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L'objectif initial de ce travail de thèse est de valoriser les informations relatives au suivi temporel de la vigne, du raisin et de l'environnement de la plante et enregistrées dans des bases de données (BD) de traçabilité pour permettre la comparaison entre parcelles et millésimes, en vue de décisions par analogies.Les travaux réalisés durant cette thèse ont permis de proposer une méthode de transformation qui permet de représenter des ensembles de données asynchrones dans un espace commun afin de les comparer. Cette méthode s'appuie sur l'expertise du système de production. Dans ce travail de thèse, cette méthode a été appliquée à la comparaison de couples parcelle×millésime.L'expertise du système de production viticole permet, dans une première phase, de définir (i) la forme générale de la cinétique d'évolution de grandeurs de mesures évaluées sur la vigne, le raisin ou l'environnement de la plante et (ii) l'effet du climat sur la plante. Cette expertise est utilisée, dans une seconde phase, pour proposer des modèles paramétriques de l'évolution de chaque grandeur. Les données de suivi de chaque couple parcelle×millésime permettent d'ajuster les paramètres du modèle. Un vecteur de paramètres est défini par couple parcelle×millésime. Ce vecteur représente l'espace commun qui rend les couples parcelle×millésime comparables. Deux stratégies de comparaison sontalors possibles : (i) les comparaisons sont réalisées à partir des paramètres (méthode intensive), ou (ii) les comparaisons sont réalisées à partir de l'estimation de la valeur de la grandeur pour chaque couple parcelle×millésime et chaque unité de temps, commune à tous les couples (méthode extensive).Cette méthode a été appliquée à trois exemples différents.Dans une première application, les climats de différents millésimes intervenus sur différents cépages, entre la floraison et la véraison, ont été comparés entre eux après modélisation des grandeurs de mesure climatiques, à l'aide de modèles très simples.Dans une seconde puis une troisième application, la cinétique d'augmentation du pH et d'accumulation des sucres dans les baies de raisin pendant la maturation a été modélisée sous la forme d'une sigmoïde. Les comparaisons ont ensuite été réalisées en travaillant sur (i) la courbe représentative de chaque cinétique (pH), (ii) les paramètres du modèle (sucres) et (iii) une estimation journalière de la concentration en sucres dans les baies.Les bases de données utilisées dans ces applications proviennent de deux régions très différentes. Des données issues du suivi de la station expérimentale INRA Pech Rouge en Languedoc-Roussillon, dans le sud de la France, ont été utilisées pour l'application 1 et une partie de l'application 3. Des données de suivi de différents domaines de la Napa Valley en Californie ont servi pour l'application 2 et une partie de l'application 3.Le changement d'espace de représentation des données apporte une connaissance nouvelle pour décrire les individus et les phénomènes temporels de la vigne. Cette connaissance pourrait permettre de formaliser un raisonnement par analogies utilisant et valorisant l'expérience passée pour la gestion du millésime en cours. / The initial objective of this thesis is to enhance the in-time follow-up information of the vine, the grape and the environment of the plant stored in traceability databases (BD) traceability to allow comparison between plots and vintages, to a future analogy-based decision support.The work done during this thesis allowed to propose a transformation method for representing sets of asynchronous data in a common space for comparison. This method relies on the expertise of the production system. In this thesis, this method was applied to the comparison of pairs of plot×vintage.The expert knowledge of the vineyard production system allows, in a first phase, to define (i) the general shape of the kinetics of on the vine, the grapes or the plant environment measured grandeurs, and (ii) the effect of the climate on the plant.This expertise is used in a second phase, to propose parametrical models that represent each grandeur kinetic. Monitoring data of each pair plot×vintage are used to adjust the model parameters. A vector of parameters is defined for each pair plot×vintage. This vector represents the common space that makes pairs of plot×vintage comparable. Two comparison strategies are possible: (i) comparisons are made from the parameters (intensive method), or (ii) comparisons are made from the estimation of the value of the quantity for each pair plot×vintage and each time unit, common to all pairs (extensive method).This method was applied to three different examples.In a first application, the climate of different vintages occurred on different grape varieties, between flowering and veraison, were compared with each other after modeling of the measured climate grandeurs, with very simple models.In a second and a third application, the kinetics of the increase of pH and accumulation of sugars in grape berries during ripening was modeled using a sigmoid. Comparisons were then made by working on (i) the graph of each kinetic (pH), (ii) parameters (sugars) and (iii) an estimation of the daily sugar concentration in berries.The databases used in these applications come from two very different winegrowing regions. Data from the monitoring of the INRA Pech Rouge Experimental Station, in Languedoc-Roussillon in the south of France, were used for the application 1 and part of the application 3. Monitoring data from different estates of Napa Valley in California were used for the application 2 and part of the application 3.The change of space where data are represented constitutes a new knowledge that permit one to describe individuals and temporal phenomena of the vine. This knowledge could allow to formalize an analogy-based reasoning that uses and promotes past experience to manage the current vintage.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-09-14T13:38:15Z No. of bitstreams: 1 marianacalifenobrega.pdf: 794218 bytes, checksum: bd5394f3f188980963c8acb8c077780b (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-10-04T13:10:41Z (GMT) No. of bitstreams: 1 marianacalifenobrega.pdf: 794218 bytes, checksum: bd5394f3f188980963c8acb8c077780b (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-10-04T13:10:49Z (GMT) No. of bitstreams: 1 marianacalifenobrega.pdf: 794218 bytes, checksum: bd5394f3f188980963c8acb8c077780b (MD5) / Made available in DSpace on 2016-10-04T13:10:50Z (GMT). No. of bitstreams: 1 marianacalifenobrega.pdf: 794218 bytes, checksum: bd5394f3f188980963c8acb8c077780b (MD5) Previous issue date: 2011-06-29 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A evasão e abandono dos alunos nos diferentes níveis de aprendizagem é tema recorrente de discussões acerca da eficácia da educação pública no Brasil. Este trabalho propõe um estudo sobre o abandono escolar no Ensino Médio. Para tanto, o primeiro capítulo versará sobre o Ensino Médio em si e sua situação no campo legislativo. O segundo capítulo apresentará uma revisão de bibliografia do tema abandono escolar expondo as principais linhas de pesquisa e destacando os fatores diagnosticados como relevantes para saída desses jovens do sistema de ensino – com mais de nove anos de escolaridade – sem o diploma do ensino médio. No que tange à análise de dados, o terceiro capítulo pretende apresentar a pesquisa desenvolvida no ano de 2009, a metodologia utilizada, as análises de dados, equações, modelos e, ainda, as tabelas e gráficos. Por último, o capítulo final apresentará as conclusões às quais esta pesquisa foi capaz de encontrar por meio da metodologia utilizada. / This research proposes a study about the abandon on High Schools. This evasion and abandon of students in the different degrees of learning is constant theme on discussions about the efficacy of public education in Brazil. The first chapter will talk about High School itself and its situation in the legislative camp. The second one will show a bibliographic revision about this problem exposing the main lines of the research and pointing the main factors responsible for abandon of this students from the learning system – with more then nine years in school – without High School’s certification. In the third chapter tends to show the research made in the year of 2009, the methodology used, the data analyses, equations, models and even schedules and graphics. In the last chapter will show the conclusions about what this research was able to find by the methodology used.

BACKGROUND Rehabilitation therapies are effective for older persons in home-based settings, and have the potential to save money for the health system, while also improving the quality of life for older adults who may otherwise be hospitalized or institutionalized. Although there is evidence that home-based rehabilitation can improve functional outcomes in older adults, research has shown that many older home care clients do not receive the rehabilitation services they need. Despite the home care sector’s increasing importance within Ontario’s health care system, we have a limited understanding of the population that currently utilizes these services and how these services are allocated in the province. This dissertation project aims to enhance the understanding of this domain using a large provincial data repository of home care client information (RAI-HC information system). METHODS Using the Andersen-Newman Framework to guide this research from a conceptual standpoint, and combining it with the CRoss Industry Standard Process for Data Mining (CRISP-DM) as an organizational framework, this dissertation focuses on examining data collected on older long-stay home care clients. Prior to the data mining modeling procedures, knowledge of the rehabilitation services in home care was developed through a series of semi-structured interviews with key informants. The results of this qualitative study were then used to inform quantitative analyses that included creating rehabilitation service user profiles using the K-means clustering algorithm, and the development of predictive models of rehabilitation service provision using a Random forest algorithm and multilevel models. RESULTS Older home care clients who receive occupational therapy and physiotherapy in the Ontario Home Care System form a complex and heterogeneous client population. These services are often provided to clients following an acute event, yet many older adults who could benefit from therapy services for functional improvement and maintenance are not provided services due to limited resources. K-means clustering analyses resulted in the creation of seven profiles of rehab service users illustrating the multidimensional diversity of the service user population. Predictive models were able to identify client characteristics that are commonly associated with service provision. These models confirmed the large amount of regional variation found across the province and highlighted the differences between factors that lead to occupational therapy and physiotherapy service provision. CONCLUSIONS Using multiple methods to systematically examine rehabilitation services for long-stay clients, new insights into the current user population and the client characteristics related to service provision were obtained. Future research activities should focus on ways to use the regularly collected standardized data to identify older long-stay home care clients who would benefit most from the rehabilitation therapy services provided by the provincial home care system.

BACKGROUND Rehabilitation therapies are effective for older persons in home-based settings, and have the potential to save money for the health system, while also improving the quality of life for older adults who may otherwise be hospitalized or institutionalized. Although there is evidence that home-based rehabilitation can improve functional outcomes in older adults, research has shown that many older home care clients do not receive the rehabilitation services they need. Despite the home care sector’s increasing importance within Ontario’s health care system, we have a limited understanding of the population that currently utilizes these services and how these services are allocated in the province. This dissertation project aims to enhance the understanding of this domain using a large provincial data repository of home care client information (RAI-HC information system). METHODS Using the Andersen-Newman Framework to guide this research from a conceptual standpoint, and combining it with the CRoss Industry Standard Process for Data Mining (CRISP-DM) as an organizational framework, this dissertation focuses on examining data collected on older long-stay home care clients. Prior to the data mining modeling procedures, knowledge of the rehabilitation services in home care was developed through a series of semi-structured interviews with key informants. The results of this qualitative study were then used to inform quantitative analyses that included creating rehabilitation service user profiles using the K-means clustering algorithm, and the development of predictive models of rehabilitation service provision using a Random forest algorithm and multilevel models. RESULTS Older home care clients who receive occupational therapy and physiotherapy in the Ontario Home Care System form a complex and heterogeneous client population. These services are often provided to clients following an acute event, yet many older adults who could benefit from therapy services for functional improvement and maintenance are not provided services due to limited resources. K-means clustering analyses resulted in the creation of seven profiles of rehab service users illustrating the multidimensional diversity of the service user population. Predictive models were able to identify client characteristics that are commonly associated with service provision. These models confirmed the large amount of regional variation found across the province and highlighted the differences between factors that lead to occupational therapy and physiotherapy service provision. CONCLUSIONS Using multiple methods to systematically examine rehabilitation services for long-stay clients, new insights into the current user population and the client characteristics related to service provision were obtained. Future research activities should focus on ways to use the regularly collected standardized data to identify older long-stay home care clients who would benefit most from the rehabilitation therapy services provided by the provincial home care system.

This thesis is concerned with the application of recently developed epidemiological and statistical tools to inform the optimisation of a national surveillance strategy of considerable importance to human health. The results of a series of epidemiological investigations of surveillance strategies for zoonotic Salmonella are presented. Salmonella are one of the most common and serious zoonotic foodborne pathogenic bacteria globally. These studies were motivated by the increasing focus on the cost-effectiveness of surveillance while maintaining consumer confidence in food supply. Although data from the Danish Salmonella surveillance and control programme has been used in these investigations, the techniques may be readily applied to other surveillance data of similar quality. The first study describes the spatial epidemiological features of Danish Salmonella surveillance and control programme data from 1995 to 2004, using a novel method of spatially adaptive smoothing. The conditional probability of a farm being a case was consistently high in the the south-west of Sonderjylland on the Jutland peninsula, identifying this area for further investigation and targeted surveillance. The identification of clustering of case farms led into the next study, which closely examines one year of data, 2003, for patterns of spatial dependency. K-function analyses provided evidence for aggregation of Salmonella case farms over that of all farms at distances of up to six kilometres. Visual semivariogram analyses of random farm-level effects from a Bayesian logistic regression model (adjusted for herd size) of Salmonella seropositivity, revealed spatial dependency between pairs of farms up to a distance of four kilometres apart. The strength of the spatial dependency was positively associated with slaughter pig farm density. We describe how this might inform the surveillance programme by potentially targeting herds within a four kilometre radius of those with high levels of Salmonella infection. In the third study, farm location details, routinely recorded surveillance information, and industry survey data from 1995 were combined to build a logistic seroprevalence model. This identified wet-feeding and specific pathogen free herd health status as protective factors for Salmonella seropositivity, while purchasing feed was a risk factor. Once adjusting for these covariates, we identified pockets of unexplained risk for Salmonella seropositivity and found spatial dependency at distances of up to six km (95% CI: 2–35 km) between farms. A generalised linear spatial model was fitted to the Jutland data allowing formal estimation of the range of spatial correlation and a measure of the uncertainty about it. There was a large within-farm component to the variance, suggesting that gathering more farm level information would be advantageous if this approach was to be used to target surveillance strategy. The fourth study again considers data from the whole study period, 1995 to 2004. A detailed temporal analysis of the data revealed there was no consistent seasonal pattern and correspondingly no benefit in targeting sampling to particular times of the year. Spatiotemporal analyses suggested a local epidemic of increased seroprevalence occured in west Jutland in late 2000. Lorelogram analyses showed a defined period of statistically significant temporal dependency, suggesting that there is little value in sampling more frequently than every 10 weeks on the average farm. The final study uses findings from the preceding chapters to develop a zero-inflated binomial model which predicts which farms are most at risk of Salmonella, and then preferentially samples these high-risk farms. This type of modelling allows assessment of similarities and differences between factors that affect herd infection status (introduction) and those that affect the seroprevalence in infected herds (persistence and spread). The model suggested that many of the herds where Salmonella was not detected were infected but at a low prevalence. Using cost and sensitivity, we compared the results with those under the standard sampling scheme based on herd size, and the recently introduced risk-based approach. Model based results were less sensitive, but showed significant cost savings. Further model refinements, sampling schemes, and the methods to evaluate their performance are important areas for future work, and should continue to occur in direct consultation with Danish authorities.

This thesis is concerned with the application of recently developed epidemiological and statistical tools to inform the optimisation of a national surveillance strategy of considerable importance to human health. The results of a series of epidemiological investigations of surveillance strategies for zoonotic Salmonella are presented. Salmonella are one of the most common and serious zoonotic foodborne pathogenic bacteria globally. These studies were motivated by the increasing focus on the cost-effectiveness of surveillance while maintaining consumer confidence in food supply. Although data from the Danish Salmonella surveillance and control programme has been used in these investigations, the techniques may be readily applied to other surveillance data of similar quality. The first study describes the spatial epidemiological features of Danish Salmonella surveillance and control programme data from 1995 to 2004, using a novel method of spatially adaptive smoothing. The conditional probability of a farm being a case was consistently high in the the south-west of Sonderjylland on the Jutland peninsula, identifying this area for further investigation and targeted surveillance. The identification of clustering of case farms led into the next study, which closely examines one year of data, 2003, for patterns of spatial dependency. K-function analyses provided evidence for aggregation of Salmonella case farms over that of all farms at distances of up to six kilometres. Visual semivariogram analyses of random farm-level effects from a Bayesian logistic regression model (adjusted for herd size) of Salmonella seropositivity, revealed spatial dependency between pairs of farms up to a distance of four kilometres apart. The strength of the spatial dependency was positively associated with slaughter pig farm density. We describe how this might inform the surveillance programme by potentially targeting herds within a four kilometre radius of those with high levels of Salmonella infection. In the third study, farm location details, routinely recorded surveillance information, and industry survey data from 1995 were combined to build a logistic seroprevalence model. This identified wet-feeding and specific pathogen free herd health status as protective factors for Salmonella seropositivity, while purchasing feed was a risk factor. Once adjusting for these covariates, we identified pockets of unexplained risk for Salmonella seropositivity and found spatial dependency at distances of up to six km (95% CI: 2–35 km) between farms. A generalised linear spatial model was fitted to the Jutland data allowing formal estimation of the range of spatial correlation and a measure of the uncertainty about it. There was a large within-farm component to the variance, suggesting that gathering more farm level information would be advantageous if this approach was to be used to target surveillance strategy. The fourth study again considers data from the whole study period, 1995 to 2004. A detailed temporal analysis of the data revealed there was no consistent seasonal pattern and correspondingly no benefit in targeting sampling to particular times of the year. Spatiotemporal analyses suggested a local epidemic of increased seroprevalence occured in west Jutland in late 2000. Lorelogram analyses showed a defined period of statistically significant temporal dependency, suggesting that there is little value in sampling more frequently than every 10 weeks on the average farm. The final study uses findings from the preceding chapters to develop a zero-inflated binomial model which predicts which farms are most at risk of Salmonella, and then preferentially samples these high-risk farms. This type of modelling allows assessment of similarities and differences between factors that affect herd infection status (introduction) and those that affect the seroprevalence in infected herds (persistence and spread). The model suggested that many of the herds where Salmonella was not detected were infected but at a low prevalence. Using cost and sensitivity, we compared the results with those under the standard sampling scheme based on herd size, and the recently introduced risk-based approach. Model based results were less sensitive, but showed significant cost savings. Further model refinements, sampling schemes, and the methods to evaluate their performance are important areas for future work, and should continue to occur in direct consultation with Danish authorities.

This thesis is concerned with the application of recently developed epidemiological and statistical tools to inform the optimisation of a national surveillance strategy of considerable importance to human health. The results of a series of epidemiological investigations of surveillance strategies for zoonotic Salmonella are presented. Salmonella are one of the most common and serious zoonotic foodborne pathogenic bacteria globally. These studies were motivated by the increasing focus on the cost-effectiveness of surveillance while maintaining consumer confidence in food supply. Although data from the Danish Salmonella surveillance and control programme has been used in these investigations, the techniques may be readily applied to other surveillance data of similar quality. The first study describes the spatial epidemiological features of Danish Salmonella surveillance and control programme data from 1995 to 2004, using a novel method of spatially adaptive smoothing. The conditional probability of a farm being a case was consistently high in the the south-west of Sonderjylland on the Jutland peninsula, identifying this area for further investigation and targeted surveillance. The identification of clustering of case farms led into the next study, which closely examines one year of data, 2003, for patterns of spatial dependency. K-function analyses provided evidence for aggregation of Salmonella case farms over that of all farms at distances of up to six kilometres. Visual semivariogram analyses of random farm-level effects from a Bayesian logistic regression model (adjusted for herd size) of Salmonella seropositivity, revealed spatial dependency between pairs of farms up to a distance of four kilometres apart. The strength of the spatial dependency was positively associated with slaughter pig farm density. We describe how this might inform the surveillance programme by potentially targeting herds within a four kilometre radius of those with high levels of Salmonella infection. In the third study, farm location details, routinely recorded surveillance information, and industry survey data from 1995 were combined to build a logistic seroprevalence model. This identified wet-feeding and specific pathogen free herd health status as protective factors for Salmonella seropositivity, while purchasing feed was a risk factor. Once adjusting for these covariates, we identified pockets of unexplained risk for Salmonella seropositivity and found spatial dependency at distances of up to six km (95% CI: 2–35 km) between farms. A generalised linear spatial model was fitted to the Jutland data allowing formal estimation of the range of spatial correlation and a measure of the uncertainty about it. There was a large within-farm component to the variance, suggesting that gathering more farm level information would be advantageous if this approach was to be used to target surveillance strategy. The fourth study again considers data from the whole study period, 1995 to 2004. A detailed temporal analysis of the data revealed there was no consistent seasonal pattern and correspondingly no benefit in targeting sampling to particular times of the year. Spatiotemporal analyses suggested a local epidemic of increased seroprevalence occured in west Jutland in late 2000. Lorelogram analyses showed a defined period of statistically significant temporal dependency, suggesting that there is little value in sampling more frequently than every 10 weeks on the average farm. The final study uses findings from the preceding chapters to develop a zero-inflated binomial model which predicts which farms are most at risk of Salmonella, and then preferentially samples these high-risk farms. This type of modelling allows assessment of similarities and differences between factors that affect herd infection status (introduction) and those that affect the seroprevalence in infected herds (persistence and spread). The model suggested that many of the herds where Salmonella was not detected were infected but at a low prevalence. Using cost and sensitivity, we compared the results with those under the standard sampling scheme based on herd size, and the recently introduced risk-based approach. Model based results were less sensitive, but showed significant cost savings. Further model refinements, sampling schemes, and the methods to evaluate their performance are important areas for future work, and should continue to occur in direct consultation with Danish authorities.

Made available in DSpace on 2010-04-20T21:00:36Z (GMT). No. of bitstreams: 4 Andre Alvares Leite Bucione - Turma 2006.pdf.jpg: 2508 bytes, checksum: a2f65c5af5b23551a4dc0fe1c3abcbd3 (MD5) Andre Alvares Leite Bucione - Turma 2006.pdf.txt: 52096 bytes, checksum: 449900717082efece5863c8e2fe88909 (MD5) license.txt: 4712 bytes, checksum: 4dea6f7333914d9740702a2deb2db217 (MD5) Andre Alvares Leite Bucione - Turma 2006.pdf: 168087 bytes, checksum: a635f49727d9a7e37d08060c75001c86 (MD5) Previous issue date: 2010-02-11T00:00:00Z / Top management from retail bank industry (PRINCIPAL) needs to delegate authority to lower level managers (AGENTS) under the existence of conflicting interests, asymmetric information and limited monitoring. A system of performance targets and incentives is adopted in order to induct those agents into principal’s interests. The aim of this paper is to evaluate the existence of a casual relationship between the so called “contract of guaranteed variable wage” and the performance of the lower level managers. It means, to investigate how the appliances of this implicit contract, which promote a substantial change in the direct incentive scheme, affect the performance delivered by those agents. We analyze, econometrically, data from jan.2007 to jun.2009 got from one of the largest Brazilian retail bank through an estimator of fixed effects for an unbalanced panel data. The results indicate that the agents subject to the contract of guaranteed variable wage have delivered an inferior performance compared to the agents subject to variable payment. We conclude, therefore, that problem of moral hazard can be observed on the behavior of the agents subject to this contract. / A alta gerência do banco de varejo (PRINCIPAL) necessita delegar autoridade a gerentes de níveis inferiores (AGENTES) sob a existência de interesses conflitantes, informações assimétricas e a impossibilidade de monitoração completa. Um sistema de metas e incentivos é adotado de modo a induzir estes agentes na direção dos interesses do principal. O objetivo deste trabalho é avaliar a relação causal existente entre o chamado 'contrato de salário variável garantido' e o desempenho dos agentes. Isto é, investigar de que forma a aplicação deste contrato implícito, que promove uma substancial mudança no sistema de incentivos diretos, afeta o desempenho destes agentes. Analisamos econometricamente dados de jan.2007 a jun.2009 obtidos junto a um grande banco de varejo nacional através de um estimador de efeitos fixos para um painel de dados não balanceado. Os resultados indicam que os agentes sujeitos ao contrato de salário variável garantido têm um desempenho inferior aos agentes sujeitos a remuneração variável. Concluímos que não podemos descartar existência do problema de risco moral no comportamento dos agentes sujeitos a este contrato.