Made available in DSpace on 2016-04-25T18:39:59Z (GMT). No. of bitstreams: 1 Gerson Costa.pdf: 1689508 bytes, checksum: b3518607c5899f533ec462f78e432186 (MD5) Previous issue date: 2014-03-17 / This research presents the results of a descriptive study on the applicability of Brazilian models to predict bankruptcy in Brazilian football clubs. Initially, the study is produced from literature searches, constituting the foundation of the theoretical underpinning of the work. It aims to expand the information about the origin of football, his arrival in Brazil and its present situation, seeking to understand the formation of football clubs, the transition of professionalism and the training of athletes and the level of insolvency that the clubs are suffering. The Brazilian models of bankruptcy (Kanitz, Elisabetsky, Altman and Matias) were applied in eighteen Brazilian clubs that offer on their website, the financial statements for the years 2008, 2009, 2010 and 2011. The results revealed that the majority of clubs is in a high degree of insolvency, or has the ability to pay its debts. It is the result of gross mismanagement of the amateur leaders in previous years, we now carry the clubs in their day to day / A presente pesquisa apresenta os resultados de um estudo descritivo sobre a aplicabilidade dos modelos brasileiros de previsão de falência nos clubes brasileiros de futebol. Inicialmente, o estudo é produzido a partir de pesquisas bibliográficas, constituindo-se no alicerce da sustentação teórica do trabalho. Ela visa ampliar as informações a respeito da origem do futebol, sua chegada no Brasil e sua situação atual, buscando entender a formação dos clubes de futebol, a transição do profissionalismo, a formação dos atletas e o nível de insolvência que os clubes passam atualmente. Os modelos brasileiros de falência (Kanitz, Elisabetsky, Altman e Matias), foram aplicados em dezoito clubes brasileiros que disponibilizam em seu site oficial, as demonstrações contábeis dos anos de 2008, 2009, 2010 e 2011. Os resultados revelaram que a maioria dos clubes encontra-se num grau elevado de insolvência, ou seja, não tem a capacidade de pagar suas dividas. Trata-se do fruto de péssima gestão amadora dos dirigentes de anos anteriores, que hoje os clubes carregam no seu dia a dia

Reserves estimation in an unconventional-reservoir setting is a daunting task because of geologic uncertainty and complex flow patterns evolving in a long-stimulated horizontal well, among other variables. To tackle this complex problem, we present a reserves-evaluation workflow that couples the traditional decline-curve analysis with a probabilistic forecasting frame. The stretched-exponential production decline model (SEPD) underpins the production behavior. Our recovery appraisal workflow has two different applications: forecasting probabilistic future performance of wells that have production history; and forecasting production from new wells without production data. For the new field case, numerical model runs are made in accord with the statistical design of experiments for a range of design variables pertinent to the field of interest. In contrast, for the producing wells the early-time data often need adjustments owing to restimulation, installation of artificial-lift, etc. to focus on the decline trend. Thereafter, production data of either new or existing wells are grouped in accord with initial rates to obtain common SEPD parameters for similar wells. After determining the distribution of model parameters using well grouping, the methodology establishes a probabilistic forecast for individual wells. We present a probabilistic performance forecasting methodology in unconventional reservoirs for wells with and without production history. Unlike other probabilistic forecasting tools, grouping wells with similar production character allows estimation of self-consistent SEPD parameters and alleviates the burden of having to define uncertainties associated with reservoir and well-completion parameters.

The doctoral thesis presents various methods of wind data analysis. Its first part summarizes the undesirable factors that influence the measured wind data. In particular, the effects of anemometer placement with regard to the near-by obstacles are investigated. In addition to the theoretical review, the practical examples of analysis of these effects at the wind mast measurements are demonstrated. The second part is focused on the measure-correlate-predict methods. Two original matrix-type methods are presented. Furthermore, a comparison of accuracy of measure-correlate-predict methods for various types of reference data series, various methods and various configurations of applied methods has been performed. The reanalyzed wind proved to be a suitable source of reference data in most cases. The applicability of surface wind data from meteorological stations depends on the combination of reference and target series, as well as on the homogeneity of involved data. The newly introduced methods proved to be suitable and universal tool for measure-correlate-predict application. The final part of the thesis analyses the wind conditions over the Czech Republic. Besides to the overview of the knowledge of the Czech wind climate, the calculation of the wind map of the Czech Republic is described. The final map was...

Made available in DSpace on 2016-08-19T12:56:41Z (GMT). No. of bitstreams: 1 Dissertacao Marcelo Jose.pdf: 1590491 bytes, checksum: 7be3e83649dd910e0afe9a5a25de4e73 (MD5) Previous issue date: 2013-10-22 / The ethanol has continuously gained interests in many countries including Brazil due to the PROÁLCOOL program. The experimental determination of properties of ethanol and other fuels through official methods is very time consuming as well as tedious process. The estimation of these properties with the help of computational tools can be very useful. In the present work, the methods of partial least squares regression (PLS) and artificial neural network multilayer (ANN) were used to estimate one of the most important properties of fuel ethanol, density, using official quality parameters for ethanol, collected from LAPQAP/UFMA laboratory corresponding to 12 years (period: 2002-2013) of analyzes. A careful analysis of the data was performed to obtain a set of variables and data that best represents satisfactory performance of the two models. The estimates of both approaches were compared and validated. The predictive ability of the network obtained was very good for the parameters studied, consistent with the accuracy of the experimental measurements. The low mean square error, the randomness, the zero mean and the constant variance, obtained for the residues, indicated the suitability of the models, suggesting their use to estimate (predict) the density of ethanol. Results indicated that the model ANN was adequate, and the value of NMSE (normalized mean square error) of 0.0012, less than the PLS model of 0.2221. The result achieved is less than the range of measurement uncertainty of the equipment responsible for testing the density proving that the model used has satisfactory performance. / O etanol tem alcançado crescente interesse em muitos países, principalmente, no Brasil devido ao programa PROÁLCOOL. A determinação experimental das propriedades deste biocombustível e de outros combustíveis por meio de métodos oficiais é muito demorada, bem como é considerado um tedioso processo. A estimativa dessas propriedades com a ajuda de ferramentas computacionais pode ser de grande utilidade. No presente trabalho, os métodos de regressão por mínimos quadrados parciais (PLS) e redes neurais artificiais de múltiplas camadas (RNA) foram usados para estimar uma das mais importantes propriedades do etanol combustível, massa específica, utilizando parâmetros de qualidade oficiais de etanol, oriundos de análises realizadas no laboratório LAPQAP/UFMA, durante 12 anos (período: 2002-2013). Inicialmente, uma análise cuidadosa dos dados foi realizada a fim de selecionar um conjunto de variáveis e dados que melhor representasse um desempenho satisfatório dos dois modelos estudados. As estimativas de ambas as abordagens foram comparadas e validadas. A capacidade preditiva da rede neural obtida foi considerada muito boa para os parâmetros estudados, e compatível com a precisão das medidas experimentais. O baixo erro quadrático médio, a aleatoriedade, a média nula e a variância constante, obtida para os resíduos, evidenciaram a adequabilidade dos modelos usados, sugerindo a utilização destes modelos para estimar (predizer) a massa específica do etanol. Resultados indicaram que o modelo de RNA foi adequado, sendo o valor de NMSE (erro quadrático médio normalizado) de 0,0012, valor este, muito inferior ao modelo de PLS de 0,2221. Este resultado alcançado é inferior aos valores da faixa de incerteza de medição do equipamento responsável pelo ensaio experimental da massa específica, comprovando que o modelo utilizado possui desempenho considerado muito bom.

The Financial analysis examines a general financial situation of the company from year 2000 to 2007. There were used classical methods for financial analysis. Parf of this thesis is about aplication of creditworthy and bankruptcy models. The aim was to find out if these models were able to predict the bad current situation of this firm.

This knowledge overview aims to examine the importance of decoding for students learning how to read and if it can be used as a tool to measure approximate future development in reading comprehension. The study aims to answer the questions “What does current research say about decoding and its implications for monolingual students and their future reading comprehension?” and “What tests are used by researchers to measure students decoding, reading comprehension and fluency”. Reading comprehension is explained as an umbrella term for several smaller groups. Mainly decoding, phonological awareness and language comprehension.  In this overview several scientific studies about decoding and its potential implications will be analyzed and compared with each other and prior research. This research was collected through the database ERIC (EBSCO) with key words with the purpose of finding scientific papers pertaining to the subject in question.  These studies examine students' current decoding abilities to try to distinguish what their reading comprehension levels will be in the future. These results are then followed up with reading comprehension tests to see if the approximations were correct.  The results indicate that the majority of researchers agree that decoding is a good way of estimating students' future performance and growth in reading comprehension. These results lay the foundation for further research that will examine three things: What is the best way to teach kids decoding in order to help with future reading, How do bi- and multilingual students feel about the Swedish subject in schools and how are students with dyslexia affected by the current strategy used to teach them to read. / Denna kunskapsöversikt ämnar att undersöka hur viktig avkodning är för elevers läsutveckling samt om den kan användas som ett verktyg för att mäta framtida läsförståelseutveckling. Frågeställningarna “Vad säger nuvarande didaktisk forskning om avkodning och dess implikationer för enspråkiga elevers framtida läsförståelse i grundskolan?” och “Vilka tester använder forskarna för att mäta elevers avkodning, läsförståelse och läsflyt?”. Läsförståelse används som ett paraplybegrepp för flera mindre delar. Främst avkodning, fonologisk medvetenhet och språkförståelse.  I denna översikt analyseras och jämförs flera forskningar om avkodning och dess potentiella implikationer, både med varandra och med tidigare forskning. Denna forskning samlades genom databasen ERIC (EBSCO) med hjälp av nyckelord med anledning av att hitta vetenskapliga studier som behandlade ämnet.  Forskningarna undersöker elevers avkodningsförmåga och försöker uppskatta hur deras läsförståelsenivåer kommer vara i framtiden. Resultaten grundas i läsförståelsetest för att se om de uppskattade resultaten var korrekta. Resultaten indikerar att majoriteten av forskarna var överens om att avkodning är ett bra verktyg för att uppskatta elevers framtida prestation och utveckling när det gäller läsförståelse. Resultaten lägger grund för vidare forskning som kommer undersöka tre saker: “Hur lär man elever att avkoda på bästa sätt för att ge dem bra förutsättningar inför deras framtida läsning?”, “Hur upplever flerspråkiga elever svenskämnet i skolan?” och “Hur påverkas elever med problematiken dyslexi av de nuvarande strategier som används för att lära dem läsa?

This qualitative study focuses on finding out how middle school teachers work with the reading strategy “to predict” to develop students into good readers. The starting point was to find out how they work and how they help students become better readers through scaffolding. In addition, the study focuses on teachers' different experiences regarding the reading strategy. The results are analyzed based on Duke & Pearson's reading teaching model, Vygotsky's theory about scaffolding as well as a phenomenographic approach.  The results show that teachers work differently with the reading strategy. Their main reason for using the strategy is to arouse students' interest and thus get them to read more. This will make students good readers. The results also show that they are working with the strategy when reading a new book or text. Students will have the opportunity to explain, motivate and argue. The teachers support the students by being there as the competent second and through guidance that provides students with enough knowledge to cope with a task on their own. Finally, the results can be summarized in such way that teachers have different experiences and knowledge regarding the strategy “to predict” and therefore interpret the curriculum differently. The teaching therefore does not look the same in all classrooms and the use of the strategy becomes visible in different teachers.

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This thesis explores the application of machine learning techniques, a type of artificial intelligence that enables computers to learn from data, in hydroponic systems for predicting basil plant height. Hydroponics is a method of growing plants without soil, using nutrient-rich water instead. Conducted at Devoteam, an IT consulting firm in Malmö, the study involved the implementation of two hydroponic systems: Deep Water Culture and Nutrient Film Technique, focusing on monitoring and collecting data such as electrical conductivity, pH levels, water temperature. Utilizing five distinct machine learning models, namely Linear Regression, Decision Tree, Random Forest, Support Vector Regression, and K-Nearest Neighbours, we analyzed their performance in predicting basil plant height. Data were collected using a system equipped with a microcontroller unit, EC sensor, and water temperature sensor, supplemented by data from the open dataset, OpenAg. Our findings indicate that the Random Forest model consistently outperformed other models across datasets, demonstrating superior accuracy and predictive capability. This research provides insights into leveraging machine learning for optimizing hydroponic cultivation practices.

MSc Health Research Methodology - Health Technology Assessment specialization / Immune thrombocytopenia (ITP) is an autoimmune disease characterized by reduced production and augmented destruction of platelets. Adults with ITP have platelet blood counts less than 100x109/L. Ranging from mild to severe, bleeding symptoms may include epistaxis, gingival, petechiae, mucosal, gastrointestinal, vaginal, or intracranial bleeding. ITP can be primary or secondary to other medical conditions. Three phases categorize primary ITP based on the onset and persistence of symptoms: newly diagnosed, persistent, or chronic (1-4). An ITP diagnosis includes a complete blood count, blood film, and viral and autoimmune testing. Depending on patients' comorbidities, the type and number of examinations may vary (3). Diagnosis may also depend on the platelet count response to medications or treatment of secondary causes. There is the need to streamline ITP diagnosis. The time-consuming and high-cost approaches to ruling out other thrombocytopenic conditions, have led Michael G. DeGroote Centre for Transfusion Research (MCTR) researchers to optimize ITP care by developing the Predict-ITP Tool to identify patients with ITP during the initial hematology consultation. The clinical prediction model incorporates data such as platelet count variability, maximum mean platelet volume (MPV), lowest platelet count value, and a history of severe bleeding at any time (5). Improving diagnostic accuracy may improve the quality of life and help reduce expensive, unnecessary, and potentially harmful treatments. Overall, this project vi aims to determine the cost savings of the Predict-ITP tool when implemented in practice, compared to current ITP diagnostic practices. To achieve this goal, in this thesis, we will first estimate the current cost of ITP care and design a health economic evaluation to accompany a randomized controlled trial (RCT) comparing the quality of life and economic impact of the Predict-ITP tool versus current ITP care / Thesis / Master of Health Sciences (MSc) / Platelets help to stop bleeding. Immune thrombocytopenia (ITP) is a disease characterized by decreased platelet counts in the blood. This condition may cause symptoms such as recurring gums and nosebleeds, effortless bruising, and potential life-threatening bleeding. There is no specific test to identify ITP, and its diagnosis is based on excluding other causes of low platelet counts. As a result, an incorrect diagnosis is common in the clinic, resulting in unnecessary testing, wrong treatment, decreased quality of life, and increased costs. To identify the probability of a patient having ITP at the initial hematology consultation, McMaster researchers developed a clinical prediction model. The objectives of this study protocol were to determine the cost savings of the prediction model compared to the standard of care. I have designed an economic analysis that will accompany a randomized trial, comparing the use of the prediction model vs. no model (the current standard of care). The primary outcome of the economic analysis will be to demonstrate the clinical prediction model's cost-effectiveness. Secondary outcomes are the difference in costs between the prediction model and current ITP care, resource utilization, and life quality.