Global ETD Search

131	Statistické vyhodnocení fylogeneze biologických sekvencí / Statistic evaluation of phylogeny of biological sequences Vadják, Šimon January 2014 (has links) The master's thesis provides a comprehensive overview of resampling methods for testing the correctness topology of the phylogenetic trees which estimate the process of phylogeny on the bases of biological sequences similarity. We focused on the possibility of errors creation in this estimate and the possibility of their removal and detection. These methods were implemented in Matlab for Bootstrapping, jackknifing, OTU jackknifing and PTP test (Permutation tail probability). The work aims to test their applicability to various biological sequences and also to assess the impact of the choice of input analysis parameters on the results of these statistical tests.
132	The Impact of Therapeutic Alliance on Outcomes in Parent-Child Dyadic Interventions Smith, Ryan M. 13 October 2010 (has links) No description available. Families and Family Life Personal Relationships Psychology Psychotherapy Social Work early childhood infant mental health attachment Devereux Early Childhood Assessment Working Alliance Inventory therapeutic relationship parenting home visitation quantitative bootstrapping mediation
133	Função da probabilidade da seleção do recurso (RSPF) na seleção de habitat usando modelos de escolha discreta / Resource of selection probability function (RSPF ) the habitat selection using discrete choice models (DCM) Cardozo, Sandra Vergara 16 February 2009 (has links) Em ecologia, o comportamento dos animais é freqüentemente estudado para entender melhor suas preferências por diferentes tipos de alimento e habitat. O presente trabalho esta relacionado a este tópico, dividindo-se em três capítulos. O primeiro capitulo refere-se à estimação da função da probabilidade da seleção de recurso (RSPF) comparado com um modelo de escolha discreta (DCM) com uma escolha, usando as estatísticas qui-quadrado para obter as estimativas. As melhores estimativas foram obtidas pelo método DCM com uma escolha. No entanto, os animais não fazem a sua seleção baseados apenas em uma escolha. Com RSPF, as estimativas de máxima verossimilhança, usadas pela regressão logística ainda não atingiram os objetivos, já que os animais têm mais de uma escolha. R e o software Minitab e a linguagem de programação Fortran foram usados para obter os resultados deste capítulo. No segundo capítulo discutimos mais a verossimilhança do primeiro capítulo. Uma nova verossimilhança para a RSPF é apresentada, a qual considera as unidades usadas e não usadas, e métodos de bootstrapping paramétrico e não paramétrico são usados para estudar o viés e a variância dos estimadores dos parâmetros, usando o programa FORTRAN para obter os resultados. No terceiro capítulo, a nova verossimilhança apresentada no capítulo 2 é usada com um modelo de escolha discreta, para resolver parte do problema apresentado no primeiro capítulo. A estrutura de encaixe é proposta para modelar a seleção de habitat de 28 corujas manchadas (Strix occidentalis), assim como a uma generalização do modelo logit encaixado, usando a maximização da utilidade aleatória e a RSPF aleatória. Métodos de otimização numérica, e o sistema computacional SAS, são usados para estimar os parâmetros de estrutura de encaixe. / In ecology, the behavior of animals is often studied to better understand their preferences for different types of habitat and food. The present work is concerned with this topic. It is divided into three chapters. The first concerns the estimation of a resource selection probability function (RSPF) compared with a discrete choice model (DCM) using chi-squared to obtain estimates. The best estimates were obtained by the DCM method. Nevertheless, animals were not selected based on choice alone. With RSPF, the maximum likelihood estimates used with the logistic regression still did not reach the objectives, since the animals have more than one choice. R and Minitab software and the FORTRAN programming language were used for the computations in this chapter. The second chapter discusses further the likelihood presented in the first chapter. A new likelihood for a RSPF is presented, which takes into account the units used and not used, and parametric and non-parametric bootstrapping are employed to study the bias and variance of parameter estimators, using a FORTRAN program for the calculations. In the third chapter, the new likelihood presented in chapter 2, with a discrete choice model is used to resolve a part of the problem presented in the first chapter. A nested structure is proposed for modelling selection by 28 spotted owls (Strix occidentalis) as well as a generalized nested logit model using random utility maximization and a random RSPF. Numerical optimization methods and the SAS system were employed to estimate the nested structural parameters. Análise de regressão e correlação Boostrap Jackniffe re-amostragem Discrete choice model (DCM) Ecologia animal - Métodos estatísticos Generalized nested logit model (GNL) Habitat - Seleção Inferência em população animal Modelos matemáticos Probabilidade aplicada. Random utility maximization Resource selection function (RSF)
134	Multiscale and meta-analytic approaches to inference in clinical healthcare data Hamilton, Erin Kinzel 29 March 2013 (has links) The field of medicine is regularly faced with the challenge of utilizing information that is complicated or difficult to characterize. Physicians often must use their best judgment in reaching decisions or recommendations for treatment in the clinical setting. The goal of this thesis is to use innovative statistical tools in tackling three specific challenges of this nature from current healthcare applications. The first aim focuses on developing a novel approach to meta-analysis when combining binary data from multiple studies of paired design, particularly in cases of high heterogeneity between studies. The challenge is in properly accounting for heterogeneity when dealing with a low or moderate number of studies, and with a rarely occurring outcome. The proposed approach uses a Rasch model for translating data from multiple paired studies into a unified structure that allows for properly handling variability associated with both pair effects and study effects. Analysis is then performed using a Bayesian hierarchical structure, which accounts for heterogeneity in a direct way within the variances of the separate generating distributions for each model parameter. This approach is applied to the debated topic within the dental community of the comparative effectiveness of materials used for pit-and-fissure sealants. The second and third aims of this research both have applications in early detection of breast cancer. The interpretation of a mammogram is often difficult since signs of early disease are often minuscule, and the appearance of even normal tissue can be highly variable and complex. Physicians often have to consider many important pieces of the whole picture when trying to assess next steps. The final two aims focus on improving the interpretation of findings in mammograms to aid in early cancer detection. When dealing with high frequency and irregular data, as is seen in most medical images, the behaviors of these complex structures are often difficult or impossible to quantify by standard modeling techniques. But a commonly occurring phenomenon in high-frequency data is that of regular scaling. The second aim in this thesis is to develop and evaluate a wavelet-based scaling estimator that reduces the information in a mammogram down to an informative and low-dimensional quantification of the innate scaling behavior, optimized for use in classifying the tissue as cancerous or non-cancerous. The specific demands for this estimator are that it be robust with respect to distributional assumptions on the data, and with respect to outlier levels in the frequency domain representation of the data. The final aim in this research focuses on enhancing the visualization of microcalcifications that are too small to capture well on screening mammograms. Using scale-mixing discrete wavelet transform methods, the existing detail information contained in a very small and course image will be used to impute scaled details at finer levels. These "informed" finer details will then be used to produce an image of much higher resolution than the original, improving the visualization of the object. The goal is to also produce a confidence area for the true location of the shape's borders, allowing for more accurate feature assessment. Through the more accurate assessment of these very small shapes, physicians may be more confident in deciding next steps. Rasch model Bayesian hierarchical model Paired data Meta-analysis Heterogeneity Scale-mixing wavelet transform Sampling distribution Bootstrapping Dental sealants Waveletes Spectral tools Breast cancer Scaling Wavelet spectra Weighted regression Theil Microcalcification Diagnostic classification Image enhancement Rasch models Item response theory Sampling (Statistics) Bootstrap (Statistics)
135	Calorimeter-Based Triggers at the ATLAS Detector for Searches for Supersymmetry in Zero-Lepton Final States / Kalorimeterbasierte Trigger am ATLAS-Detektor für Suchen nach Supersymmetrie in Null-Lepton-Endzuständen Mann, Alexander 16 February 2012 (has links) No description available. 530 Physik Physics CERN Large Hadron Collider LHC ATLAS ATLAS-Detektor Supersymmetrie SUSY Null-Lepton-Kanal Trigger Triggereffizienz Bootstrap-Methode Triggerrate Modell fehlende transversale Energie Ausschlussgrenze CERN Large Hadron Collider LHC ATLAS detector Search Supersymmetry SUSY Zero-lepton channel Trigger efficiency Bootstrapping method Trigger rate Model Missing transverse energy Exclusion limit 33.56 33.50 33.05 RTM 000: Physik der Elementarteilchen RDE 000: Experimentalphysik
136	Função da probabilidade da seleção do recurso (RSPF) na seleção de habitat usando modelos de escolha discreta / Resource of selection probability function (RSPF ) the habitat selection using discrete choice models (DCM) Sandra Vergara Cardozo 16 February 2009 (has links) Em ecologia, o comportamento dos animais é freqüentemente estudado para entender melhor suas preferências por diferentes tipos de alimento e habitat. O presente trabalho esta relacionado a este tópico, dividindo-se em três capítulos. O primeiro capitulo refere-se à estimação da função da probabilidade da seleção de recurso (RSPF) comparado com um modelo de escolha discreta (DCM) com uma escolha, usando as estatísticas qui-quadrado para obter as estimativas. As melhores estimativas foram obtidas pelo método DCM com uma escolha. No entanto, os animais não fazem a sua seleção baseados apenas em uma escolha. Com RSPF, as estimativas de máxima verossimilhança, usadas pela regressão logística ainda não atingiram os objetivos, já que os animais têm mais de uma escolha. R e o software Minitab e a linguagem de programação Fortran foram usados para obter os resultados deste capítulo. No segundo capítulo discutimos mais a verossimilhança do primeiro capítulo. Uma nova verossimilhança para a RSPF é apresentada, a qual considera as unidades usadas e não usadas, e métodos de bootstrapping paramétrico e não paramétrico são usados para estudar o viés e a variância dos estimadores dos parâmetros, usando o programa FORTRAN para obter os resultados. No terceiro capítulo, a nova verossimilhança apresentada no capítulo 2 é usada com um modelo de escolha discreta, para resolver parte do problema apresentado no primeiro capítulo. A estrutura de encaixe é proposta para modelar a seleção de habitat de 28 corujas manchadas (Strix occidentalis), assim como a uma generalização do modelo logit encaixado, usando a maximização da utilidade aleatória e a RSPF aleatória. Métodos de otimização numérica, e o sistema computacional SAS, são usados para estimar os parâmetros de estrutura de encaixe. / In ecology, the behavior of animals is often studied to better understand their preferences for different types of habitat and food. The present work is concerned with this topic. It is divided into three chapters. The first concerns the estimation of a resource selection probability function (RSPF) compared with a discrete choice model (DCM) using chi-squared to obtain estimates. The best estimates were obtained by the DCM method. Nevertheless, animals were not selected based on choice alone. With RSPF, the maximum likelihood estimates used with the logistic regression still did not reach the objectives, since the animals have more than one choice. R and Minitab software and the FORTRAN programming language were used for the computations in this chapter. The second chapter discusses further the likelihood presented in the first chapter. A new likelihood for a RSPF is presented, which takes into account the units used and not used, and parametric and non-parametric bootstrapping are employed to study the bias and variance of parameter estimators, using a FORTRAN program for the calculations. In the third chapter, the new likelihood presented in chapter 2, with a discrete choice model is used to resolve a part of the problem presented in the first chapter. A nested structure is proposed for modelling selection by 28 spotted owls (Strix occidentalis) as well as a generalized nested logit model using random utility maximization and a random RSPF. Numerical optimization methods and the SAS system were employed to estimate the nested structural parameters. Análise de regressão e correlação Boostrap Jackniffe re-amostragem Ecologia animal - Métodos estatísticos Habitat - Seleção Inferência em população animal Modelos matemáticos Probabilidade aplicada. Discrete choice model (DCM) Generalized nested logit model (GNL) Random utility maximization Resource selection function (RSF)
137	Motivations and incentives for pro-environmental behaviour : the case of silvopasture adoption in the tropical forest frontier Zabala, Aiora January 2015 (has links) On the frontier of biodiversity-rich tropical forests, how land is used has an important role in buffering the primary ecosystem. Unsustainable small-scale cattle farming endangers soil quality and degrades the landscape. Silvopasture is a type of agroforestry that provides both ecological and livelihood benefits. A number of projects have been implemented across the tropics to encourage silvopasture adoption, with varying success. This dissertation questions the reasons for variable outcomes among participants within these projects: what motivates smallholders to adopt innovative land-use practices, and what form of incentives may help to overcome obstacles and catalyse adoption. This dissertation contributes to the ongoing debate on payments for ecosystem services, specifically about their suitability and effectiveness. To understand what influences decisions to adopt sustainable land-use practices, I review systematically and quantitatively the literature on adoption predictors, and I empirically analyse participation and short-term adoption in a pilot project for planting fodder trees in the border of a protected forest in Chiapas, Mexico, using primary and secondary data. I focus on subjective perspectives and livelihood strategies of actual and potential participants as explanatory variables, which have received unduly scarce attention in past studies. This lack of attention is partially caused by the difficulties of operationalising internal variables. I address this challenge by developing an analytical approach that increases the precision of the resulting perspectives in Q methodology. I cluster livelihood strategies and model adoption. This in-depth case-study suggests the type of incentives that are adequate to encourage adoption of sustainable land-use practices. Results indicate that payments may not be the best incentive for pioneer adopters, and that the adoption process is composed of separate individual steps, which are influenced distinctly by identifiable predictors, such as livelihood diversity. Uncovering this heterogeneity of motivations towards adoption provides useful knowledge for designing more effective external policy interventions. 333
138	THEORY OF AUTOMATICITY IN CONSTRUCTION Ikechukwu Sylvester Onuchukwu (17469117) 30 November 2023 (has links) <p dir="ltr">Automaticity, an essential attribute of skill, is developed when a task is executed repeatedly with minimal attention and can have both good (e.g., productivity, skill acquisitions) and bad (e.g., accident involvement) implications on workers’ performance. However, the implications of automaticity in construction are unknown despite their significance. To address this knowledge gap, this research aimed to examine methods that are indicative of the development of automaticity on construction sites and its implications on construction safety and productivity. The objectives of the dissertation include: 1) examining the development of automaticity during the repetitive execution of a primary task of roofing construction and a concurrent secondary task (a computer-generated audio-spatial processing task) to measure attentional resources; 2) using eye-tracking metrics to distinguish between automatic and nonautomatic subjects and determine the significant factors contributing to the odds of automatic behavior; 3) determining which personal characteristics (such as personality traits and mindfulness dimensions) better explain the variability in the attention of workers while developing automaticity. To achieve this objective, 28 subjects were recruited to take part in a longitudinal study involving a total of 22 repetitive sessions of a simulated roofing task. The task involves the installation of 17 pieces of 25 ft2 shingles on a low-sloped roof model that was 8 ft wide, 8 ft long, and 4 ft high for one month in a laboratory. The collected data was analyzed using multiple statistical and data mining techniques such as repeated measures analysis of variance (RM-ANOVA), pairwise comparisons, principal component analysis (PCA), support vector machine (SVM), binary logistic regression (BLR), relative weight analyses (RWA), and advanced bootstrapping techniques to address the research questions. First, the findings showed that as the experiment progressed, there were significant improvements in the mean automatic performance measures such as the mean primary task duration, mean primary task accuracy, and mean secondary task score over the repeated measurements (p-value < 0.05). These findings were used to demonstrate that automaticity develops during repetitive construction activities. This is because these automatic performance measures provide an index for assessing feature-based changes that are synonymous with automaticity development. Second, this study successfully used supervised machine learning methods including SVM to classify subjects (with an accuracy of 76.8%) based on their eye-tracking data into automatic and nonautomatic states. Also, BLR was used to estimate the probability of exhibiting automaticity based on eye-tracking metrics and ascertain the variables significantly contributing to it. Eye-tracking variables collected towards safety harness and anchor, hammer, and work area AOIs were found to be significant predictors (p < 0.05) of the probability of exhibiting automatic behavior. Third, the results revealed that higher levels of agreeableness significantly impact increased levels of change in attention to productivity-related cues during automatic behavior. Additionally, higher levels of nonreactivity to inner experience significantly reduce the changes in attention to safety-related AOIs while developing automaticity. The findings of this study provide metrics to assess training effectiveness. The findings of this study can be used by practitioners to better understand the positive and negative consequences of developing automaticity, measure workers’ performance more accurately, assess training effectiveness, and personalize learning for workers. In long term, the findings of this study will also aid in improving human-AI teaming since the AI will be better able to understand the cognitive state of its human counterpart and can more precisely adapt to him or her.</p> Construction engineering Construction safety Automaticity Automatic performance Analysis of variance Attention Principal component analysis Support vector machines Binary logistic regression Machine learning Data mining Artificial intelligence Eye-tracking metrics Personal characteristics Personality traits Mindfulness dimensions Five facets of mindfulness Big Five personality traits Relative weight analysis Bootstrapping
139	Collaborating in the electric age: [onto]Riffological experiments in posthumanizing education and theorizing a machinic arts-based research Stevens, Shannon Rae 05 February 2021 (has links) Collaborating in the Electric Age: [onto]Riffological Experiments in Posthumanizing Education and Theorizing a Machinic Arts-Based Research is a study about locating opportunities and entry points for introducing consideration of the nonhuman and posthuman to pedagogical perspectives that are traditionally concerned with human beings and epistemological subjects. The research, herein, engages doings in collaborative effort, during conditions of unprecedented interconnectedness facilitated by the electric age. Steeped in a environment thus created by technologies’ immense ubiquity and influence, this collaboration endeavours to recognize their full research participation, alongside that of humans. This research presents collaboratively conducted, published inquiries that have been coauthored by myself and fellow doctoral candidate Richard Wainwright. Each facilitates, then attempts to articulate ways to decentre the human in educational contexts, beginning with our own human perspectives. As exercises in broadening our considerations of the life forms, matter, and nonhuman entities that surround humanity, this research prompts us to recognize much more than what humanity typically acknowledges as existing, given the anthropocentric frameworks it has constructed. We reorientate the nature of these relationships—posthumanizing them—and in doing so, disrupt our own thinking to work something different than our circumstances have hitherto informed us to consider. We have co-developed a study and conducted research in collaboration with human and nonhuman research participants.Five nationally and internationally published co-authored journal articles, a book chapter, and five intermezzos (short “observational” pieces) comprise this study that explores collaboration and recombinatoriality during “the electric age” (McLuhan, 1969, 10:05). Recognizing humanity’s increasingly inextricable relationships with technologies, this collaboratively conducted study draws into creative assemblage Gilles Deleuze and Félix Guattari’s philosophical concepts; new materialism as cultural theory; the prescient observations and predictions of Marshall McLuhan and a media studies curriculum he co-developed over forty years ago; arts-based research; museum exhibitions; features of music production such as sampling, mashup, remix, and turntabling; among many other notes and tones. A conceptually developed riff mobilizes our inquiries as “plug in and play,” while its academic study is theorized as [onto]Riffology. Ontological shifts beget a machinic arts-based research (MABR) that develops a posthuman critical pedagogy inspired by Negri and Guattari (2010). Collaborating in the Electric Age: [onto]Riffological Experiments in Posthumanizing Education and Theorizing a Machinic Arts-Based Research celebrates collaborativity, discovery, and learning during the electric age. / Graduate / 2023-01-07 Collaborating Electric age [onto]Riffology Posthuman Posthuman education Machinic arts-based research MABR Posthuman critical pedagogy Turntabling Forcework Riff Arts-based research Riffology MashUp Mash up Vancouver Art Gallery VAG Treachery of images Marshall McLuhan City as classroom Hypercity Figure/ground analysis Thanatourism Bootstrapping Remix Collaboration The Anthropocene Project In-Review DeleuzoGuattarian concepts Poststructuralist philosophy Posthumanism Critical pedagogy Recombinatoriality Assemblage Learning event The Jimmy Dore Show Jimmy Dore Nonhuman Speculative realism Post truth era Land acknowledgements Ontologies
140	Temporal Variations in the Compliance of Gas Hydrate Formations Roach, Lisa Aretha Nyala 20 March 2014 (has links) Seafloor compliance is a non-intrusive geophysical method sensitive to the shear modulus of the sediments below the seafloor. A compliance analysis requires the computation of the frequency dependent transfer function between the vertical stress, produced at the seafloor by the ultra low frequency passive source-infra-gravity waves, and the resulting displacement, related to velocity through the frequency. The displacement of the ocean floor is dependent on the elastic structure of the sediments and the compliance function is tuned to different depths, i.e., a change in the elastic parameters at a given depth is sensed by the compliance function at a particular frequency. In a gas hydrate system, the magnitude of the stiffness is a measure of the quantity of gas hydrates present. Gas hydrates contain immense stores of greenhouse gases making them relevant to climate change science, and represent an important potential alternative source of energy. Bullseye Vent is a gas hydrate system located in an area that has been intensively studied for over 2 decades and research results suggest that this system is evolving over time. A partnership with NEPTUNE Canada allowed for the investigation of this possible evolution. This thesis describes a compliance experiment configured for NEPTUNE Canada’s seafloor observatory and its failure. It also describes the use of 203 days of simultaneously logged pressure and velocity time-series data, measured by a Scripps differential pressure gauge, and a Güralp CMG-1T broadband seismometer on NEPTUNE Canada’s seismic station, respectively, to evaluate variations in sediment stiffness near Bullseye. The evaluation resulted in a (- 4.49 x10-3± 3.52 x 10-3) % change of the transfer function of 3rd October, 2010 and represents a 2.88% decrease in the stiffness of the sediments over the period. This thesis also outlines a new algorithm for calculating the static compliance of isotropic layered sediments. SEAFLOOR COMPLIANCE GAS HYDRATES BULLSEYE VENT TREND ANALYSIS SENSITIVITY ANALYSIS EIGENPARAMETER ANALYSIS HYDRATE MASS VARIATION LONG TERM TRENDS IN HYDRATE MASS MODIFIED YORK METHOD MARINE GEOPHYISCS MARINE SEDIMENT NEPTUNE CANADA SHEAR MODULUS GAS HYDRATE CONCENTRATIONS CASCADIA MARGIN MARINE GAS HYDRATES INFRA-GRAVITY WAVES SEISMOMETERS SCRIPPS DIFFERENTIAL PRESSURE GAUGE SCRIPPS DPG ODP SITE 889 BROADBAND SEISMOMETER gPhone DGP calibration Bottom Pressure Recorder Guralp CGM-1T Coherence transfer function bounds f-test bootstrapping wave propagation matrix static solution ocean bottom seismometer tsunami earthquakes Modified York least squares temporal variations linear trend in gas hydrates Power spectral densities 1D compliance solution 1D compliance algorithm seafloor compliance instrumentation Micro-g gravitimeter triple phase boundary equation ultra-low frequency seismics seafloor pressure spectrum seafloor gravity spectrum pacific ocean off-shore British Columbia seafloor observatory static compliance of layered structures geophysics gas hydrate characterization 0373

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