70 resultados para Information search – models

em Université de Lausanne, Switzerland


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Despite the tremendous amount of data collected in the field of ambulatory care, political authorities still lack synthetic indicators to provide them with a global view of health services utilization and costs related to various types of diseases. Moreover, public health indicators fail to provide useful information for physicians' accountability purposes. The approach is based on the Swiss context, which is characterized by the greatest frequency of medical visits in Europe, the highest rate of growth for care expenditure, poor public information but a lot of structured data (new fee system introduced in 2004). The proposed conceptual framework is universal and based on descriptors of six entities: general population, people with poor health, patients, services, resources and effects. We show that most conceptual shortcomings can be overcome and that the proposed indicators can be achieved without threatening privacy protection, using modern cryptographic techniques. Twelve indicators are suggested for the surveillance of the ambulatory care system, almost all based on routinely available data: morbidity, accessibility, relevancy, adequacy, productivity, efficacy (from the points of view of the population, people with poor health, and patients), effectiveness, efficiency, health services coverage and financing. The additional costs of this surveillance system should not exceed Euro 2 million per year (Euro 0.3 per capita).

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Simple Heuristics in a Social World invites readers to discover the simple heuristics that people use to navigate the complexities and surprises of environments populated with others. The social world is a terrain where humans and other animals compete with conspecifics for myriad resources, including food, mates, and status, and where rivals grant the decision maker little time for deep thought, protracted information search, or complex calculations. Yet, the social world also encompasses domains where social animals such as humans can learn from one another and can forge alliances with one another to boost their chances of success. According to the book's thesis, the undeniable complexity of the social world does not dictate cognitive complexity as many scholars of rationality argue. Rather, it entails circumstances that render optimization impossible or computationally arduous: intractability, the existence of incommensurable considerations, and competing goals. With optimization beyond reach, less can be more. That is, heuristics--simple strategies for making decisions when time is pressing and careful deliberation an unaffordable luxury--become indispensible mental tools. As accurate as or even more accurate than complex methods when used in the appropriate social environments, these heuristics are good descriptive models of how people make many decisions and inferences, but their impressive performance also poses a normative challenge for optimization models. In short, the Homo socialis may prove to be a Homo heuristicus whose intelligence reflects ecological rather than logical rationality.

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Rare species have restricted geographic ranges, habitat specialization, and/or small population sizes. Datasets on rare species distribution usually have few observations, limited spatial accuracy and lack of valid absences; conversely they provide comprehensive views of species distributions allowing to realistically capture most of their realized environmental niche. Rare species are the most in need of predictive distribution modelling but also the most difficult to model. We refer to this contrast as the "rare species modelling paradox" and propose as a solution developing modelling approaches that deal with a sufficiently large set of predictors, ensuring that statistical models aren't overfitted. Our novel approach fulfils this condition by fitting a large number of bivariate models and averaging them with a weighted ensemble approach. We further propose that this ensemble forecasting is conducted within a hierarchic multi-scale framework. We present two ensemble models for a test species, one at regional and one at local scale, each based on the combination of 630 models. In both cases, we obtained excellent spatial projections, unusual when modelling rare species. Model results highlight, from a statistically sound approach, the effects of multiple drivers in a same modelling framework and at two distinct scales. From this added information, regional models can support accurate forecasts of range dynamics under climate change scenarios, whereas local models allow the assessment of isolated or synergistic impacts of changes in multiple predictors. This novel framework provides a baseline for adaptive conservation, management and monitoring of rare species at distinct spatial and temporal scales.

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This dissertation focuses on the strategies consumers use when making purchase decisions. It is organized in two main parts, one centering on descriptive and the other on applied decision making research. In the first part, a new process tracing tool called InterActive Process Tracing (IAPT) is pre- sented, which I developed to investigate the nature of consumers' decision strategies. This tool is a combination of several process tracing techniques, namely Active Information Search, Mouselab, and retrospective verbal protocol. To validate IAPT, two experiments on mobile phone purchase de- cisions were conducted where participants first repeatedly chose a mobile phone and then were asked to formalize their decision strategy so that it could be used to make choices for them. The choices made by the identified strategies correctly predicted the observed choices in 73% (Experiment 1) and 67% (Experiment 2) of the cases. Moreover, in Experiment 2, Mouselab and eye tracking were directly compared with respect to their impact on information search and strategy description. Only minor differences were found between these two methods. I conclude that IAPT is a useful research tool to identify choice strategies, and that using eye tracking technology did not increase its validity beyond that gained with Mouselab. In the second part, a prototype of a decision aid is introduced that was developed building in particular on the knowledge about consumers' decision strategies gained in Part I. This decision aid, which is called the InterActive Choice Aid (IACA), systematically assists consumers in their purchase decisions. To evaluate the prototype regarding its perceived utility, an experiment was conducted where IACA was compared to two other prototypes that were based on real-world consumer decision aids. All three prototypes differed in the number and type of tools they provided to facilitate the process of choosing, ranging from low (Amazon) to medium (Sunrise/dpreview) to high functionality (IACA). Overall, participants slightly preferred the prototype of medium functionality and this prototype was also rated best on the dimensions of understandability and ease of use. IACA was rated best regarding the two dimensions of ease of elimination and ease of comparison of alternatives. Moreover, participants choices were more in line with the normatively oriented weighted additive strategy when they used IACA than when they used the medium functionality prototype. The low functionality prototype was the least preferred overall. It is concluded that consumers can and will benefit from highly functional decision aids like IACA, but only when these systems are easy to understand and to use.

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1 6 STRUCTURE OF THIS THESIS -Chapter I presents the motivations of this dissertation by illustrating two gaps in the current body of knowledge that are worth filling, describes the research problem addressed by this thesis and presents the research methodology used to achieve this goal. -Chapter 2 shows a review of the existing literature showing that environment analysis is a vital strategic task, that it shall be supported by adapted information systems, and that there is thus a need for developing a conceptual model of the environment that provides a reference framework for better integrating the various existing methods and a more formal definition of the various aspect to support the development of suitable tools. -Chapter 3 proposes a conceptual model that specifies the various enviromnental aspects that are relevant for strategic decision making, how they relate to each other, and ,defines them in a more formal way that is more suited for information systems development. -Chapter 4 is dedicated to the evaluation of the proposed model on the basis of its application to a concrete environment to evaluate its suitability to describe the current conditions and potential evolution of a real environment and get an idea of its usefulness. -Chapter 5 goes a step further by assembling a toolbox describing a set of methods that can be used to analyze the various environmental aspects put forward by the model and by providing more detailed specifications for a number of them to show how our model can be used to facilitate their implementation as software tools. -Chapter 6 describes a prototype of a strategic decision support tool that allow the analysis of some of the aspects of the environment that are not well supported by existing tools and namely to analyze the relationship between multiple actors and issues. The usefulness of this prototype is evaluated on the basis of its application to a concrete environment. -Chapter 7 finally concludes this thesis by making a summary of its various contributions and by proposing further interesting research directions.

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Internet is increasingly used as a source of information on health issues and is probably a major source of patients' empowerment. This process is however limited by the frequently poor quality of web-based health information designed for consumers. A better diffusion of information about criteria defining the quality of the content of websites, and about useful methods designed for searching such needed information, could be particularly useful to patients and their relatives. A brief, six-items DISCERN version, characterized by a high specificity for detecting websites with good or very good content quality was recently developed. This tool could facilitate the identification of high-quality information on the web by patients and may improve the empowerment process initiated by the development of the health-related web.

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Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

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Classical treatments of problems of sequential mate choice assume that the distribution of the quality of potential mates is known a priori. This assumption, made for analytical purposes, may seem unrealistic, opposing empirical data as well as evolutionary arguments. Using stochastic dynamic programming, we develop a model that includes the possibility for searching individuals to learn about the distribution and in particular to update mean and variance during the search. In a constant environment, a priori knowledge of the parameter values brings strong benefits in both time needed to make a decision and average value of mate obtained. Knowing the variance yields more benefits than knowing the mean, and benefits increase with variance. However, the costs of learning become progressively lower as more time is available for choice. When parameter values differ between demes and/or searching periods, a strategy relying on fixed a priori information might lead to erroneous decisions, which confers advantages on the learning strategy. However, time for choice plays an important role as well: if a decision must be made rapidly, a fixed strategy may do better even when the fixed image does not coincide with the local parameter values. These results help in delineating the ecological-behavior context in which learning strategies may spread.

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Among the largest resources for biological sequence data is the large amount of expressed sequence tags (ESTs) available in public and proprietary databases. ESTs provide information on transcripts but for technical reasons they often contain sequencing errors. Therefore, when analyzing EST sequences computationally, such errors must be taken into account. Earlier attempts to model error prone coding regions have shown good performance in detecting and predicting these while correcting sequencing errors using codon usage frequencies. In the research presented here, we improve the detection of translation start and stop sites by integrating a more complex mRNA model with codon usage bias based error correction into one hidden Markov model (HMM), thus generalizing this error correction approach to more complex HMMs. We show that our method maintains the performance in detecting coding sequences.

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In traditional criminal investigation, uncertainties are often dealt with using a combination of common sense, practical considerations and experience, but rarely with tailored statistical models. For example, in some countries, in order to search for a given profile in the national DNA database, it must have allelic information for six or more of the ten SGM Plus loci for a simple trace. If the profile does not have this amount of information then it cannot be searched in the national DNA database (NDNAD). This requirement (of a result at six or more loci) is not based on a statistical approach, but rather on the feeling that six or more would be sufficient. A statistical approach, however, could be more rigorous and objective and would take into consideration factors such as the probability of adventitious matches relative to the actual database size and/or investigator's requirements in a sensible way. Therefore, this research was undertaken to establish scientific foundations pertaining to the use of partial SGM Plus loci profiles (or similar) for investigation.

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Summary: Lipophilicity plays an important role in the determination and the comprehension of the pharmacokinetic behavior of drugs. It is usually expressed by the partition coefficient (log P) in the n-octanol/water system. The use of an additional solvent system (1,2-dichlorethane/water) is necessary to obtain complementary information, as the log Poct values alone are not sufficient to explain ail biological properties. The aim of this thesis is to develop tools allowing to predict lipophilicity of new drugs and to analyze the information yielded by those log P values. Part I presents the development of theoretical models used to predict lipophilicity. Chapter 2 shows the necessity to extend the existing solvatochromic analyses in order to predict correctly the lipophilicity of new and complex neutral compounds. In Chapter 3, solvatochromic analyses are used to develop a model for the prediction of the lipophilicity of ions. A global model was obtained allowing to estimate the lipophilicity of neutral, anionic and cationic solutes. Part II presents the detailed study of two physicochemical filters. Chapter 4 shows that the Discovery RP Amide C16 stationary phase allows to estimate lipophilicity of the neutral form of basic and acidic solutes, except of lipophilic acidic solutes. Those solutes present additional interactions with this particular stationary phase. In Chapter 5, 4 different IANI stationary phases are investigated. For neutral solutes, linear data are obtained whatever the IANI column used. For the ionized solutes, their retention is due to a balance of electrostatic and hydrophobie interactions. Thus no discrimination is observed between different series of solutes bearing the same charge, from one column to an other. Part III presents two examples illustrating the information obtained thanks to Structure-Properties Relationships (SPR). Comparing graphically lipophilicity values obtained in two different solvent systems allows to reveal the presence of intramolecular effects .such as internai H-bond (Chapter 6). SPR is used to study the partitioning of ionizable groups encountered in Medicinal Chemistry (Chapter7). Résumé La lipophilie joue un .rôle important dans la détermination et la compréhension du comportement pharmacocinétique des médicaments. Elle est généralement exprimée par le coefficient de partage (log P) d'un composé dans le système de solvants n-octanol/eau. L'utilisation d'un deuxième système de solvants (1,2-dichloroéthane/eau) s'est avérée nécessaire afin d'obtenir des informations complémentaires, les valeurs de log Poct seules n'étant pas suffisantes pour expliquer toutes les propriétés biologiques. Le but de cette thèse est de développer des outils permettant de prédire la lipophilie de nouveaux candidats médicaments et d'analyser l'information fournie par les valeurs de log P. La Partie I présente le développement de modèles théoriques utilisés pour prédire la lipophilie. Le chapitre 2 montre la nécessité de mettre à jour les analyses solvatochromiques existantes mais inadaptées à la prédiction de la lipophilie de nouveaux composés neutres. Dans le chapitre 3, la même méthodologie des analyses solvatochromiques est utilisée pour développer un modèle permettant de prédire la lipophilie des ions. Le modèle global obtenu permet la prédiction de la lipophilie de composés neutres, anioniques et cationiques. La Partie II présente l'étude approfondie de deux filtres physicochimiques. Le Chapitre 4 montre que la phase stationnaire Discovery RP Amide C16 permet la détermination de la lipophilie de la forme neutre de composés basiques et acides, à l'exception des acides très lipophiles. Ces derniers présentent des interactions supplémentaires avec cette phase stationnaire. Dans le Chapitre 5, 4 phases stationnaires IAM sont étudiées. Pour les composés neutres étudiés, des valeurs de rétention linéaires sont obtenues, quelque que soit la colonne IAM utilisée. Pour les composés ionisables, leur rétention est due à une balance entre des interactions électrostatiques et hydrophobes. Donc aucune discrimination n'est observée entre les différentes séries de composés portant la même charge d'une colonne à l'autre. La Partie III présente deux exemples illustrant les informations obtenues par l'utilisation des relations structures-propriétés. Comparer graphiquement la lipophilie mesurée dans deux différents systèmes de solvants permet de mettre en évidence la présence d'effets intramoléculaires tels que les liaisons hydrogène intramoléculaires (Chapitre 6). Cette approche des relations structures-propriétés est aussi appliquée à l'étude du partage de fonctions ionisables rencontrées en Chimie Thérapeutique (Chapitre 7) Résumé large public Pour exercer son effet thérapeutique, un médicament doit atteindre son site d'action en quantité suffisante. La quantité effective de médicament atteignant le site d'action dépend du nombre d'interactions entre le médicament et de nombreux constituants de l'organisme comme, par exemple, les enzymes du métabolisme ou les membranes biologiques. Le passage du médicament à travers ces membranes, appelé perméation, est un paramètre important à optimiser pour développer des médicaments plus puissants. La lipophilie joue un rôle clé dans la compréhension de la perméation passive des médicaments. La lipophilie est généralement exprimée par le coefficient de partage (log P) dans le système de solvants (non miscibles) n-octanol/eau. Les valeurs de log Poct seules se sont avérées insuffisantes pour expliquer la perméation à travers toutes les différentes membranes biologiques du corps humain. L'utilisation d'un système de solvants additionnel (le système 1,2-dichloroéthane/eau) a permis d'obtenir les informations complémentaires indispensables à une bonne compréhension du processus de perméation. Un grand nombre d'outils expérimentaux et théoriques sont à disposition pour étudier la lipophilie. Ce travail de thèse se focalise principalement sur le développement ou l'amélioration de certains de ces outils pour permettre leur application à un champ plus large de composés. Voici une brève description de deux de ces outils: 1)La factorisation de la lipophilie en fonction de certaines propriétés structurelles (telle que le volume) propres aux composés permet de développer des modèles théoriques utilisables pour la prédiction de la lipophilie de nouveaux composés ou médicaments. Cette approche est appliquée à l'analyse de la lipophilie de composés neutres ainsi qu'à la lipophilie de composés chargés. 2)La chromatographie liquide à haute pression sur phase inverse (RP-HPLC) est une méthode couramment utilisée pour la détermination expérimentale des valeurs de log Poct.

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The objective of this work is to present a multitechnique approach to define the geometry, the kinematics, and the failure mechanism of a retrogressive large landslide (upper part of the La Valette landslide, South French Alps) by the combination of airborne and terrestrial laser scanning data and ground-based seismic tomography data. The advantage of combining different methods is to constrain the geometrical and failure mechanism models by integrating different sources of information. Because of an important point density at the ground surface (4. 1 points m?2), a small laser footprint (0.09 m) and an accurate three-dimensional positioning (0.07 m), airborne laser scanning data are adapted as a source of information to analyze morphological structures at the surface. Seismic tomography surveys (P-wave and S-wave velocities) may highlight the presence of low-seismic-velocity zones that characterize the presence of dense fracture networks at the subsurface. The surface displacements measured from the terrestrial laser scanning data over a period of 2 years (May 2008?May 2010) allow one to quantify the landslide activity at the direct vicinity of the identified discontinuities. An important subsidence of the crown area with an average subsidence rate of 3.07 m?year?1 is determined. The displacement directions indicate that the retrogression is controlled structurally by the preexisting discontinuities. A conceptual structural model is proposed to explain the failure mechanism and the retrogressive evolution of the main scarp. Uphill, the crown area is affected by planar sliding included in a deeper wedge failure system constrained by two preexisting fractures. Downhill, the landslide body acts as a buttress for the upper part. Consequently, the progression of the landslide body downhill allows the development of dip-slope failures, and coherent blocks start sliding along planar discontinuities. The volume of the failed mass in the crown area is estimated at 500,000 m3 with the sloping local base level method.