Search results for "Linea"

showing 10 items of 7724 documents

Revisited mixed-value method via symmetric BEM in the substructuring approach

2012

Abstract Within the Symmetric Boundary Element Method, the mixed-value analysis is re-formulated. This analysis method contemplates the subdivision of the body into substructures having interface kinematical and mechanical quantities. For each substructure an elasticity equation, connecting weighted displacements and tractions to nodal displacements and forces of the same interface boundary and to external action vector, is introduced. The assembly of the substructures is performed through both the strong and weak regularity conditions of the displacements and tractions. We obtain the solving equations where the compatibility and the equilibrium are guaranteed in the domain Ω for the use of…

business.industryApplied MathematicsLinear elasticityMathematical analysisGeneral EngineeringGeometrySymmetric GalerkinBEMMacro-element Substructuring Displacement approach Mixed-value approachDisplacement methodComputational MathematicsCompatibility (mechanics)Fundamental solutionSubstructureSettore ICAR/08 - Scienza Delle CostruzionibusinessBoundary element methodAnalysisMathematicsEquation solvingSubdivisionEngineering Analysis with Boundary Elements
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Ensemble feature selection with the simple Bayesian classification

2003

Abstract A popular method for creating an accurate classifier from a set of training data is to build several classifiers, and then to combine their predictions. The ensembles of simple Bayesian classifiers have traditionally not been a focus of research. One way to generate an ensemble of accurate and diverse simple Bayesian classifiers is to use different feature subsets generated with the random subspace method. In this case, the ensemble consists of multiple classifiers constructed by randomly selecting feature subsets, that is, classifiers constructed in randomly chosen subspaces. In this paper, we present an algorithm for building ensembles of simple Bayesian classifiers in random sub…

business.industryBayesian probabilityFeature selectionPattern recognitionMachine learningcomputer.software_genreLinear subspaceRandom subspace methodNaive Bayes classifierBayes' theoremComputingMethodologies_PATTERNRECOGNITIONHardware and ArchitectureSignal ProcessingArtificial intelligencebusinesscomputerClassifier (UML)SoftwareCascading classifiersInformation SystemsMathematicsInformation Fusion
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Improving IEEE 802.11 Performance in Chain Topologies through Distributed Polling and Network Coding

2009

Wireless multi-hop networks often rely on the use of IEEE 802.11 technology. Despite of the robustness of the IEEE 802.11 Distributed Coordination Function (DCF) for working in various network scenarios, it has been proven that critical inefficiencies can arise in the case of multi-hop packet forwarding. In this paper, we propose a MAC scheme, based on the virtualization of the Point Coordination Function, optimized for working on chain topologies with bidirectional traffic flows. Our scheme is based on a token-like access mechanism coupled with network coding. The basic idea is the use of multiple Point Coordinators (PCs) along the node chain, which are elected by passing special token fra…

business.industryBidirectional trafficComputer scienceSettore ING-INF/03 - TelecomunicazioniDistributed computingComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSPacket forwardingThroughputnetwork codingDistributed coordination functionNetwork topologyWLANToken passingPoint coordination functionIEEE 802.11Linear network codingWireless lanTelecommunications linkComputer Science::Networking and Internet ArchitectureWirelessPollingbusinessComputer network
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Nonlinear radial-harmonic correlation using binary decomposition for scale-invariant pattern recognition

2003

We introduce a new scale-invariant pattern-recognition method that uses nonlinear correlation. We applied several common linear correlations to images decomposed into disjoint binary images, which is very discriminant even when the target is embedded in strong noise. We combine our sliced orthogonal nonlinear generalized correlation method and the radial-harmonic expansion in order to achieve scale-invariant pattern recognition. The information from a radial harmonic for each binary slice of the reference object is combined with binary slices of the target. The method avoids the time-consuming process of finding expansion centers for the radial harmonics. The stability of the correlation pe…

business.industryBinary imageBinary numberPattern recognitionScale invarianceAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsBackground noiseNonlinear systemsymbols.namesakeNoiseOpticsGaussian noiseHarmonicsymbolsArtificial intelligenceElectrical and Electronic EngineeringPhysical and Theoretical ChemistrybusinessMathematicsOptics Communications
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Visible-NIR reflectance spectroscopy and manifold learning methods applied to the detection of fungal infections on citrus fruit

2015

Abstract The development of systems for automatically detecting decay in citrus fruit during quality control is still a challenge for the citrus industry. The feasibility of reflectance spectroscopy in the visible and near infrared (NIR) regions was evaluated for the automatic detection of the early symptoms of decay caused by Penicillium digitatum fungus in citrus fruit. Reflectance spectra of sound and decaying surface parts of mandarins cv. ‘Clemenvilla’ were acquired in two different spectral regions, from 650 nm to 1050 nm (visible–NIR) and from 1000 nm to 1700 nm (NIR), pointing to significant differences in spectra between sound and decaying skin for both spectral ranges. Three diffe…

business.industryChemistryDimensionality reductionFeature vectorNear-infrared spectroscopyNonlinear dimensionality reductionLinear discriminant analysisSammon mappingOpticsPrincipal component analysisbusinessSpectroscopyBiological systemFood Science
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Development of a thermodesorption sensor system for the detection of residual solvents in packaging materials

2004

Application specific sensor systems (formerly electronic noses) use static headspace for the volatile generation from condensed phase samples. This extraction method is very simple to implement, but suffers many drawbacks, i.e. in terms of efficiency or sensitivity to partitioning and is very time-consuming. To circumvent these problems, we developed a new method using dynamic extraction of volatiles (stripping). Although this method is known for GC (gas chromatography), the utilization of direct thermal desorption (DTD) in conjunction with gas sensors is quite novel. The unhandy cold trapping step can be avoided by a software integration of the instantaneous volatile concentration over the…

business.industryChemistry[SPI.GPROC] Engineering Sciences [physics]/Chemical and Process EngineeringThermal desorptionAnalytical chemistry02 engineering and technology[SDV.IDA] Life Sciences [q-bio]/Food engineering010402 general chemistry021001 nanoscience & nanotechnologyResidual01 natural sciencesStripping (fiber)0104 chemical sciencesLinearizationDesorption[SDV.IDA]Life Sciences [q-bio]/Food engineeringCalibrationGas detector[SPI.GPROC]Engineering Sciences [physics]/Chemical and Process EngineeringGas chromatography0210 nano-technologyProcess engineeringbusinessComputingMilieux_MISCELLANEOUS
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Nonlinear data description with Principal Polynomial Analysis

2012

Principal Component Analysis (PCA) has been widely used for manifold description and dimensionality reduction. Performance of PCA is however hampered when data exhibits nonlinear feature relations. In this work, we propose a new framework for manifold learning based on the use of a sequence of Principal Polynomials that capture the eventually nonlinear nature of the data. The proposed Principal Polynomial Analysis (PPA) is shown to generalize PCA. Unlike recently proposed nonlinear methods (e.g. spectral/kernel methods and projection pursuit techniques, neural networks), PPA features are easily interpretable and the method leads to a fully invertible transform, which is a desirable property…

business.industryCodingDimensionality reductionNonlinear dimensionality reductionDiffusion mapSparse PCAComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONElastic mapPattern recognitionManifold LearningClassificationKernel principal component analysisComputingMethodologies_PATTERNRECOGNITIONPrincipal component analysisPrincipal Polynomial AnalysisArtificial intelligencePrincipal geodesic analysisbusinessDimensionality ReductionMathematics
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Análisis tiempo-frecuencia de la fibrilación ventricular. Estudio experimental

2006

Introduction and objectives. The analysis of frequency variability during ventricular fibrillation has yielded inconsistent results. We used an experimental model of ventricular fibrillation, with a short timescale, to analyze variations in frequency and their associated spatial distribution. Methods. Epicardial recordings of ventricular fibrillation were made in 10 perfused isolated rabbit heart preparations using a multiple electrode system (i.e., 240 unipolar electrodes). Both spectral and time-frequency analysis were used to derive the dominant frequency in the anterolateral wall of the left ventricle. Results. Linear regression analysis showed that there was a good correlation between …

business.industryCoefficient of variationRabbit heartmedicine.diseaseFree wallmedicine.anatomical_structureNuclear magnetic resonanceStandard errorVentricleLinear regressionVentricular fibrillationmedicineSpectral analysisCardiology and Cardiovascular MedicinebusinessRevista Española de Cardiología
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WiHAR : From Wi-Fi Channel State Information to Unobtrusive Human Activity Recognition

2020

A robust and unobtrusive human activity recognition system is essential to a multitude of applications, such as health care, active assisted living, robotics, sports, and tele-immersion. Existing well-performing activity recognition methods are either vision- or wearable sensor-based. However, they are not fully passive. In this paper, we develop WiHAR—an unobtrusive Wi-Fi-based activity recognition system. WiHAR uses the Wi-Fi network interface card to capture the channel state information (CSI) data. These CSI data are effectively processed, and then amplitude and phase information is used to obtain the spectrogram. In the subsequent step, the time-variant mean Doppler shift (MDS) caused …

business.industryComputer science05 social sciencesDecision treeWearable computer050801 communication & media studies020206 networking & telecommunicationsComputingMilieux_LEGALASPECTSOFCOMPUTING02 engineering and technologyLinear discriminant analysisActivity recognitionSupport vector machine0508 media and communicationsChannel state information0202 electrical engineering electronic engineering information engineeringSpectrogramComputer visionArtificial intelligencebusinessVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550
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Text Classification Using Novel “Anti-Bayesian” Techniques

2015

This paper presents a non-traditional “Anti-Bayesian” solution for the traditional Text Classification (TC) problem. Historically, all the recorded TC schemes work using the fundamental paradigm that once the statistical features are inferred from the syntactic/semantic indicators, the classifiers themselves are the well-established statistical ones. In this paper, we shall demonstrate that by virtue of the skewed distributions of the features, one could advantageously work with information latent in certain “non-central” quantiles (i.e., those distant from the mean) of the distributions. We, indeed, demonstrate that such classifiers exist and are attainable, and show that the design and im…

business.industryComputer scienceBayesian probabilityPattern recognitioncomputer.software_genreComputingMethodologies_PATTERNRECOGNITIONData miningArtificial intelligencebusinesscomputerClassifier (UML)Linear numberVector spaceQuantile
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