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Dynamic Bayesian networks

CNC Machine Tool's wear diagnostic and prognostic by using dynamic bayesian networks.

CNC Machine Tool's wear diagnostic and prognostic by using dynamic bayesian networks.

... recently, Dynamic Bayesian Networks [11], a tool generalizing the HMMs and the Kalman filter, have been exploited to perform failure prog- ...

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Dynamic Bayesian Networks for Integrated Neural Computation

Dynamic Bayesian Networks for Integrated Neural Computation

... how networks of cerebral structures implement cognitive or sensorimotor ...the networks are, and when and how much they ...large-scale networks derives from the cerebral information processing ...

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Modeling dynamic reliability using dynamic Bayesian networks

Modeling dynamic reliability using dynamic Bayesian networks

... dependability measures and to update beliefs given evidence. The existence of efficient algorithms for learning and inference make it possible to integrate them into decision support system for maintenance purpose or to ...

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Reducing Particle Filtering Complexity for 3D Motion Capture using Dynamic Bayesian Networks

Reducing Particle Filtering Complexity for 3D Motion Capture using Dynamic Bayesian Networks

... Dynamic Bayesian networks are a graphical formalism that can be used to model dy- namic processes such as Kalman filter, hidden Markov Model and more generally any kind of Markov process over a set ...

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CNC machine tool health assessment using Dynamic Bayesian Networks.

CNC machine tool health assessment using Dynamic Bayesian Networks.

... as Dynamic Bayesian Networks (DBNs) In the last decade a new tool, namely the Dynamic Bayesian Networks (DBNs), derived from the artificial intelligence domain became popular ...

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New structure learning algorithms and evaluation methods for large dynamic Bayesian networks

New structure learning algorithms and evaluation methods for large dynamic Bayesian networks

... Generating a very large BN randomly is not very realistic. In many large ap- plications, the global model can be decomposed in coherent repeated subgraphs. In the second familly, they chose the reference model as ...

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Dynamic Bayesian Networks for Speaker Verification

Dynamic Bayesian Networks for Speaker Verification

... Par exemple, les paramètres TPC pour le graphe de la Figure F.7 pourraient être ceux indiqués dans les tableaux suivants en supposant que toutes les variables sont binaires X = {x, ¬x} :[r] ...

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Cerebral modeling and dynamic Bayesian networks

Cerebral modeling and dynamic Bayesian networks

... and haemodynamic activation (provided by fMRI). Transcranial Magnetic Stimulation should allow getting some insights on hidden variables (i.e. neuronal phenomena). 5. Conclusion We have presented a general framework, ...

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Benchmarking dynamic Bayesian network structure learning algorithms

Benchmarking dynamic Bayesian network structure learning algorithms

... Dynamic Bayesian networks (DBNs) are a general and flexible model class for representing complex stochastic tem- poral processes ...reference networks used change over each ...to ...

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Incorporating Bayesian networks in Markov Decision Processes

Incorporating Bayesian networks in Markov Decision Processes

... Incorporating Bayesian Networks in Markov Decision Processes R. Faddoul, Ph.D. 1 ; W. Raphael 2 ; A.-H. Soubra 3 ; and A. Chateauneuf 4 This paper presents an extension to a partially observable Markov ...

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Reconstruction of gene regulation networks from microarray data by Bayesian networks

Reconstruction of gene regulation networks from microarray data by Bayesian networks

... gene-regulatory networks from time series knock-out data, and prior ...Wang. Bayesian inference of genetic regulatorynetworks from time series microarray data using dynamic bayesian ...

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Dynamic Bayesian modeling of the cerebral activity

Dynamic Bayesian modeling of the cerebral activity

... the networks of cerebral structures are, and when and how much they ...large-scale networks derives from the cerebral information processing mechanisms involved in cognitive ...a dynamic biological ...

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Dynamic DASH Aware Scheduling in Cellular Networks

Dynamic DASH Aware Scheduling in Cellular Networks

... cellular networks, fairness, scheduling ...cellular networks, mobile operators have been forced to deliberate on their current resource management ...cellular networks, users’ Quality of Experience ...

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Adaptive Spatiotemporal Node Selection in Dynamic Networks

Adaptive Spatiotemporal Node Selection in Dynamic Networks

... all other nodes at all times. Realistically, however, applica- tions must make difficult choices about when and where to spend scarce credits in order to maximize their productivity. Our work builds upon the central ...

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Dynamic Networks High Glass-Transition Temperature Polymer Networks Harnessing the Dynamic Ring Opening of Pinacol Boronates

Dynamic Networks High Glass-Transition Temperature Polymer Networks Harnessing the Dynamic Ring Opening of Pinacol Boronates

... polyaramides, polyetherimides or polybenzimidazoles). 23 Alternatively and historically, one can use non-reprocessable, very densely crosslinked thermosetting resins such as maleimide or phenolic formaldehyde, or ...

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Controller and estimator for dynamic networks

Controller and estimator for dynamic networks

... 5.4 Extending labeling schemes We now show how to use our size-estimation protocol for extending various existing distributed data structures for local queries to dynamic settings. We consider distributed data ...

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Dynamic Arc-Flags in Road Networks

Dynamic Arc-Flags in Road Networks

... edges in the reverse graph ¯ G. The query phase consists of a modified version of bidirectional Dijkstra’s algorithm: the forward search only considers those edges for which the flag of the target node’s region is true, ...

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WDM Mesh Networks with Dynamic Traffic

WDM Mesh Networks with Dynamic Traffic

... WDM Mesh Networks with Dynamic Traffic 3 1 Introduction The dynamic nature of the Internet requires backbone networks to be reconfigurable. Wavelength Division Multiplexing (WDM) technology ...

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Bayesian inference of a dynamic vegetation model for grassland

Bayesian inference of a dynamic vegetation model for grassland

... Hyman, Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling, International Journal of Nonlinear Sciences and Numeri[r] ...

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Bayesian networks applications on dependability, risk analysis and maintenance

Bayesian networks applications on dependability, risk analysis and maintenance

... Keywords: Bayesian networks dependability, risk analysis, maintenance. 1. INTRODUCTION The management of complex industrial systems requires a high performance and a reliability analysis. Nowadays, some of ...

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