Search results for "algorithm."

showing 10 items of 4617 documents

A control strategy based on intelligent algorithm (PSO) to perform electrical stimulation systems

2017

International audience; Adjusting stimulation parameters using control strategy based on reliable mathematical model that can predict perfectly the muscle response, may improve the efficiency of Functional Electrical Stimulation (FES) systems. In the present project, we investigate the PID control tuning based on the Particle Swarm Optimization (PSO) algorithm at the first time in neuro-muscular systems for updating automatically the stimulation pulse amplitude to track a desired force profiles. In the beginning, The PSO algorithm is used to identify unknown force model parameters. Next, optimal PID gains are found by the same intelligent algorithm to improve the control system. The obtaine…

pulse amplitude.[SPI.AUTO] Engineering Sciences [physics]/Automaticmuscle force modelFunctional Electrical Stimulation[ SPI.AUTO ] Engineering Sciences [physics]/AutomaticPID controllerPSO algorithm[SPI.AUTO]Engineering Sciences [physics]/Automatic
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Enhancing identification of causal effects by pruning

2018

Causal models communicate our assumptions about causes and effects in real-world phe- nomena. Often the interest lies in the identification of the effect of an action which means deriving an expression from the observed probability distribution for the interventional distribution resulting from the action. In many cases an identifiability algorithm may return a complicated expression that contains variables that are in fact unnecessary. In practice this can lead to additional computational burden and increased bias or inefficiency of estimates when dealing with measurement error or missing data. We present graphical criteria to detect variables which are redundant in identifying causal effe…

päättelyFOS: Computer and information sciencesalgorithmcausal modelMachine Learning (stat.ML)Machine Learning (cs.LG)Computer Science - Learningleikkaus (kasvit)koneoppiminenStatistics - Machine Learningidentiafiabilityalgoritmitkausaliteetticausal inferencetunnistaminen
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Computational aspects in checking of coherence and propagation of conditional probability bounds

2000

In this paper we consider the problem of reducing the computational difficulties in g-coherence checking and propagation of imprecise conditional probability assessments. We review some theoretical results related with the linear structure of the random gain in the betting criterion. Then, we propose a modi ed version of two existing algorithms, used for g-coherence checking and propagation, which are based on linear systems with a reduced number of unknowns. The reduction in the number of unknowns is obtained by an iterative algorithm. Finally, to illustrate our procedure we give some applications.

reduced sets of variables and constrainsCoherent probability assessments propagation random gain computation algorithmsSettore MAT/06 - Probabilita' E Statistica MatematicaChecking of coherencerandom gainpropagationChecking of coherence; computational aspects; propagation; linear systems; random gain; reduced sets of variables and constrainslinear systemscomputational aspects
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Algorithms for coherence checking and propagation of conditional probability bounds

2001

In this paper, we propose some algorithms for the checking of generalized coherence (g-coherence) and for the extension of imprecise conditional probability assessments. Our concept of g-coherence is a generalization of de Finetti’s coherence principle and is equivalent to the ”avoiding uniform loss” property for lower and upper probabilities (a la Walley). By our algorithms we can check the g-coherence of a given imprecise assessment and we can correct it in order to obtain the associated coherent assessment (in the sense of Walley and Williams). Exploiting some properties of the random gain we show how, in the linear systems involved in our algorithms, we can work with a reduced set of va…

reduced sets of variables and constraintsSettore MAT/06 - Probabilita' E Statistica MatematicaUncertain knowledgeUncertain knowledge probabilistic reasoning under coherence imprecise conditional probability assessments g-coherence checking g-coherent extension algorithms computational aspects reduced sets of variables reduced sets of linear constraints.g-coherent extensionimprecise conditional probability assessmentsg-coherence checkingUncertain knowledge; probabilistic reasoning under coherence; imprecise conditional probability assessments; g-coherence checking; g-coherent extension; algorithms.; computational aspects; reduced sets of variables and constraints.algorithmsprobabilistic reasoning under coherencecomputational aspects
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Jet fragmentation transverse momentum distributions in pp and p-Pb collisions at √s, √sNN = 5.02 TeV

2021

Jet fragmentation transverse momentum (jT) distributions are measured in proton-proton (pp) and proton-lead (p-Pb) collisions at √sNN = 5.02 TeV with the ALICE experiment at the LHC. Jets are reconstructed with the ALICE tracking detectors and electromagnetic calorimeter using the anti-kT algorithm with resolution parameter R = 0.4 in the pseudorapidity range |η| < 0.25. The jT values are calculated for charged particles inside a fixed cone with a radius R = 0.4 around the reconstructed jet axis. The measured jT distributions are compared with a variety of parton-shower models. Herwig and Pythia 8 based models describe the data well for the higher jT region, while they underestimate the low…

related to the perturbative component of the fragmentation processthe measured trends are successfully described by all models except for Herwig. For the wide componentHerwig and PYTHIA 8 based models slightly underestimate the data for the higher jet transverse momentum region. These measurements set constraints on models of jet fragmentation and hadronisation.Nuclear and High Energy Physicswhile that of the inverse gamma function increases with increasing jet transverse momentum. For the narrow componentHeavy Ion Experimentsand with a Gaussian for lower jT values (called the “narrow component”)hiukkasfysiikkawhile they underestimate the lower jT region. The jT distributions are further characterised by fitting them with a function composed of an inverse gamma function for higher jT values (called the “wide component”)predominantly connected to the hadronisation process. The width of the Gaussian has only a weak dependence on jet transverse momentumJet fragmentation transverse momentum (jT) distributions are measured in proton-proton (pp) and proton-lead (p-Pb) collisions at √sNN = 5.02 TeV with the ALICE experiment at the LHC. Jets are reconstructed with the ALICE tracking detectors and electromagnetic calorimeter using the anti-kT algorithm with resolution parameter R = 0.4 in the pseudorapidity range |η| < 0.25. The jT values are calculated for charged particles inside a fixed cone with a radius R = 0.4 around the reconstructed jet axis. The measured jT distributions are compared with a variety of parton-shower models. Herwig and PYTHIA 8 based models describe the data well for the higher jT region
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Fault diagnosis of induction motors broken rotor bars by pattern recognition based on noise cancelation

2014

Current signal monitoring (CSM) can be used as an effective tool for diagnosing broken rotor bars fault in induction motors. In this paper, fault diagnosis and classification based on artificial neural networks (ANNs) is done in two stages. In the first stage, a filter is designed to remove irrelevant fault components (such as noise) of current signals. The coefficients of the filter are obtained by least square (LS) algorithm. Then by extracting suitable time domain features from filter's output, a neural network is trained for fault classification. The output vector of this network is represented in one of four categories that includes healthy mode, a 5 mm crack on a bar, one broken bar, …

removing irrelevant fault componentsEngineeringArtificial neural networkneural networkRotor (electric)Bar (music)business.industryComputer Science::Neural and Evolutionary ComputationFilter (signal processing)Fault (power engineering)law.inventionNoisefault diagnosis and classificationControl and Systems Engineeringlawfault diagnosis and classification; neural network; removing irrelevant fault components; Stator current signal monitoring; Electrical and Electronic Engineering; Control and Systems EngineeringElectronic engineeringTime domainElectrical and Electronic EngineeringStator current signal monitoringbusinessAlgorithmInduction motor2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE)
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Novel VAMPIRE algorithms for quantitative analysis of the retinal vasculature

2013

This paper summarizes three recent, novel algorithms developed within VAMPIRE, namely optic disc and macula detection, arteryvein classification, and enhancement of binary vessel masks, and their performance assessment. VAMPIRE is an international collaboration growing a suite of software tools to allow efficient quantification of morphological properties of the retinal vasculature in large collections of fundus camera images. VAMPIRE measurements are currently mostly used in biomarker research, i.e., investigating associations between the morphology of the retinal vasculature and a number of clinical and cognitive conditions.

retinaRetinaSettore INF/01 - InformaticaContextual image classificationbusiness.industryComputer scienceVampireRetinalImage segmentationClassificationFeature detectionRetina; Feature detection; Segmentation; Classification; Biomarkerschemistry.chemical_compoundSegmentationmedicine.anatomical_structurechemistrymedicineSegmentationComputer visionArtificial intelligencebusinessAlgorithmBiomarkersOptic discFeature detection (computer vision)2013 ISSNIP Biosignals and Biorobotics Conference: Biosignals and Robotics for Better and Safer Living (BRC)
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On the use of multi-temporal series of COSMO-SkyMed data for LANDcover classification and surface parameter retrieval over agricultural sites

2011

The objective of this paper is to report on the activities carried out during the first year of the Italian project “Use of COSMO-SkyMed data for LANDcover classification and surface parameters retrieval over agricultural sites” (COSMOLAND), funded by the Italian Space Agency. The project intends to contribute to the COSMO-SkyMed mission objectives in the agriculture and hydrology application domains.

retrieval algorithmsContextual image classificationbusiness.industryCOSMO-SkyMedCOSMO-SkyMed classification retrieval algorithmsClassificationData modelingStatistical classificationHydrology (agriculture)AgricultureClassification; COSMO-SkyMed; retrieval algorithmsEnvironmental scienceTerrain mappingbusinessRetrieval algorithmRemote sensing
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Selection of spawning substratum by European river lampreys (Lampetra fluviatilis) in experimental tanks

2014

The selection of spawning substratum by the river lamprey (Lampetra fluviatilis) was studied in two experimental tanks with different flow conditions. In both tanks, four gravel sizes mixed with 15% sand were available to the test animals. In the tank with the lower current speed, lampreys selected in favour of the finest (2–8 mm) gravel size available against gravel sizes 4–20 mm and 8–40 mm. Selection was also significantly different in the tank with higher current speed where selection against the medium-sized substratum (4–20 mm) was evident, but there were no differences between selection for gravel sizes 2–8 mm, 2–40 mm and 8–40 mm relative to availability. Substratum selection and ob…

river lampreyPhysiologyLampreyspawninghabitatselectionsubstrateAquatic ScienceBiologyOceanographybiology.organism_classificationSubstrate (marine biology)FisheryCurrent (stream)Lampetra fluviatilisHabitatLampetraNestta1181Selection (genetic algorithm)Marine and Freshwater Behaviour and Physiology
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Impact Evaluation of Innovative Selective Harmonic Mitigation Algorithm for Cascaded H-Bridge Inverter on IPMSM Drive Application

2021

This paper presents a detailed analysis of the use of a novel Harmonic Mitigation algorithm for Cascaded H-Bridge Multilevel Inverter in electrical drives for the transportation field. For this purpose, an enhanced mathematical model of Interior Permanent Magnet Synchronous Motor (IPMSM), that takes into account simultaneously saturation, cross-coupling, spatial harmonics, and iron loss effects, has been used. In detail, this model allows estimating accurately the efficiency and the torque ripple of the IPMSM, crucial parameters for transportation applications. Moreover, two traditional pulse width modulation strategies, Sinusoidal Phase-Shifted and Switching Frequency Optimal Phase-Shifted…

selective harmonic mitigation algorithmComputer scienceImpact evaluationHarmonic mitigationSettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciCascaded H-bridge multilevel inverter (CHBMI)torque rippleH bridge inverterTK1-9971Settore ING-IND/31 - ElettrotecnicaefficiencyElectronic engineeringCascaded H-bridge multilevel inverter (CHBMI) efficiency interior permanent magnet synchronous machine (IPMSM) selective harmonic mitigation algorithm torque rippleElectrical engineering. Electronics. Nuclear engineeringinterior permanent magnet synchronous machine (IPMSM)IEEE Open Journal of Industry Applications
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