Made available in DSpace on 2015-04-11T14:02:56Z (GMT). No. of bitstreams: 1 Ludimila.pdf: 1270701 bytes, checksum: 300c827c33013fc4aaa7278441f4a620 (MD5) Previous issue date: 2013-03-27 / FAPEAM - Fundação de Amparo à Pesquisa do Estado do Amazonas / The large offer of contents nowadays makes it hard to find relevant information. Recommender systems (RS) have been developed to tackle with such information overloading. Such systems are tools that recommend, from a large number of alternatives, the ones that the users will probably be interested in. The main RS applications are based on two approaches, content based filtering and collaborative filtering. Among them, collaborative filtering is the most used one since, in general, it employs a more effective strategy to capture user preferences: to determine groups of users with similar likes and dislikes. The recommendation problem, as viewed by collaborative filtering, can be viewed as the problem of predicting the preference of the user, normally represented as a rating. Traditional systems predict such ratings by means of manually-crafted regression equations obtained by combining different evidences such as: users reputation and its strictness level. As with any other heuristic strategy, there is no guarantee that the used equations are the best for a particular dataset in the sense of minimizing the prediction error. Thus, in this work, we intend to determine if it would be better to learn regression equations instead of using heuristically built ones. Such learned equations should be obtained by using a machine learning regression task to find the most effective combination of evidence on minimizing error. According to our experiments, a simple regression method is able to significantly outperform the best traditional equations using only evidence explored by those equations. Further, features like ratings that neighbors give to item (as all or individually) and user, item and neighbors average ratings have the best performance. Finally, we obtained gain of until 7% over the baseline with trust feature and gain of 6% over baseline without it. / A grande oferta de conteúdos na sociedade contemporânea torna difícil a tarefa de busca por informações que interessem aos usuários. Uma forma de lidar com tal sobrecarga de informações é prover ferramentas que recomendem para os usuários, dentre as informações alternativas, aquelas que devem ser de seu interesse. Tais ferramentas são os Sistemas de Recomendação (SR). As principais aplicações em SR se baseiam em duas técnicas, filtragem baseada em conteúdo e filtragem colaborativa. Dentre as duas, a filtragem colaborativa é a mais utilizada uma vez que, em geral, a estratégia que emprega, determinar grupos de usuários com interesses similares, é mais efetiva para capturar preferências. O problema de recomendação, como abordado em filtragem colaborativa, pode ser visto como um problema de previsão da preferência do usuário, normalmente representada por uma nota. Sistemas tradicionais prevêem esta nota através de uma equação de regressão obtida heuristicamente, envolvendo diversas evidências como nível de rigor do usuário e sua reputação. Como em qualquer estratégia heurística, não há nenhuma garantia que as equações usadas para a previsão sejam mais adequadas para um conjunto particular de dados, no sentido de minimizar o erro de previsão. Assim, neste trabalho, buscamos determinar se, em lugar de usar fórmulas heurísticas, não seria mais eficaz determinar automaticamente, por meio de uma técnica de aprendizagem de máquina, a melhor combinação das evidências disponíveis de forma a reduzir o erro de previsão. Nossos experimentos indicam que usando apenas evidências empregadas em métodos tradicionais, um método de regressão, como o proposto, pode alcançar resultados significativamente melhores que métodos tradicionais. Além disso, evidências como as notas que vizinhos atribuem ao item (como um todo ou individualmente) e as notas médias do usuário, do item e dos vizinhos possuíram melhor desempenho. Por fim, obtivemos ganhos de até 7% sobre o baseline com característica de confiança e de 6% sobre baseline sem uso de confiança.

Orientador: Waldir Antonio Bizzo / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica / Made available in DSpace on 2018-08-12T09:03:59Z (GMT). No. of bitstreams: 1 Ferraz_JoseLazaro_D.pdf: 4654631 bytes, checksum: 6f3dae66a712e68bf5d420c0e04fc031 (MD5) Previous issue date: 2008 / Resumo: O presente trabalho tem por objetivo o desenvolvimento de um modelo de gestão integrada dos resíduos sólidos urbanos com ênfase na sustentabilidade e uma metodologia para avaliação de sistemas municipais de gestão dos resíduos. Uma pesquisa de campo foi realizada em municípios selecionados para testar a robustez do modelo e validar a metodologia proposta. A área de abrangência da pesquisa envolveu os vinte municípios que compõem a bacia hidrográfica do rio Sorocaba - UGRHI - 10. Para mensurar o nível de gestão dos resíduos praticado pelos municípios foi proposto o IGR - Índice de Gestão de Resíduos. Este índice estabelece parâmetros que possibilitam a comparação entre os níveis de gestão praticados nas localidades pesquisadas. A aplicação do modelo permite diagnosticar a situação dos resíduos urbanos nos municípios em relação à geração, coleta, tratamento e destinação final dos resíduos municipais, bem como, o nível estratégico e tecnológico de suas gestões. Pretende-se com este trabalho gerar uma base de dados e informações que possam contribuir na formulação de políticas públicas, estratégias e ações voltadas para a melhoria e otimização dos sistemas avaliados. Os resultados obtidos demonstraram que a metodologia desenvolvida mostrou-se adequada para a avaliação proposta. A aplicação do modelo e da metodologia pode favorecer o desenvolvimento e aperfeiçoamento da situação dos resíduos e contribuir para a minimização dos impactos ambientais e sociais criados pela geração e destinação final inadequada dos resíduos sólidos urbanos municipais. / Abstract: The present work aims at the development of an integrated solid urban waste management model highlighting the sustainability and the development of a methodology for evaluation of municipal waste management system. A field work was conducted in the cities selected for testing and validating the proposed methodology. The research range included the 20 cities that form the basin of the Sorocaba River - UGRHI - 10. The IGR - Waste Management Rating was proposed to measure the waste management level conducted by the cities. This rating establishes patterns that allow the comparison between the waste management levels conducted in the researched locations. The application of the model allows to diagnose the condition of the urban waste in the cities regarding its generation, its collecting, its treatment and its final destination of the city waste, as well as the strategy and technology level of their management. This work intends to generate data and information base that can contribute to the creation of public policies, strategies and actions directed to improvement and optimization of the evaluated systems. The obtained results showed that the methodology developed was appropriate to the proposed evaluation. The application of the model and methodology can promote the development and improvement of the waste condition and contribute to the minimization of the environmental impacts caused by the inadequate generation and final destination of the solid urban waste. / Doutorado / Termica e Fluidos / Doutor em Engenharia Mecânica

Située à l’articulation de la sociologie de l’économie, de l’histoire de la finance et de la sociologie de la connaissance, cette thèse présente donc une analyse du rôle de la notation du crédit dans la régulation financière, et plus largement, du rôle de l’incertitude et de l’incomplétude juridiques sur les anticipations économiques des acteurs financiers. Le cadre d’analyse de la recherche se résume en quatre points : Premièrement, la thèse rompt avec une lecture strictement intellectualiste de l’action publique et présente une approche de la régulation financière par ses instruments, empruntant ainsi l’approche pragmatiste développée par les social studies of finance et par la nouvelle sociologie économique d’inspiration américaine. Deuxièmement, l’hypothèse centrale de la recherche est que les instruments réglementaires sont à la fois des techniques de connaissance et des outils juridiques. Aussi, ce sont les frictions qu’occasionnent les deux activités parfois contradictoires de calculer et de gouverner qui donnent au changement réglementaire sa dynamique historique. Troisièmement, prenant l’exemple de l’usage de la notation dans la supervision financière comme dispositif de calcul et technique de gouvernement, la thèse propose une histoire de longue durée (1865-2010) de l’activité réglementaire sur les marchés financiers aux Etats-Unis et en Europe au travers de cinq régimes de régulation (régime statutaire, d’appel, disciplinaire, fictionnel et contractuel). Quatrièmement, l’originalité de la recherche est de combiner une approche macroscopique du changement réglementaire avec une approche méticuleuse de plusieurs courtes séquences historiques durant lesquelles d’importantes innovations réglementaires ont vu le jour, notamment le New Deal aux Etats-Unis et la crise de la dette souveraine en Europe. Ainsi, en plus de définir les contours de cinq régimes réglementaires, la thèse analyse la façon dont les régulateurs se sont saisis de la notation financière comme « mécanisme d’embrayage » afin d’opérationnaliser la transition d’un régime à un autre. / Located at the intersection of economic sociology, financial history, and the sociology of knowledge, this dissertation examines the role of credit ratings in financial regulation, and more broadly, the role of financial uncertainties and legal incompleteness on financial actors’ anticipatory decisions. The framework set forth in this study can be summarized as follows. First, this study breaks with an intellectualist approach of public action to analyze financial regulation from the perspective of its instruments. As such, this research draws on a pragmatist agenda developed in social studies of finance and recent work in economic sociology. Second, the main hypothesis of this dissertation is to approach regulatory instruments as technologies of knowing and tools of government. From this double viewpoint, I hypothesize that the frictions generated by the two competing activities of calculating and governing impart the regulatory activity with both its structural features and historical dynamics. Third, using the example of regulatory reliance on ratings, I propose a longue durée historical analysis (1865-2010) of the regulatory activity in the U.S. and Europe through the examination of five regulatory regimes (statutory, appeal, disciplinary, fictional, and contractual). Four, one original feature of this dissertation is to combine a macroscopic analysis of regulatory change with a meticulous approach of several short historical sequences during which important regulatory innovations came into being, notably the New Deal in the U.S. and the European sovereign debt crisis. Thus, in addition to setting the contours of five regulatory frameworks, this dissertation analyses the ways in which regulators used ratings as “clutching” devices to operationalize the legal transition from one regime to another.

This research is an investigation of the relationship between employees 'happiness' and the financial performance of a financial services organisation in South Africa. As a component of the financial services industry the banking sector contributes greatly to the economic growth of the country. The South African Banking sector is concentrated and highly competitive. It is vital for banks to maintain competitiveness and ever increasing global competition adds further pressure on organisations to financially perform so as to meet the demands of their shareholders. The literature that has been reviewed and previous research suggest that employee 'happiness' is a vital variable influencing the performance and success of individuals. Organisational performance will be measured in terms of financial performance for the purposes of this research. The concept of financial performance and 'happiness' are discussed and a questionnaire based on the Satisfaction With Life Scale (Diener et al,1985) is used to determine the levels of 'happiness' at selected branches within the institution. The individual branches financial performance is determined via calculating selected ratios, namely cumulative leverage, cost to income ratio and net yield. An analysis of correlation was conducted to establish whether or not a relationship of statistical significance exists between employee 'happiness' and financial performance. It was concluded that there is no relationship of statistical significance between employee 'happiness' and the financial performance of branches within the organisation, it was suggested that other factors exert a much greater influence over financial performance. Some of these factors influencing financial performance are discussed and recommendations for further research are made.

This dissertation proposes stress testing of a bank’s corporate credit portfolio in a Basel Internal Ratings Based (IRB) framework, using publicly available macroeconomic variables. Corporate insolvencies are used to derive a credit cycle index, which is linked to macroeconomic variables through a multiple regression model. Probability of default (PD) and loss given default (LGD) that are conditional on the worst state of the credit cycle are derived from through-the-cycle PDs and LGDs. These are then used as stressed inputs into the Basel regulatory and Economic capital calculation for credit risk. Contrary to the usual expert judgement stress testing approaches, where management apply their subjective view to stress the portfolio, this approach allows macroeconomic variables to guide the severity of selected stress testing scenarios. The result is a robust stress testing framework using Rösch and Scheule (2008) conditional LGD that is correlated to the stressed PD. The downturn LGD used here is an alternative to the widely used Federal Reserve downturn LGD which assumes no correlation between PDs and LGDs. / Dissertation (MSc)--University of Pretoria, 2014. / gm2014 / Mathematics and Applied Mathematics / Unrestricted

Since a deficit in empathy is not only characteristic among individuals with autism spectrum disorder (ASD) but categorically used in defining ASD, it is of utmost importance to explore educational avenues to build prosocial skills among this group. This study sought to explore the primary research question: What impact does the implementation of an empathy-focused video modeling intervention have on frequency of empathic behaviour among adolescents with ASD? The secondary research questions examined were: In what ways does employing a video modeling simulation intervention using the Model Me Kids Friendship program impact the ability of adolescents with ASD to demonstrate empathic behaviour? How do adolescents with ASD express or speak about their empathic behaviour following participation in a simulation intervention using Model Me Kids Friendship? How do the Educational Resource Facilitators (teaching assistants) perceive the same individuals’ empathic behaviour following participation in a simulation intervention using Model Me Kids Friendship (MMF)? This mixed methods study explores 1 particular video modeling simulation program as a focused approach to building empathic behaviour among adolescents with ASD. The theoretical framework presented blends theory of mind, simulation theory, and psychological theories of empathic behaviour including the inherent motor, cognitive, and emotional components. Individuals with ASD may not learn empathic behaviours solely through observation as typically developing children do, but findings suggest that through video simulation, practice may, in fact, lead to increased empathic behaviour. The quantitative findings were not significant but did show increase in motor empathy behaviour ratings among intervention group participants. Support for video modeling as a vehicle to teach empathic behaviour was provided by qualitative data collected over the course of 4 months contextualizing specific examples of empathic behaviour exhibited by participating teens with ASD. There is a link made between high levels of systematizing among teens on the spectrum (the drive to analyze and build a system) and video modeling as a means to foster empathic behaviour, thereby supporting an increased use of video simulation strategies to teach social skills among this group.

This thesis focuses on the topic of marketing strategy of FTV Prima s.r.o. in the television market. The main objective of this thesis is the definition of marketing activities and the use of marketing tools by FTV Prima, a company operating nationwide TV broadcast television stations Prima, Prima COOL, Prima Love and Prima ZOOM, leading to a better position in the television market. The theoretical part of the thesis is the application of marketing mix 4P in the television as a media. The practical part is a description of the inner workings of FTV Prima in connection with charting the television market

We propose a Markov chain model for credit rating changes. We do not use any distributional assumptions on the asset values of the rated companies but directly model the rating transitions process. The parameters of the model are estimated by a maximum likelihood approach using historical rating transitions and heuristic global optimization techniques. We benchmark the model against a GLMM model in the context of bond portfolio risk management. The proposed model yields stronger dependencies and higher risks than the GLMM model. As a result, the risk optimal portfolios are more conservative than the decisions resulting from the benchmark model.

Este trabalho tem por meta focalizar a adaptação necessária na metodologia de planejamento atual, norteada segundo uma ótica determinística e conservadora, afim de permitir a elaboração de Programas de Obras de Transmissão/Subtransmissão, condicionados por limitações de teto no montante de investimento a curto e médio prazos. Para tanto, como tema central, busca-se desenvolver uma base conceitual e metodológica, para permitir uma exploração maximizada das possibilidades de carregamento de equipamentos e instalações do sistema de transmissão, contemplando a especificação das ferramentas computacionais necessárias para dar consequência prática à proposta. Considerando o potencial de análise proporcionado por métodos e técnicas de natureza probabilística, aplicados ao planejamento de Sistemas Elétricos, a espinha dorsal da evolução metodológica delineada no texto repousa sobre a avaliação de confiabilidade global e quantificação de riscos operativos. O texto foi estruturado em 8 capítulos onde, a partir de um capítulo introdutório, enfoca-se sequencialmente os temas: * Conceitos e Metodologias para Maximização do Carregamento de Transformadores de Potência. * Conceitos e Metodologias para Maximização do Carregamento de Linhas aéreas de Transmissão. * Impacto das Restrições Financeiras no planejamento e possibilidade de atuação a nível técnico para administrar o conflito entre qualidade de serviço e recursos limitados. * Conceitos e Metodologias para relaxação dos Critérios limitantes para o carregamento máximo de componentes do sistema, em ambiente de severas restrições financeiras, no horizonte de curto prazo. * Resultados obtidos em aplicações concretas a situações do Setor Elétrico, visando caracterizar o alcance do ferramental preconizado nos capítulos anteriores. * Critérios e Procedimentos para Padronização de Subestações e Linhas de Transmissão , coerentes com os conceitos de maximização de carregamento introduzidos nos dois primeiros capítulos. Ao final do texto, incluiu-se um capítulo de \"Conclusões\", com o objetivo de sumarizar os aspectos mais relevantes abordados no texto, assim como indicar linhas de ação e novos desenvolvimentos, necessários para permitir a efetivação prática da metodologia proposta. / An important problem posed to power system planners in developing countries is now becoming commonplace, even in developed countries, and concerns on how to fit an expansion plan into a tight budget, with the least reduction in reliability levels. This problem is known as power system planning under financial constraints and a series of methods is now available to deal with it. So, this work addresses the necessary adjustments in order to permit the Transmission / Sub-transmission Expansion Program establishment when there are investments constraints in a medium/short term range. The main emphasis is on the development of a methodological and conceptual framework, aiming at a maximizes exploration of the loading capability of transformers and transmission lines of the power network. In this context, a new methodological framework for transmission system planning in a financial constrained environment is presented. The proposed approach combines transmission projects priority evaluation and ranking as well as criteria flexibilization, being particularly suitable for short-term planning. The problem to be faced is to operate the system after a project postponement, while the service quality is kept so adequate as it is possible. One of the main issues to be focused is the transmission system uprating since a maximized equipment utilization can contribute to avoid a more significant restriction to the costumers. Therefore, a detailed description of the models for transmission lines and transformers loading limits assessment is presented, with emphasis on the main concepts and the application of probabilistic tools to circumvent the inherent conservatism of deterministic methods. A summary of the contents is presented in what follows: * Concepts and Methodology for Transformers loading maximization. * Concepts and Methodology for Transmission Lines loading maximization. * Financial Restrictions impacts on Expansion Planning Process and the possibilities to manager the conflict between service quality and investment constraints. * Concepts and Methodologies to the relaxation of Criteria that limits the loading capability of transmission lines, aiming at short term Planning under severe financial restrictions, * Obtained results in concrete applications of the proposed methodology and computational tools to Brazilian Electric Power System. * Methods and Criteria to standardization of Substations and Transmission Lines, according the main issues formerly introduced. * Conclusion and Future Research.

The thesis is focused on improving the motivation and satisfiction of emploees of manufacturing company. The first part focuses on the theoretical basis to the issue. The second part focuses on the selected company and describes its current motivation system. Based on the results from empirical research and hypothesis testing are in the last part contains suggestions for improving the current motivational system of the company