1997年爆發的亞洲金融危機起因之一為金融機構信用過度擴充，隨著企業紛紛倒閉，金融機構的逾放比迅速攀升，因此，提高放款的質與量，便成了目前各金融機構經營的首重目標。為降低逾放比率、提高放款量、爭取放款時效、減少審核時間，使用自動化的審核制度是有必要的，而客觀科學化的評分方法更能使徵信資料得到迅速的整理與分析，以利放款決策的有效釐定。 本研究以國內某金融機構為研究對象，採用Logistic Regression Model為信用評等模式，針對其目前所使用之個人擔保放款的信用評分表表列變數和表外變數，深入探討並從中找出影響授信成敗之顯著變數，建立最適之信用評等模式。

<p>The aim of the thesis has been to study methods to minimize the slosh when moving liquid-filled packages in packaging machines. An automatic method for generation of the movement of a package in a packaging machine is of growing importance. The main reason is that reduced slosh leads to increased production rate. Progress within measurement technology creates possibilities for new solutions. One purpose has been to find methods and equipment to detect the height of the wave, perhaps at several places or alternatively the entire liquid surface shape. When suitable equipment for detection of the wave movements was found, collected measurements were analyzed and criteria for describing improvements of the slosh properties have been formulated. </p><p>Initially a sensor specification was written in order to simplify the search for suitable equipment. Sources of information have mainly been catalogues and Internet. The search resulted in that a number of sensors were borrowed for tests. The results of the tests supported the choice of the most suitable sensor, in this case a laser sensor. The main reason is that the sensors detection ability is good compared to its price. An analysis of the sensors most important properties confirmed the choice of the laser sensor. To be able to compare waves, criteria for what is considered to be good wave properties have been formulated and evaluated. </p><p>The work has confirmed that it is difficult to find a simple and cheap solution for wave detection given that the solution should have good detection ability. It has also been difficult to formulate simple but working criteria for wave performance, and this has led to a compromise between the complexity of the criterion functions and the result of the wave score. Ideas about how an automatic method, based on the chosen sensor and the criterion functions, can be implemented, have been introduced. During the work, some interesting discoveries have been made. These have led to better understanding of how some parameters should be chosen, to better understanding of wave movements and to better choice of future work.</p>

L'objectif de ce travail est de développer et d'évaluer des approches méthodologiques pour la prédiction de séquences cis-régulatrices. Ces approches ont été intégrées dans la suite logicielle RSAT (Regulatory Sequences Analysis Tools). Ces séquences jouent un rôle important dans la régulation de l'expression des gènes. Cette régulation, au niveau transcriptionnel, s'effectue à travers la reconnaissance spécifique entre les facteurs de transcription et leurs sites de fixation (TFBS) au niveau de l'ADN. Nous avons développé et évalué une série d'outils bioinformatiques qui utilisent les matrices position-poids pour prédire les TFBS ainsi que les modules cis-régulateurs (CRM). Nos outils présentent l'avantage d'intégrer les différentes approches déjà proposées par d'autres auteurs tout en proposant des fonctionnalités innovantes. Nous proposons notamment une nouvelle approche pour la prédiction de CRM basé sur la détection de régions significativement enrichies en TFBS. Nous les avons appelés les CRER (pour Cis-Regulatory Elements Enriched Regions). Un autre aspect essentiel de toute notre approche réside dans le fait que nous proposons des mesures statistiques rigoureuses pour estimer théoriquement et empiriquement le risque associé aux différentes prédictions. Les méthodes de prédictions de séquences cis-regulatrices prédisent en effet un taux de fausses prédictions généralement élevé. Nous intégrons un calcul des P-valeurs associées à toutes les prédictions. Nous proposons ainsi une mesure fiable de la probabilité de faux positifs. Nous avons appliqué nos outils pour une évaluation systématique de l'effet du modèle de background sur la précision des prédictions à partir de la base de données de TRANSFAC. Nos résultats suggèrent une grande variabilité pour les modèles qui optimisent la précision des prédictions. Il faut choisir le modèle de background au cas par cas selon la matrice considérée. Nous avons ensuite évalué la qualité des matrices de tous les facteurs de transcription de drosophile de la base de données ORegAnno, c'est à dire leur pouvoir de discrimination entre les TFBS et les séquences génomiques. Nous avons ainsi collecté des matrices des facteurs de transcription de drosophile de bonne qualité. A partir des matrices de drosophile que nous avons collectées, nous avons entamé une analyse préliminaire multi-genome de prédictions de TFBS et de CRM dans la région de lʼenhancer dorsocentral (DCE) du complexe achaete-scute de drosophile. Les gènes de ce complexe jouent un rôle important dans la détermination des cellules système nerveux périphérique de drosophile. Il a été prouvé expérimentalement qu'il existe un lien direct entre le phénotype du système nerveux périphérique et les séquences cis-régulateurs des gènes de ce complexe. Les outils que nous avons développés durant ce projet peuvent s'appliquer à la prédiction des séquences de régulation dans les génomes de tous les organismes.

A drug discovery project typically starts with a pharmacological hypothesis: that the modulation of a specific molecular biological mechanism would be beneficial in the treatment of the targeted disease. In a small-molecule project, the next step is to identify hits, i.e. molecules that can effect this modulation. These hits are subsequently expanded into hit series, which are optimised with respect to pharmacodynamic and pharmacokinetic properties, through medicinal chemistry. Finally, a drug candidate is clinically developed into a new drug. This thesis concerns the use of structure-based virtual screening in the hit identification phase of drug discovery. Structure-based virtual screening involves using the known 3D structure of a target protein to predict binders, through the process of docking and scoring. Docking is the prediction of potential binding poses, and scoring is the prediction of the free energy of binding from those poses. Two new methodologies, based on post-processing of scoring results, were developed and evaluated using model systems. Both methods significantly increased the enrichment of true positives. Furthermore, correlation was observed between scores and simple molecular properties, and identified as a source of false positives in structure-based virtual screening. Two target proteins, Mycobacterium tuberculosis ribose-5-phosphate isomerase, a potential drug target in tuberculosis, and Plasmodium falciparum spermidine synthase, a potential drug target in malaria, were subjected to docking and virtual screening. Docking of substrates and products of ribose-5-phosphate isomerase led to hypotheses on the role of individual residues in the active site. Additionally, virtual screening was used to predict 48 potential inhibitors, but none was confirmed as an inhibitor or binder to the target enzyme. For spermidine synthase, structure-based virtual screening was used to predict 32 potential active-site binders. Seven of these were confirmed to bind in the active site.

Controlling for the wide variability in the physical health status of geriatric populations is important as severity of illness is known to both moderate and suppress relationships examined in psychosocial research. The purpose of the present investigation was to develop a uniform, easily administered quantitative index of illness severity, composed of disease-specific scales, that was independent of psychosocial factors and appropriate for use with a geriatric population. As well, the aim was to collect preliminary data on the reliability and validity of the scale. The development of the Severity of Illness-Geriatric (SOI­G) scale involved the adaptation of a previously developed severity of illness instrument Severity of Renal Disease Scale (SORDS). <p>The present investigation involved five programmatically linked studies. Study 1 involved the determination of the items to be included on SOI-G while Study 2 defined the severity criteria for each item. In Study 3, five geriatric specialists scaled each level of each item on the same underlying threat to life scale. There was a high level of initial agreement between the raters supporting the reliability of the severity values. The final scale consisted of 32 items. <p>In Study 4, archival data was collected on 61 patients admitted to the geriatric unit of a rehabilitation hospital. The SOI-G was compared to the Cumulative Illness Rating Scale-Geriatric (CIRS-G) and a global severity rating. <p>SOI-G inter-rater reliability estimates were low (likely due to rater error) but promising. SOI-G demonstrated support for content validity, face validity, and construct validity but evidence for convergent validity was not established. SOI-G scores were sensitive to differences among patients with respect to discharge outcome. The utility of SOI-G as a moderator variable in psychosocial research with the elderly could not be explored in Study 5 due to a limited sample size. <p>It was concluded that the present investigation demonstrated the potential usefulness of SOI-G in psychosocial research with the elderly but further research is needed before definitive conclusions can be made. The SOI-G offers researchers a tool for controlling disease variability that is not measured by psychological tests but must be accounted for in research designs.

<p>Risk factors such as intrauterine and vaginal infection put pregnant women at risk for delivering preterm. Bacterial vaginosis (BV) is a polymicrobial clinical syndrome commonly diagnosed in women of reproductive age, with women of African descent with low socioeconomic status and previous preterm delivery at high risk. Although frequently isolated from healthy women,&nbsp / Gardnerella vaginalis has been most frequently associated with BV. There is limited data available on the prevalence of BV in Southern Africa / therefore, we embarked on a study to determine the&nbsp / prevalence of BV and G. vaginalis in predominantly black communities in the Western Cape, in order to establish the role of G. vaginalis in BV. Women attending various Maternity and Obstetrics&nbsp / units (MOU) in the Cape Peninsula with and without a history of pre-term delivery (PTD) were invited to participate in the study. Several factors were statistically associated with pregnancy history,&nbsp / including location of study population, parity, smoking and presence of clinical symptoms. The presence of G. vaginalis was determined by culture in 51.7% of the preterm delivery group (PTDG)&nbsp / and 44% of the full-term delivery group (FTDG) women. BV was detected in 31.13% of PTDG and 23.67% of FTDG by Gram stained analysis according to Nugent scoring criteria, with age and HIV&nbsp / status posing as risk factors. When comparing PTDG and FTDG for an association between the presence of G. vaginalis and BV, a stronger association was observed in the PTDG but it was not statistically significant. In both PTDG and FTDG, G. vaginalis was isolated significantly more often in women diagnosed with BV at 24.5% (p &lt / 0.05). Antibiogram studies revealed both Metronidazole and Clindamycin resistant strains of G. vaginalis. G. vaginalis Biotype 7 is specifically associated with BV, while Biotype 2 appears to be associated with BV in women with a history&nbsp / of PTD. Accuracy of diagnostic tools were tested and it was determined that Nugent scoring is more sensitive in diagnosing BV (76.04%), but culture for G. vaginalis is more specific (83.21%). Although this study was limited in that we were unable to follow-up pregnancy outcomes, we were able to confirm the perceived role of G. vaginalis in BV.&nbsp / </p>

The aim of the thesis has been to study methods to minimize the slosh when moving liquid-filled packages in packaging machines. An automatic method for generation of the movement of a package in a packaging machine is of growing importance. The main reason is that reduced slosh leads to increased production rate. Progress within measurement technology creates possibilities for new solutions. One purpose has been to find methods and equipment to detect the height of the wave, perhaps at several places or alternatively the entire liquid surface shape. When suitable equipment for detection of the wave movements was found, collected measurements were analyzed and criteria for describing improvements of the slosh properties have been formulated. Initially a sensor specification was written in order to simplify the search for suitable equipment. Sources of information have mainly been catalogues and Internet. The search resulted in that a number of sensors were borrowed for tests. The results of the tests supported the choice of the most suitable sensor, in this case a laser sensor. The main reason is that the sensors detection ability is good compared to its price. An analysis of the sensors most important properties confirmed the choice of the laser sensor. To be able to compare waves, criteria for what is considered to be good wave properties have been formulated and evaluated. The work has confirmed that it is difficult to find a simple and cheap solution for wave detection given that the solution should have good detection ability. It has also been difficult to formulate simple but working criteria for wave performance, and this has led to a compromise between the complexity of the criterion functions and the result of the wave score. Ideas about how an automatic method, based on the chosen sensor and the criterion functions, can be implemented, have been introduced. During the work, some interesting discoveries have been made. These have led to better understanding of how some parameters should be chosen, to better understanding of wave movements and to better choice of future work.

Fair division is the problem of dividing one or several goods among a set of agents in a way that satisfies a suitable fairness criterion. Traditionally studied in economics, philosophy, and political science, fair division has drawn a lot of attention from the multiagent systems community, since this field is strongly concerned about how a surplus (or a cost) should be divided among a group of agents. Arguably, the Shapley value is the single most important contribution to the problem of fair division. It assigns to each agent a share of the resource equal to the expected marginal contribution of that agent. Thus, it is implicitly assumed that individual marginal contributions can be objectively computed. In this thesis, we propose a game-theoretic model for sharing a joint reward when the quality of individual contributions is subjective. In detail, we consider scenarios where a group has been formed and has accomplished a task for which it is granted a reward, which must be shared among the group members. After observing the contribution of the peers in accomplishing the task, each agent is asked to provide evaluations for the others. Mainly to facilitate the sharing process, agents can also be requested to provide predictions about how their peers are evaluated. These subjective opinions are elicited and aggregated by a central, trusted entity, called the mechanism, which is also responsible for sharing the reward based exclusively on the received opinions. Besides the formal game-theoretic model for sharing rewards based on subjective opinions, we propose three different mechanisms in this thesis. Our first mechanism, the peer-evaluation mechanism, divides the reward proportionally to the evaluations received by the agents. We show that this mechanism is fair, budget-balanced, individually rational, and strategy-proof, but that it can be collusion-prone. Our second mechanism, the peer-prediction mechanism, shares the reward by considering two aspects: the evaluations received by the agents and their truth-telling scores. To compute these scores, this mechanism uses a strictly proper scoring rule. Under the assumption that agents are Bayesian decision-makers, we show that this mechanism is weakly budget-balanced, individually rational, and incentive-compatible. Further, we present approaches that guarantee the mechanism to be collusion-resistant and fair. Our last mechanism, the BTS mechanism, is the only one to elicit both evaluations and predictions from the agents. It considers the evaluations received by the agents and their truth-telling scores when sharing the reward. For computing the scores, it uses the Bayesian truth serum method, a powerful scoring method based on the surprisingly common criterion. Under the assumptions that agents are Bayesian decision-makers, and that the population of agents is sufficiently large so that a single evaluation cannot significantly affect the empirical distribution of evaluations, we show that this mechanism is incentive-compatible, budget-balanced, individually rational, and fair.

Controlling for the wide variability in the physical health status of geriatric populations is important as severity of illness is known to both moderate and suppress relationships examined in psychosocial research. The purpose of the present investigation was to develop a uniform, easily administered quantitative index of illness severity, composed of disease-specific scales, that was independent of psychosocial factors and appropriate for use with a geriatric population. As well, the aim was to collect preliminary data on the reliability and validity of the scale. The development of the Severity of Illness-Geriatric (SOI­G) scale involved the adaptation of a previously developed severity of illness instrument Severity of Renal Disease Scale (SORDS). <p>The present investigation involved five programmatically linked studies. Study 1 involved the determination of the items to be included on SOI-G while Study 2 defined the severity criteria for each item. In Study 3, five geriatric specialists scaled each level of each item on the same underlying threat to life scale. There was a high level of initial agreement between the raters supporting the reliability of the severity values. The final scale consisted of 32 items. <p>In Study 4, archival data was collected on 61 patients admitted to the geriatric unit of a rehabilitation hospital. The SOI-G was compared to the Cumulative Illness Rating Scale-Geriatric (CIRS-G) and a global severity rating. <p>SOI-G inter-rater reliability estimates were low (likely due to rater error) but promising. SOI-G demonstrated support for content validity, face validity, and construct validity but evidence for convergent validity was not established. SOI-G scores were sensitive to differences among patients with respect to discharge outcome. The utility of SOI-G as a moderator variable in psychosocial research with the elderly could not be explored in Study 5 due to a limited sample size. <p>It was concluded that the present investigation demonstrated the potential usefulness of SOI-G in psychosocial research with the elderly but further research is needed before definitive conclusions can be made. The SOI-G offers researchers a tool for controlling disease variability that is not measured by psychological tests but must be accounted for in research designs.

<p> Probability forecasts play an important role in many decision and risk analysis applications. Research and practice over the years have shown that the shift towards distributional forecasts provides a more accurate and appropriate means of capturing risk in models for these applications. This means that mathematical tools for analyzing the quality of these forecasts, may it come from experts, models or data, become important to the decision maker. In this regard, strictly proper scoring rules have been widely studied because of their ability to encourage assessors to provide truthful reports. This dissertation contributes to the scoring rule literature in two main areas of assessment - probability forecasts and quantile assessments. </p><p>In the area of probability assessment, scoring rules typically studied in the literature, and commonly used in practice, evaluate probability assessments relative to a default uniform measure. In many applications, the uniform baseline used to represent some notion of ignorance is inappropriate. In this dissertation, we generalize the power and pseudospherical family of scoring rules, two large parametric families of commonly-used scoring rules, by incorporating the notion of a non-uniform baseline distribution for both the discrete and continuous cases. With an appropriate normalization and choice of parameters, we show that these new families of scoring rules relate to various well-known divergence measures from information theory and to well-founded decision models when framed in an expected utility maximization context. </p><p>In applications where the probability space considered has an ordinal ranking between states, an important property often considered is sensitivity to distance. Scoring rules with this property provide higher scores to assessments that allocate higher probability mass to events “closer” to that which occurs based on some notion of distance. In this setting, we provide an approach that allows us to generate new sensitive to distance strictly proper scoring rules from well-known strictly proper binary scoring rules. Through the use of the weighted scoring rules, we also show that these new scores can incorporate a specified baseline distribution, in addition to being strictly proper and sensitive to distance. </p><p>In the inverse problem of quantile assessment, scoring rules have not yet been well-studied and well-developed. We examine the differences between scoring rules for probability and quantile assessments, and demonstrate why the tools that have been developed for probability assessments no longer encourage truthful reporting when used for quantile assessments. In addition, we shed light on new properties and characterizations for some of these rules that could guide decision makers trying to choosing an appropriate scoring rule. </p> / Dissertation