Search results for "infer"

showing 10 items of 1371 documents

Empirical Bayes improves assessments of diversity and similarity when overdispersion prevails in taxonomic counts with no covariates

2019

Abstract The assessment of diversity and similarity is relevant in monitoring the status of ecosystems. The respective indicators are based on the taxonomic composition of biological communities of interest, currently estimated through the proportions computed from sampling multivariate counts. In this work we present a novel method to estimate the taxonomic composition able to work even with a single sample and no covariates, when data are affected by overdispersion. The presence of overdispersion in taxonomic counts may be the result of significant environmental factors which are often unobservable but influence communities. Following the empirical Bayes approach, we combine a Bayesian mo…

0106 biological sciencesMultivariate statisticsBiological dataEmpirical Bayesian estimationEcologyTaxonomic compositionGeneral Decision SciencesEnvironmental monitoring010501 environmental sciencesBayesian inference010603 evolutionary biology01 natural sciencesBiodiversity assessment; Dirichlet-Multinomial model; Empirical Bayesian estimation; Environmental monitoring; Taxonomic compositionMarginal likelihoodBayes' theoremOverdispersionStatisticsTaxonomic rankDirichlet-Multinomial modelBiodiversity assessmentEcology Evolution Behavior and Systematics0105 earth and related environmental sciencesEmpirical Bayes methodMathematics
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Monitoring internet trade to inform species conservation actions

2017

Specimens, parts and products of threatened species are now commonly traded on the internet. This could threaten the survival of some wild populations if inadequately regulated. We outline two methods to monitor internet sales of threatened species in order to assess potential threats and inform conservation actions. Our first method combines systematic monitoring of online offers of plants for sale over the internet with consultation by experts experienced in identifying plants collected from the wild based on images of the specimens, species identity and details of the trade. Our second method utilises a computational model, trained using Bayesian techniques to records that have been clas…

0106 biological sciencesSettore BIO/07 - EcologiaEcologybusiness.industry010604 marine biology & hydrobiologyInternet privacyfood and beverages010603 evolutionary biology01 natural scienceslcsh:QK1-989Geographylcsh:Botanylcsh:ZoologySettore BIO/03 - Botanica Ambientale E ApplicataThe InternetAdenia Commiphora Operculicarya Uncarina Machine learning Infer.NET Naive Bayes classifierlcsh:QL1-991businessNature and Landscape Conservation
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Hierarchical log Gaussian Cox process for regeneration in uneven-aged forests

2021

We propose a hierarchical log Gaussian Cox process (LGCP) for point patterns, where a set of points x affects another set of points y but not vice versa. We use the model to investigate the effect of large trees to the locations of seedlings. In the model, every point in x has a parametric influence kernel or signal, which together form an influence field. Conditionally on the parameters, the influence field acts as a spatial covariate in the intensity of the model, and the intensity itself is a non-linear function of the parameters. Points outside the observation window may affect the influence field inside the window. We propose an edge correction to account for this missing data. The par…

0106 biological sciencesStatistics and ProbabilityFOS: Computer and information sciences62F15 (Primary) 62M30 60G55 (Secondary)MCMCGaussianBayesian inferenceMarkovin ketjutStatistics - Applications010603 evolutionary biology01 natural sciencesCox processMethodology (stat.ME)010104 statistics & probabilitysymbols.namesakeregeneraatio (biologia)Applied mathematicsApplications (stat.AP)0101 mathematicsLaplace approximationStatistics - MethodologyGeneral Environmental ScienceParametric statisticsMathematicsspatial random effectsbayesilainen menetelmäMarkov chain Monte CarloFunction (mathematics)15. Life on landMissing dataMonte Carlo -menetelmätcompetition kernelLaplace's methodKernel (statistics)symbolstree regenerationpuustometsänhoitomatemaattiset mallitStatistics Probability and Uncertainty
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Fossorial but widespread: the phylogeography of the common spadefoot toad (Pelobates fuscus), and the role of the Po Valley as a major source of gene…

2007

International audience; Pelobates fuscus is a fossorial amphibian that inhabits much of the European plain areas. To unveil traces of expansion and contraction events of the species' range, we sequenced 702 bp of the mitochondrial cytochrome b gene. To infer the population history we applied phylogeographical methods, such as nested clade phylogeographical analysis (NCPA), and used summary statistics to analyse population structure under a neutral model of evolution. Populations were assigned to different drainage systems and we tested hypotheses of explicit refugial models using information from analysis of molecular variance, nucleotide diversity, effective population size estimation, NCP…

0106 biological scienceshaplotypesPelobates fuscuspopulation-structuremismatch distribution01 natural sciencesNucleotide diversityCoalescent theorypostglacial range expansionEffective population sizePhylogeny[SDV.EE]Life Sciences [q-bio]/Ecology environment0303 health scienceseducation.field_of_studybiologyGeographyEcologyFossilssummarycoalescentCytochromes bEuropeMitochondrial-dnastatisticsAnuracladistic-analysisPopulationPelobates[SDV.BID]Life Sciences [q-bio]/Biodiversitynucleotide diversity010603 evolutionary biology03 medical and health sciencesstatistical phylogeographygeographical-distributionGeneticsVicarianceAnimalseducationEcology Evolution Behavior and Systematics030304 developmental biologyPopulation DensityinferenceDNA15. Life on landbiology.organism_classificationPhylogeographyspeciationEvolutionary biologyphylogeographical analysis[SDE.BE]Environmental Sciences/Biodiversity and EcologydivergencePelobates cultripesMolecular ecology
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Assortative mating by size without a size-based preference: the female-sooner norm as a mate-guarding criterion.

2013

7 pages; International audience; The study of size-assortative mating, or homogamy, is of great importance in speciation and sexual selection. However, the proximate mechanisms that lead to such patterns are poorly understood. Homogamy is often thought to come from a directional preference for larger mates. However, many constraints affect mating preferences and understanding the causes of size assortment requires a precise evaluation of the pair formation mechanism. Mate-guarding crustaceans are a model group for the study of homogamy. Males guard females until moult and reproduction. They are also unable to hold a female during their own moult and tend to pair with females closer to moult…

0106 biological sciencestime left to moultamplexusBiology010603 evolutionary biology01 natural sciencessize-assortative matingAmplexus[ SDV.EE.IEO ] Life Sciences [q-bio]/Ecology environment/Symbiosis0501 psychology and cognitive sciences050102 behavioral science & comparative psychologyEcology Evolution Behavior and Systematics[ SDE.BE ] Environmental Sciences/Biodiversity and EcologyMate guarding05 social sciencesAssortative matingstate-dependent preferenceDecision ruleMating preferencesmale mate choicePair formationinferential fallacymale-taller normSexual selectionAnimal Science and ZoologyNorm (social)[SDE.BE]Environmental Sciences/Biodiversity and EcologycrustaceanSocial psychology[SDV.EE.IEO]Life Sciences [q-bio]/Ecology environment/Symbiosis
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FeatherCNN: Fast Inference Computation with TensorGEMM on ARM Architectures

2020

Deep Learning is ubiquitous in a wide field of applications ranging from research to industry. In comparison to time-consuming iterative training of convolutional neural networks (CNNs), inference is a relatively lightweight operation making it amenable to execution on mobile devices. Nevertheless, lower latency and higher computation efficiency are crucial to allow for complex models and prolonged battery life. Addressing the aforementioned challenges, we propose FeatherCNN – a fast inference library for ARM CPUs – targeting the performance ceiling of mobile devices. FeatherCNN employs three key techniques: 1) A highly efficient TensorGEMM (generalized matrix multiplication) routine is app…

020203 distributed computingSource codeIterative methodComputer sciencebusiness.industrymedia_common.quotation_subjectDeep learningInference02 engineering and technologyParallel computingConvolutional neural networkMatrix multiplicationARM architectureComputational Theory and MathematicsHardware and ArchitectureSignal Processing0202 electrical engineering electronic engineering information engineeringArtificial intelligencebusinessmedia_commonIEEE Transactions on Parallel and Distributed Systems
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Predictive Model Markup Language (PMML) Representation of Bayesian Networks: An Application in Manufacturing

2018

International audience; Bayesian networks (BNs) represent a promising approach for the aggregation of multiple uncertainty sources in manufacturing networks and other engineering systems for the purposes of uncertainty quantification, risk analysis, and quality control. A standardized representation for BN models will aid in their communication and exchange across the web. This article presents an extension to the predictive model markup language (PMML) standard for the representation of a BN, which may consist of discrete variables, continuous variables, or their combination. The PMML standard is based on extensible markup language (XML) and used for the representation of analytical models…

0209 industrial biotechnologyDesignComputer sciencecomputer.internet_protocol02 engineering and technologycomputer.software_genreBayesian inferenceIndustrial and Manufacturing EngineeringArticle[SPI]Engineering Sciences [physics]020901 industrial engineering & automationPMML0202 electrical engineering electronic engineering information engineeringanalyticsUncertainty quantificationMonte-Carlouncertaintycomputer.programming_languageParsingBayesian networkInformationSystems_DATABASEMANAGEMENTstandardPython (programming language)XMLComputer Science ApplicationsmanufacturingComputingMethodologies_PATTERNRECOGNITIONBayesian networksControl and Systems EngineeringSurface-RoughnessData analysisPredictive Model Markup Language020201 artificial intelligence & image processingData miningcomputerXML
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Finite-time stability and stabilisation for a class of nonlinear systems with time-varying delay

2014

This paper is concerned with the problems of finite-time stability FTS and finite-time stabilisation for a class of nonlinear systems with time-varying delay, which can be represented by Takagi–Sugeno fuzzy system. Some new delay-dependent FTS conditions are provided and applied to the design problem of finite-time fuzzy controllers. First, based on an integral inequality and a fuzzy Lyapunov–Krasovskii functional, a delay-dependent FTS criterion is proposed for open-loop fuzzy system by introducing some free fuzzy weighting matrices, which are less conservative than other existing ones. Then, the parallel distributed compensation controller is designed to ensure FTS of the time-delay fuzzy…

0209 industrial biotechnologyEngineeringfinite-time stabilisation; finite-time stability; fuzzy control; nonlinear system; time-delay system; Control and Systems Engineering; Theoretical Computer Science; Computer Science Applications1707 Computer Vision and Pattern RecognitionStability (learning theory)fuzzy controltime-delay system02 engineering and technologynonlinear systemFuzzy logicCompensation (engineering)Theoretical Computer Science020901 industrial engineering & automationControl theory0202 electrical engineering electronic engineering information engineeringfinite-time stabilisationfinite-time stabilityAdaptive neuro fuzzy inference systembusiness.industryComputer Science Applications1707 Computer Vision and Pattern RecognitionFuzzy control systemComputer Science ApplicationsWeightingNonlinear systemControl and Systems Engineering020201 artificial intelligence & image processingbusiness
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Optimal control of discrete-time interval type-2 fuzzy-model-based systems with D-stability constraint and control saturation

2016

This paper investigates the optimal control problem for discrete-time interval type-2 (IT2) fuzzy systems with pole constraints. An IT2 fuzzy controller is characterized by two predefined functions, and the membership functions and the premise rules of the IT2 fuzzy controller can be chosen freely. The pole assignment is considered, which is constrained in a presented disk region. Based on Lyapunov stability theory, sufficient conditions of asymptotic stability with an H ∞ performance are obtained for the discrete-time IT2 fuzzy model based (FMB) system. Based on the criterion, the desired IT2 state-feedback controller is designed to guarantee that the closed-loop system is asymptotically s…

0209 industrial biotechnologyMathematical optimizationAdaptive neuro fuzzy inference system02 engineering and technologyFuzzy control systemOptimal controlDefuzzificationFuzzy logic020901 industrial engineering & automationControl and Systems EngineeringControl theorySignal Processing0202 electrical engineering electronic engineering information engineeringFuzzy set operationsFuzzy number020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionElectrical and Electronic EngineeringSoftwareMathematicsSignal Processing
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JOINT TOPOLOGY LEARNING AND GRAPH SIGNAL RECOVERY VIA KALMAN FILTER IN CAUSAL DATA PROCESSES

2018

In this paper, a joint graph-signal recovery approach is investigated when we have a set of noisy graph signals generated based on a causal graph process. By leveraging the Kalman filter framework, a three steps iterative algorithm is utilized to predict and update signal estimation as well as graph topology learning, called Topological Kalman Filter or TKF. Similar to the regular Kalman filter, we first predict the a posterior signal state based on the prior available data and then this prediction is updated and corrected based on the recently arrived measurement. But contrary to the conventional Kalman filter algorithm, we have no information of the transition matrix and hence we relate t…

0209 industrial biotechnologyMean squared errorIterative methodComputer scienceStochastic matrixInference020206 networking & telecommunications02 engineering and technologyKalman filterTopology020901 industrial engineering & automationSignal recovery0202 electrical engineering electronic engineering information engineeringGraph (abstract data type)Topological graph theory2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP)
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