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Hur låter miljöförstöring? : Självgenererande och slumpmässig musik sprungen ur statistiska data / What does environmental pollution sound like? : Self generative and randomized music interprets dataWahlström, Gustav January 2020 (has links)
Hur låter miljöförstöring – Självgenererande och slumpmässig sprungen ur statistiska data är ett mastersarbete som fokuserar på hur man kan omvandla data till att kontrollera musik och ljud. Om vi tillåter konstnärliga uttryck, med data som utgångspunkt, kan det få oss att uppleva och förstår original data på ett nytt sätt? Projektets resultat består av sju generativa kompositioner, där parametrar är kontrollerade av olika typer av miljödata, och försöker utforska forskningsområdet sonifikation och generativ musik genom att ställa frågan: Hur låter miljöförstöring? Med generativ musik menas att musiken skapar, utvecklar och förändrar sig själv utifrån de verktyg som bildats inom detta projekt. Texten går också djupare in på metoden av att utveckla dessa verktyg för att möjliggöra liknande kompositioner i framtiden. Med erfarenheter av att använda slumpmässiga parametrar för att manipulera bakgrundsdetaljer, utforskar det här projekt istället möjligheten att utveckla de metoderna och applicera det på hela kompositioner. De sju kompositionerna ligger också till grund för utforskandet av området sonifikation. I tidigare forskning har ämnet främst bemöts ifrån ett vetenskapligt perspektiv. Syftet med det här projektet har istället varit att bemöta det inom ramarna för musikalisk gestaltning och ett konstnärligt perspektiv. Begreppet sonifikation betyder, användandet av icke-talande ljud som uppmärksammar data och statistik, med målet att agera som ett substitut, eller ett komplement, till att visualisera data. Utifrån dessa kompositioner reflekterar sedan texten kring generativ musik i allmänhet, och sonifikation i synnerhet, där bland annat möjligheterna, framtida forskning och autenticiteten inom sonifikation tas upp. / What does environmental pollution sound like? – Self generative and randomized music interprets data is a master thesis focused on transforming data and letting it control music and sounds. If we create artistic outputs out of data, will it allow us to experience and understand the original data in a new way? The core, and the result, of this project where seven compositions, created and controlled by different environmental data which tries to explore the research areas of sonification and generative music by asking the question: What does environmental pollution sound like? Generative music means that the music creates, develops and changes itself based on the established tools that this project provides. This thesis also focuses on the method of developing these tools in order to enable similar productions in the future. With previous experiences in using randomized events, to manipulate details in a production, this project delves deeper into applying the same technique to a whole composition. The seven compositions were formed in order to understand and reflect upon the research areas of sonification. Earlier research tends to approach the subject from a scientific perspective. The purpose of this project was to instead approach it from a more artistic perspective. Sonification means, the use of non-speech audio to perceptualize data which enables the possibilities as an alternative, or complement, to visualize the original data. Drawing from these seven compositions, this thesis also discusses generative music and sonification in general, as well as the opportunities, future research and authenticity of sonification. / <p>Bifogad ljudfil är ett kollage av de sju kompositionerna som arbetet resulterat i, med anledning av att i framtiden kunna publiceras i sin helhet.</p>
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Molekulargenetische Faktoren der Suszeptibilität für Karotis-PlaquesPott, Janne 20 February 2019 (has links)
No description available.
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Domain Adaptation to Meet the Reality-Gap from Simulation to RealityForsberg, Fanny January 2022 (has links)
Being able to train machine learning models on simulated data can be of great interest in several applications, one of them being for autonomous driving of cars. The reason is that it is easier to collect large labeled datasets as well as performing reinforcement learning in simulations. However, transferring these learned models to the real-world environment can be hard due to differences between the simulation and the reality; for example, differences in material, textures, lighting and content. One approach is to use domain adaptation, by making the simulations as similar as possible to the reality. The thesis's main focus is to investigate domain adaptation as a way to meet the reality-gap, and also compare it to an alternative method, domain randomization. Two different methods of domain adaptation; one adapting the simulated data to reality, and the other adapting the test data to simulation, are compared to using domain randomization. These are evaluated with a classifier making decisions for a robot car while driving in reality. The evaluation consists of a quantitative evaluation on real-world data and a qualitative evaluation aiming to observe how well the robot is driving and avoiding obstacles. The results show that the reality-gap is very large and that the examined methods reduce it, with the two using domain adaptation resulting in the largest decrease. However, none of them led to satisfactory driving.
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Genetic determinants of respiratory diseases and their clinical implications / ゲノミクスで拓く呼吸器疾患病態解明とその臨床的意義の検討Nakanishi, Tomoko 26 September 2022 (has links)
京都大学 / マギル大学 / 新制・課程博士 / 博士(ゲノム医学) / 甲第24203号 / 医博JD第1号 / 新制||医||JD1(附属図書館) / 京都大学大学院医学研究科京都大学マギル大学ゲノム医学国際連携専攻 / (主査)教授 稲垣 暢也, 教授 YOUSSEFIAN Shohab, 准教授 Majewski Jacek (マギル大学), 准教授 Gravel Simon (マギル大学), 教授 Gagneur Julien (ミュンヘン工科大学) / 学位規則第4条第1項該当 / Doctor of Philosophy in Human Genetics / Kyoto University / McGill University / DFAM
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Increasing Engagement Utilizing Video Modeling and the Good Behavior Game with Students with Emotional and Behavioral DisordersFlowers, Emily M. 05 December 2017 (has links)
No description available.
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Electronic Strategies to Enhance Venous Thromboprophylaxis in Hospitalized Medical Patients: A Randomized Controlled TrialPai, Menaka 10 1900 (has links)
<p>Venous thromboembolism (VTE), which encompasses deep vein thrombosis (DVT) and pulmonary embolism (PE), is the most preventable cause of death in hospitalized patients. Due to its high mortality, morbidity, and cost, health care providers are obligated to not only effectively diagnose and treat VTE, but also to prevent it if possible. This has been reinforced by a number of national and international quality initiatives to prevent hospital-acquired VTE. Despite the existence of well-accepted clinical practice guidelines on VTE prophylaxis, 1 in 3 hospitalized medical patients receives an inappropriate VTE prophylaxis strategy. Both underuse of prophylaxis in patients with VTE risk, and overuse of prophylaxis in patients without VTE risk are problems. The use of inappropriate VTE prophylaxis strategies is likely due to the complexity and heterogeneity of hospitalized medical patients, and the difficulty of applying “one size fits all” practice guidelines to this group. Institution-wide knowledge translation strategies are required to close the gap between evidence and practice, and promote evidence-based VTE prophylaxis strategies in hospitalized medical patients. The objective of this thesis is to design a cluster randomized controlled trial to determine if a standardized electronic order set, with an embedded computerized decision support system and audit and feedback component, affects the use of appropriate VTE prophylaxis in hospitalized medical patients. The unit of randomization in this study is the hospital, which serves as the cluster. The unit of observation in this study is the individual patient. The primary outcome of this study is the proportion of in-hospital days during which appropriate VTE prophylaxis is administered, in intervention versus control hospitals. Secondary outcomes are the rates of hospital-acquired VTE, major bleeding and mortality, in intervention versus control hospitals. Design, analytic and ethical challenges unique to cluster randomized trials will also be discussed. Strategies to overcome them in this trial will be presented.</p> / Master of Science (MSc)
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Effect of Depression Treatment on Somatic Depressive Symptoms and Cardiometabolic Biomarkers among People without DiabetesAubrey Lynn Shell (6622241) 09 September 2022 (has links)
<p>Examining the effect of a modernized collaborative care intervention for depression consisting of both behavioral and pharmacologic treatments on 12-month change in individual somatic depressive symptoms (hyperphagia, poor appetite, hypersomnia, and disturbed sleep) and 12-month change in</p>
<p>cardiometabolic biomarkers (HOMA-IR, BMI, hsCRP, leptin, and ghrelin). Further examining whether 12-month change in individual somatic depressive symptoms mediates the eIMPACT intervention’s effect on 12-month change in cardiometabolic biomarkers.</p>
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Fairneß, Randomisierung und Konspiration in verteilten AlgorithmenVölzer, Hagen 08 December 2000 (has links)
Fairneß (d.h. faire Konfliktlösung), Randomisierung (d.h. Münzwürfe) und partielle Synchronie sind verschiedene Konzepte, die häufig zur Lösung zentraler Synchronisations- und Koordinationsprobleme in verteilten Systemen verwendet werden. Beispiele für solche Probleme sind das Problem des wechselseitigen Ausschlusses (kurz: Mutex-Problem) sowie das Konsens-Problem. Für einige solcher Probleme wurde bewiesen, daß ohne die oben genannten Konzepte keine Lösung für das betrachtete Problem existiert. Unmöglichkeitsresultate dieser Art verbessern unser Verständnis der Wirkungsweise verteilter Algorithmen sowie das Verständnis des Trade-offs zwischen einem leicht analysierbaren und einem ausdrucksstarken Modell für verteiltes Rechnen. In dieser Arbeit stellen wir zwei neue Unmöglichkeitsresultate vor. Darüberhinaus beleuchten wir ihre Hintergründe. Wir betrachten dabei Modelle, die Randomisierung einbeziehen, da bisher wenig über die Grenzen der Ausdrucksstärke von Randomisierung bekannt ist. Mit einer Lösung eines Problems durch Randomisierung meinen wir, daß das betrachtete Problem mit Wahrscheinlichkeit 1 gelöst wird. Im ersten Teil der Arbeit untersuchen wir die Beziehung von Fairneß und Randomisierung. Einerseits ist bekannt, daß einige Probleme (z.B. das Konsens- Problem) durch Randomisierung nicht aber durch Fairneß lösbar sind. Wir zeigen nun, daß es andererseits auch Probleme gibt (nämlich das Mutex-Problem), die durch Fairneß, nicht aber durch Randomisierung lösbar sind. Daraus folgt, daß Fairneß nicht durch Randomisierung implementiert werden kann. Im zweiten Teil der Arbeit verwenden wir ein Modell, das Fairneß und Randomisierung vereint. Ein solches Modell ist relativ ausdrucksstark: Es erlaubt Lösungen für das Mutex-Problem, das Konsens-Problem, sowie eine Lösung für das allgemeine Mutex-Problem. Beim allgemeinen Mutex-Problem (auch bekannt als Problem der speisenden Philosophen) ist eine Nachbarschaftsrelation auf den Agenten gegeben und ein Algorithmus gesucht, der das Mutex-Problem für jedes Paar von Nachbarn simultan löst. Schließlich betrachten wir das ausfalltolerante allgemeine Mutex-Problem -- eine Variante des allgemeinen Mutex-Problems, bei der Agenten ausfallen können. Wir zeigen, daß sogar die Verbindung von Fairneß und Randomisierung nicht genügt, um eine Lösung für das ausfalltolerante allgemeine Mutex-Problem zu konstruieren. Ein Hintergrund für dieses Unmöglichkeitsresultat ist ein unerwünschtes Phänomen, für das in der Literatur der Begriff Konspiration geprägt wurde. Konspiration wurde bisher nicht adäquat charakterisiert. Wir charakterisieren Konspiration auf der Grundlage nicht-sequentieller Abläufe. Desweiteren zeigen wir, daß Konspiration für eine große Klasse von Systemen durch die zusätzliche Annahme von partieller Synchronie verhindert werden kann, d.h. ein konspirationsbehaftetes System kann zu einem randomisierten System verfeinert werden, das unter Fairneß und partieller Synchronie mit Wahrscheinlichkeit 1 konspirationsfrei ist. Partielle Synchronie fordert, daß alle relativen Geschwindigkeiten im System durch eine Konstante beschränkt sind, die jedoch den Agenten nicht bekannt ist. Die Darstellung der Unmöglichkeitsresultate und die Charakterisierung von Konspiration wird erst durch die Verwendung nicht-sequentieller Abläufe möglich. Ein nicht-sequentieller Ablauf repräsentiert im Gegensatz zu einem sequentiellen Ablauf kausale Ordnung und nicht zeitliche Ordnung von Ereignissen. Wir entwickeln in dieser Arbeit eine nicht-sequentielle Semantik für randomisierte verteilte Algorithmen, da es bisher keine in der Literatur gibt. In dieser Semantik wird kausale Unabhängigkeit durch stochastische Unabhängigkeit widergespiegelt. / Concepts such as fairness (i.e., fair conflict resolution), randomization (i.e., coin flips), and partial synchrony are frequently used to solve fundamental synchronization- and coordination-problems in distributed systems such as the mutual exclusion problem (mutex problem for short) and the consensus problem. For some problems it is proven that, without such concepts, no solution to the particular problem exists. Impossibilty results of that kind improve our understanding of the way distributed algorithms work. They also improve our understanding of the trade-off between a tractable model and a powerful model of distributed computation. In this thesis, we prove two new impossibility results and we investigate their reasons. We are in particular concerned with models for randomized distributed algorithms since little is yet known about the limitations of randomization with respect to the solvability of problems in distributed systems. By a solution through randomization we mean that the problem under consideration is solved with probability 1. In the first part of the thesis, we investigate the relationship between fairness and randomization. On the one hand, it is known that to some problems (e.g. to the consensus problem), randomization admits a solution where fairness does not admit a solution. On the other hand, we show that there are problems (viz. the mutex problem) to which randomization does not admit a solution where fairness does admit a solution. These results imply that fairness cannot be implemented by coin flips. In the second part of the thesis, we consider a model which combines fairness and randomization. Such a model is quite powerful, allowing solutions to the mutex problem, the consensus problem, and a solution to the generalized mutex problem. In the generalized mutex problem (a.k.a. the dining philosophers problem), a neighborhood relation is given and mutual exclusion must be achieved for each pair of neighbors. We finally consider the crash-tolerant generalized mutex problem where every hungry agent eventually becomes critical provided that neither itself nor one of its neighbors crashes. We prove that even the combination of fairness and randomization does not admit a solution to the crash-tolerant generalized mutex problem. We argue that the reason for this impossibility is the inherent occurrence of an undesirable phenomenon known as conspiracy. Conspiracy was not yet properly characterized. We characterize conspiracy on the basis of non-sequential runs, and we show that conspiracy can be prevented by help of the additional assumption of partial synchrony, i.e., we show that every conspiracy-prone system can be refined to a randomized system which is, with probability 1, conspiracy-free under the assumptions of partial synchrony and fairness. Partial synchrony means that each event consumes a bounded amount of time where, however, the bound is not known. We use a non-sequential semantics for distributed algorithms which is essential to some parts of the thesis. In particular, we develop a non-sequential semantics for randomized distributed algorithms since there is no such semantics in the literature. In this non-sequential semantics, causal independence is reflected by stochastic independence.
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Évaluation de l’effet du neurofeedback sur les capacités d’inhibition d’enfants ayant un Trouble déficitaire de l’attention avec hyperactivitéPerreau-Linck, Elisabeth 05 1900 (has links)
Le neurofeedback (NF) suscite actuellement un vif intérêt dans la prise en charge du trouble déficitaire de l’attention avec hyperactivité (TDAH) chez l’enfant. Proposée comme méthode alternative à la médication par de nombreux cliniciens, notamment aux États-Unis, le NF est une intervention non-invasive de type électrophysiologique qui repose sur l’apprentissage par conditionnement opérant de l’autorégulation d’ondes cérébrales déviantes. Les études empiriques qui étayent cette pratique font toutefois l’objet de virulentes critiques de la part de spécialistes dans le domaine du TDAH en raison de résultats systématiquement positifs mais non spécifiques, auxquels s’ajoutent de nombreuses lacunes méthodologiques.
Les travaux de cette thèse visent à appliquer une méthodologie stricte de type essai clinique contrôlé avec assignation aléatoire afin d’isoler les effets particuliers du NF, en appliquant un protocole d’entraînement propre au déficit primaire sous-tendant le TDAH, soit l’inhibition motrice, dans le but d’évaluer la spécificité de cette intervention. Dans un premier temps, les connaissances relatives à la nosologie du TDAH, à ses principaux traitements, au NF et aux capacités d’inhibition chez l’enfant ayant un TDAH sont présentées (Chapitre 1). Ensuite, les études réalisées dans le cadre de cette thèse sont exposées. Dans l’étude initiale, la spécificité du NF est évaluée sur les capacités d’inhibition grâce à des mesures subjectives, soit des questionnaires de comportements complétés par les parents, ainsi que des mesures objectives, à savoir des tâches neuropsychologiques (Chapitre 2). Afin de préciser davantage les conséquences d’un entraînement à l’autorégulation d’ondes cérébrales, l’étude subséquente s’est intéressée à l’impact neurophysiologiques de l’amélioration des capacités d’inhibition, par le biais d’une étude en potentiels évoqués employant une tâche de performance continue de type Stop-signal (Chapitre 3).
Les principaux résultats reflètent un recrutement sous optimal, avec une puissance statistique insuffisante pour réaliser des statistiques quantitatives de groupe. Néanmoins, l’appréciation des données selon une approche d’étude de cas multiples permet de mettre en évidence la présence d’une réponse placebo sur les capacités d’inhibition suite à un entraînement en NF. Finalement, les implications de la taille de l’échantillon, ainsi que les limites et les critiques de ces études sont discutées au Chapitre 4. / In recent years, there has been a lively interest in the use of neurofeedback (NF) as an alternative treatment to pharmacotherapy in pediatric Attention-deficit hyperactivity disorder (ADHD). NF is defined as an operant conditioning procedure whereby an individual learns to self-regulate electrical brain activity. Yet, empirical studies supporting its practice are harshly criticized in the field of ADHD research due to systematic unspecific positive results associated to numerous methodological flaws.
Studies presented in this dissertation aim at applying a randomized placebo-controlled clinical trial to the investigation of NF specific effects. In order to further establish treatment specificity, we trained the participants using a NF protocol characteristic to motor-inhibition functioning since it has repeatedly been described as the core deficit in ADHD. The fist part of this thesis comprises a brief review of knowledge concerning ADHD, principal treatments offered for this disorder, NF research in pediatric ADHD and inhibition abilities in these children (Chapter 1). Following are the two studies conducted as part of this dissertation. In the initial study, effects of NF training are investigated on inhibition capacities by means of behavior rating scales and neuropsychological tests (Chapter 2). With the aim of further defining the consequence of training to self-regulate ones brain activity, the subsequent study looks at the neurophysiologic impact of improving inhibition capacities with an event-related potential study using a Stop-signal continuous performance task (Chapter 3).
The principal results reveal a non optimal recruitment, with insufficient statistical power, thus precluding quantitative group statistics. Nevertheless, appreciating the data from a multiple case study perspective enables to suggest that a placebo response could be at play following NF training, such as measured by improvements on inhibition capacities. Finally, the implications of such a small sample size, limits and critics of these studies are discussed in Chapter 4.
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Analysis of Longitudinal Surveys with Missing ResponsesCarrillo Garcia, Ivan Adolfo January 2008 (has links)
Longitudinal surveys have emerged in recent years as an important data collection tool for population studies where the primary interest is to examine population changes over time at the individual level. The National Longitudinal Survey of Children and Youth (NLSCY), a large scale survey with a complex sampling design and conducted by Statistics Canada, follows a large group of children and youth over time and collects measurement on various indicators related to their educational, behavioral and psychological development. One of the major objectives of the study is to explore how such development is related to or affected by familial, environmental and economical factors.
The generalized estimating equation approach, sometimes better known as the GEE method, is the most popular statistical inference tool for longitudinal studies. The vast majority of existing literature on the GEE method, however, uses the method for non-survey settings; and issues related to complex sampling designs are ignored.
This thesis develops methods for the analysis of longitudinal surveys when the response variable contains missing values. Our methods are built within the GEE framework, with a major focus on using the GEE method when missing responses are handled through hot-deck imputation. We first argue why, and further show how, the survey weights can be incorporated into the so-called Pseudo GEE method under a joint randomization framework. The consistency of the resulting Pseudo GEE estimators with complete responses is established under the proposed framework.
The main focus of this research is to extend the proposed pseudo GEE method to cover cases where the missing responses are imputed through the hot-deck method. Both weighted and unweighted hot-deck imputation procedures are considered. The consistency of the pseudo GEE estimators under imputation for missing responses is established for both procedures. Linearization variance estimators are developed for the pseudo GEE estimators under the assumption that the finite population sampling fraction is small or negligible, a scenario often held for large scale population surveys.
Finite sample performances of the proposed estimators are investigated through an extensive simulation study. The results show that the pseudo GEE estimators and the linearization variance estimators perform well under several sampling designs and for both continuous response and binary response.
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