existe correlação entre a extensão das plumas de fase dissolvida (benzeno) real e a calculada. E ao comparar as extensões das plumas calculadas (Domenico) com os PPP calculados por modelo numérico, pode-se notar que somente em 3 cenários houve alguma correlação. Uma das principais recomendações é a reavaliação dos PPP, considerando os dados deste trabalho. / The current work has aimed to establish typical hydrogeological scenarios within the boundaries of São Paulo state, Brazil, based on environmental assessment data obtained at sites that store, manipulate or commercialize petroleum originated fuel (gas stations, TRR and fuel distribution plants). The dissolved phase contamination plumes were characterized based on field obtained data and numeric modeling, adopting Domenico model. In this way, it was possible to analyze the features of the real contamination plumes, compared with the modeled ones, and establish a discussion about production wells protection perimeter (PPP). One of the main conclusions is that there is no correlation between the extension of the real dissolved plumes (benzene) and the modeled ones. While comparing the extension of the modeled plumes (Domenico) with the PPP calculated by numeric modeling, it is possible to observe that only 3 of the analyzed scenarios have presented some identifiable correlation. One of the main recommendations is to perform a reevaluation of the PPP methodology, taking into account the data obtained in the current work.

Este trabalho estabeleceu cenários típicos para o Estado de São Paulo, a partir de dados de investigações ambientais de empreendimentos que armazenam, manipulam ou comercializam combustíveis derivados de petróleo (posto de combustíveis, TRR - transportador retalhista e revendedor, garagem e bases). As plumas de contaminação em fase dissolvida foram caracterizadas a partir de dados levantados em campo e dos resultados obtidos com o modelamento das plumas, usando o modelo Domenico. Desse modo, foi possível comparar as características das plumas reais com as calculadas e posteriormente discutir sobre os perímetros de proteção de poços de abastecimento (PPP). Uma das conclusões é de que não existe correlação entre a extensão das plumas de fase dissolvida (benzeno) real e a calculada. E ao comparar as extensões das plumas calculadas (Domenico) com os PPP calculados por modelo numérico, pode-se notar que somente em 3 cenários houve alguma correlação. Uma das principais recomendações é a reavaliação dos PPP, considerando os dados deste trabalho. / The current work has aimed to establish typical hydrogeological scenarios within the boundaries of São Paulo state, Brazil, based on environmental assessment data obtained at sites that store, manipulate or commercialize petroleum originated fuel (gas stations, TRR and fuel distribution plants). The dissolved phase contamination plumes were characterized based on field obtained data and numeric modeling, adopting Domenico model. In this way, it was possible to analyze the features of the real contamination plumes, compared with the modeled ones, and establish a discussion about production wells protection perimeter (PPP). One of the main conclusions is that there is no correlation between the extension of the real dissolved plumes (benzene) and the modeled ones. While comparing the extension of the modeled plumes (Domenico) with the PPP calculated by numeric modeling, it is possible to observe that only 3 of the analyzed scenarios have presented some identifiable correlation. One of the main recommendations is to perform a reevaluation of the PPP methodology, taking into account the data obtained in the current work.

Risk management is composed of three major elements viz., hazard identification, risk estimation and risk evaluation. The aim of hazard identification and risk estimation is to identify the outcomes from risk, the magnitude of the associated con&quences from risk, and the estimation of the probabilities of these outcomes. Previous work focused on hazard identification and risk estimation and identified the relatively high risks associated with playing professional football. By adhering to the risk management process, the aim of this thesis was to determine the significance of these high risks to football clubs and their players. A theoretical framework was designed to evaluate the influence of player injury on the financial and playing performance of professional football clubs. This framework was also used to assess, through use of cost benefit analysis, the practicalities of investing in suitable injury prevention strategies, to reduce the risks to football clubs and their players. Former professional footballers were surveyed to investigate the long-term medical and socioeconomic consequences associated with the high risks of playing professional football. The results identified the high financial costs associated with player injury on professional football clubs. Although the high risks of player injury have a relatively minor effect on teamperformance of the Premier League clubs, this effect still has a relatively major influence on the financial performance of the club. In contrast, the influence of player injury to teamperformance was relatively major for Division I and Division 2 clubs, but this had a relatively minor effect on financial performance. The application of cost benefit analysis to the investment of specialist personnel to reduce the risks of injury demonstrated that the proposals were practicable for Premier League and Division I clubs only. In addition, it was also demonstrated that the high risks associated with playing professional football have a significant influence on the long-term well-being of foriner players. One-third of former players had been medically diagnosed osteoarthritic in a lower limb joint. The majority of players also perceived that injury had a negative influence on their present and future welfare. The results demonstrate that the consequences associated with the relatively high acute injury risk also have a significant effect on the financial and playing performance of football clubs and the future welfare of their players.

Populations are aging and the prevalence of chronic disease, persisting for many years, is increasing. The most common, non-communicable chronic diseases in developed countries are; cardiovascular disease (CVD), type 2 diabetes, obesity, arthritis and specific cancers. Chronic diseases such as cardiovascular disease, type 2 diabetes and obesity have high prevalence and develop over the course of life due to a number of interrelated factors including genetic predisposition, nutrition and lifestyle. With the development and completion of human genome sequencing, we are able to trace genes responsible for proteins and metabolites that are linked with these diseases. A computerized model focused on organizing knowledge related to genes, nutrition and the three chronic diseases, namely, cardiovascular disease, type 2 diabetes and obesity has been developed for the Ontology-Based Personalized Risk Evaluation for Chronic Disease Project. This model is a Protégé-based ontological representation which has been developed for entering and linking concepts and data for these three chronic diseases. This model facilitates to identify interrelationships between concepts. The ontological representation provides the framework into which information on individual patients, disease symptoms, gene maps, diet and life history can be input, and risks, profiles, and recommendations derived. Personal genome and health data could provide a guide for designing and building a medical health administration system for taking relevant annual medical tests, e.g. gene expression level changes for health surveillance. One method, called transductive neuro-fuzzy inference system with weighted data normalization is used to evaluate personalized risk of chronic disease. This personalized approach has been used for two different chronic diseases, predicting the risk of cardiovascular disease and predicting the risk of type 2 diabetes. For predicting the risk of cardiovascular disease, the National Nutrition Health Survey 97 data from New Zealand population has been used. This data contains clinical, anthropometric and nutritional variables. For predicting risk of type 2 diabetes, data from the Italian population with clinical and genetic variables has been used. It has been discovered that genes responsible for causing type 2 diabetes are different in male and female samples. A framework to integrate the personalized model and the chronic disease ontology is also developed with the aim of providing support for further discovery through the integration of the ontological representation in order to build an expert system in genes of interest and relevant dietary components.

Populations are aging and the prevalence of chronic disease, persisting for many years, is increasing. The most common, non-communicable chronic diseases in developed countries are; cardiovascular disease (CVD), type 2 diabetes, obesity, arthritis and specific cancers. Chronic diseases such as cardiovascular disease, type 2 diabetes and obesity have high prevalence and develop over the course of life due to a number of interrelated factors including genetic predisposition, nutrition and lifestyle. With the development and completion of human genome sequencing, we are able to trace genes responsible for proteins and metabolites that are linked with these diseases. A computerized model focused on organizing knowledge related to genes, nutrition and the three chronic diseases, namely, cardiovascular disease, type 2 diabetes and obesity has been developed for the Ontology-Based Personalized Risk Evaluation for Chronic Disease Project. This model is a Protégé-based ontological representation which has been developed for entering and linking concepts and data for these three chronic diseases. This model facilitates to identify interrelationships between concepts. The ontological representation provides the framework into which information on individual patients, disease symptoms, gene maps, diet and life history can be input, and risks, profiles, and recommendations derived. Personal genome and health data could provide a guide for designing and building a medical health administration system for taking relevant annual medical tests, e.g. gene expression level changes for health surveillance. One method, called transductive neuro-fuzzy inference system with weighted data normalization is used to evaluate personalized risk of chronic disease. This personalized approach has been used for two different chronic diseases, predicting the risk of cardiovascular disease and predicting the risk of type 2 diabetes. For predicting the risk of cardiovascular disease, the National Nutrition Health Survey 97 data from New Zealand population has been used. This data contains clinical, anthropometric and nutritional variables. For predicting risk of type 2 diabetes, data from the Italian population with clinical and genetic variables has been used. It has been discovered that genes responsible for causing type 2 diabetes are different in male and female samples. A framework to integrate the personalized model and the chronic disease ontology is also developed with the aim of providing support for further discovery through the integration of the ontological representation in order to build an expert system in genes of interest and relevant dietary components.

Populations are aging and the prevalence of chronic disease, persisting for many years, is increasing. The most common, non-communicable chronic diseases in developed countries are; cardiovascular disease (CVD), type 2 diabetes, obesity, arthritis and specific cancers. Chronic diseases such as cardiovascular disease, type 2 diabetes and obesity have high prevalence and develop over the course of life due to a number of interrelated factors including genetic predisposition, nutrition and lifestyle. With the development and completion of human genome sequencing, we are able to trace genes responsible for proteins and metabolites that are linked with these diseases. A computerized model focused on organizing knowledge related to genes, nutrition and the three chronic diseases, namely, cardiovascular disease, type 2 diabetes and obesity has been developed for the Ontology-Based Personalized Risk Evaluation for Chronic Disease Project. This model is a Protégé-based ontological representation which has been developed for entering and linking concepts and data for these three chronic diseases. This model facilitates to identify interrelationships between concepts. The ontological representation provides the framework into which information on individual patients, disease symptoms, gene maps, diet and life history can be input, and risks, profiles, and recommendations derived. Personal genome and health data could provide a guide for designing and building a medical health administration system for taking relevant annual medical tests, e.g. gene expression level changes for health surveillance. One method, called transductive neuro-fuzzy inference system with weighted data normalization is used to evaluate personalized risk of chronic disease. This personalized approach has been used for two different chronic diseases, predicting the risk of cardiovascular disease and predicting the risk of type 2 diabetes. For predicting the risk of cardiovascular disease, the National Nutrition Health Survey 97 data from New Zealand population has been used. This data contains clinical, anthropometric and nutritional variables. For predicting risk of type 2 diabetes, data from the Italian population with clinical and genetic variables has been used. It has been discovered that genes responsible for causing type 2 diabetes are different in male and female samples. A framework to integrate the personalized model and the chronic disease ontology is also developed with the aim of providing support for further discovery through the integration of the ontological representation in order to build an expert system in genes of interest and relevant dietary components.

Orientador: Sávio Souza Venâncio Vianna / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química / Made available in DSpace on 2018-08-27T22:56:33Z (GMT). No. of bitstreams: 1 Tolentino_IsabelaBarreto_M.pdf: 3871526 bytes, checksum: d968be133fccd0350bf46330c8b774f6 (MD5) Previous issue date: 2015 / Resumo: Este trabalho tem como objetivo desenvolver um simulador dinâmico para análise de consequência em plantas químicas industriais. Nele, todas as etapas de um possível acidente foram estudadas e implementadas, baseadas em modelos empíricos e semi-empíricos da literatura para acidentes de gás, líquido e de duas fases (líquido e gás). Através dos resultados obtidos com o estudo do vazamento, da dispersão do material, da possível formação de poça, e dos processos de evaporação e flash, os efeitos dos acidentes foram estimados. Os efeitos de radiação térmica e sobrepressão foram analisados para acidentes que resultam em jato de fogo, poça de fogo e bola de fogo (no caso de radiação) e explosão de nuvem de vapor (no caso de sobrepressão). Os resultados obtidos possuem boa concordância em relação ao comportamento esperado dos parâmetros e daquele esperado pela literatura. Simulação de Monte Carlo também foi realizada para a determinação da probabilidade e frequência de sobrepressões baseada em variáveis probabilísticas, como: descarga, direção e velocidade do vento, e direção do vazamento. A metodologia foi executada utilizando superfícies de respostas obtidas a partir de estudos de CFD para o cálculo do volume de nuvem inflamável e sobrepressão de uma explosão. Os resultados obtidos demonstraram que a metodologia desenvolvida fornece dados interessantes para análise de risco / Abstract: The current work proposes the development of a dynamic simulator that could be used in processing plants for consequence analysis. All stages of an accident have been studied and implemented in the software based on known empirical and semi-empirical models from the literature, regarding the state of matter of the substance (gas, liquid or two-phase). Based on results of the release rate, dispersion of clouds, pool formation, evaporation and flash processes, the incident outcomes have been determined for different accident scenarios. Thermal radiation and overpressure effects have been analysed for outcomes as jet fire, pool fire, fireball (for radiation) and vapour cloud explosions (for overpressures). Results show good agreement with expected behaviour of the parameters of accidents and also with the literature. A Monte Carlo simulation has been performed to determine the probability and frequency of overpressure based on stochastic parameters such as: discharge distribution, wind direction, wind speed and leak direction. The methodology has been executed with response surfaces based on CFD studies for flammable volume of gases and overpressure. Results demonstrated that such methodology can provide interesting data for risk analysis / Mestrado / Engenharia Química / Mestra em Engenharia Química

acase@tulane.edu / 1 / Shelly L Harris