This work in the first chapter describes reasons for the formation of nonprofit sector and the necessity of its existence. Further, individual sources of funding nonprofit organizations in the Czech Republic are described and also explained using examples from common life. I mainly focus on specificities of individual financial sources and also compare sources of funding among NPO. I also submit some conclusions of conducted research. It gives possibility to study diversity of financing different types of NPO. Last chapter is based on regression analysis. I examine certain conclusions from theoretical part of work.

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Made available in DSpace on 2017-07-21T14:19:35Z (GMT). No. of bitstreams: 1 Joaquim Honorio Lima.pdf: 515371 bytes, checksum: 8f95a1f08506d7bdd58cee52c06a4a1b (MD5) Previous issue date: 2012-09-24 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The search for alternative water sources for agriculture activities have been an actual concern due to decreasing of available potable water. The agricultural use of secondary treated sewage effluent (STSE) for crops irrigation has been an attractive practice in several soil and climate conditions. However, the changes in soil-plant system after STSE application is not well comprehended in tropical environment, specially under pasture crops. The aim of this work, to model scenarios, including soil-pasture systems subjected to irrigation and rates of nitrogen by mineral fertilization (NMF), aiming mathematics models to understand of the dynamic attributes of the total carbon (TC), total nitrogen (TN) and available phosphorus (Pavai) soil. The linear regression models (LRM) were used to approach. The variable selection methods of stepwise, forward and backward were used to LRM development and compared to standard method, through the adjusted coefficient of determination and variance influence factor. The models developed using variable selection methods were the most indicated. The CT has most of its concentration explained by the variables block, time, temperature and precipitation. The concentration of NT and P were not explained by the same group of variables in the different scenarios. The organic carbon from Tifton 85 grass and TN from STSE inputs appeared not to be enough to mitigate the TC and TN losses of soil, respectively. The grass was, in adequate conditions for growth and above ground dry mass accumulation, an important Pavai sink and, moreover, the input of P from STSE few changed the concentration of soil Pavai. / A preocupação com a diminuição na oferta de água potável tem implicado na busca por fontes alternativas, particularmente, para atividades agrícolas. A utilização de efluente de tratamento secundário de esgoto (ETSE) na irrigação das culturas tem sido prática comum em diversas situações de clima e solo. Todavia, as mudanças ocorridas no sistema solo-planta mediante o uso de ETSE não são bem compreendidas em situação de ambiente tropical, particularmente, sob pastagens cultivadas. Objetivou-se neste trabalho, modelar cenários, incluindo sistemas solopastagem submetido à irrigação e doses de nitrogênio via fertilizante mineral, mediante uso de regressão linear múltipla (RLM), visando auxiliar no entendimento da dinâmica dos atributos carbono total (CT), nitrogênio total (NT) e fósforo disponível (Pdisp) no solo. Na construção dos modelos de RLM foram utilizados os métodos de seleção de variáveis stepwise, forward e backward e comparados com o método padrão, através dos índices de coeficiente de determinação ajustado e do fator de inflação de variância. Os modelos gerados com seleção de variáveis foram os mais indicados. O CT teve a maior parte de sua concentração explicada pelas variáveis bloco, tempo, temperatura e precipitação. As concentrações de NT e Pdisp não foram explicadas por um mesmo conjunto de variáveis nos diferentes cenários. O aporte de carbono orgânico oriundo do capim-Tifton 85 e do NT oriundo do ETSE parecem não ser suficientes para resultar em reposição das perdas de CT e NT do solo, respectivamente. O capim atuou como um dreno de Pdisp e, o aporte de P oriundo do ETSE pouco influenciou a concentração deste nutriente no solo.

Energy is increasingly becoming more important in today&rsquo / s world. Ascending of energy consumption due to development of technology and dense population of earth causes greenhouse effect. One of the most valuable energy sources is hydro energy. Because of limited energy sources and excessive energy usage, cost of energy is rising. There are many ways to generate electricity. Among the electricity generation units, hydroelectric power plants are very important, since they are renewable energy sources and they have no fuel cost. Electricity is one of the most expensive input in production. Every hydro energy potential should be considered when making investment on this hydro energy potential. To decide whether a hydroelectric power plant investment is feasible or not, project cost and amount of electricity generation of the investment should be precisely estimated. This study is about cost estimation of hydroelectric power plant projects. Many design parameters and complexity of construction affect the cost of hydroelectric power plant projects. In this thesis fifty four hydroelectric power plant projects are analyzed. The data set is analyzed by using regression analysis and artificial neural network tools. As a result, two cost estimation models have been developed to determine the hydroelectric power plant project cost in early stage of the project.

The duration of construction of a project depends on many factors, such as: cost, location, site characteristics, procurement methods, area of construction, footprint of the building and its height, etc. It is very important to be able to predict these durations accurately in order to successfully complete a project on time. Various construction duration estimation tools have been developed to make accurate predictions, as &ldquo / time is money.&rdquo / The main objective of this study was to develop a model that can be used to predict the construction duration of a project in a reliable and practical way. Contractors can thus use a project&#039 / s characteristics, as given in the tender documents, to estimate the actual amount time it would take them to complete the construction works. In this study, factors affecting the duration of a construction project and models for estimating construction durations were investigated. Within this framework, duration estimation models such as / Bromilow&rsquo / s Time-Cost (BTC) Model and Building Cost Information Service (BCIS) Model were used while Simple Linear Regression (SLR) and Multiple Linear Regression (MLR) analyses were conducted on data related to seven case study buildings that are situated at the Middle East Technical University (METU) campus in Ankara. This data was obtained from the Department of Construction and Technical Works (DCTW) at METU. The closeness in estimation of the regression analyses was investigated and finally an MLR model was obtained which was based on two parameters / the area of the building and the area of its fa&ccedil / ade. On the other hand, as opposed to studies reported in literature, the effect of cost on duration was not seen to be significant.

GeoGebra is a free, open-source, and multi-platform software that combines dynamic geometry, algebra and calculus in one easy-to-use package. Students from middle-school to university can use it in classrooms and at home. In this workshop, we will introduce the features of GeoGebra with a special focus on not very common applications of a dynamic geometry program. We will inform about plans for developing training and research networks connected to GeoGebra. We can expect that at the time of the conference a spreadsheet will be integrated into GeoGebra which offers new ways teaching mathematics using the interplay between the features of a spreadsheet and the objects of dynamic geometry.

Made available in DSpace on 2017-07-21T14:19:22Z (GMT). No. of bitstreams: 1 Rodrigo Souza.pdf: 360141 bytes, checksum: 6bf9d8f9ce30fb6fa717ad9798736d1e (MD5) Previous issue date: 2013-07-22 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The competition of water in different regions of the world, between agriculture and the human needs, has led to restrictions in the increase of food production, resulting in search for alternative sources. The use of effluent from secondary treatment of sewage (ETSE) has been a common practice in several seasonal situations. The aims of this work were: (i) create regression models to assist in the understanding of the dynamics of acidity (current, exchangeable and total), the exchangeable bases and the exchangeable sodium percentage (ESP) in the soil, through the use of multiple linear regression (RLM), considering variables of soil, soil solution, plant, ETSE, weather and complementary variables, and (ii) compare the generated models with the standard method and the models generated from selecting variables. For the construction of the MLR models, the method of stepwise variable selection, forward and backward were used and compared with the standard method through the index adjusted determination coefficient (R2adj) and the variance inflation factor (VIF). The models developed from the method of variables selection were the most indicated. All the attributes in the scenarios and layers of the studied soils were not explained by the same group of variables. In general the results were consistent as far as the pH increased, the H + Al (total acidity) and Al (potential acidity) concentration decreased and Ca (calcium), Mg (magnesium) were increased. Because of the low-K (potassium) in the soil, the contribution of this nutrient by irrigation with ETSE cause little influence in the concentrations of this element. Due to the high sodium absorption ratio (SAR) in the effluent concentrations of this element, as well as PST were increased over time in soil. The accumulation and export of Na (sodium) by plants was not sufficient to prevent the increase in the concentrations of exchangeable Na and ESP in all studied scenarios and layers. / A concorrência de água entre o setor agrícola e as necessidades humanas em diversas regiões do mundo tem ocasionado restrições no incremento da produção de alimentos, implicando em buscas por fontes alternativas. A utilização de efluente de tratamento secundário de esgoto (ETSE) tem sido uma prática comum em várias situações sazonais. Objetivou-se neste trabalho:(i) criar modelos de regressão para auxiliar no entendimento da dinâmica da acidez (trocável e total), bases trocáveis e percentual de sódio trocável (PST) no solo, através do uso de regressão linear múltipla (RLM), considerando variáveis de solo, solução no solo, planta, ETSE, meteorológicas e variáveis complementares; e (ii) comparar os modelos gerados com método padrão e os modelos gerados com seleção de variáveis. Para construção dos modelos de RLM foram utilizados o método de seleção de variáveis stepwise, forward e backward e comparados com o método padrão, através dos índices de coeficiente de determinação ajustado (R2adj) e do fator de inflação de variância (FIV). Os modelos desenvolvidos a partir do método de seleção de variáveis foram os mais indicados. Todos os atributos nos cenários e camadas de solos estudados não foram explicadas por um mesmo grupo de variáveis. De modo geral, os resultados foram coerentes, pois na medida em que o pH aumentou, as concentrações H+Al e Al diminuíram e as de Ca e Mg foram incrementadas. O baixo teor de K no solo, evidenciou que o aporte desse nutriente pela irrigação com ETSE pouco influência as concentrações desse elemento. Devido à alta razão de adsorção de sódio (RAS) no ETSE as concentrações deste elemento, bem como PST foram aumentadas ao longo do tempo no solo. O acúmulo e a exportação de Na pelas plantas não foi suficiente para evitar o incremento nas concentrações de Na trocável e PST em todos os cenários e camadas estudados.

Title: Dose-response curves Author: Martin Hezoučký Department: Department of Probability and Mathematical Statistics Supervisor: doc. RNDr. Zdeněk Hlávka, Ph.D., Department of Probability and Mathematical Statistics Abstract: In this thesis, we deal with the process of research and development of new medical substances with a focus on statistical methods used to determine appropriate doses. For this purpose, we examine the dose-response relationship. First, we describe a typical procedure for the development of a new drug. Second, we focus in detail on the MCP-Mod method. Third, we propose a new method based on the theory of gradual change models. This approach tests whether the administration of the drug has a significant effect. If so, the dose with desired effect is estimated using an appropriate model. Specifically, we provide an esti- mate using linear, quadratic and Emax gradual change models. We also describe a construction of a confidence interval for the point of change and also for the dose with the desired effect. The advantage of the proposed method over the MCP-Mod is the determination of the confidence intervals. Finally, we apply the above mentioned methods to data from the U.S. Tox21 research program and compare the results based on several tested substances and clearly demonstrate the...