Climate change, a reality, a myth, a conspiracy, remains a point of research and concern, specifically with regards to the impact it has on human health. Reports concerning climate change are accepted by many but are also rejected by prominent figures of society and powerful enterprises flourishing in the race for economic development. Yet all living organisms on Earth are dependent on its natural resources and delicate balance of co-existence. A disruption of ecological balance will bring about changes to biomes and niches. These changes will affect disease patterns and well-being for all. Vulnerable groups will be most affected. If these changes have occurred and continue to occur what provision should be made to reduce population vulnerability? What investment should be made to public healthcare to assist vulnerable population groups and improve adaptability? This study was conducted with the aide of the South African Red Cross Society in three large South African provinces, Limpopo, Mpumalanga and Kwa-Zulu Natal, each known for its rich diverse ecologies and tropical to sub-tropical climates. The study aimed to determine the level of awareness amongst the healthcare workers with emphasis on education. The participants were counsellors working closely with the National Department of Health and local clinics. A total of 101 participants completed a close-ended questionnaire. The results indicated a strong workforce of young people with post-matric qualifications and strong views. Qualitative research was used with descriptive statistics to analyse and describe the data collected. It was, therefore, recommended that investment be made into this growing workforce in healthcare, as well as healthcare as a whole, since climate change, as documented, will threaten food security and water availability, see altered diseases patterns including emerging and re-emergence of infectious diseases and cardiovascular concerns brought on by heat stress. Funding must support education and training to strengthen awareness and preparedness so as to empower this workforce so that they may assist local populations to better adapt to the changes, become more resilient and, thereby, reduce their vulnerability and risk / Health Studies / M.Sc. (Life Sciences)

Climate change, a reality, a myth, a conspiracy, remains a point of research and concern, specifically with regards to the impact it has on human health. Reports concerning climate change are accepted by many but are also rejected by prominent figures of society and powerful enterprises flourishing in the race for economic development. Yet all living organisms on Earth are dependent on its natural resources and delicate balance of co-existence. A disruption of ecological balance will bring about changes to biomes and niches. These changes will affect disease patterns and well-being for all. Vulnerable groups will be most affected. If these changes have occurred and continue to occur what provision should be made to reduce population vulnerability? What investment should be made to public healthcare to assist vulnerable population groups and improve adaptability? This study was conducted with the aide of the South African Red Cross Society in three large South African provinces, Limpopo, Mpumalanga and Kwa-Zulu Natal, each known for its rich diverse ecologies and tropical to sub-tropical climates. The study aimed to determine the level of awareness amongst the healthcare workers with emphasis on education. The participants were counsellors working closely with the National Department of Health and local clinics. A total of 101 participants completed a close-ended questionnaire. The results indicated a strong workforce of young people with post-matric qualifications and strong views. Qualitative research was used with descriptive statistics to analyse and describe the data collected. It was, therefore, recommended that investment be made into this growing workforce in healthcare, as well as healthcare as a whole, since climate change, as documented, will threaten food security and water availability, see altered diseases patterns including emerging and re-emergence of infectious diseases and cardiovascular concerns brought on by heat stress. Funding must support education and training to strengthen awareness and preparedness so as to empower this workforce so that they may assist local populations to better adapt to the changes, become more resilient and, thereby, reduce their vulnerability and risk / Health Studies / M.Sc. (Life Sciences)

As a result of the United Nations’ International Decade for Natural Disaster Reduction (1990-2000), and recent high profile disasters, disaster risk reduction has climbed high on the international political agenda. There has been a paradigm shift from reacting to disasters towards preparing for and mitigating effects of disasters. Among the measures that have been highlighted on the disaster risk reduction agenda are early warning systems. In a Swedish context, there are needs for early warnings for various flood risk types. Municipalities carry big responsibilities for managing flood risks, and early warnings have a potential to facilitate decision-making and ultimately reduce flood losses. The aim of this thesis is to describe how a variety of flood warning signals are used in the risk management process of Swedish municipalities, how they can contribute to the flood risk reducing process, and which factors influence the success of this. The thesis is based on two papers. Paper I is based on interviews with three respondents from Swedish municipalities that have invested in and established local early warning systems. The paper shows that the possible effects from a local early warning system are not only reduced flood losses but also potential spinoff, the occurrence of which is dependent on the well-being of the organisation and its risk management processes. Paper II is based on interviews with 23 respondents at 18 Swedish municipalities, who have responsibilities related to flood risk management, and one respondent who works at SMHI with hydrological warning. The paper shows that municipalities can use a variety of complementary flood warning signals to facilitate decision-making for a proactive flood response. This is however not systematically the case, and is dependent on available resources. The theoretical contribution of this thesis is a development of existing conceptual models of early warning systems with respect to risk management and system contexts, and the use of complementary warning signals. / Following the United Nations’ International Decade for Natural Disaster Reduction (1990-2000), and recent high profile disasters, disaster risk reduction has climbed high on the international political agenda. Among the measures that have been highlighted are early warning systems – for Swedish municipalities who are responsible for managing flood risks, early warnings have a potential to facilitate decision-making and ultimately reduce flood losses. This licentiate thesis, based on two articles, aims to describe how a variety of flood warning signals are used in the risk management process of Swedish municipalities, how they can contribute to the flood risk reducing process, and which factors influence the success of this. The articles show that the possible effects from a local early warning system are not only reduced flood losses but also potential spin-off benefits, the occurrence of which is dependent on factors such as organisational culture and the functioning of the wider risk management system, and that municipalities can use a variety of complementary flood warning signals to facilitate decision-making for a proactive flood response which, however, is not systematically the case as benefits are dependent on available resources.

De Förenta Nationernas Agenda 2030 fastställer som ett delmål att säkerställa utbildning av hög kvalitet och främja livslångt lärande för alla som en del av arbetet för ett mer hållbart samhälle. Vikten av detta delmål blir särskilt tydlig i och med det observerbara sambandet mellan en fullständig gymnasieexamen och allmän hälsa i Sverige; gymnasiestudenter som går ut med en gymnasieexamen tenderar att erhålla bättre allmän hälsa. Learning Analytics är ett relativt nytt område inom utbildningsvetenskaplig forskning som syftar till att förbättra utbildning med hjälp av elevdata. Detta arbete undersökte vilken möjlig påverkan och begränsningar som förekommer vid implementering av en multipel linjär regressionsmodell utvecklad för en matematikkurs i en gymnasieskola. Vid utvecklingen av denna modell fastställdes tre signifikanta indikatorer för att förutsäga elevernas slutbetyg; Diagnos resultat,resultat på nationella proven och frånvaro. Prognosmodellen har utvärderats statistiskt varpå den visade sig vara tillförlitlig i 90% av bedömningarna, vilket inte är tillräckligt säkert för att användas i verkliga bedömningstillfällen eftersom lärare kräver att resultaten är obestridliga. Genom en fokusgruppsintervju med lärare granskas dessa resultat och deltagarna uttrycker sitt intresse för prognosmodeller tillsammans med en reflektion över elevers potentiella negativa reaktioner på en ogynnsam prognos. Utvärdering av modellen visar att den i dagsläget har en rimlig förmåga att förutsäga elevers slutbetyg men att det finns ett starkt behov av insamling av mer nyanserade data för att öka möjligheten till innovation i framtida arbeten / The 2030 Agenda establishes the goal to ensure quality education and promote lifelong learning opportunities for all. The importance of this goal becomes particularly clear when taking into account the link between upper secondary school graduation and general health in Sweden; Upper secondary school graduates tend to have better general health. Learning Analytics is a relatively new area of education research which aims to improve education using student data. This report examines the possible impact and limitations when implementing a multiple linear regression model developed for a mathematics course in an upper secondary school. In developing this model, three major indicators are established to be significant in predicting students' final grade; Diagnosis results, national test results and the amount of student absence. The model was statistically evaluated and found to be reliable in 90% of cases, which is not secure enough to be used in real assessment situations as teachers require the results to be indisputable. Through a focus group interview with teachers these results are evaluated and the participants establish their interest in predictive tools along with concerns for students' negative reactions to poor results. Evaluation of the model shows it has a reasonable ability to anticipate students' final grades but with a strong need for improvement in data collection methods and acquisition of more nuanced data to support greater possibility for innovation in future works.

L’auteure traite des stratagèmes de propriété occulte et de vote vide orchestrés par l’entremise des instruments dérivés. Dans un premier temps, cette recherche expose les diverses perturbations occasionnées par ces stratagèmes sur le système d’alerte et de notification ainsi que sur le droit corporatif canadien. Pour illustrer ces propos, une revue de la jurisprudence est détaillée. De plus, de nombreuses solutions législatives sont proposées afin de pallier aux utilisations potentiellement abusives des instruments dérivés. La solution la mieux adaptée au contexte des marchés financiers canadiens est finalement sélectionnée. / The research paper herein deals with hidden morphable ownership schemes and empty voting strategies orchestrated through derivatives. Initially, the author exposes the various disturbances caused by these schemes on early warning systems and follows up with repercussions that reverberate through to the Canadian corporate laws framework. Detailed case reviews are also presented to highlight the practical implications of these aforementioned schemes. Legislative solutions to mitigate the potential misuse of derivatives are proposed and ultimately the preferred solution tailored to Canadian financial markets is selected.

Submitted by JOSIANE SANTOS DE OLIVEIRA (josianeso) on 2017-06-27T13:30:09Z No. of bitstreams: 1 Paulo Fernando Benetti Marcon_.pdf: 962793 bytes, checksum: 8c45fbcf4084b51d6348450029bf5f28 (MD5) / Made available in DSpace on 2017-06-27T13:30:09Z (GMT). No. of bitstreams: 1 Paulo Fernando Benetti Marcon_.pdf: 962793 bytes, checksum: 8c45fbcf4084b51d6348450029bf5f28 (MD5) Previous issue date: 2017-03-31 / Nenhuma / O uso de recursos tecnológicos para auxiliar nas tarefas de ensino e aprendizagem é uma realidade. A disseminação de ambientes virtuais de aprendizado, como meio de promover a realização de cursos on-line, demonstra franca expansão. Além de tarefas que propiciam a ampliação dos meios de ensino, tais sistemas permitem o registro completo de todas as interações dos alunos no decorrer da realização de disciplinas. Essa gama de informação produzida pode ser utilizada para predição de estudantes em situação de risco enquanto a disciplina ocorre, o que para instituições de ensino pode representar redução nos índices de reprovação e evasão. Entretanto o número elevado de variáveis envolvidas, ainda mais quando várias disciplinas são consideradas, dificulta a construção de modelos computacionais eficientes. Desta forma, este trabalho visa investigar a construção de modelos generalistas – treinados com dados de diversas disciplinas disponíveis – contrapondo a construção de modelos individualizados – treinados individualmente com dados de cada disciplina. Para isto um amplo conjunto de dados educacionais foi extraído, obtido de uma instituição de ensino superior, composto de diferentes cursos, disciplinas e períodos letivos, não sendo utilizadas variáveis que invadissem a privacidade dos estudantes. Uma vez definidas as características e transformações dos dados que contribuíam à identificação de insucesso acadêmico no decorrer da disciplina então foram aplicados algoritmos clássicos de Mineração de Dados seguindo ambas as abordagens, generalista e individualizada, e a cada unidade de conteúdo das disciplinas. Os resultados obtidos demonstram vantagens e desvantagens de ambas as abordagens e que dadas as circunstâncias os modelos individualizados podem ser melhores, obtendo taxas de acerto maiores, e que em outras circunstâncias modelos generalistas apresentam um custo menor para a obtenção e manutenção dos modelos preditivos, mesmo com uma queda nos índices de acerto. / The use of technological resources to assist teaching and learning tasks is a reality. The dissemination of virtual learning environments, as a mean of promoting online courses, shows a clear expansion. In addition to tasks that allow the expansion of teaching resources, such systems allow the complete recording of all the interactions of the students inside the courses. This range of information produced can be used to predict at-risk students while the course is taking place, which for educational institutions may represent a reduction in failure and dropout rates. However, the high number of variables involved, especially when several courses are considered, makes it difficult to construct efficient computational models. In this way, this work aims to investigate the construction of generalist models – trained with data from several available courses – counterposing the construction of individualized models – individually trained with data from each course. In this way, a broad set of educational data was extracted, obtained from a higher education institution, composed of different undergraduate programs, courses and academic periods, not using variables that invaded students' privacy. Once the characteristics and transformations of the data that contributed to the identification of academic insuccess during the course were defined, then classical data mining algorithms were applied following both generalist and individualized approaches and to each content unit of the course. The results obtained demonstrate the advantages and disadvantages of both approaches and that given the circumstances the individualized models may be better, obtaining higher hit rates, and that in other circumstances generalist models present a lower cost for the obtaining and maintenance of the predictive models, even with a drop in hit rates.

Mozambique is one of the countries most affected by natural hazards in the world. Therefore it can benefit greatly from enhancements on its early warning system. Cell broadcast, which is a technology able to send simultaneous alert messages to all mobile phones in a geographical area has gained attention of emergency authorities since various catastrophes in the years 2000’s and increasing diffusion of the mobile network. This research has looked into the disaster risk management routines in Mozambique, interviewing relevant institutions, to identify the currently in use early warning system and analyze the circuit of information from detecting a hazard until the transmission of alert messages to the population. The goal of this research has been to identify how alert messages are sent to the population and, based on currently available infrastructure, analyze the possibilities to use Cell Broadcast to target alerts to all subscribers on specific geographic zones. It has been identified that the country already uses a solution that sends SMS to a list of phone numbers registered in a database. Nonetheless, telecommunication operators in the country are willing to cooperate with emergency authorities to design a solution in which Cell Broadcast can be used to strategically target alerts to subscribers at designated areas of risk. In this way, enabling enhanced accuracy and efficiency of the public alert system in Mozambique, with reduced time between detection and the simultaneously delivery of public alert messages to the entire population or only to people located on relevant geographic zones. Furthermore, the results also allowed to speculate on the viability of automated solutions, which can be used in combination to the enhancements that Cell Broadcast can bring to disaster risk management routines.

Transmits decision SS.VII/2 of UNEP Governing Council/Global Ministerial Environment. / UN Job no.: N0230044 E. Material type: Resolutions/decisions (UN). Issued under agenda item 1, agenda document A/CONF.199/PC/1.

Submitted by Murilo Resende Ferreira (muriloresende82@gmail.com) on 2014-10-28T15:22:42Z No. of bitstreams: 1 Tesedoutoradomuriloresende.PDF: 806113 bytes, checksum: e6d9cfcc660128de80d20f44f9c5213e (MD5) / Approved for entry into archive by BRUNA BARROS (bruna.barros@fgv.br) on 2014-11-10T11:34:49Z (GMT) No. of bitstreams: 1 Tesedoutoradomuriloresende.PDF: 806113 bytes, checksum: e6d9cfcc660128de80d20f44f9c5213e (MD5) / Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2014-11-13T13:40:01Z (GMT) No. of bitstreams: 1 Tesedoutoradomuriloresende.PDF: 806113 bytes, checksum: e6d9cfcc660128de80d20f44f9c5213e (MD5) / Made available in DSpace on 2014-11-13T13:40:15Z (GMT). No. of bitstreams: 1 Tesedoutoradomuriloresende.PDF: 806113 bytes, checksum: e6d9cfcc660128de80d20f44f9c5213e (MD5) Previous issue date: 2014-06-27 / This thesis contains two chapters, each one dealing with banking theory and the history of financiai arrangements. In Chapter 1, we extend a Diamond and Dybvig economy with imperfect monitoring of early withdrawals and make a welfare comparison between all possible allocations, as proposed by Prescott and Weinberg(2003) [37]. This imperfect monitoring is introduced by establishing indirect communication( trough a mean of payment) between the agents and the machine that is an aggregate of the financiai and the productive sector. The extension consists in studying allocations where a fraction of the agents can exploit imperfect monitoring and defraud the contracted arrangement by consuming more in the early period trough multiple means of payment. With limited punishment in the period of late consumption, this new allocation is called a separating allocation in contrast with pooling allocations where the agent with the ability of fraud is blocked from it by a costly mean of payment or by receiving enough future consumption to make fraud unattractive. The welfare comparison in the chosen range of parameters show that separating allocations are optimal for poor economies and pooling allocations for intermediary and rich ones. We end with a possible historical context for this kind of model, which connects with the historical narrative in chapter 2. In Chapter 2 we explore the quantitative properties of an early warning system for financiai crises based on the boom and bust framework described in more detail in appendix 1. The main variables are: real growth in equity and housing prices, the yield spread between the 10-year government bond and the 3-month interbank rate and the growth in total banking system assets. These variables display a higher degree of correct signals for recent crises (1984-2008) than comparable early warning systerns. Taking into account an increasing base-line risk ( due to increasing rates of credit expansion , lower interest rates and the accumulation of distortions) also proves to be informative and to help signaling crises in countries that did not go trough a great boom in previous years. / Esta tese contém dois capítulos, cada um lidando com a teoria e a história dos bancos e arranjos financeiros. No capítulo 1, busca-se extender uma economia Diamond-Dybvig com monitoramento imperfeito dos saques antecipados e realizar uma comparação do bem estar social em cada uma das alocações possíveis, como proposto em Presscott and Weinberg(2003). Esse monitoramento imperfeito é implementado a partir da comunicação indireta ( através de um meio de pagamento) entre os agentes e a máquina de depósitos e saques que é um agregado do setor produtivo e financeiro. A extensão consiste em estudar alocações onde uma fração dos agentes pode explorar o monitoramento imperfeito e fraudar a alocação contratada ao consumirem mais cedo além do limite, usando múltiplos meios de pagamento. Com a punição limitada no período de consumo tardio, essa nova alocação pode ser chamada de uma alocação separadora em contraste com as alocações agregadoras onde o agente com habilidade de fraudar é bloqueado por um meio de pagamento imune a fraude, mas custoso, ou por receber consumo futuro suficiente para tornar a fraude desinteressante. A comparação de bem estar na gama de parâmetros escolhida mostra que as alocações separadoras são ótimas para as economias com menor dotação e as agregadoras para as de nível intermediário e as ricas. O capítulo termina com um possível contexto histórico para o modelo, o qual se conecta com a narrativa histórica encontrada no capítulo 2. No capítulo 2 são exploradas as propriedade quantitativas de um sistema de previsão antecedente para crises financeiras, com as váriaveis sendo escolhidas a partir de um arcabouço de ``boom and bust'' descrito mais detalhadamente no apêndice 1. As principais variáveis são: o crescimento real nos preços de imóveis e ações, o diferencial entre os juros dos títulos governamentais de 10 anos e a taxa de 3 meses no mercado inter-bancário e o crescimento nos ativos totais do setor bancário. Essas variáveis produzem uma taxa mais elevada de sinais corretos para as crises bancárias recentes (1984-2008) do que os sistemas de indicadores antecedentes comparáveis. Levar em conta um risco de base crescente ( devido à tendência de acumulação de distorções no sistema de preços relativos em expansões anteriores) também provê informação e eleva o número de sinais corretos em países que não passaram por uma expansão creditícia e nos preços de ativos tão vigorosa.

The growth in the number of connected devices, in the volume of data traffic and of applications used has shown a significant increase in the complexity of today's networks, leaving the activity of management increasingly difficult for network and system administrators. Management aspects, such as the security of these systems has been a major challenge faced by the researchers, especially considering that, in parallel, there has been also a significant increase in the degree of sophistication of malicious activities. This scenario requires the development of sophisticated security systems also, in order to prevent or contain attacks increasingly destructive to systems, such as worm attacks. And the biological inspiration has been a main ally in this endeavor, bringing several concepts and new ways of thinking and solving these problems. This work used the bio-inspired concepts of Autonomic Networks (self-managing networks inspired by the functioning of the human nervous system)and Artificial Immune Systems (computer security systems inspired by the functioning of the human immune system), to define a management architecture for network self-protection, through the prediction of security attacks. This architecture incorporates the Danger Theory immune-inspired model and uses its Dendritic Cells algorithm to correlate events and detect anomalies. The architecture analysis was performed on an Early Warning System, which uses notifications received from worm already infected machines as additional information to identify the imminence of an infection in still vulnerable machines. In the experiments the gain in time obtained with this early identification was used in the Conficker worm propagation model and the results showed a reduction in the number of infected machines and, consequently, in the worm propagation across a network / O crescimento do número de dispositivos conectados, do volume de dados trafegados e das aplicações utilizadas tem evidenciado um aumento importante na complexidade das redes atuais, deixando a atividade de gerência cada vez mais difícil para os administradores de redes e sistemas. Aspectos de gerência, como a segurança desses sistemas tem sido um dos principais desafios enfrentados pelos pesquisadores, principalmente, considerando que, em paralelo, observa-se um também importante aumento no grau de sofisticação das atividades maliciosas. Tal cenário exige o desenvolvimento de sistemas de segurança igualmente sofisticados, com o intuito de impedir ou conter ataques cada vez mais destrutivos aos sistemas, como os ataques de worms. E a inspiração biológica tem sido uma das grandes aliadas nesta empreitada, trazendo diversos conceitos e novas formas de pensar e resolver esses problemas. Este trabalho utilizou os conceitos bio-inspirados das Redes Autonômicas (redes autogerenciáveis inspiradas nos funcionamento do sistema nervoso humano) e dos Sistemas Imunes Artificiais (sistemas de segurança computacional inspirados no funcionamento do sistema imunológico humano), para definir uma arquitetura de gerência para autoproteção de redes, através da predição de ataques de segurança. Tal arquitetura incorpora o modelo imuno-inspirado da Teoria do Perigo e utiliza o seu Algoritmo das Células Dendríticas para correlacionar eventos e detectar anomalias. A análise da arquitetura foi realizada em um Sistema de Alerta Antecipado, que usa notificações recebidas de máquinas já infectadas por worm como informação adicional para identificar a iminência de uma infecção em máquinas ainda vulneráveis. Nos experimentos o ganho de tempo obtido com essa identificação precoce foi utilizado no modelo de propagação do worm Conficker e os resultados apontaram uma redução no número de máquinas infectadas e, consequentemente, na propagação deste worm em uma rede