Submitted by Silvana Teresinha Dornelles Studzinski (sstudzinski) on 2016-05-25T12:28:08Z No. of bitstreams: 1 Jean Carlos Araújo Costa_.pdf: 1155126 bytes, checksum: 15210c31e7d20bb22cb98f8732173d6d (MD5) / Made available in DSpace on 2016-05-25T12:28:09Z (GMT). No. of bitstreams: 1 Jean Carlos Araújo Costa_.pdf: 1155126 bytes, checksum: 15210c31e7d20bb22cb98f8732173d6d (MD5) Previous issue date: 2016-03-01 / Nenhuma / Técnicas de visualização de dados podem auxiliar nas mais diversas áreas de atuação humana, em especial na compreensão de dados e informações de diferentes fenômenos que se quer estudar. Quanto mais variáveis estão relacionadas com esse fenômeno, mais desafiador se torna seu tratamento e representação visual. Pensando em educação no Brasil e suas bases de dados abertas, bem como em bases de dados acadêmicas existentes nas instituições, o uso de técnicas matemáticas para correlacionar conjuntos de dados e métodos de visualização para apresentar essas correlações, disponíveis em uma ferramenta de fácil acesso e operação, podem tornar públicas informações sobre a qualidade da educação de determinada região, estado, município e instituição de ensino. Outro benefício pode ser a indicação de fatores que antes eram ignorados, como alvos de investimento e ainda ajudar na elaboração de políticas públicas, nacionais ou regionais, que tornem a educação mais eficiente, abrangente e inclusiva. Iniciativas de organizações não governamentais e algumas vinculadas ao governo brasileiro tem elaborado ferramentas de filtragem de informações e divulgação de dados sobre qualidade e investimento de recursos na educação. O governo brasileiro usa índices de desempenho para avaliar suas Instituições de Ensino Superior. O Conceito Preliminar de Curso é um desses. Este trabalho apresenta uma solução, visando elaborar uma metodologia de visualização de dados através de uma aplicação web, com tecnologias open source, utilizando o método de análise de componentes principais (ACP) como técnica matemática de correlação de variáveis, e distribuindo resultados sobre um mapa com a utilização da API do Google Maps, porém, tendo como foco, a busca do nível de influência de diferentes fatores, inclusive de alguns não ligados diretamente à educação, na performance de instituições de ensino e no rendimento acadêmico de alunos, tendo como estudo de caso, a análise de um índice de desempenho na educação superior. / Data visualization techniques can help in several areas of human activity, especially in understanding data and information from different phenomena to be studied. The more variables are related to this phenomenon, the more challenging it becomes their treatment and visual representation. Thinking about education in Brazil and its open databases, as well as in existing academic databases in institutions, using mathematical techniques to correlate data sets and visualization methods to present these correlations available in an easy tool access and operation may disclose information on the quality of education in a region, state, county and educational institution. Another benefit coud be the indication of factors that were ignored, as investment targets and also help in the development of public policies, national or regional, that make more efficient, comprehensive and inclusive education. Initiatives of non-governmental organizations and some linked to the Brazilian government has prepared information filtering tools and dissemination of data on quality and investment of resources in education. Brazilian government uses performance indicators to assess their undergraduation institutions. Course Preliminar Concept (CPC) is one of those. This paper presents a solution to this profile, aiming to develop a data visualization methodology through a web application with open source technologies, using principal component analysis method (PCA) as mathematical technique of variable correlation, and distributing results on a map using the Google Maps API, however, focusing on the search for the level of influence of different factors, including some not directly related to education, performance of educational institutions and the academic performance of students, taking as a case study, the analysis of a performance index in undergraduation.

Due to mining activities, the natural vegetation cover in Gatumba area was removed and replaced either by crops or bare wasteland with reduced available arable land. The main aim of the study was to assess the impact of the mining activities on the plant mineral uptake and the dynamics of the vegetation. The vegetation in this area under investigation was diversified and heterogeneous. Trace element concentrations in soils were similar to those in plant parts but some elements were highly concentrated in soils than in plants. According to the bioaccumulation factors of the analyzed trace elements in plant parts, two categories of plants were identified, and these are excluders and accumulators. No toxic levels of the evaluated trace elements were found in the analyzed plant samples. As a recommendation for the adaptation of plants to Gatumba mining environment, the most useful plant species for the revegetation/restitution of the technosols should be Sesbania sesban, Crotalaria dewildemaniana and Tithonia diversifolia subject to further experiments on trace elements bioaccumulation and organic matter production / Environmental Sciences / M.A. Science (Environmental Sciences)

La presente investigación de carácter cuantitativo tiene el propósito de demostrar que el uso de la Metodología de Valor Ganado (Earned Value Management - EVM) para controlar los costos en una obra influye en la optimización de la rentabilidad de un proyecto inmobiliario; en este caso en la ejecución de la especialidad de estructuras de la obra: Proyecto Multifamiliar Los Fresnos. Para ello, se determinó el desempeño de la obra mediante los índices propuestos por el EVM, para conocer el estado del proyecto; se calculó el rendimiento y las variaciones de costo y tiempo de la ejecución de obra para estimar el rendimiento al cierre de la obra; y por último, se tomó acciones en obra para optimizar la gestión de costos. La investigación se aborda de acuerdo al tipo de estudio correlacional - transversal, ya que se midió el desempeño de costo y tiempo de la ejecución de la obra usando los índices de Rendimiento y Variación que ofrece la teoría del EVM tabulados en formatos de tablas y gráficos (validado por las ecuaciones propuestas en la Guía del PMBOK ® 5ta versión del PMI®) determinando el estado económico, la fidelidad del cronograma en el que se encontraba la obra para determinados periodos y la proyección de cómo terminaría la ejecución de la especialidad de estructuras, luego se tomaron acciones en función de los resultados obtenidos. Los resultados finales para el último periodo de aplicación del EVM en la especialidad de estructuras fue de un ahorro de hasta S/. 60 mil nuevos soles con un ligero retraso del 3% con respecto al cronograma planificado. Concluyéndose que la aplicación de la Metodología del Valor Ganado resultó efectiva para controlar las desviaciones que presentó la obra Los Fresnos, medir el progreso de la obra y actuar de forma correctiva en esta investigación. This quantitative research aims to demonstrate that the use of the Earned Value Management (EVM) to control costs in a job influences the optimization of the performance of a real estate project; in this case the execution of the specialty structures of the job: Multifamily Project Los Fresnos. To do this, the performance of the job was determined by the rates proposed by the EVM, to find out the status of the project; calculations were taken of the performance and changes in cost and time of the execution of work to estimate the performance at the end of the job; and finally, action was taken on the job to optimize cost management. The research is discussed according to the type of correlational study - transversely, as the performance of cost and time of execution of the job was measured using indexes of performance and variation offered by the theory of EVM tabulated formats charts and graphs (validated by the equations proposed in the PMBOK ® Guide 5th Version PMI®) determining the economic status, the fidelity of schedule in which the work was at for certain periods and projecting how to end the execution of the specialty structures, then actions were taken depending on the results obtained. The final results for the latest period of EVM implementation specializing in structures were savings of up 60,000 nuevos soles with a slight delay of 3% compared to the planned schedule. Concluding that the application of Earned Value Management was effective in controlling the deviations that the Los Fresnos job presented, measuring the progress of the job, and acting in the correct manner for this investigation.

本文以全球第一個演算法交易雲端平台－Quantopian進行研究，藉由平台社群討論區內公開之演算法交易策略，透過交易策略篩選和初步優化，以演算法交易策略為投資標的，搭配不同權重策略建構投資組合。權重策略部分，本文提出適用於組合式交易策略的績效指標加權 (Performance Index Weighted) 法，應用因子投資的觀念，融合排序相關性較低、不同面向之績效指標作為報酬率驅動因子，並參考Asness et al. (2013) 以因子排序作為權重計算依據，提供了簡單直覺、非最適化求解而且穩健的加權方式，更直接地將交易策略各面向績效的優劣反應在權重上。 根據數值分析，發現組合式交易策略長期而言，整體績效表現平均優於個別演算法交易策略，最小變異、績效指標加權和均等權重投資組合的風險亦明顯低於個別交易策略，且最小變異、績效指標加權和均等權重投資組合在降低投資組合風險的同時，並未犧牲過多報酬，風險調整後績效表現優於個別交易策略。而績效指標加權投資組合之年化報酬率、風險衡量和風險調整後績效表現皆優於最小變異、平均數－變異數、均等權重的加權投資組合，此種權重策略可使投資組合之夏普比率 (Sharpe ratio) 顯著提升，且投資組合的風險大幅降低，最大跌幅 (Max drawdown) 在四年半的實驗區間內降至10%以下的水準，風險調整後績效優異。 透過Quantopian社群演算法交易平台，個人投資者也能站在巨人的肩膀上學習，集合眾人的力量，憑藉量化交易創造出和機構法人一樣具有競爭力的投資組合。如Chan (2009) 所言，個人投資者也能憑藉量化交易，設計一套演算法交易策略。 / Quantopian is a crowd-sourced hedge fund which allows members on the platform to develop their own algorithmic strategies and even get capital allocations from Quantopian. In this paper, we constructed portfolios by Quantopian trading platform and proposed Performance Index Weighted method which generate consistently profit in our study. First, we filtered algorithmic trading strategies shared on the Quantopian community and improved the performance slightly. Second, we combined multiple algorithmic strategies with varied portfolio weight method, such as minimize-variance, performance index weighted, mean-variance, and equal weighed method to construct a portfolio. To elaborate, Performance Index Weighted portfolio is actually an application of factor investing, in which the portfolio weight depends on the ranking of performance index (factors), and these index measure returns, risk, and also risk-adjusted returns, which truly reflects how well the algorithmic strategy is. As a result, we used the performance index as a return driver and invested more in well-ranked strategies directly. Performance index weighted is a simple, robust, and fully intuitively way to construct a portfolio. In numerical analysis, we found that using multiple strategies to construct a portfolio could generate better performance than a single algorithm strategy on average. Moreover, the annual returns, risk measure, and risk-adjusted returns of Performance Index Weighted portfolio turn out to be better than minimize-variance portfolio, mean-variance portfolio, and equal weighted portfolio. As a result, Performance Index Weighted portfolio has significantly higher Sharpe ratio and lower Max Drawdown (lower than 10% in our out-of-sample test) than other portfolios, which shows excellent risk-adjusted performance. Most important of all, retail traders could learn more precisely by standing on the shoulders of giants through Quantopian trading platform. Also, by collecting wisdom from the crowd, we create an opportunity for retail traders to construct competitive portfolios just as institutional investors do.

Esta dissertação visou analisar se a observância dos mecanismos estabelecidos pela Lei de Responsabilidade Fiscal consagrados no princípio da gestão fiscal responsável principalmente relativos a dois dos seus pilares: o equilíbrio das contas públicas e a obediência aos limites e condições por ela estabelecidas foi eficiente para também promover a responsabilidade social, de forma a cumprir as garantias constitucionais de acesso à educação e saúde públicas de qualidade, além da geração de emprego e renda aos seus cidadãos, na Região Metropolitana do Vale do Paraíba e Litoral Norte (RMVPLN), abrangendo os anos de 2005/2008 e 2009/2012; dois ciclos políticos, portanto. Para tanto, se verificou o comportamento de oito fundamentos da gestão fiscal dos municípios: capacidade de arrecadação das receitas próprias, execução orçamentária, endividamento de longo prazo, endividamento de curto prazo, liquidez, despesa com pessoal e grau de investimento. Criou-se, então, uma matriz de risco que verificou o comportamento destes fundamentos nos últimos anos de mandato dos gestores municipais (2008 e 2012). Para aferir os desempenhos sociais, este trabalho utilizou os indicadores de Desenvolvimento Municipal disponibilizados pela Federação das Indústrias do Estado do Rio de Janeiro (FIRJAN). A partir da combinação destes dois resultados, os 39 municípios da RMVPLN foram distribuídos em cinco classes que compuseram o Índice de Desempenhos Fiscal e Social Agregados (IDFSA), e analisada a sua evolução nos mesmos anos de referência: 2008 e 2012. O método de pesquisa utilizado foi analítico, quanto à abordagem, e quali-quantitativo em relação ao seu objetivo. Os resultados obtidos evidenciaram ser realmente necessário cumprir as regras estabelecidas pela Lei de Responsabilidade Fiscal, até como instrumento que viabilizará a disponibilidade de recursos necessários não só para a manutenção das políticas públicas existentes, mas também para a expansão ou a implementação de novos programas sociais. Entretanto, não são bastantes em si mesmos, de forma que alguns dos municípios analisados, mesmo obtendo o mais elevado grau de desempenho fiscal, não tiveram bons resultados sociais. Assim, a Lei de Responsabilidade Fiscal teve um importante papel nas circunstâncias em que foi editada. Entretanto, decorridos mais de quinze anos de sua edição, é imprescindível se fazer a sua revisão para nela integrar uma outra diretriz: a da responsabilidade social. / This work aimed to analyze the observance of strict mechanisms established by the Fiscal Responsibility Act enshrined the principle of fiscal management responsible - mainly related to two of its pillars: the balance of public accounts and obedience to the limits and conditions established by it - was effective also to promote social responsibility in order to comply with the constitutional guarantees of access to education and public health quality, and the generation of employment and income to its citizens, the metropolitan area of the Paraiba and the North Coast Valley (RMVPLN) covering the years 2005/2008 and 2009/2012; two political cycles so. To this end, he found the behavior of eight grounds of fiscal management of municipalities: storage capacity of its own revenues, budget execution, long-term debt, short-term debt, liquidity, personnel expenditures and investment grade. Was created, then a risk matrix that investigated the behavior of these fundamentals in recent years mandate of municipal managers (2008 and 2012). To measure the social performance, this study used the Municipal Development of indicators provided by the Federation of Industries of the State of Rio de Janeiro (FIRJAN). From the combination of these two index, the 39 municipalities of RMVPLN were divided into five classes that composed the Fiscal Performance Index and Social Aggregates (IDFSA), and analyzed its development in the same reference years: 2008 and 2012. The research method used was analytical, as the approach, and qualitative and quantitative in relation to your goal. The results indicate that it is really necessary to comply with rules established by the Fiscal Responsibility Law, even as a tool to enable the availability of necessary resources not only for the maintenance of existing public policies, but also for expansion or implementation of new social programs. However, they are not enough in themselves, so that some of the municipalities analyzed, even getting the highest degree of fiscal performance, did not have satisfactory social outcomes. Thus, the Fiscal Responsibility Act played an important role in the circumstances in which it was edited. However, after more than fifteen years of its issue, it is essential to do your review to integrate it another guideline: the social responsibility.

The subject of this thesis is to create evaluation criteria of technical condition of water treatment plants. The thesis is divided into four parts. In the first part of this thesis are presented evaluation systems by performance indicators drinking water treatment plants, which are then applied in real time. There are detailed descriptions of individual performance indicators. Each evaluation conducted certain period of time. After the expiry of the period under review was to evaluate and create charts to display results. In the next chapter the thesis focuses on the identification data. First, it was necessary to find out all necessary information about the water treatment plant. Necessary information means information relating to building construction, human resources, mechanical parts, technological equipment and other entities with links to the operation of the water treatment plant. All these data were sorted for better overview and facilitate setting evaluation indicators. The third part of this thesis is focused on the development of indicators that are used to determine the current status of the water treatment plant. As a first step was established 19 indicators used to evaluate the condition of the entire water treatment plant. Followed by a description of the individual indicators and then determine the individual evaluation criteria. In the last part of this thesis was carried out by the proposed criteria on selected water treatment plants. They were selected three water treatment plants located in the Czech Republic, which held a personal tour of each water treatment plant. This was followed by an overall assessment of the technical condition of water treatment plants.

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This research study focuses on the application models of Data Mining and Machine Learning covering cellular network traffic, in the objective to arm Mobile Network Operators with full view of performance branches (Services, Device, Subscribers). The purpose is to optimize and minimize the time to detect service and subscriber patterns behaviour. Different data mining techniques and predictive algorithms have been applied on real cellular network datasets to uncover different data usage patterns using specific Key Performance Indicators (KPIs) and Key Quality Indicators (KQI). The following tools will be used to develop the concept: RStudio for Machine Learning and process visualization, Apache Spark, SparkSQL for data and big data processing and clicData for service Visualization. Two use cases have been studied during this research. In the first study, the process of Data and predictive Analytics are fully applied in the field of Telecommunications to efficiently address users’ experience, in the goal of increasing customer loyalty and decreasing churn or customer attrition. Using real cellular network transactions, prediction analytics are used to predict customers who are likely to churn, which can result in revenue loss. Prediction algorithms and models including Classification Tree, Random Forest, Neural Networks and Gradient boosting have been used with an exploratory Data Analysis, determining relationship between predicting variables. The data is segmented in to two, a training set to train the model and a testing set to test the model. The evaluation of the best performing model is based on the prediction accuracy, sensitivity, specificity and the Confusion Matrix on the test set. The second use case analyses Service Quality Management using modern data mining techniques and the advantages of in-memory big data processing with Apache Spark and SparkSQL to save cost on tool investment; thus, a low-cost Service Quality Management model is proposed and analyzed. With increase in Smart phone adoption, access to mobile internet services, applications such as streaming, interactive chats require a certain service level to ensure customer satisfaction. As a result, an SQM framework is developed with Service Quality Index (SQI) and Key Performance Index (KPI). The research concludes with recommendations and future studies around modern technology applications in Telecommunications including Internet of Things (IoT), Cloud and recommender systems. / Cellular networks have evolved and are still evolving, from traditional GSM (Global System for Mobile Communication) Circuit switched which only supported voice services and extremely low data rate, to LTE all Packet networks accommodating high speed data used for various service applications such as video streaming, video conferencing, heavy torrent download; and for say in a near future the roll-out of the Fifth generation (5G) cellular networks, intended to support complex technologies such as IoT (Internet of Things), High Definition video streaming and projected to cater massive amount of data. With high demand on network services and easy access to mobile phones, billions of transactions are performed by subscribers. The transactions appear in the form of SMSs, Handovers, voice calls, web browsing activities, video and audio streaming, heavy downloads and uploads. Nevertheless, the stormy growth in data traffic and the high requirements of new services introduce bigger challenges to Mobile Network Operators (NMOs) in analysing the big data traffic flowing in the network. Therefore, Quality of Service (QoS) and Quality of Experience (QoE) turn in to a challenge. Inefficiency in mining, analysing data and applying predictive intelligence on network traffic can produce high rate of unhappy customers or subscribers, loss on revenue and negative services’ perspective. Researchers and Service Providers are investing in Data mining, Machine Learning and AI (Artificial Intelligence) methods to manage services and experience. This research study focuses on the application models of Data Mining and Machine Learning covering network traffic, in the objective to arm Mobile Network Operators with full view of performance branches (Services, Device, Subscribers). The purpose is to optimize and minimize the time to detect service and subscriber patterns behaviour. Different data mining techniques and predictive algorithms will be applied on cellular network datasets to uncover different data usage patterns using specific Key Performance Indicators (KPIs) and Key Quality Indicators (KQI). The following tools will be used to develop the concept: R-Studio for Machine Learning, Apache Spark, SparkSQL for data processing and clicData for Visualization. / Electrical and Mining Engineering / M. Tech (Electrical Engineering)

In advanced process control, the Model Predictive Control (MPC) may be considered the most important innovation in recent years and the standard tool for industrial applications due to the fact that it keeps the plant operating in the constraints more profitable. However, like every control algorithm, the MPC after some time in operation rarely works as originally designed. Thus, to preserve the benefits of MPC systems for a long period of time, their performance needs to be monitored and evaluated during the operation. This task require the presence of reliable and effective tools to detect when the controller performance is below of the desirable, to define the need, or not, of recommissioning the system. Thus, the objective of this work is development of techniques for monitoring and evaluating the performance of multivariable predictive controllers, being developed two new tools: LQG benchmark Modified and IHMC benchmark. The results obtained from numerical simulations were satisfactory and consistent with the technical literature applied in the developments of the evaluators, which were used in the monitoring of the control system MPC of the oil-water-gas three-phase separation process, offering an appropriate solution and providing subsidies for implementations in real industrial systems. / Em controle avançado de processos, o controlador preditivo ou MPC (Model Predictive Control) pode ser considerado como a mais importante inovação dos últimos anos e a ferramenta padrão para aplicações industriais, devido ao fato do MPC manter a planta operando dentro das suas restrições de forma mais lucrativa. Entretanto, como todo algoritmo de controle, o MPC depois de algum tempo em operação dificilmente funciona como quando fora inicialmente projetado. Desta forma, com o objetivo de manter os benefícios dos sistemas MPC por um longo período de tempo, seu desempenho precisa ser monitorado e avaliado durante a operação. Esta tarefa requer a presença de ferramentas efetivas e confiáveis para detectar quando o desempenho do controlador estiver abaixo do desejável, para definir a necessidade, ou não, de um recomissionamento do sistema. Destarte, aborda-se neste trabalho o desenvolvimento de técnicas para monitoramento e avaliação de desempenho de controladores preditivos multivariáveis, sendo desenvolvidas duas novas ferramentas: LQG benchmark Modificado e IHMC benchmark. Os resultados obtidos a partir de simulações numéricas foram satisfatórios e coerentes com a literatura técnica aplicada no desenvolvimento dos avaliadores, os quais foram utilizados no monitoramento do sistema de controle MPC do processo de separação trifásica água-óleo-gás, oferecendo assim uma solução apropriada e fornecendo subsídios para implementações em sistemas industrias reais.