Depression, intertwined with sleep deprivation and self-esteem, presents a significant challenge to mental health worldwide. The research shown in this paper employs advanced statistical methodologies to unravel the complex interactions among these factors. Through log-linear homogeneous association, multinomial logistic regression, and generalized linear models, the study scrutinizes large datasets to uncover nuanced patterns and relationships. By elucidating how depression, sleep disturbances, and self-esteem intersect, the research aims to deepen understanding of mental health phenomena. The study clarifies the relationship between these variables and explores reasons for prioritizing depression research. It evaluates how statistical models, such as log-linear, multinomial logistic regression, and generalized linear models, shed light on their intricate dynamics. Findings offer insights into risk and protective factors associated with these variables, guiding tailored interventions for individuals in psychological distress. Additionally, policymakers can utilize these insights to develop comprehensive strategies promoting mental health and well-being at a societal level.

[ES] Los problemas de selección de talla y ajuste en la compra online de ropa son la causa de aproximadamente el 70% de las devoluciones. Esto se debe principalmente a la falta de estandarización del tallaje y al funcionamiento deficiente de los métodos de recomendación de talla. Actualmente, el comercio online de ropa tiene mucho potencial, sin embargo, las elevadas tasas de devolución, suponen costes relevantes en logística y gestión de stocks. En el estado del arte de esta tesis se refleja la complejidad del problema del ajuste de ropa, en el que intervienen múltiples factores tanto objetivos (tipo de tejido, patronaje, número de tallas, moda, morfotipo del usuario, medidas corporales, etc.), como subjetivos (percepción de ajuste y preferencias del usuario). Siendo el ajuste de las prendas uno de los problemas de mayor relevancia en el sector de la confección es de crucial interés avanzar en la generación de un conocimiento que permita relacionar con mayor precisión las dimensiones corporales, el ajuste de las prendas y el tallaje. El objetivo general de esta tesis consiste en establecer los fundamentos para desarrollar un sistema de recomendación del ajuste y talla de prendas de ropa a partir de medidas antropométricas del usuario y valoraciones de ajuste planteando un desarrollo metodológico que sirve de punto de partida para posteriormente escalar el proceso a cualquier tipo de prenda, estilo y sistema de tallaje de ropa. La aproximación propuesta consiste en la predicción del ajuste por zonas de la prenda a partir de medidas antropométricas del usuario y pruebas de ajuste previas utilizando el método estadístico de regresión logística multinomial. A partir de esta predicción de ajuste por zonas, y aplicando de nuevo modelos de regresión logística multinomial, se obtiene la probabilidad de ajuste de la serie de tallas de la prenda analizada. En primer lugar, se ha determinado la fiabilidad de las medidas antropométricas obtenidas a partir de escaneados 3D del cuerpo. Para desarrollar los modelos de predicción, se ha puesto a punto un método de caracterización del ajuste de ropa mediante valoración subjetiva de usurarios y expertos. Además, se han definido los conjuntos de medidas antropométricas relacionadas con el ajuste de la prenda en cada zona. El proceso de entrenamiento de los modelos de predicción de ajuste ha permitido determinar cuáles son las medidas antropométricas más relevantes para el ajuste de cada tipo de prenda, así como las zonas de ajuste que influyen en la selección de la talla. En la fase de validación, se ha demostrado que, con un porcentaje de acierto entre el 80-100%, los modelos de predicción de talla basados en probabilidades de ajuste obtenidas mediante regresión logística multinomial en zonas relevantes de la prenda, ofrecen mayor fiabilidad que los métodos actuales que solo consideran una variable corporal y sus intervalos. Finalmente, se ha propuesto un método para extrapolar los modelos individuales de predicción de talla a toda población objetivo, estimar la cuota de mercado potencial y optimizar la distribución de tallas de cada prenda. / [CA] Els problemes de selecció de talla i ajust en les compres de roba en la xarxa representen aproximadament el 70% de les devolucions. Això es degut principalment a la manca d'estandardització en les talles i al funcionament deficient dels mètodes de recomanació de talles. Actualment, el comerç de roba en la xarxa té molt potencial, no obstant això, les altes taxes de devolució comporten costos rellevants en logística i gestió d'estocs. L'estat de l'art en aquesta tesi reflecteix la complexitat del problema de l'ajust de la roba, que implica múltiples factors, tant objectius (tipus de teixit, patró, nombre de talles, tendències de moda, tipus de cos de l'usuari, mesures corporals, etc.) com subjectius (percepció de l'ajust per part de l'usuari i preferències). Ja que l'ajust de les peces de vestir és un dels problemes més importants en la indústria de la moda, és crucial avançar en la generació de coneixement que permeti establir una relació més precisa entre les dimensions del cos, l'ajust de la roba i les talles. L'objectiu general d'aquesta tesi és establir els fonaments per al desenvolupament d'un sistema de recomanació de l'ajust i la talla de peces de roba basat en les mesures antropomètriques de l'usuari. Això implica un desenvolupament metodològic que serveix com a punt de partida per a posteriorment escalar el procés a qualsevol tipus de peça de roba, estil i sistema de mides. L'aproximació proposada consistix en predir l'ajust per zones de la peça de roba basat en les mesures antropomètriques de l'usuari i proves prèvies d'ajust mitjançant el mètode estadístic de la regressió logística multinomial. A partir d'aquesta predicció d'ajust per zones, i aplicant novament models de regressió logística multinomial, s'obté la probabilitat d'ajust per a la gamma de talles de la peça de roba analitzada. S'ha determinat la fiabilitat de les mesures antropomètriques obtingudes a partir d'escaneigs 3D del cos. Per desenvolupar els models de predicció, s'ha posat a punt un mètode per caracteritzar l'ajust de la roba mitjançant avaluacions subjectives dels usuaris i experts. A més, s'han definit conjunts de mesures antropomètriques relacionades amb l'ajust de la peça a cada zona. El procés de formació dels models de predicció de l'ajust ha permès determinar les mesures antropomètriques més rellevants per a l'ajust de cada tipus de peça, així com les zones d'ajust que influeixen en la selecció de la talla. En la fase de validació, s'ha demostrat que, amb un percentatge d'encert entre el 80-100%, els models de predicció de talla basats en les probabilitats d'ajust obtingudes mitjançant la regressió logística multinomial en zones rellevants de la peça de roba ofereixen una major fiabilitat que els mètodes actuals que només consideren una variable corporal i els seus intervals. Finalment, s'ha proposat un mètode per extrapol·lar els models individuals de predicció de talla a tota la població objectiu, estimar la quota de mercat potencial i optimitzar la distribució de talles per a cada peça. / [EN] The problems of size selection and fit in online clothing purchases account for approximately 70% of returns. This is primarily due to the lack of standardization in sizing and the inefficient performance of current size recommendation methods. Currently, online clothing retail has a lot of potential; however, the high product return rates result in significant costs in logistics and stock management. The state of the art in this thesis reflects the complexity of the clothing fit problem, which involves multiple factors, both objective (fabric type, pattern, number of sizes, fashion trends, user body type, body measurements, etc.) and subjective (user's perception of fit and preferences). Since garment fit is one of the most significant issues in the fashion industry, it is crucial to advance in generating knowledge that allows for a more precise relationship between body dimensions, garment fit, and sizing. The general objective of this thesis is to establish the foundations for developing a recommendation system for clothing fit and size based on user anthropometric measurements and fit evaluations. This involves a methodological development that serves as a starting point for subsequently scaling the process to any type of garment, style, and sizing system. The proposed approach consists of predicting the fit by garment zones based on user anthropometric measurements and previous fit trials using the statistical method of multinomial logistic regression. From this prediction of fit by zones, and by once again applying multinomial logistic regression models, the probability of fit for the range of sizes of the analyzed garment is obtained. The reliability of anthropometric measurements obtained from 3D body scans has been determined. To develop the prediction models, a method for characterizing garment fit through subjective assessments by users and experts has been refined. In addition, sets of anthropometric measurements related to garment fit in each zone have been defined. The training process of the fit prediction models has enabled determining the most relevant anthropometric measurements for the fit of each type of garment, as well as the fit zones that influence size selection. In the validation phase, it has been demonstrated that, with an accuracy rate between 80-100%, size prediction models based on fit probabilities obtained through multinomial logistic regression in relevant garment zones offer greater reliability than current methods that only consider a single body variable and its intervals. Finally, a method has been proposed to extrapolate individual size prediction models to the entire target population, estimate the potential market share, and optimize the distribution of sizes for each garment. / Alemany Mut, MS. (2023). Desarrollo de modelos estadísticos de predicción del ajuste y talla de prendas de ropa a partir de la percepción y características antropométricas del usuario [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/202617

過去都市的發展與道路規劃多以汽機車為主體，對於自行車的騎乘環境相對不夠友善，而隨著近年國內自行車使用率逐年攀升，據資料指出自行車發生事故的機率也有提高的趨勢，顯示自行車於道路上之安全性考量更需重視。故本研究將針對台北市自行車肇事資料進行深入探討，找出影響肇事嚴重度之因素，進而從規劃設計面研擬降低自行車事故之改善策略。 本研究係以民國98年至102年台北市自行車事故資料為分析對象，將肇事嚴重程度分為「死亡或頭部受傷」、「人員受傷」及「未受傷」三類，同時根據文獻回顧及實務上所能取得之資料，蒐集人、路、環境等24項研究變數。首先透過統計分析了解肇事資料之特性，而後再以多項式羅吉斯迴歸模型，分別針對整體事故以及不同空間及不同事故型態之自行車肇事資料，建構自行車肇事嚴重度模型，以釐清影響自行車事故之主要因素。 研究結果顯示，道路因素中事故位置為路口及路段對於自行車事故皆有顯著影響，其中路口造成死亡或受傷之機率更高；環境因素中，因彎道或建物造成視距不良對於增加自行車事故亦有顯著影響，而坡道則會降低事故發生之機率；在人的因素中，18歲以下和年齡越大、酒駕、直行或右轉，皆會增加因自行車事故致死或受傷之機率。最後依據實證之結果，謹從交通管理中的3E政策-交通工程（Engineering）、交通教育（Education）及交通執法（Enforcement）三面向之觀念及角度帶入都市設計層面，提出道路及環境改善措施，以提升都市街道之自行車騎乘環境，並透過教育宣導、推廣活動及相關法令規範等配套措施，藉以增加自行車之騎乘安全。

隨著氣候變遷與溫室效應影響日益明顯，台灣近年發生極端強降雨颱風的次數越來越頻繁，更造成流域地區嚴重災情，而從莫拉克風災經驗可體會到家戶風險溝通的重要性，也意識到我國實務與學術上相關研究的缺乏，故本研究探討家戶風險溝通機制中各項重要因素與調適行為間的關係，以及找出影響家戶調適行為決策之關鍵因素，進而提出家戶風險溝通策略之改善建議，以促進家戶採取調適行為。 本研究經由文獻回顧建立家戶調適行為之風險溝通概念架構，依循此架構研擬問卷，以高屏溪流域地區家戶為研究對象進行問卷調查，透過結構方程模式(SEM)驗證風險溝通架構，了解風險溝通機制各項因素與影響調適行為各因素之關係，後以面對災害回應之強烈將調適行為積極程度分為「消極或低度積極」、「中度積極」與「高度積極」，運用多項式羅吉斯迴歸模型建立家戶應變措施決策模型與調適措施決策模型，找出影響家戶調適行為決策之關鍵因素。 研究結果顯示，調適行為受到內在認知的影響，而內在認知同時受風險溝通機制與外在環境之影響，就風險溝通機制而言，親友鄰居、村里長與地方政府等社區網絡為重要管道。影響調適行為之關鍵因素以災害認知為主，其次為調適行為認知，居住村里次之，其中災害認知與調適行為認知越高，越有可能採取較積極之調適行為，此外，由於自然社會環境、風險溝通特性與社會經濟背景等因素交互影響下，各村里在調適行為決策上也有所差異。最後依據實證結果，與水患自主防災社區風險溝通現況，提出改善家戶風險溝通之策略建議，期望增進風險溝通機制的完備與促進家戶採取調適行為，以減緩極端氣候造成的衝擊。 / Along with the intensification of global climate change and greenhouse effect, typhoons with extreme rainfall strike Taiwan more and more frequently, which cause severe disasters in watershed area. From the experience of Typhoon Morakot in 2009, we realized the importance of risk communication with households and also the lack of related academic research. As a result, this study aims to discuss important factors in risk communication mechanism and their relationships with adaptive behaviors. It also find out key factors influencing decision-making of adaptive behaviors. Based on literature review, this study build a conceptual framework of risk communication process to describe how to trigger adaptive behaviors and encourage adaptive behaviors with risk communication. This study send out questionnaires to the households in Kaoping River Watershed and use structural equation modeling(SEM) to verify the conceptual framework. Then according to attitude of positive degree, adaptive behaviors are classified into“passive or low”,“medium” and “high” levels. By multinomial logistic regression, an empirical analysis was performed to analyze the key factors influencing decision-making of adaptive behaviors. The results show that adaptive behaviors are affected by internal cognition and at the same time internal cognition are affected by risk communication mechanism and external environment. As for risk communication mechanism, family, friends, neighbors and local governments are crucial communication channel. Key factors influencing decision-making of adaptive behaviors are cognition of disaster and adaptive behavior. People with higher cognition of disaster and adaptive behavior would more likely to take positive adaptive behaviors. Besides, community they lived in is also a key factor. Because the interaction of environments, risk communication patterns and socioeconomic attributes, people from different communities would take different adaptive behaviors. Based on empirical results, this study propose suggestions of risk communication strategies in order to better the risk communication mechanism and encourage households to take adaptive behaviors.

Doctor of Philosophy / Department of Physics / Dean Zollman / As part of a collaborative study of the science preparation of elementary school teachers, we investigated the quality of students’ reasoning and explored the relationship between sophistication of reasoning and the degree to which the courses were considered inquiry oriented. To probe students’ reasoning, we developed open-ended written content questions with the distinguishing feature of applying recently learned concepts in a new context. We devised a protocol for developing written content questions that provided a common structure for probing and classifying students’ sophistication level of reasoning. In designing our protocol, we considered several distinct criteria, and classified students’ responses based on their performance for each criterion. First, we classified concepts into three types: Descriptive, Hypothetical, and Theoretical and categorized the abstraction levels of the responses in terms of the types of concepts and the inter-relationship between the concepts. Second, we devised a rubric based on Bloom’s revised taxonomy with seven traits (both knowledge types and cognitive processes) and a defined set of criteria to evaluate each trait. Along with analyzing students’ reasoning, we visited universities and observed the courses in which the students were enrolled. We used the Reformed Teaching Observation Protocol (RTOP) to rank the courses with respect to characteristics that are valued for the inquiry courses. We conducted logistic regression for a sample of 18 courses with about 900 students and reported the results for performing logistic regression to estimate the relationship between traits of reasoning and RTOP score. In addition, we analyzed conceptual structure of students’ responses, based on conceptual classification schemes, and clustered students’ responses into six categories. We derived regression model, to estimate the relationship between the sophistication of the categories of conceptual structure and RTOP scores. However, the outcome variable with six categories required a more complicated regression model, known as multinomial logistic regression, generalized from binary logistic regression. With the large amount of collected data, we found that the likelihood of the higher cognitive processes were in favor of classes with higher measures on inquiry. However, the usage of more abstract concepts with higher order conceptual structures was less prevalent in higher RTOP courses.

This project aims to support pharmacovigilance, the science and activities relating to drug-safety and prevention of adverse drug reactions (ADRs). We focus on a specific ADR called QT prolongation, a serious reaction affecting the heartbeat. Our main goal is to group medicinal ingredients that might cause QT prolongation. This grouping can be used in safety analysis and for exclusion lists in clinical studies. It should preferably be ranked according to level of suspected correlation. We wished to create an automated and standardised process. Drug safety-related reports describing patients' experienced ADRs and what medicinal products they have taken are collected in a database called VigiBase, that we have used as source for ingredient extraction. The ADRs are described in free-texts and coded using an international standardised terminology. This helps us to process the data and filter ingredients included in a report that describes QT prolongation. To broaden our project scope to include uncoded data, we extended the process to use free-text verbatims describing the ADR as input. By processing and filtering the free-text data and training a classification model for natural language processing released by Google on VigiBase data, we were able to predict if a free-text verbatim is describing QT prolongation. The classification resulted in an F1-score of 98%. For the ingredients extracted from VigiBase, we wanted to validate if there is a known connection to QT prolongation. The VigiBase occurrences is a parameter to consider, but it might be misleading since a report can include several drugs, and a drug can include several ingredients, making it hard to validate the cause. For validation, we used product labels connected to each ingredient of interest. We used a tool to download, scan and code product labels in order to see which ones mention QT prolongation. To rank our final list of ingredients according to level of suspected QT prolongation correlation, we used a multinomial logistic regression model. As training data, we used a data subset manually labeled by pharmacists. Used on unlabeled validation data, the model accuracy was 68%. Analyzing the training data showed that it was not easily separated linearly explaining the limited classification performance. The final ranked list of ingredients suspected to cause QT prolongation consists of 1086 ingredients.

Cette recherche se penche sur l’impact des facteurs contextuels, familiaux et individuels dans l’accessibilité au postsecondaire des Premières Nations et des Métis âgés entre 18 et 34 ans qui vivent hors collectivités des Premières Nations au Canada. En plus de l’impact de ces facteurs au niveau national, cette recherche s’intéresse aussi à leur impact selon les trois types de systèmes scolaires canadiens « à choix exclusif », « à choix progressif » et « à choix multiples ». Des régressions logistiques multinomiales ont été réalisées sur les données de l’enquête auprès des peuples Autochtones de 2012. Trois groupes de facteurs qui totalisent 24 indicateurs ont été examinés afin de répondre aux questions de recherche. Les résultats de cette recherche montrent que même si les facteurs contextuels, tels que l’environnement social et scolaire au secondaire et les facteurs familiaux, tels que la scolarité des membres de la famille sont déterminants dans l’accès au postsecondaire des Autochtones, les facteurs individuels sont les principaux facteurs prédictifs de cet accès. Parmi les facteurs les plus importants, il y a la performance académique et le décrochage scolaire, suivi de l’âge qui affecte considérablement cet accès, particulièrement à l’université. De plus, l’analyse de l’effet de modération selon les trois systèmes scolaires canadiens a également permis de distinguer une différence significative entre ces derniers qui est perceptible, d’une part, par les variances expliquées et, d’autre part, par l’impact différé des trois groupes de facteurs étudiés. / This research assesses the impact of contextual, family and individual factors in access to postsecondary education of First Nations and Métis people aged between 18 and 34 years old, living outside First Nations communities in Canada. This research examines also the impact of these factors across the three postsecondary types of school systems of Canada, i.e., “exclusive choice”, “progressive choice” and “multiple choice”. Multinomial logistic regression analyses were performed on the data of the Aboriginal Peoples Survey of 2012. Three groups of factors totaling 24 indicators were examined in order to answer the research questions. The results of this research show that, while contextual factors, such as the social and academic environment and family factors, such as the high academic level of family’s members are determinant in access to postsecondary education among Aboriginals living outside First Nations communities, the individual factors are the main predictors of this access. Among these main predictors, there are academic performance, dropping out of school and age. In addition, the analysis of moderation effects according to the three postsecondary types of systems present in Canada showed significant differences that can be seen, first, in the explained variance and second, in the difference between the importance of the different groups of factors in each system.

Dans cette étude, j’examine la propension à former une union interethnique parmi les Canadiens arabes de seconde génération et de génération 1.5 en utilisant les données du recensement canadien de 2016. L’analyse descriptive montre que les unions interethniques sont fréquentes au sein de cette population. Environ la moitié des hommes (56%) et des femmes (49%) sont dans une union interethnique avec une personne non-Arabe d’origine immigrante ou un(e) Canadien(ne) de troisième génération ou des générations suivantes. La régression logistique multinomiale révèle que les hommes et les femmes avec un niveau d’éducation plus élevé, une ascendance partiellement arabe et un statut d’immigrant de deuxième génération sont significativement plus enclins à être en union interethnique qu’à être en union intraethnique avec un immigrant de première génération. Conformément à la théorie de l’assimilation segmentée, ces résultats suggèrent que l’intégration socioéconomique et l’acculturation contribuent à la propension des descendants arabes à former des unions avec des individus non-arabes. La propension des descendants arabes à être en union intraethnique avec des immigrants de première génération ou des descendants est aussi une problématique dont je discute. / In this study, I examine the propensity to form interethnic unions among the 1.5 and second generations of Arab Canadians using the 2016 Canadian census data. The descriptive analysis shows that interethnic unions are common within this population. About half the men (56%) and the women (49%) are in an interethnic union with a non-Arab person with an immigrant background or a Canadian of third generation or subsequent generations. The multinomial logistic regression reveals that men and women with higher educational attainment, part Arab ancestry and second-generation immigrant status are significantly more prone to be in an interethnic union than in an intraethnic union with a first-generation immigrant. In accordance with the segmented assimilation theory, these results suggest that socioeconomic integration and acculturation contribute to the propensity of Arab descendants to form unions with non-Arab individuals. The propensity of Arab descendants to be in intraethnic unions with first generation-immigrants or with descendants of immigrants (1.5 and second generations) is also discussed in this thesis.