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Relevant bibliographies by topics / Continuous Time Bayesian Network / Dissertations / Theses

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Dissertations / Theses on the topic 'Continuous Time Bayesian Network'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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1

CODECASA, DANIELE. "Continuous time bayesian network classifiers." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2014. http://hdl.handle.net/10281/80691.

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Streaming data are relevant to finance, computer science, and engineering, while they are becoming increasingly important to medicine and biology. Continuous time Bayesian networks are designed for analyzing efficiently multivariate streaming data, exploiting the conditional independencies in continuous time homogeneous Markov processes. Continuous time Bayesian network classifiers are a specialization of continuous time Bayesian networks designed for multivariate streaming data classification when time duration of events matters and the class occurs in the future. Continuous time Bayesian net

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Nodelman, Uri D. "Continuous time bayesian networks /." May be available electronically:, 2007. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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Fan, Yu. "Continuous time Bayesian Network approximate inference and social network applications." Diss., [Riverside, Calif.] : University of California, Riverside, 2009. http://proquest.umi.com/pqdweb?index=0&did=1957308751&SrchMode=2&sid=1&Fmt=2&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1268330625&clientId=48051.

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Thesis (Ph. D.)--University of California, Riverside, 2009.<br>Includes abstract. Title from first page of PDF file (viewed March 8, 2010). Available via ProQuest Digital Dissertations. Includes bibliographical references (p. 130-133). Also issued in print.

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ACERBI, ENZO. "Continuos time Bayesian networks for gene networks reconstruction." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2014. http://hdl.handle.net/10281/52709.

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Dynamic aspects of gene regulatory networks are typically investigated by measuring system variables at multiple time points. Current state-of-the-art computational approaches for reconstructing gene networks directly build on such data, making a strong assumption that the system evolves in a synchronous fashion at fixed points in time. However, nowadays omics data are being generated with increasing time course granularity. Thus, modellers now have the possibility to represent the system as evolving in continuous time and improve the models' expressiveness. Continuous time Bayesian network

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VILLA, SIMONE. "Continuous Time Bayesian Networks for Reasoning and Decision Making in Finance." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2015. http://hdl.handle.net/10281/69953.

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L'analisi dell'enorme quantità di dati finanziari, messi a disposizione dai mercati elettronici, richiede lo sviluppo di nuovi modelli e tecniche per estrarre efficacemente la conoscenza da utilizzare in un processo decisionale informato. Lo scopo della tesi concerne l'introduzione di modelli grafici probabilistici utilizzati per il ragionamento e l'attività decisionale in tale contesto. Nella prima parte della tesi viene presentato un framework che utilizza le reti Bayesiane per effettuare l'analisi e l'ottimizzazione di portafoglio in maniera olistica. In particolare, esso sfrutta, da un l

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GATTI, ELENA. "Graphical models for continuous time inference and decision making." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2011. http://hdl.handle.net/10281/19575.

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Reasoning about evolution of system in time is both an important and challenging task. We are interested in probability distributions over time of events where often observations are irregularly spaced over time. Probabilistic models have been widely used to accomplish this task but they have some limits. Indeed, Hidden Markov Models and Dynamic Bayesian Networks in general require the specification of a time granularity between consecutive observations. This requirement leads to computationally inefficient learning and inference procedures when the adopted time granularity is finer than the

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Alharbi, Randa. "Bayesian inference for continuous time Markov chains." Thesis, University of Glasgow, 2019. http://theses.gla.ac.uk/40972/.

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Continuous time Markov chains (CTMCs) are a flexible class of stochastic models that have been employed in a wide range of applications from timing of computer protocols, through analysis of reliability in engineering, to models of biochemical networks in molecular biology. These models are defined as a state system with continuous time transitions between the states. Extensive work has been historically performed to enable convenient and flexible definition, simulation, and analysis of continuous time Markov chains. This thesis considers the problem of Bayesian parameter inference on these mo

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Parton, Alison. "Bayesian inference for continuous-time step-and-turn movement models." Thesis, University of Sheffield, 2018. http://etheses.whiterose.ac.uk/20124/.

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This thesis concerns the statistical modelling of animal movement paths given observed GPS locations. With observations being in discrete time, mechanistic models of movement are often formulated as such. This popularity remains despite an inability to compare analyses through scale invariance and common problems handling irregularly timed observations. A natural solution is to formulate in continuous time, yet uptake of this has been slow, often excused by a difficulty in interpreting the ‘instantaneous’ parameters associated with a continuous-time model. The aim here was to bolster usage by

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Elshamy, Wesam Samy. "Continuous-time infinite dynamic topic models." Diss., Kansas State University, 2012. http://hdl.handle.net/2097/15176.

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Doctor of Philosophy<br>Department of Computing and Information Sciences<br>William Henry Hsu<br>Topic models are probabilistic models for discovering topical themes in collections of documents. In real world applications, these models provide us with the means of organizing what would otherwise be unstructured collections. They can help us cluster a huge collection into different topics or find a subset of the collection that resembles the topical theme found in an article at hand. The first wave of topic models developed were able to discover the prevailing topics in a big collection of

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Acciaroli, Giada. "Calibration of continuous glucose monitoring sensors by time-varying models and Bayesian estimation." Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3425746.

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Minimally invasive continuous glucose monitoring (CGM) sensors are wearable medical devices that provide frequent (e.g., 1-5 min sampling rate) real-time measurements of glucose concentration for several consecutive days. This can be of great help in the daily management of diabetes. Most of the CGM systems commercially available today have a wire-based electrochemical sensor, usually placed in the subcutaneous tissue, which measures a "raw" electrical current signal via a glucose-oxidase electrochemical reaction. Observations of the raw electrical signal are frequently revealed by the sensor

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Murray, Lawrence. "Bayesian learning of continuous time dynamical systems with applications in functional magnetic resonance imaging." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/4157.

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Temporal phenomena in a range of disciplines are more naturally modelled in continuous-time than coerced into a discrete-time formulation. Differential systems form the mainstay of such modelling, in fields from physics to economics, geoscience to neuroscience. While powerful, these are fundamentally limited by their determinism. For the purposes of probabilistic inference, their extension to stochastic differential equations permits a continuous injection of noise and uncertainty into the system, the model, and its observation. This thesis considers Bayesian filtering for state and parameter

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Ratiu, Alin. "Continuous time signal processing for wake-up radios." Thesis, Lyon, INSA, 2015. http://www.theses.fr/2015ISAL0078/document.

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La consommation des systèmes de communication pour l'IoT peut être réduite grâce à un nouveau paradigme de réception radio. La technique consiste à ajouter un récepteur supplémentaire à chaque noeud IoT, appelé Wake Up Radio (WU-RX). Le rôle du WU-RX est de surveiller le canal de communication et de réveiller le récepteur principal (aussi appelé récepteur de données) lors de la réception d'une demande de communication. Une analyse des implémentations des WU-RX existants montre que les systèmes de l'état de l'art sont suffisamment sensibles par rapport aux récepteurs de données classiques mais

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Arastuie, Makan. "Generative Models of Link Formation and Community Detection in Continuous-Time Dynamic Networks." University of Toledo / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1596718772873086.

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Murphy, James Kevin. "Hidden states, hidden structures : Bayesian learning in time series models." Thesis, University of Cambridge, 2014. https://www.repository.cam.ac.uk/handle/1810/250355.

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This thesis presents methods for the inference of system state and the learning of model structure for a number of hidden-state time series models, within a Bayesian probabilistic framework. Motivating examples are taken from application areas including finance, physical object tracking and audio restoration. The work in this thesis can be broadly divided into three themes: system and parameter estimation in linear jump-diffusion systems, non-parametric model (system) estimation and batch audio restoration. For linear jump-diffusion systems, efficient state estimation methods based on the vari

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Sahin, Elvan. "Discrete-Time Bayesian Networks Applied to Reliability of Flexible Coping Strategies of Nuclear Power Plants." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/103817.

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The Fukushima Daiichi accident prompted the nuclear community to find a new solution to reduce the risky situations in nuclear power plants (NPPs) due to beyond-design-basis external events (BDBEEs). An implementation guide for diverse and flexible coping strategies (FLEX) has been presented by Nuclear Energy Institute (NEI) to manage the challenge of BDBEEs and to enhance reactor safety against extended station blackout (SBO). To assess the effectiveness of FLEX strategies, probabilistic risk assessment (PRA) methods can be used to calculate the reliability of such systems. Due to the uniquen

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Burchett, Woodrow. "Improving the Computational Efficiency in Bayesian Fitting of Cormack-Jolly-Seber Models with Individual, Continuous, Time-Varying Covariates." UKnowledge, 2017. http://uknowledge.uky.edu/statistics_etds/27.

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The extension of the CJS model to include individual, continuous, time-varying covariates relies on the estimation of covariate values on occasions on which individuals were not captured. Fitting this model in a Bayesian framework typically involves the implementation of a Markov chain Monte Carlo (MCMC) algorithm, such as a Gibbs sampler, to sample from the posterior distribution. For large data sets with many missing covariate values that must be estimated, this creates a computational issue, as each iteration of the MCMC algorithm requires sampling from the full conditional distributions of

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Yang, Jianxiang. "Time-delay neural network systems for stop and unstop phoneme discrimination in continuous speech signal." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/MQ31661.pdf.

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Wu, Xinying. "Reliability Assessment of a Continuous-state Fuel Cell Stack System with Multiple Degrading Components." Ohio University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1556794664723115.

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Arthur, Jacob D. "Enhanced Prediction of Network Attacks Using Incomplete Data." NSUWorks, 2017. http://nsuworks.nova.edu/gscis_etd/1020.

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For years, intrusion detection has been considered a key component of many organizations’ network defense capabilities. Although a number of approaches to intrusion detection have been tried, few have been capable of providing security personnel responsible for the protection of a network with sufficient information to make adjustments and respond to attacks in real-time. Because intrusion detection systems rarely have complete information, false negatives and false positives are extremely common, and thus valuable resources are wasted responding to irrelevant events. In order to provide bette

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Lebre, Sophie. "Stochastic process analysis for Genomics and Dynamic Bayesian Networks inference." Phd thesis, Université d'Evry-Val d'Essonne, 2007. http://tel.archives-ouvertes.fr/tel-00260250.

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This thesis is dedicated to the development of statistical and computational methods for the analysis of DNA sequences and gene expression time series.<br /><br />First we study a parsimonious Markov model called Mixture Transition Distribution (MTD) model which is a mixture of Markovian transitions. The overly high number of constraints on the parameters of this model hampers the formulation of an analytical expression of the Maximum Likelihood Estimate (MLE). We propose to approach the MLE thanks to an EM algorithm. After comparing the performance of this algorithm to results from the litter

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Van, Lierde Boris. "Developing Box-Pushing Behaviours Using Evolutionary Robotics." Thesis, Högskolan Dalarna, Datateknik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:du-6250.

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The context of this report and the IRIDIA laboratory are described in the preface. Evolutionary Robotics and the box-pushing task are presented in the introduction.The building of a test system supporting Evolutionary Robotics experiments is then detailed. This system is made of a robot simulator and a Genetic Algorithm. It is used to explore the possibility of evolving box-pushing behaviours. The bootstrapping problem is explained, and a novel approach for dealing with it is proposed, with results presented.Finally, ideas for extending this approach are presented in the conclusion.

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Junuthula, Ruthwik Reddy. "Modeling, Evaluation and Analysis of Dynamic Networks for Social Network Analysis." University of Toledo / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1544819215833249.

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Webb, Jared Anthony. "A Topics Analysis Model for Health Insurance Claims." BYU ScholarsArchive, 2013. https://scholarsarchive.byu.edu/etd/3805.

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Mathematical probability has a rich theory and powerful applications. Of particular note is the Markov chain Monte Carlo (MCMC) method for sampling from high dimensional distributions that may not admit a naive analysis. We develop the theory of the MCMC method from first principles and prove its relevance. We also define a Bayesian hierarchical model for generating data. By understanding how data are generated we may infer hidden structure about these models. We use a specific MCMC method called a Gibbs' sampler to discover topic distributions in a hierarchical Bayesian model called Topics Ov

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Kramer, Gregory Robert. "An analysis of neutral drift's effect on the evolution of a CTRNN locomotion controller with noisy fitness evaluation." Wright State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=wright1182196651.

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Vigraham, Saranyan A. "An Analog Evolvable Hardware Device for Active Control." Wright State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=wright1195506953.

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Tugui, Catalin Adrian. "Design Methodology for High-performance Circuits Based on Automatic Optimization Methods." Thesis, Supélec, 2013. http://www.theses.fr/2013SUPL0002/document.

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Ce travail de thèse porte sur le développement d’une méthodologie efficace pour la conception analogique, des algorithmes et des outils correspondants qui peuvent être utilisés dans la conception dynamique de fonctions linéaires à temps continu. L’objectif principal est d’assurer que les performances pour un système complet peuvent être rapidement investiguées, mais avec une précision comparable aux évaluations au niveau transistor.Une première direction de recherche a impliqué le développement de la méthodologie de conception basée sur le processus d'optimisation automatique de cellules au ni

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BARTHELMES, VERENA MARIE. "Impact of Occupant Behaviour (OB) on building energy use and thermal comfort: From stochastic modelling and occupant profiling to interdisciplinary user engagement." Doctoral thesis, Politecnico di Torino, 2019. http://hdl.handle.net/11583/2748936.

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Tribastone, Mirco. "Scalable analysis of stochastic process algebra models." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/4629.

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The performance modelling of large-scale systems using discrete-state approaches is fundamentally hampered by the well-known problem of state-space explosion, which causes exponential growth of the reachable state space as a function of the number of the components which constitute the model. Because they are mapped onto continuous-time Markov chains (CTMCs), models described in the stochastic process algebra PEPA are no exception. This thesis presents a deterministic continuous-state semantics of PEPA which employs ordinary differential equations (ODEs) as the underlying mathematics for the p

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Tagscherer, Michael. "Dynamische Neuronale Netzarchitektur für Kontinuierliches Lernen." Doctoral thesis, Universitätsbibliothek Chemnitz, 2001. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200100725.

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Am Beispiel moderner Automatisierungssysteme wird deutlich, dass die Steuerung und optimale Führung der technischen Prozesse eng verbunden ist mit der Verfügbarkeit eines möglichst exakten Prozessmodells. Steht jedoch kein Modell des zu steuernden Systems zur Verfügung oder ist das System nicht ausreichend genau analytisch beschreibbar, muss ein adäquates Modell auf der Basis von Beobachtungen (Messdaten) abgeleitet werden. Erschwerend wirken sich hierbei starke Nichtlinearitäten sowie der zeitvariante Charakter der zu identifizierenden Systeme aus. Die Zeitvarianz, beispielsweise durch Alteru

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Kocour, Martin. "Automatic Speech Recognition System Continually Improving Based on Subtitled Speech Data." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-399164.

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V dnešnej dobe systémy rozpoznávania reči s veľkým slovníkom dosahujú pomerne vysoké presnosti. Za ich výsledkami však často stoja desiatky ba až stovky hodín manuálne oanotovaných trénovacích dát. Takéto dáta sú často bežne nedostupné alebo pre požadovaný jazyk vôbec neexistujú. Možným riešením je použitie bežne dostupných no menej kvalitných audiovizuálnych dát. Táto práca sa zaoberá technikou zpracovania práve takýchto dát a ich použitím pre trénovanie akustických modelov. Ďalej táto práca pojednáva o možnom využití týchto dát pre kontinuálne vylepšovanie modelov, kedže tieto dáta sú prakti

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Gannon, Mark Andrew. "Passeios aleatórios em redes finitas e infinitas de filas." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-16102017-154842/.

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Um conjunto de modelos compostos de redes de filas em grades finitas servindo como ambientes aleatorios para um ou mais passeios aleatorios, que por sua vez podem afetar o comportamento das filas, e desenvolvido. Duas formas de interacao entre os passeios aleatorios sao consideradas. Para cada modelo, e provado que o processo Markoviano correspondente e recorrente positivo e reversivel. As equacoes de balanceamento detalhado sao analisadas para obter a forma funcional da medida invariante de cada modelo. Em todos os modelos analisados neste trabalho, a medida invariante em uma grade finita tem

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Gönner, Lorenz, Julien Vitay, and Fred Hamker. "Predictive Place-Cell Sequences for Goal-Finding Emerge from Goal Memory and the Cognitive Map: A Computational Model." Universitätsbibliothek Chemnitz, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-230378.

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Hippocampal place-cell sequences observed during awake immobility often represent previous experience, suggesting a role in memory processes. However, recent reports of goals being overrepresented in sequential activity suggest a role in short-term planning, although a detailed understanding of the origins of hippocampal sequential activity and of its functional role is still lacking. In particular, it is unknown which mechanism could support efficient planning by generating place-cell sequences biased toward known goal locations, in an adaptive and constructive fashion. To address these quest

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Adeli, Mohammad. "Recherche de caractéristiques sonores et de correspondances audiovisuelles pour des systèmes bio-inspirés de substitution sensorielle de l'audition vers la vision." Thèse, Université de Sherbrooke, 2016. http://hdl.handle.net/11143/8194.

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Résumé: Les systèmes de substitution sensorielle convertissent des stimuli d’une modalité sensorielle en des stimuli d’une autre modalité. Ils peuvent fournir les moyens pour les personnes handicapées de percevoir des stimuli d’une modalité défectueuse par une autre modalité. Le but de ce projet de recherche était d’étudier des systèmes de substitution de l’audition vers la vision. Ce type de substitution n’est pas bien étudié probablement en raison de la complexité du système auditif et des difficultés résultant de la désadaptation entre les sons audibles qui peuvent changer avec des fréquenc

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(9847832), Dawei Zhang. "Network-based output tracking control for continuous-time systems." Thesis, 2012. https://figshare.com/articles/thesis/Network-based_output_tracking_control_for_continuous-time_systems/13463123.

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Jia, Jin. "Object highlighting : real-time boundary detection using a Bayesian network." Thesis, 2004. http://hdl.handle.net/1957/30045.

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Image segmentation continues to be a fundamental problem in computer vision and image understanding. In this thesis, we present a Bayesian network that we use for object boundary detection in which the MPE (most probable explanation) before any evidence can produce multiple non-overlapping, non-self-intersecting closed contours and the MPE with evidence where one or more connected boundary points are provided produces a single non-self-intersecting, closed contour that accurately defines an object's boundary. We also present a near-linear-time algorithm that determines the MPE by computing the

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Walker, James. "Bayesian Inference and Model Selection for Partially-Observed, Continuous-Time, Stochastic Epidemic Models." Thesis, 2019. http://hdl.handle.net/2440/124703.

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Emerging infectious diseases are an ongoing threat to the health of populations around the world. In response, countries such as the USA, UK and Australia, have outlined data collection protocols to surveil these novel diseases. One of the aims of these data collection protocols is to characterise the disease in terms of transmissibility and clinical severity in order to inform an appropriate public health response. This kind of data collection protocol is yet to be enacted in Australia, but such a protocol is likely to be tested during a seasonal in uenza ( u) outbreak in the next few years.

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Lin, Yi-San, and 林怡姍. "A Bayesian-Network Risk Assessment Incorporating Human Factors Based on Continuous Fuzzy Set Theory." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/10170624603696988034.

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碩士<br>國立臺灣海洋大學<br>商船學系所<br>100<br>Recently, maritime accidents emerge in an endless stream, and the causes of the maritime accidents result largely from human factors. Thus, a comprehensive risk assessment considering human elements needs to be developed in advance in order to reduce the risks of disasters. It is, however, difficult to acquire sufficient and historical data in the maritime industry, hence expert judgment is a critical reference sources. Fuzzy set theory is one of the methods often applied to convert the expert judgment into numerical values. How to properly express the real th

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BARONE, ROSARIO. "MCMC methods for continuous time multi-state models and high dimensional copula models." Doctoral thesis, 2020. http://hdl.handle.net/11573/1365737.

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In this Thesis we propose Markov chain Monte Carlo (MCMC) methods for several classes of models. We consider both parametric and nonparametric Bayesian approaches proposing either alternatives in computation to already existent methods or new computational tools. In particular, we consider continuous time multi-state models (CTMSM), that is a class of stochastic processes useful for modelling several phenomena evolving continuously in time, with a finite number of states. Inference for these models is straightforward if the processes are fully observed, while it presents some computational d

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Chen, Jyun-Lin, and 陳俊霖. "Cost and Survival Prognosis Model for Lung Cancer Patients: A Continuous Gaussian Bayesian Network Approach." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/16087186742646333410.

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碩士<br>國立臺灣科技大學<br>工業管理系<br>103<br>In Taiwan, cancer has always become one of the leading cause of death since 1982. Ministry of Health and Welfare mortality statistics showed that 44,791 people died of cancer in 2013, accounting for 29 percent of all deaths. Furthermore, lung cancer is the leading cause of mortalities no matter in men or women in 2013, which accounted 19.77% of all cancer deaths. The resources for lung cancer patients’ medical care should be considered much deep. Risk adjustment deals with the issues of equity and efficiency separately by establishing a risk equalization, whic

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謝明佳. "A Bayesian Study on the Plant-Capture Approach for Population Size Estimation in Continuous Time." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/14406744993162482411.

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Robinson, Joshua Westly. "Modeling Time-Varying Networks with Applications to Neural Flow and Genetic Regulation." Diss., 2010. http://hdl.handle.net/10161/3109.

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<p>Many biological processes are effectively modeled as networks, but a frequent assumption is that these networks do not change during data collection. However, that assumption does not hold for many phenomena, such as neural growth during learning or changes in genetic regulation during cell differentiation. Approaches are needed that explicitly model networks as they change in time and that characterize the nature of those changes.</p><p>In this work, we develop a new class of graphical models in which the conditional dependence structure of the underlying data-generation process is permi

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Lemp, Jason David. "Capturing random utility maximization behavior in continuous choice data : application to work tour scheduling." 2009. http://hdl.handle.net/2152/18643.

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Recent advances in travel demand modeling have concentrated on adding behavioral realism by focusing on an individual’s activity participation. And, to account for trip-chaining, tour-based methods are largely replacing trip-based methods. Alongside these advances and innovations in dynamic traffic assignment (DTA) techniques, however, time-of-day (TOD) modeling remains an Achilles’ heel. As congestion worsens and operators turn to variable road pricing, sensors are added to networks, cell phones are GPS-enabled, and DTA techniques become practical, accurate time-of-day forecasts become criti

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Chuang, Yin Yin, and 莊茵茵. "Using Bayesian network for analyzing cycle time to find key influenced factors and Constructing cycle time evolution table to predict cycle time in PCB industry with case studies." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/qj262q.

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碩士<br>國立清華大學<br>工業工程與工程管理學系<br>105<br>Competition in high tech industry forces the field to consider the ways to monitor the duration of cycle time and to keep produce efficiency within a budget. Particularly, Printed Circuit Board (PCB) industry is sensitive to this issue since their product characteristic is about small-volume and large-variety production. The product complexity of PCB is high, and its manufacturing processes of PCB go through thirty-six processes so how to monitor each station and to estimate the total cycle time are the issues we concerned. In this paper, we use data minin

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Liu, Yen-Ling, and 劉燕玲. "A Comparative Study on Using Supervised Bayesian Network, Unsupervised DINA, G-DINA, and DINO Models in the Cognitive Diagnostic Assessment of "Time Unit" for the Fourth Graders." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/5r5336.

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Abstract:

碩士<br>國立臺中教育大學<br>教育測驗統計研究所<br>100<br>The main purposes of this study are to establish the computerized diagnostic test for the “time unit” in the fourth grade based on the concept of cognitive diagnostic assessment, and use supervised Bayesian network and unsupervised DINA, G-DINA, DINO models to analyze test data. Finally, the diagnostic accuracy is estimated and compared to find the best model. The major findings of this study are summarized as follows: 1. The Cronbach α, average difficulty, and average discrimination of this computerized diagnostic test are 0.82, 0.673, and 0.474 respe

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Ribeiro, Ana Custódia da Silva. "Contabilidade de custos na definição de tabelas de preços : custeio de uma unidade de cuidados continuados." Master's thesis, 2014. http://hdl.handle.net/10400.14/17694.

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A contabilidade de custos na área da saúde, revela-se fundamental como instrumento de informação para a tomada de decisão, num setor onde os gestores são cada vez mais incitados a providenciar mais e melhores cuidados a preços inferiores. O principal objetivo deste estudo de caso, foi determinar o custo de um dia de internamento numa unidade de cuidados continuados, para três tipologias de doente caracterizados segundo o grau de dependência, com base nos custos reais da atividade utilizando a metodologia Time-Driven Activity-Based Costing. A escolha da metodologia de custeio, relaciona-se com

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