The study investigates the depression in a group 55 adults (14 women and 41 men) who live with VJH, between 18 and 58 years, oflow and medium low socioeconomic leve! which attend public health centers, NGO and mutual support groups (MSG) of Lima. The Beck Depression Inventory was used to study the level of depression, as well as the five factors found in this population.The descriptive results were correlated with the following demographic variables: age,sex, time of diagnosis, the presence or absence of symptoms associated to VIH, the participationor not in a MSG, sexual orientation and sex. Results indicated that depression varies depending on whether the person belongs or not to a MSG, sex and sexual orientation. / El estudio investiga la depresión en un grupo 55 adultos (14 mujeres y 41 hombres) que viven con VIH, entre 18 y 58 años, de nivel socio económico bajo y medio bajo que acuden a centros de salud estatales, ONG y grupos de ayuda mutua (GAM) de Lima. Se uso el Inventario de Depresión de Beck para estudiar el nivel de depresión. así como los cinco factores encontrados en esta población. Se correlacionaron los resultados descriptivos con las siguientes variables demográficas: edad, sexo, tiempo de diagnóstico, presencia o no de síntomas asociados al VIH, participación o no en un GAM, orientación sexual y sexo. Los resultados indicaron que la depresión varía según la persona pertenezca o no a un GAM, el sexo y la orientación sexual.

Commercial pelagic longline fishers within the U.S. Atlantic, Gulf of Mexico, and Caribbean are required to report all fishing interactions per each gear deployment to NOAA’s Vessel Logbook Program of the Southeast Fisheries Science Center to quantify bycatch, increase conservation efforts, and avoid jeopardizing the existence of vulnerable species listed under the Endangered Species Act (ESA). To provide additional accuracy, the Pelagic Observer Program (POP) of the SEFSC deploys professionally trained observers on longline vessels to produce a statistically reliable subset of longline fisheries data. A comparison of self-reported (“unobserved”) datasets versus observer-collected (“observed”) datasets showed a general consistency for most target species but non-reporting or under-reporting for a number of bycatch species and “lesser-valued” target species. These discrepancies between catch compositions and abundancies regarding targeted species, species of bycatch concern, and species of minimum economic value can provide insight into increased fisheries regulations, stricter requirements, or additional observer coverage.

This thesis examines what game designs cause players to exhibit communication, cooperation and prosocial behavior towards each other in cooperative action games. This study used qualitative research methods to analyze a cooperative action game called Warhammer: Vermintide 2 as a case study. The gathering of data is done through Stimulated recall. The data gathered from the analysis provides information about their behaviors and how players communicate with each other. The results indicate that players' communication, cooperation, and prosocial behavior increased during threatening situations and when aid is required by the players. Players' expectations of others changed depending on their level of experience in the game, and on the console.

No description available.

Cette recherche aborde la médication psychiatrique à partir du point de vue des usagers. Des entrevues en profondeur ont été réalisées auprès de dix personnes utilisatrices en provenance d’une ressource communautaire et alternative en santé mentale. Les répondants éprouvent ou ont éprouvé des problèmes importants de santé mentale. La majorité des usagers de notre échantillon consomme des neuroleptiques. Les participants sélectionnés ont cheminé avec l’approche de la gestion autonome de la médication en santé mentale (GAM). La GAM constitue un terrain fertile, car l’approche favorise la réflexion critique, la diversité de pratiques autour de la médication psychotrope. Un état des connaissances portant sur l’expérience subjective de la médication est présenté. Les effets de la médication sur les personnes et leur contexte de vie ainsi que les aspects symboliques ont été analysés. Parmi les effets majeurs de la médication, on compte : l’effet de « gel », la grande fatigue, les difficultés d’attribution, le désir d’arrêt et les effets paradoxaux. La médication peut avoir des effets positifs ou négatifs sur l’entourage, le travail, les études ou autres implications sociales. Le rapport des usagers relatif à la médication a évolué vers un usage planifié, modulé et moindre. À cet effet, les dix usagers sont passés d’une phase de « novice » à une « d’expert ». Les résultats de cette recherche indiquent que la notion d’observance au traitement doit être revisitée et la notion d’efficacité élargie. Cette étude qualitative démontre que les versants « intérieurs » de la médication, l’expérience subjective et l’intersubjectif apportent une perspective plutôt rare, mais riche, du médicament en tant qu’objet social. / This research looks at psychiatric medication from the perspective of service users. In-depth interviews were conducted with 10 service users from a community-based, alternative mental health resource. The respondents experience or have experienced serious mental health problems. The majority of service users in our sample take neuroleptics. Selected participants followed the mental-health approach known as GAM: Gaining Autonomy & Medication Management. GAM provides a perfect ground, since this approach encourages critical thinking and promotes diverse practices around psychotropic medication. Current knowledge around the subjective experience of medication is presented. The effects of medication on people and their life contexts are analyzed, as well as their symbolic aspects. Among the main effects of medication are: the “anaesthetizing” effect, intense fatigue, difficulties of attribution, the desire to quit and paradoxical effects. Medication can have positive or negative effects on one’s circle of family and friends, work, studies or other social commitments. The relationship between service users and their medication has evolved toward a planned, adapted and reduced use. In this sense, the 10 service users went from a “novice” phase to that of “expert”. Results from this research show that the notion of treatment compliance must be revisited, and the concept of efficiency, broadened. This research shows that the “interior” dimensions of medication, the subjective experience and intersubjectivity provide rare and rich insights into medication as a social object.

Cette recherche aborde la médication psychiatrique à partir du point de vue des usagers. Des entrevues en profondeur ont été réalisées auprès de dix personnes utilisatrices en provenance d’une ressource communautaire et alternative en santé mentale. Les répondants éprouvent ou ont éprouvé des problèmes importants de santé mentale. La majorité des usagers de notre échantillon consomme des neuroleptiques. Les participants sélectionnés ont cheminé avec l’approche de la gestion autonome de la médication en santé mentale (GAM). La GAM constitue un terrain fertile, car l’approche favorise la réflexion critique, la diversité de pratiques autour de la médication psychotrope. Un état des connaissances portant sur l’expérience subjective de la médication est présenté. Les effets de la médication sur les personnes et leur contexte de vie ainsi que les aspects symboliques ont été analysés. Parmi les effets majeurs de la médication, on compte : l’effet de « gel », la grande fatigue, les difficultés d’attribution, le désir d’arrêt et les effets paradoxaux. La médication peut avoir des effets positifs ou négatifs sur l’entourage, le travail, les études ou autres implications sociales. Le rapport des usagers relatif à la médication a évolué vers un usage planifié, modulé et moindre. À cet effet, les dix usagers sont passés d’une phase de « novice » à une « d’expert ». Les résultats de cette recherche indiquent que la notion d’observance au traitement doit être revisitée et la notion d’efficacité élargie. Cette étude qualitative démontre que les versants « intérieurs » de la médication, l’expérience subjective et l’intersubjectif apportent une perspective plutôt rare, mais riche, du médicament en tant qu’objet social. / This research looks at psychiatric medication from the perspective of service users. In-depth interviews were conducted with 10 service users from a community-based, alternative mental health resource. The respondents experience or have experienced serious mental health problems. The majority of service users in our sample take neuroleptics. Selected participants followed the mental-health approach known as GAM: Gaining Autonomy & Medication Management. GAM provides a perfect ground, since this approach encourages critical thinking and promotes diverse practices around psychotropic medication. Current knowledge around the subjective experience of medication is presented. The effects of medication on people and their life contexts are analyzed, as well as their symbolic aspects. Among the main effects of medication are: the “anaesthetizing” effect, intense fatigue, difficulties of attribution, the desire to quit and paradoxical effects. Medication can have positive or negative effects on one’s circle of family and friends, work, studies or other social commitments. The relationship between service users and their medication has evolved toward a planned, adapted and reduced use. In this sense, the 10 service users went from a “novice” phase to that of “expert”. Results from this research show that the notion of treatment compliance must be revisited, and the concept of efficiency, broadened. This research shows that the “interior” dimensions of medication, the subjective experience and intersubjectivity provide rare and rich insights into medication as a social object.

隨著電子商務近年的蓬勃發展，許多形形色色的創新服務應運而生。本研究針對具指標性的線上餐飲訂位平台---EZTable(簡單桌)進行分析，對於EZTable而言，前來訂位的客戶是十分重要的，因為高客戶忠誠度能為其帶來更多市佔率。因此，本研究將會針對以下兩點問題進行研究分析：(1)為了能夠準確預測顧客回訪率，那些因素與客戶回訪率是高關聯性的？如訂位者、餐廳、地理位置等資訊。(2)應如何建構並驗證高準確度的預測模型？根據以上問題，本研究使用廣義加成模型(GAM)、決策樹(decision tree)、套袋抽樣(bagging)、隨機森林(random forest)等模型訓練方法，搭配EZTable大量的訂位資料，建構不同的預測模型來預測客戶回訪率。以EZTable的資料而言，本研究發現比起訓練模型的方法，模型變數的選擇更明顯影響了預測表現，而關於訂位本身的資訊，如訂位狀態，能夠大幅度提升預測準確度。這些發現能夠幫助如EZTable等服務提供者，了解哪些變數對於顧客忠誠度是相當重要的；再者，公司能夠透過這些資訊，為有較高回訪率的會員量身打造適合的促銷活動。透過將行銷資源集中在特定的客戶上，這些提供服務公司的行銷成本也能夠因此減少。 / Electronic commerce still grows rapidly in the recent years and innovative services are introduced in the recent years accordingly. This research analyzes a representative online reservation service provider – EZTable. Loyalty of customer is crucial because EZTable can obtain more market share with high customer loyalty. Therefore, we expect to answer the following research questions: (1) What are relevant and useful consumer, restaurant, and demographic factors to predict customer retention? (2) How do we develop and determine effective predictive models? We apply generalized additive model, decision tree, bagging, and random forest, to a large volume of operational data from EZTable and develop a set of predictive models. Instead of model complexity, identifying critical variables from the research context determines predictive performance. Transaction-dependent factors could substantially enhance predictive performance. Our findings enable companies like EZTable to understand what predictors are critical to customers’ loyalty. Further, the company can design effective promotions for customers with higher return probability. Our modeling effort could help those service providers reduce advertising cost by allocating limited resources to customers with higher probability to place orders again.

Background: Great strides have been made in combating malaria, however, the indicators in sub Saharan Africa still do not show promise for elimination in the near future as malaria infections still result in high morbidity and mortality among children. The abundance of the malaria-transmitting mosquito vectors in these regions are driven by climate suitability. In order to achieve malaria elimination by 2030, strengthening of surveillance systems have been advocated. Based on malaria surveillance and climate monitoring, forecasting models may be developed for early warnings. Therefore, in this thesis, we strived to illustrate the use malaria surveillance and climate data for policy and decision making by assessing the association between weather variability (from ground and remote sensing sources) and malaria mortality, and by building malaria admission forecasting models. We further propose an economic framework for integrating forecasts into operational surveillance system for evidence based decisionmaking and resource allocation.  Methods: The studies were based in Asembo, Gem and Karemo areas of the KEMRI/CDC Health and Demographic Surveillance System in Western Kenya. Lagged association of rainfall and temperature with malaria mortality was modeled using general additive models, while distributed lag non-linear models were used to explore relationship between remote sensing variables, land surface temperature(LST), normalized difference vegetation index(NDVI) and rainfall on weekly malaria mortality. General additive models, with and without boosting, were used to develop malaria admissions forecasting models for lead times one to three months. We developed a framework for incorporating forecast output into economic evaluation of response strategies at different lead times including uncertainties. The forecast output could either be an alert based on a threshold, or absolute predicted cases. In both situations, interventions at each lead time could be evaluated by the derived net benefit function and uncertainty incorporated by simulation.  Results: We found that the environmental factors correlated with malaria mortality with varying latencies. In the first paper, where we used ground weather data, the effect of mean temperature was significant from lag of 9 weeks, with risks higher for mean temperatures above 250C. The effect of cumulative precipitation was delayed and began from 5 weeks. Weekly total rainfall of more than 120 mm resulted in increased risk for mortality. In the second paper, using remotely sensed data, the effect of precipitation was consistent in the three areas, with increasing effect with weekly total rainfall of over 40 mm, and then declined at 80 mm of weekly rainfall. NDVI below 0.4 increased the risk of malaria mortality, while day LST above 350C increased the risk of malaria mortality with shorter lags for high LST weeks. The lag effect of precipitation was more delayed for precipitation values below 20 mm starting at week 5 while shorter lag effect for higher precipitation weeks. The effect of higher NDVI values above 0.4 were more delayed and protective while shorter lag effect for NDVI below 0.4. For all the lead times, in the malaria admissions forecasting modelling in the third paper, the boosted regression models provided better prediction accuracy. The economic framework in the fourth paper presented a probability function of the net benefit of response measures, where the best response at particular lead time corresponded to the one with the highest probability, and absolute value, of a net benefit surplus.  Conclusion: We have shown that lagged relationship between environmental variables and malaria health outcomes follow the expected biological mechanism, where presentation of cases follow the onset of specific weather conditions and climate variability. This relationship guided the development of predictive models showcased with the malaria admissions model. Further, we developed an economic framework connecting the forecasts to response measures in situations with considerable uncertainties. Thus, the thesis work has contributed to several important components of early warning systems including risk assessment; utilizing surveillance data for prediction; and a method to identifying cost-effective response strategies. We recommend economic evaluation becomes standard in implementation of early warning system to guide long-term sustainability of such health protection programs.

現行公告土地現值的評估，係採用人工的傳統方法，估價結果誤差甚大且過於主觀，無法達到大量估價客觀、快速、精確之目標。本文首先利用土地經濟理論的分析，探討土地市場價值、交易價格、評估價值之間的關係，釐清常見的混淆概念。並藉由估價比率研究，討論公告現值與市價差距的檢定模型，針對台南市的實際資料進行統計檢定，結果發現平均估價比率落於46.74﹪~48.52﹪之區間，並存在輕微的垂直不公平。 為改進現行公告現值不夠準確之缺失，本研究基於都市經濟理論與估價先驗訊息之基礎，利用特徵價格法與可加性模型建立大量估價模式。實證結果發現，影響台南市地價之因素，以區位、臨街關係、路寬、使用分區最為重要。在部份年度中，亦證實存在基地面積規模不經濟（plattage）現象。 傳統特徵價格法必須預設函數型態，若函數設定錯誤則將使參數估計產生偏誤。可加性模型結合無母數迴歸與母數迴歸之優點，不須預設函數型態、估計結果易於解釋且維持母數迴歸之收斂速度。其可經由修勻法配適出更客觀的函數關係，無論在樣本內與樣本外之估計均較特徵價格法為佳。 研究結果發現，本文所提出的二種估價模式確可達到快速精確的目標，使估價比率接近１，比目前評估效率提高一倍；在公平性方面雖無改善，但亦無嚴重之垂直不公平。其中可加性模型又較特徵價格法為佳，在電腦技術快速進步的今天，應用至大量估價的可行性大為提高，值得後續進一步深入研究。 / The present Announced Land Current Value （ALCV）was evaluated by traditional appraisal method that may result in large errors. Comparing to mass assessment approaches, it is hard to be objective, quick and precise. This research begins with the analysis based on land economic theory to discuss the relation among the market value, sale price and assessed value of land in order to clarify some confusing concepts. Through assessment-sale price ratio study, we analyze the difference between ALCV and sale price, and then use the actual data of Tainan City for empirical study. The results show that the average a-s ratio falls between 46.74%~48.52% with slight vertical inequity. To improve the lack of preciseness and objectivity of the present ALCV, this research uses hedonic price theory and Generalized Additive Model（GAM）based on urban economic theory and appraisal priori information. The results show that location, relations with adjacent streets, road width and zoning are the most influencing factors of land price in Tainan City. During some years, the phenomenon of plattage effect also exits. The function form must be set beforehand in the traditional hedonic pricing, meanwhile parameters bias will occur if the pre-determined function form were wrong. GAM has the advantages of nonparametric regression and parametric regression. The function form needs not to be pre-determined, the empirical results are easy to interpret, and the speed of variable convergence can be maintained. More precise functional relations can also be smoothed by GAM. It is superior to the traditional hedonic price in the sample and out of the sample prediction alike. The results of empirical study show that both of two models can reach the goal of rapidity and preciseness and make the a-s ratio toward 1. As to the equity, although they are not improved very much, the models don't bring serious vertical inequity. However, GAM is better than hedonic pricing when compared to each other. Due to the great progress of computer technology, the application of GAM to mass assessment can be increased greatly and is worthy continuing further study.

In this thesis Generalized Additive Neural Networks (GANNs) are studied in the context of predictive Data Mining. A GANN is a novel neural network implementation of a Generalized Additive Model. Originally GANNs were constructed interactively by considering partial residual plots. This methodology involves subjective human judgment, is time consuming, and can result in suboptimal results. The newly developed automated construction algorithm solves these difficulties by performing model selection based on an objective model selection criterion. Partial residual plots are only utilized after the best model is found to gain insight into the relationships between inputs and the target. Models are organized in a search tree with a greedy search procedure that identifies good models in a relatively short time. The automated construction algorithm, implemented in the powerful SAS® language, is nontrivial, effective, and comparable to other model selection methodologies found in the literature. This implementation, which is called AutoGANN, has a simple, intuitive, and user-friendly interface. The AutoGANN system is further extended with an approximation to Bayesian Model Averaging. This technique accounts for uncertainty about the variables that must be included in the model and uncertainty about the model structure. Model averaging utilizes in-sample model selection criteria and creates a combined model with better predictive ability than using any single model. In the field of Credit Scoring, the standard theory of scorecard building is not tampered with, but a pre-processing step is introduced to arrive at a more accurate scorecard that discriminates better between good and bad applicants. The pre-processing step exploits GANN models to achieve significant reductions in marginal and cumulative bad rates. The time it takes to develop a scorecard may be reduced by utilizing the automated construction algorithm. / Thesis (Ph.D. (Computer Science))--North-West University, Potchefstroom Campus, 2006.