Search results for " Bayesian"

showing 10 items of 124 documents

Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy)

2020

The plant-pathogenic bacterium Xylella fastidiosa was first reported in Europe in 2013, in the province of Lecce, Italy, where extensive areas were affected by the olive quick decline syndrome, caused by the subsp. pauca. In Alicante, Spain, almond leaf scorch, caused by X. fastidiosa subsp. multiplex, was detected in 2017. The effects of climatic and spatial factors on the geographic distribution of X. fastidiosa in these two infested regions in Europe were studied. The presence/absence data of X. fastidiosa in the official surveys were analyzed using Bayesian hierarchical models through the integrated nested Laplace approximation (INLA) methodology. Climatic covariates were obtained from …

Xylella fastidiosa0106 biological scienceshierarchical Bayesian modelsDiurnal rangeLeaf scorchPlant Sciencelcsh:Plant cultureBayesian inference01 natural sciences010104 statistics & probabilityCovariatemedicinelcsh:SB1-11100101 mathematicsspecies distribution modelsXylella fastidiosabiologySpatial structurealmond leaf scorchintegrated nested Laplace approximation15. Life on landbiology.organism_classificationmedicine.diseaseConfounding effectstochastic partial differential equationGeographyolive quick declineSampling distributionXylella fastidiosaCartography010606 plant biology & botanyFrontiers in Plant Science
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A modeling approach to evaluate the influence of spatial and temporal structure of an epidemiological surveillance network on the intensity of phytos…

2017

National audience

[SDE] Environmental Sciences[SDV]Life Sciences [q-bio][MATH] Mathematics [math]pesticides[INFO] Computer Science [cs]pest monitoringsimulationdynamic bayesian networks[SHS]Humanities and Social Sciences[SDV] Life Sciences [q-bio]supervised control[SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology[INFO]Computer Science [cs][SHS] Humanities and Social Sciences[MATH]Mathematics [math]ComputingMilieux_MISCELLANEOUS
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A Bayesian Reconstruction of a Historical Population in Finland, 1647–1850

2020

This article provides a novel method for estimating historical population development. We review the previous literature on historical population time-series estimates and propose a general outline to address the well-known methodological problems. We use a Bayesian hierarchical time-series model that allows us to integrate the parish-level data set and prior population information in a coherent manner. The procedure provides us with model-based posterior intervals for the final population estimates. We demonstrate its applicability by estimating the long-term development of Finlands population from 1647 onward and simultaneously place the country among the very few to have an annual popula…

aikasarjatEconomics060106 history of social sciencesPopulation DynamicsBayesian probabilityPopulationPopulation developmentHistory 18th CenturyArticleHistory 17th CenturyPopulation estimateväestöhistoriaPopulation historyResidence Characteristics0502 economics and businessEconometricsPopulation growthHumansPopulation growth0601 history and archaeologyuuden ajan alkuNationalekonomi050207 economicsEarly modern eraeducationFinlandestimointiDemographyBayes estimatoreducation.field_of_studybayesilainen menetelmä05 social sciencesväestönmuutoksetBayes TheoremCensusesHistory 19th CenturyPopulation history; Population growth; Early modern era; Bayesian estimation06 humanities and the artsBayesian estimationData setGeographypopulation growthearly modern erapopulation historyDemography
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Reti bayesiane per l’indentificazione delle migliori strategie di gestione idraulica di un bacino urbano

2011

allagamenti urbani Bayesian Belief Network tecniche di retrofitting
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On the origin and diversification of Podolian cattle breeds: testing scenarios of European colonization using genome-wide SNP data

2021

AbstractBackgroundDuring the Neolithic expansion, cattle accompanied humans and spread from their domestication centres to colonize the ancient world. In addition, European cattle occasionally intermingled with both indicine cattle and local aurochs resulting in an exclusive pattern of genetic diversity. Among the most ancient European cattle are breeds that belong to the so-called Podolian trunk, the history of which is still not well established. Here, we used genome-wide single nucleotide polymorphism (SNP) data on 806 individuals belonging to 36 breeds to reconstruct the origin and diversification of Podolian cattle and to provide a reliable scenario of the European colonization, throug…

breedsmolecular markersSNP bos taurus Podolian cattle genetic diversity population structureGenetic genealogyved/biology.organism_classification_rank.speciesSNPPodolianQH426-470BiologyDiversification (marketing strategy)Polymorphism Single NucleotideSF1-1100genome-wideEvolution Molecular03 medical and health sciencesGene FrequencyevolutionGeneticsAnimalsColonizationDomesticationEcology Evolution Behavior and Systematics030304 developmental biology2. Zero hunger0303 health sciencesGenetic diversitySettore AGR/17 - ZOOTECNICA GENERALE E MIGLIORAMENTO GENETICOModels Geneticlocal breedsved/biologyTaurine cattle0402 animal and dairy scienceBayes TheoremGenomics04 agricultural and veterinary sciencesGeneral MedicineAurochsbiology.organism_classification040201 dairy & animal scienceAnimal cultureEvolutionary biologyCattleAnimal Science and ZoologyApproximate Bayesian computationAnimal Distributioncattle local breeds molecular markers evolutionResearch ArticleSelective BreedingGenetics Selection Evolution
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Use of hierarchical Bayesian framework in MTS studies to model different causes and novel possible forms of acquired MTS

2015

Abstract: An integrative account of MTS could be cast in terms of hierarchical Bayesian inference. It may help to highlight a central role of sensory (tactile) precision could play in MTS. We suggest that anosognosic patients, with anesthetic hemisoma, can also be interpreted as a form of acquired MTS, providing additional data for the model.

business.industryCognitive NeuroscienceTOUCHBODY AWARENESSSensory systemTactile perceptionBody awarenessBayesian inferenceMachine learningcomputer.software_genreHiearchical Bayesian ModelIllusionTouch PerceptionTactile PerceptionSYNAESTHESIABayesian frameworkArtificial intelligencePerceptual DisorderbusinessPsychologycomputerHumanCognitive Neuroscience
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An adaptive probabilistic approach to goal-level imitation learning

2010

Imitation learning has been recognized as a promising technique to teach robots advanced skills. It is based on the idea that robots could learn new behaviors by observing and imitating the behaviors of other skilled actors. We propose an adaptive probabilistic graphical model which copes with three core issues of any imitative behavior: observation, representation and reproduction of skills. Our model, Growing Hierarchical Dynamic Bayesian Network (GHDBN), is hierarchical (i.e. able to characterize structured behaviors at different levels of abstraction), and growing (i.e. skills are learned or updated incrementally - and at each level of abstraction - every time a new observation sequence…

business.industryComputer scienceProbabilistic logicMachine learningcomputer.software_genreRobotArtificial intelligenceGraphical modelRobotics Imitation Learning Machine Learning Bayesian ModelsbusinessRepresentation (mathematics)Hidden Markov modelcomputerDynamic Bayesian networkHumanoid robotAbstraction (linguistics)2010 IEEE/RSJ International Conference on Intelligent Robots and Systems
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Using recursive Bayesian estimation for matching GPS measurements to imperfect road network data

2010

Map-matching refers to the process of projecting positioning measurements to a location on a digital road network map. It is an important element of intelligent transportation systems (ITS) focusing on driver assistance applications, on emergency and incident management, arterial and freeway management, and other applications. This paper addresses the problem of map-matching in the applications characterized by imperfect map quality and restricted computational resources - e.g. in the context of community-based ITS applications. Whereas a number of map-matching methods are available, often these methods rely on topological analysis, thereby making them sensitive to the map inaccuracies. In …

business.industryComputer scienceProbabilistic logicMap matchingcomputer.software_genreBayes' theoremIdentification (information)Global Positioning SystemMaximum a posteriori estimationData miningbusinessRecursive Bayesian estimationIntelligent transportation systemcomputer13th International IEEE Conference on Intelligent Transportation Systems
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An adaptive probabilistic graphical model for representing skills in PbD settings

2010

business.industryComputer scienceProgramming by demonstrationBayesian probabilityProbabilistic logicMachine learningcomputer.software_genreUnsupervised learningArtificial intelligenceGraphical modelMachine Learning Imitation Learning Incremental Learning Dynamic Bayesian Network Growing Hierarchical Dynamic Bayesian NetworkAutomatic programmingbusinessHidden Markov modelcomputerDynamic Bayesian network
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Learning Bayesian Metanetworks from Data with Multilevel Uncertainty

2006

Managing knowledge by maintaining it according to dynamic context is among the basic abilities of a knowledge-based system. The two main challenges in managing context in Bayesian networks are the introduction of contextual (in)dependence and Bayesian multinets. We are presenting one possible implementation of a context sensitive Bayesian multinet-the Bayesian Metanetwork, which implies that interoperability between component Bayesian networks (valid in different contexts) can be also modelled by another Bayesian network. The general concepts and two kinds of such Metanetwork models are considered. The main focus of this paper is learning procedure for Bayesian Metanetworks.

business.industryComputer scienceTheoryofComputation_GENERALBayesian networkBayesian inferenceMachine learningcomputer.software_genreVariable-order Bayesian networkBayesian statisticsComputingMethodologies_PATTERNRECOGNITIONBayesian hierarchical modelingBayesian programmingGraphical modelArtificial intelligencebusinesscomputerDynamic Bayesian network
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