929 resultados para Asymptotic behaviour, Bayesian methods, Mixture models, Overfitting, Posterior concentration
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The main objective of the project is to enhance the already effective health-monitoring system (HUMS) for helicopters by analysing structural vibrations to recognise different flight conditions directly from sensor information. The goal of this paper is to develop a new method to select those sensors and frequency bands that are best for detecting changes in flight conditions. We projected frequency information to a 2-dimensional space in order to visualise flight-condition transitions using the Generative Topographic Mapping (GTM) and a variant which supports simultaneous feature selection. We created an objective measure of the separation between different flight conditions in the visualisation space by calculating the Kullback-Leibler (KL) divergence between Gaussian mixture models (GMMs) fitted to each class: the higher the KL-divergence, the better the interclass separation. To find the optimal combination of sensors, they were considered in pairs, triples and groups of four sensors. The sensor triples provided the best result in terms of KL-divergence. We also found that the use of a variational training algorithm for the GMMs gave more reliable results.
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This paper focuses on the development of methods and cascade of models for flood monitoring and forecasting and its implementation in Grid environment. The processing of satellite data for flood extent mapping is done using neural networks. For flood forecasting we use cascade of models: regional numerical weather prediction (NWP) model, hydrological model and hydraulic model. Implementation of developed methods and models in the Grid infrastructure and related projects are discussed.
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2000 Mathematics Subject Classification: 60F05, 60B10.
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2000 Mathematics Subject Classification: 05A16, 05A17.
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2000 Mathematics Subject Classification: 30C40, 30D50, 30E10, 30E15, 42C05.
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A szerzők ebben a tanulmányukban az információs és kommunikációs technológiai (továbbiakban IKT) eszközök közül az asztali számítógépekkel (desktopok), laptopokkal (notebookok és netbookok), táblagépekkel és okostelefonokkal foglalkoznak. Az IKT-eszközök elterjedtségének vizsgálatánál meghatározó szerepet játszik a technológia jelenléte mellett a társadalom befogadóképessége. A technológia és társadalom kapcsolatát különböző módszerekkel és modellekkel mutatják be, melyek indokolják ezen eszközök növekvő használatának szükségességét. Ebben a tanulmányban a modellekből és a felmérésekből összeállított tényezők beépítésével és az általuk feldolgozott kérdőívek elemzése által kirajzolódnak minták és olyan összefüggések, amelyek magyarázatot adhatnak a különböző eszközhasználat okainak megértésére. _____ In their study the authors deal with the desktop computers (Desktop), laptops (notebooks and netbooks), smartphones and tablet machines among of information and communication technology (hereinafter referred to as ICT) tools. The capacity of society is one of the key elements in the examination of spread of ICT. The relationship between technology and society is presented with different methods and models that are justified by the need for increasing the use of these devices. In this paper such samples and correlations are emerged of the models and surveys, which may explain the reasons for understanding of the different tool use.
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Valuable genetic variation for bean breeding programs is held within the common bean secondary gene pool which consists of Phaseolus albescens, P. coccineus, P. costaricensis, and P. dumosus. However, the use of close relatives for bean improvement is limited due to the lack of knowledge about genetic variation and genetic plasticity of many of these species. Characterisation and analysis of the genetic diversity is necessary among beans' wild relatives; in addition, conflicting phylogenies and relationships need to be understood and a hypothesis of a hybrid origin of P. dumosus needs to be tested. This thesis research was orientated to generate information about the patterns of relationships among the common bean secondary gene pool, with particular focus on the species Phaseolus dumosus. This species displays a set of characteristics of agronomic interest, not only for the direct improvement of common bean but also as a source of valuable genes for adaptation to climate change. Here I undertake the first comprehensive study of the genetic diversity of P. dumosus as ascertained from both nuclear and chloroplast genome markers. A germplasm collection of the ancestral forms of P. dumosus together with wild, landrace and cultivar representatives of all other species of the common bean secondary gene pool, were used to analyse genetic diversity, phylogenetic relationships and structure of P. dumosus. Data on molecular variation was generated from sequences of cpDNA loci accD-psaI spacer, trnT-trnL spacer, trnL intron and rps14-psaB spacer and from the nrDNA the ITS region. A whole genome DArT array was developed and used for the genotyping of P. dumosus and its closes relatives. 4208 polymorphic markers were generated in the DArT array and from those, 742 markers presented a call rate >95% and zero discordance. DArT markers revealed a moderate genetic polymorphism among P. dumosus samples (13% of polymorphic loci), while P. coccineus presented the highest level of polymorphism (88% of polymorphic loci). At the cpDNA one ancestral haplotype was detected among all samples of all species in the secondary genepool. The ITS region of P. dumosus revealed high homogeneity and polymorphism bias to P. coccineus genome. Phylogenetic reconstructions made with Maximum likelihood and Bayesian methods confirmed previously reported discrepancies among the nuclear and chloroplast genomes of P. dumosus. The outline of relationships by hybridization networks displayed a considerable number of interactions within and between species. This research provides compelling evidence that P. dumosus arose from hybridisation between P. vulgaris and P. coccineus and confirms that P. costaricensis has likely been involved in the genesis or backcrossing events (or both) in the history of P. dumosus. The classification of the specie P. persistentus was analysed based on cpDNA and ITS sequences, the results found this species to be highly related to P. vulgaris but not too similar to P. leptostachyus as previously proposed. This research demonstrates that wild types of the secondary genepool carry a significant genetic variation which makes this a valuable genetic resource for common bean improvement. The DArT array generated in this research is a valuable resource for breeding programs since it has the potential to be used in several approaches including genotyping, discovery of novel traits, mapping and marker-trait associations. Efforts should be made to search for potential populations of P. persistentus and to increase the collection of new populations of P. dumosus, P. albescens and P. costaricensis that may provide valuable traits for introgression into common bean and other Phaseolus crops.
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Brain injury due to lack of oxygen or impaired blood flow around the time of birth, may cause long term neurological dysfunction or death in severe cases. The treatments need to be initiated as soon as possible and tailored according to the nature of the injury to achieve best outcomes. The Electroencephalogram (EEG) currently provides the best insight into neurological activities. However, its interpretation presents formidable challenge for the neurophsiologists. Moreover, such expertise is not widely available particularly around the clock in a typical busy Neonatal Intensive Care Unit (NICU). Therefore, an automated computerized system for detecting and grading the severity of brain injuries could be of great help for medical staff to diagnose and then initiate on-time treatments. In this study, automated systems for detection of neonatal seizures and grading the severity of Hypoxic-Ischemic Encephalopathy (HIE) using EEG and Heart Rate (HR) signals are presented. It is well known that there is a lot of contextual and temporal information present in the EEG and HR signals if examined at longer time scale. The systems developed in the past, exploited this information either at very early stage of the system without any intelligent block or at very later stage where presence of such information is much reduced. This work has particularly focused on the development of a system that can incorporate the contextual information at the middle (classifier) level. This is achieved by using dynamic classifiers that are able to process the sequences of feature vectors rather than only one feature vector at a time.
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Objective: To estimate the absolute treatment effect of statin therapy on major adverse cardiovascular events (MACE; myocardial infarction, stroke and vascular death) for the individual patient aged C70 years. Methods: Prediction models for MACE were derived in patients aged C70 years with (n = 2550) and without (n = 3253) vascular disease from the ‘‘PROspective Study of Pravastatin in Elderly at Risk’’ (PROSPER) trial and validated in the ‘‘Secondary Manifestations of ARTerial disease’’ (SMART) cohort study (n = 1442) and the ‘‘Anglo-Scandinavian Cardiac Outcomes Trial-Lipid Lowering Arm’’ (ASCOT-LLA) trial (n = 1893), respectively, using competing risk analysis. Prespecified predictors were various clinical characteristics including statin treatment. Individual absolute risk reductions (ARRs) for MACE in 5 and 10 years were estimated by subtracting ontreatment from off-treatment risk. Results: Individual ARRs were higher in elderly patients with vascular disease [5-year ARRs: median 5.1 %, interquartile range (IQR) 4.0–6.2 %, 10-year ARRs: median 7.8 %, IQR 6.8–8.6 %] than in patients without vascular disease (5-year ARRs: median 1.7 %, IQR 1.3–2.1 %, 10-year ARRs: 2.9 %, IQR 2.3–3.6 %). Ninetyeight percent of patients with vascular disease had a 5-year ARR C2.0 %, compared to 31 % of patients without vascular disease. Conclusions: With a multivariable prediction model the absolute treatment effect of a statin on MACE for individual elderly patients with and without vascular disease can be quantified. Because of high ARRs, treating all patients is more beneficial than prediction-based treatment for secondary prevention of MACE. For primary prevention of MACE, the prediction model can be used to identify those patients who benefit meaningfully from statin therapy.
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Background: Largely due to low availability and uptake of screening in low- and middle-income countries, cervical cancer is the second ranked cancer among women in these countries. This is a tragedy because cervical cancer is one of the most preventable carcinomas. This thesis will investigate behaviour change methods, which capitalize on the recent exponential increase in ownership of mobile phones in Tanzania, to increase uptake of cervical cancer screening (CCS) in the Kilimanjaro region of Tanzania. Objectives: 1) To evaluate the effectiveness of behaviour change messages delivered via short message service (SMS) on the uptake of CCS in the Kilimanjaro region; 2) to evaluate the effectiveness of a transportation eVoucher on the uptake of CCS in the Kilimanjaro region; 3) to explore characteristics associated with CCS uptake in the Kilimanjaro region; and 4) to determine the attitudes towards and perceived benefit of behaviour change SMS messages and eVouchers intended to increase uptake of CCS. Methods: In the Kilimanjaro Region, 853 women participated in a randomized controlled trial. Baseline data was collected through self-report through systematic stratified random sampling. Participants were randomized to one of three groups: a control group, a group receiving behaviour change messages delivered via SMS, or a group receiving a travel eVoucher and identical SMS as the SMS group. A fieldworker recorded participants attending screening at the CCS clinics and administered a post-screening survey. The follow-up period was two months from the time of the participant’s enrolment. Logistic regression (both for the combined and stratified data sets) was used to determine associations between the behaviour change interventions, baseline characteristics and cervical cancer screening uptake. Results: All participants receiving SMS messages (SMS or eVoucher group) were more likely to attend cervical cancer screening in comparison with the control group. 83% of participants who attended screening shared the information contained in the messages with others. Conclusions: Behaviour change messages delivered via SMS and transportation eVouchers have the potential to increase uptake of cervical cancer screening in the Kilimanjaro region of Tanzania. Harnessing this potential will require implementing these interventions alongside other methods to achieve maximum impact.
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Esta tese de mestrado explora a gestão da inovação nas organizações desportivas. Pretende-se determinar como se inova nos clubes desportivos e determinar os processos, métodos e modelos aplicados e a forma de fomentação da inovação nas organizações desportivas. A avaliação da reação do meio desportivo à inovação é também analisada. Num primeiro momento procura-se as definições de gestão de desporto e de inovação e é realizado um enquadramento da gestão da inovação nas organizações desportivas e na gestão de desporto, através de pesquisas bibliográficas (enquadramento teórico). Na segunda etapa da tese, são realizadas entrevistas a seis coordenadores de formação de clubes de futebol com o objetivo de determinar que processos utilizam para inovar e como é feita a promoção da inovação nessas organizações. Após a análise das entrevistas são apresentadas as conclusões tendo em conta as características das organizações e compara-se as ideias apresentadas no enquadramento teórico com a prática apresentada nas entrevistas.
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While humans can easily segregate and track a speaker's voice in a loud noisy environment, most modern speech recognition systems still perform poorly in loud background noise. The computational principles behind auditory source segregation in humans is not yet fully understood. In this dissertation, we develop a computational model for source segregation inspired by auditory processing in the brain. To support the key principles behind the computational model, we conduct a series of electro-encephalography experiments using both simple tone-based stimuli and more natural speech stimulus. Most source segregation algorithms utilize some form of prior information about the target speaker or use more than one simultaneous recording of the noisy speech mixtures. Other methods develop models on the noise characteristics. Source segregation of simultaneous speech mixtures with a single microphone recording and no knowledge of the target speaker is still a challenge. Using the principle of temporal coherence, we develop a novel computational model that exploits the difference in the temporal evolution of features that belong to different sources to perform unsupervised monaural source segregation. While using no prior information about the target speaker, this method can gracefully incorporate knowledge about the target speaker to further enhance the segregation.Through a series of EEG experiments we collect neurological evidence to support the principle behind the model. Aside from its unusual structure and computational innovations, the proposed model provides testable hypotheses of the physiological mechanisms of the remarkable perceptual ability of humans to segregate acoustic sources, and of its psychophysical manifestations in navigating complex sensory environments. Results from EEG experiments provide further insights into the assumptions behind the model and provide motivation for future single unit studies that can provide more direct evidence for the principle of temporal coherence.
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Acompanha: Dupla-hélice: a construção de um conhecimento
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The objective of this study was to gain an understanding of the effects of population heterogeneity, missing data, and causal relationships on parameter estimates from statistical models when analyzing change in medication use. From a public health perspective, two timely topics were addressed: the use and effects of statins in populations in primary prevention of cardiovascular disease and polypharmacy in older population. Growth mixture models were applied to characterize the accumulation of cardiovascular and diabetes medications among apparently healthy population of statin initiators. The causal effect of statin adherence on the incidence of acute cardiovascular events was estimated using marginal structural models in comparison with discrete-time hazards models. The impact of missing data on the growth estimates of evolution of polypharmacy was examined comparing statistical models under different assumptions for missing data mechanism. The data came from Finnish administrative registers and from the population-based Geriatric Multidisciplinary Strategy for the Good Care of the Elderly study conducted in Kuopio, Finland, during 2004–07. Five distinct patterns of accumulating medications emerged among the population of apparently healthy statin initiators during two years after statin initiation. Proper accounting for time-varying dependencies between adherence to statins and confounders using marginal structural models produced comparable estimation results with those from a discrete-time hazards model. Missing data mechanism was shown to be a key component when estimating the evolution of polypharmacy among older persons. In conclusion, population heterogeneity, missing data and causal relationships are important aspects in longitudinal studies that associate with the study question and should be critically assessed when performing statistical analyses. Analyses should be supplemented with sensitivity analyses towards model assumptions.
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Atualmente, sensores remotos e computadores de alto desempenho estão sendo utilizados como instrumentos principais na coleta e produção de dados oceanográficos. De posse destes dados, é possível realizar estudos que permitem simular e prever o comportamento do oceano por meio de modelos numéricos regionais. Dentre os fatores importantes no estudo da oceanografia, podem ser destacados àqueles referentes aos impactos ambientais, de contaminação antrópica, utilização de energias renováveis, operações portuárias e etc. Contudo, devido ao grande volume de dados gerados por instituições ambientais, na forma de resultados de modelos globais como o HYCOM (Hybrid Coordinate Ocean Model) e dos programas de Reanalysis da NOAA (National Oceanic and Atmospheric Administration), torna-se necessária a criação de rotinas computacionais para realizar o tratamento de condições iniciais e de contorno, de modo que possam ser aplicadas a modelos regionais como o TELEMAC3D (www.opentelemac.org). Problemas relacionados a baixa resolução, ausência de dados e a necessidade de interpolação para diferentes malhas ou sistemas de coordenadas verticais, tornam necessária a criação de um mecanismo computacional que realize este tratamento adequadamente. Com isto, foram desenvolvidas rotinas na linguagem de programação Python, empregando interpoladores de vizinho mais próximo, de modo que, a partir de dados brutos dos modelos HYCOM e do programa de Reanalysis da NOAA, foram preparadas condições iniciais e de contorno para a realização de uma simulação numérica teste. Estes resultados foram confrontados com outro resultado numérico onde, as condições foram construídas a partir de um método de interpolação mais sofisticado, escrita em outra linguagem, e que já vem sendo utilizada no laboratório. A análise dos resultados permitiu concluir que, a rotina desenvolvida no âmbito deste trabalho, funciona adequadamente para a geração de condições iniciais e de contorno do modelo TELEMAC3D. Entretanto, um interpolador mais sofisticado deve ser desenvolvido de forma a aumentar a qualidade nas interpolações, otimizar o custo computacional, e produzir condições que sejam mais realísticas para a utilização do modelo TELEMAC3D.