Ce mémoire porte sur la relation entre les inégalités socioéconomiques et la migration des Indiens inscrits du Québec en 2006. Nous évaluons la contribution des inégalités sociales et scolaires, des inégalités économiques, des inégalités régionales et des inégalités juridiques et politiques à la migration des Indiens inscrits et la contribution de la migration à l’atteinte d’un revenu supérieur. Les résultats obtenus auprès des Autochtones sont comparés à ceux des non-Autochtones de façon à pouvoir distinguer ce qui et spécifique aux Autochtones. Des régressions logistiques ont été effectuées afin d’observer la contribution des caractéristiques individuelles et collectives sur la migration non-récente - entre 2001 et 2005, sur l’atteinte d’un revenu supérieur au 75e centile en 2005 et sur la migration récente - entre 2005 et 2006. Les résultats de la présente recherche montrent que le sexe, l’âge et les variables de migration expliquent très peu le fait de bénéficier d’un revenu supérieur. Obtenir minimalement un diplôme d’études secondaire et d’avoir un travail à temps plein augmente considérablement les chances. Chez les Indiens inscrits, la nation d’appartenance et la zone de résidence expliquent beaucoup plus la variance expliquée. Qui plus est, la contribution de l’âge et du sexe explique très peu le fait d’avoir migré - récemment ou non récemment. Par conséquent, la scolarité, l’occupation expliquent beaucoup le fait que les Indiens inscrits et que les non-Autochtones migrent. Les nations d’appartenance ainsi que les zones de résidence expliquent beaucoup le fait que les Indiens inscrits migrent. / This research shows the relationship between socioeconomics inequalities and migration of the Registered Indians in Quebec in 2006. We evaluate the contribution of social and educational inequalities, economic inequalities, regional inequalities and legal and political inequalities as the contribution of migration to achieve a higher income. The results obtains for the Registered Indians are compared to non-Aboriginals to see the specific situation of the Registered Indians. Logistic regressions are performed to evaluate the contribution of the individual and collective characteristics on non-recent and recent migration and on a 75e percentile income. The results show that sex, age and migration play a very little part in obtaining a higher income. Having minimally a high school diploma or having a full-time job greatly increase the chances. For Registered Indians, nation of belonging and residence area explain more of the variance in income. Furthermore, sex and age explain a very little part of migration recently or less recent. Migration, years of schooling and occupation explain a greater part of the migration of the Registered Indians and non-Aboriginals. Nation of belonging and residence area explains also more of the explained variance of migration.

台灣地區由於國民平均壽命延長，加速了人口結構轉型、老人人口快速增加，因此衍生許多老人居住安養之課題。為探討影響都會區民眾選擇老人住宅之因素，本研究以台北縣永和市為研究範圍。透過問卷調查收集所需資料，以安德遜服務使用行為模式之個人因素及影響服務使用之限制因素為基礎，透過卡方檢定、因子分析、羅吉特迴歸分析及交叉分析等量化分析方法，實證影響台北縣永和市50歲以上人中、老年人選擇老人住宅服務的相關因素。 本研究結果發現，在個人決定方面，性別、年齡、健康情況、現有子女數、家庭總收入、目前居住型態及理想居住型態等變項對入住老人住宅之意願有顯著影響。在限制因素方面，老人住宅之資訊、可近性、租金及老人住宅類型等變項對入住老人住宅之意願有顯著影響。大部份受訪者認為複合化、多機能的老人住宅及降低收費最能提高入住老人住宅之意願。另最廣為受訪者接受之老人住宅類型為規模在50戶以內、與醫療保健設施或社會教育設施以分棟型態複合開發之老人住宅。 本研究建議老人住宅開發業者以複合化、多樣化、小型化的開發模式興建老人住宅；建議政府應重視老人住宅出租市場，加強宣導鼓勵民眾居住老人住宅，建立老人住宅資訊平台，以活絡老人住宅出租市場，增加需求量，吸引更多優質廠商投資。在對台北縣永和市老人住宅政策之建議方面，建議老人住宅服務對象應從選擇性服務擴大到全民性服務，中興社區安養堂應轉型為多機能、複合化的老人住宅。 / In Taiwan, with the advances of medical technology, the life span of people has been extended. As a result, the population of senior people has increased dramatically; therefore, their accommodation and domiciliary care became a big issue in modern society.This research studies the middle-aged and senior people whose age over 50 and live in Yonghe City,Taipei County. Collecting data by questionnaire and using quantity methodology of Andersen model, Chi-square test, Factor Analysis, Logistic Regression and Cross Analysis to understand the factors that affect senior people to choose elderly housing. The result shows, in term of personal decision, the factors of gender, age, healthy conditions, number of children, household income, current living pattern and ideal living pattern etc. will affect senior people to choose elderly housing. In term of limiting factors, the information of elderly housing, residence distance with relatives, a rental and type of elderly housing etc. will affect senior people’s choices. Most interviewers think composite and multifunctional elderly housing as well as cheaper charge would increase the desire to live in elderly housing. Meanwhile, the most popular elderly housing type is less than 50 apartments with medicinal facilities or educational services in the community. This research suggests house building company should develop composite and multifunctional elderly housing in a small community for senior people. In addition, government should think seriously of elderly housing letting market by publicizing the information to encourage senior people to live in elderly housing. Once the house demand increased, it will attract more decent building companies developing more elderly housing to promote for senior people. Furthermore, this research suggests the housing policy in Yonghe City, Taipei County should broaden elderly housing service from selectivity senior people to general elderly. And the Jhong-sing Elderly Community Shelter should be transformed into composite and multifunctional elderly housing.

逆物流回收的複雜度遠比正向物流高，企業為專注核心價值多半將逆物流活動委外專業物流服務供應商。對第三方逆物流業者而言，選擇適當的回收處理中心位址為其重要核心能力之一，而現今研究對於選址模式中之回收不確定性，大多以歷史資料作為參數，無根據區域特性不同而有所分別。故本研究希望探討在零售商提供資訊的情境下，結合消費者問卷建構廢棄產品的使用年限機率、並以二元迴歸邏輯分析建構回收機率以此預測區域回收數量，透過資訊分享以建立更好的回收處理中心選址設置模式，使第三方逆物流業者可按照此模式選擇最適當的回收點位置與回收處理量安排用以求得利潤最大化。 / Since reverse logistics is much more complex than forward logistics, third-party logistics providers are often the prior choice for firms to obtain their core value when a reverse logistic activity is needed. For third-party logistics providers, the location is one of their crucial core values; while most of them can only rely on historical data to assume the best location, due to the uncertainty of recycling in present studies.Therefore, this paper tries to construct the probability of products’ used-years by combining the retailers’ information with consumer-oriented questionnaires. Binary logistic regression is the methodology used to analyze and predict recycling probability. By information-sharing the third-party logistics providers will be able to construct a better selecting model for the best facility location, which will reach the most suitable recycling quantity to maximize their profits.

永續發展的概念現今已被運用於都市，其中，都市綠地在環境、生態、景觀、社會各層面之機能皆可提升都市永續性，在快速的都市化下，都市內綠地減少，土地利用變遷帶來之環境衝擊影響已自個體單元累積到全球。然而，過去研究中未有關注在綠地的變化趨勢與其他土地利用間的互動關係，以及在不同區域下的變化差異。因此，本研究採用GIS和景觀指數看在1995年至2006年間台北都會區綠地變遷趨勢，並分區探討土地利用間的互動關係，最後藉由二元羅吉斯迴歸分析綠地變化可能原因。 研究結果顯示，在1995年至2006年間，台北都會區整體發展是建地增加，林地也呈上升趨勢，而草地是土地利用轉移下被犧牲掉最多的土地，綠地轉移成其他土地利用情形以都會邊緣地區最嚴重。不同綠地型態在1995年至2006年間的變遷仍有差異，林地在整個台北都會區屬於景觀中的基質，主導性未受動搖，僅在都會中心減少並受破壞；而農地面積略微下降，呈破碎化發展，尤其以都會中心外圍區農地被破壞情形最明顯；草地面積亦下降，破碎化情形較農地更嚴重，在都會郊區、次中心之草地被破壞嚴重，草地各方面機能降低。透過二元羅吉斯迴歸分析發現自然環境、社會經濟與計畫環境皆影響台北都會區的綠地變遷。根據研究結果，建議未來政府於都市計畫上應將綠地空間納入考量，對於不同綠地型態應有不同管制措施，考量各區域綠地型態之差異性，以及自然環境、社會經濟和計畫環境對於綠地變遷的影響，以促進都市朝向永續發展。 / The concept of sustainable development has been applied in cities. Urban green space plays an important role in enhancing the sustainability of the city in regards to the environment, ecology, landscape and society aspects. Under rapid urbanization, green space has greatly declined in cities. Environmental impact resulting from land use change has grown from local to global proportions. However, researches did not pay attention to interactions between green spaces and other land-use change trends or different types of change in different areas. This research used GIS and landscape metrics to investigate the green space change trend and interactions among different land use types in the Taipei metropolitan area from 1995 to 2006. Furthermore, this research analyzed possible reasons that may have caused green space change through logistic regression. The results showed that, from 1995 to 2006, the built up area and the forest increased in Taipei Metropolitan Area; however, the grass decreased because of land use change. Urban fringe was the place that green space changed to other land-use most. There were differences of land use change for different types of green space. Forest was the matrix in the landscape of Taipei metropolitan area. It still kept the predominant role, only decreased and was destroyed in the center of metropolitan area. Farmland slightly decreased and became fragmented, especially in the periphery of the urban center. Grassland area decreased and became fragmented much more than farmland. In suburb and sub-center, grassland was destroyed seriously and became less functional. Through binary logistic regression, the study found that natural environment, socio-economic and government planning do have influence on green space changes in the Taipei metropolitan area. According to the result of the study, the recommendation was that government should take green space into consideration when doing urban planning. For different types of green space and different areas, the government needs to have different measures and needs to consider the impact factors of green space change in order to accelerate sustainable development in cities.

隨著經濟繁榮和網絡發展的日新月異，線上線下每時每刻都產生龐大數據，其中約有80%的文字、影像等非結構化數據，如何量化和採取適合的分析方法，成為有效提取有價值信息及對其加以利用的關鍵。針對文字類型的資料，本文提出探索性資料分析方法，並以《新青年》雜誌的語言變化為例，呈現如何選取文本特徵并对其量化及分析的過程。 首先，本文以卷為分析單位，多角度量化《新青年》雜誌各卷的文本結構，包括文本用字、用句、文言和白虛字使用以及常用字詞共用等方面，通過多種圖表相結合的呈現方式，窺探《新青年》雜誌語言變化歷程以及轉變特點。這其中既包括了對文言文到白話文轉變機制的探索，也包括白話語言演化的探索。其次，根據各卷初探的結果，尋找可區隔文言文和白話文兩種語言形式的文本特徵變數，再以《新青年》第一卷和第七卷為訓練樣本，結合主成分和羅吉斯迴歸，對文、白兩種語言形式的文章進行分類訓練，再利用第四卷進行測試。結果證實，所提取的文本變數能夠有效實現對文、白兩種語言形式的文章的區分。此外，本文亦根據前述初探結果以及人文學者經驗，探索《新青年》雜誌後期語言形式的變化，即從五四運動時期的白話文至以「紅色中文」為特徵的白話文（二戰之後中國使用的白話文）的變化。以第七卷和第十一卷為樣本進行訓練，結果證實這兩卷語言形式存在明顯區別；並加入台灣《聯合報》和中國大陸的《人民日報》進行分類預測，發現兩類報刊的語言偏向有明顯差異，值得後續深入研究。 / Tremendous data are produced every day, due to the rapid development of computer technology and economics. Unstructured data, such as text, pictures, videos, etc., account for nearly 80 percent of all data created. Choosing appropriate methods for quantifying and analyzing this kind of data would determine whether or not we can extract useful information. For that, we propose a standard operating process of exploratory data analysis (EDA) and use a case study of language changes in New Youth Magazine as a demonstration. First, we quantify the texts of New Youth magazine from different perspectives, including the uses of words, sentences, function words, and share of common vocabulary. We aim to detect the evolution of modern language itself as well as changes from traditional Chinese to modern Chinese. Then, according to the results of exploratory data analysis, we treat the first and seventh volumes of New Youth magazine for training data to develop classification model and apply the model to fourth volume (i.e., testing data). The results show that the traditional Chinese and modern Chinese can be successfully classified. Next, we intend to verify the changes from modern Chinese of the May 4th Movement to those by advocating Socialism. We treat the seventh volume and eleventh volume of New Youth magazine as training data and again develop a classification model. Then we apply this model to the United Daily News from Taiwan and People’s Daily from Mainland China. We found these two newspapers are very different and the style of United Daily News is closer to that of seventh volume, while the style of People’s Daily is more like that of eleventh volume. This indicates that the People’s Daily is likely to be influenced by the Soviet Union.

Made available in DSpace on 2015-03-26T13:32:17Z (GMT). No. of bitstreams: 1 texto completo.pdf: 764829 bytes, checksum: 8dbd03463c4800428f75900ca1340eb0 (MD5) Previous issue date: 2012-07-23 / The use of logistic regression modeling as a tool for modeling statistical probability of an event as a function of one or more independents variables, has grown among researchers in several areas, including Phytopathology. At about the dichotomous logistic regression in which the dependent variable is the type binary or dummy, is the extensive number of studies in the literature that discuss the modeling assumptions and the interpretation of the analyzes, as well as alternatives for implementation in statistical packages. However, when the variable response requires the use three or more categories, the number of publications is scarce. This is not only due to the scarcity of relevant publications on the subject, but also the inherent difficulty of coverage on the subject. In this paper we address the applicability of the model polytomous ordinal logistic regression, as well as differences between the proportional odds models, nonproportional and partial proportional odds. For this, we analyzed data from an experiment in which we evaluated the potential antagonistic fungus Clonostachys rosea in biocontrol of the disease called "gray mold", caused by Botrytis cinerea in strawberry and tomato. The partial proportional odds models and nonproportional were adjusted and compared, since the proportionality test score accused rejection of the proportional odds assumption. The estimates of the model coefficients as well as the odds ratios were interpreted in practical terms for Phytopathology. The polytomous ordinal logistic regression is introduced as an important statistical tool for predicting values, showing the potential of C. rosea in becoming a commercial product to be developed and used in the biological control of the disease, because the application of C. rosea was as or more effective than the use of fungicides in the control of gray mold. / O uso da regressão logística como uma ferramenta estatística para modelar a probabilidade de um evento em função de uma ou mais variáveis explicativas, tem crescido entre pesquisadores em várias áreas, inclusive na Fitopatologia. À respeito da regressão logística dicotômica, na qual a variável resposta é do tipo binária ou dummy, é extenso o número de trabalhos na literatura que abordam a modelagem, as pressuposições e a interpretação das análises, bem como alternativas de implementação em pacotes estatísticos. No entanto, quando a variável resposta requer que se utilize três ou mais categorias, o número de publicações é escasso. Isso devido não somente à escassez de publicações relevantes sobre o assunto, mas também à inerente dificuldade de abrangência sobre o tema. No presente trabalho aborda-se a aplicabilidade do modelo de regressão logística politômica ordinal, bem como as diferenças entre os modelos de chances proporcionais, chances proporcionais parciais e chances não proporcionais. Para isso, foram analisados dados de um experimento em que se avaliou o potencial do fungo antagonista Clonostachys rosea no biocontrole da doença denominada mofo cinzento , causada por Botrytis cinerea em morangueiro e tomateiro. Os modelos de chances proporcionais parciais e não proporcionais foram ajustados e comparados, uma vez que o teste score de proporcionalidade acusou rejeição da pressuposição de chances proporcionais. As estimativas dos coeficientes dos modelos bem como das razões de chances foram interpretadas em termos práticos para a Fitopatologia. A regressão logística politômica ordinal se apresentou como uma importante ferramenta estatística para predição de valores, mostrando o potencial do C. rosea em se tornar um produto comercial a ser desenvolvido e usado no controle biológico da doença, pois a aplicação de C. rosea foi tão ou mais eficiente do que a utilização de fungicidas no controle do mofo cinzento.

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A study was conducted on 74 school first- and second-team rugby players from four Pretoria high schools, to investigate whether start-up A-team players differ significantly from other (B-team start-up and reserve) players on emotional intelligence. It was further investigated whether emotional intelligence is a predictor of rugby performance if measured as being included into the study’s ‘best team’ or being a start-up A-team school rugby player. Various other physical, psychological, social and spiritual predictors were also investigated singularly and in combination with the emotional intelligence predictor to indicate performance. Data were gathered through a self-reporting questionnaire developed by the researcher. The main methods for analysing data used included the Mann-Whitney Test and the Logistic Regression analysis. The study found certain spiritual and social predictor aspects to be significantly related to performance in rugby but not emotional intelligence. Certain underlying emotional aspects where more significant to the study’s B-team players’ performance. / Spiritual aspects / M.A. (Psychology)

Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro / O atual nível das mudanças uso do solo causa impactos nas mudanças ambientais globais. Os processos de mudanças do uso e cobertura do solo são processos complexos e não acontecem ao acaso sobre uma região. Geralmente estas mudanças são determinadas localmente, regionalmente ou globalmente por fatores geográficos, ambientais, sociais, econômicos e políticos interagindo em diversas escalas temporais e espaciais. Parte desta complexidade é capturada por modelos de simulação de mudanças do uso e cobertura do solo. Uma etapa do processo de simulação do modelo CLUE-S é a quantificação da influência local dos impulsores de mudança sobre a probabilidade de ocorrência de uma classe de uso do solo. Esta influência local é obtida ajustando um modelo de regressão logística. Um modelo de regressão espacial é proposto como alternativa para selecionar os impulsores de mudanças. Este modelo incorpora a informação da vizinhança espacial existente nos dados que não é considerada na regressão logística. Baseado em um cenário de tendência linear para a demanda agregada do uso do solo, simulações da mudança do uso do solo para a microbacia do Coxim, Mato Grosso do Sul, foram geradas, comparadas e analisadas usando o modelo CLUE-S sob os enfoques da regressão logística e espacial para o período de 2001 a 2011. Ambos os enfoques apresentaram simulações com muito boa concordância, medidas de acurácia global e Kappa altos, com o uso do solo para o ano de referência de 2004. A diferença entre os enfoques foi observada na distribuição espacial da simulação do uso do solo para o ano 2011, sendo o enfoque da regressão espacial que teve a simulação com menor discrepância com a demanda do uso do solo para esse ano. / Present state of land use changes impacts global environmental changes. Land use and cover changes are complex processes and do not occur at random pattern in an area. In general, they are determined locally, regionally and globally by geographic, environmental, social, economic and political factors interacting at diverse temporal and spatial scales. Part of this complexity can be modeled by land use and cover change simulation models. An important step of simulation process in CLUE-S model is local influence of driving forces over the occurrence of a land use type. This influence is obtained by logistic regression model. A spatial lag regression model is proposed to select driving forces. This model incorporates spatial neighborhood information which is ignored by logistic regression. Based on a lineal trend scenario of land use demand, simulations of land use changes for Coxim microbasin, Mato Grosso do Sul, were generated, analyzed and compared using CLUE-S model under logistic and spatial regression approaches. The period of simulations was 2001-2011. Both approaches revealed elevated concordance, high global accuracy and Kappa index, to land use for 2004 reference year. Differences were observed for spatial distribution for land use simulations for 2011. Spatial lag regression simulation for 2011 reached less discrepancy to land use demand for that year.

Made available in DSpace on 2016-06-02T20:06:06Z (GMT). No. of bitstreams: 1 4300.pdf: 2695135 bytes, checksum: c7742258a75f77aa35ccb54abc3439fe (MD5) Previous issue date: 2012-03-16 / Financiadora de Estudos e Projetos / In credit scoring problems, the interest is to associate to an element who request some kind of credit, a probability of default. However, traditional models uses samples biased because the data obtained from the tenderers has only clients who won a approval of a request for previous credit. In order to reduce the bias sample of these models, we use strategies to extract information about individuals rejected to be able to infer a response, good or bad payer. This is what we call the reject inference. With the use of these strategies, we also use the bagging technique (bootstrap aggregating), which consist in generate models based in some bootstrap samples of the training data in order to get a new predictor, when these models is combined. In this work we will discuss about some of the combination methods in the literature, especially the method of combination by logistic regression, although little used but with interesting results.We'll also discuss some strategies relating to reject inference. Analyses are given through a simulation study, in data sets generated and real data sets of public domain. / Em problemas de credit scoring, o interesse é associar a um elemento solicitante de algum tipo de crédito, uma probabilidade de inadimplência. No entanto, os modelos tradicionais utilizam amostras viesadas, pois constam apenas de dados obtidos dos proponentes que conseguiram a aprovação de uma solicitação de crédito anterior. Com o intuito de reduzir o vício amostral desses modelos, utilizamos estratégias para extrair informações acerca dos indivíduos rejeitados para que nele seja inferida uma resposta do tipo bom/- mau pagador. Isto é o que chamamos de inferência dos rejeitados. Juntamente com o uso dessas estratégias utilizamos a técnica bagging (bootstrap aggregating ), que é baseada na construção de diversos modelos a partir de réplicas bootstrap dos dados de treinamento, de modo que, quando combinados, gera um novo preditor. Nesse trabalho discutiremos sobre alguns dos métodos de combinação presentes na literatura, em especial o método de combinação via regressão logística, que é ainda pouco utilizado, mas com resultados interessantes. Discutiremos também as principais estratégias referentes à inferência dos rejeitados. As análises se dão por meio de um estudo simulação, em conjuntos de dados gerados e em conjuntos de dados reais de domínio público.