Search results for "Approx"

showing 10 items of 922 documents

Characterization of entropy measures against data loss: Application to EEG records

2012

This study is aimed at characterizing three signal entropy measures, Approximate Entropy (ApEn), Sample Entropy (SampEn) and Multiscale Entropy (MSE) over real EEG signals when a number of samples are randomly lost due to, for example, wireless data transmission. The experimental EEG database comprises two main signal groups: control EEGs and epileptic EEGs. Results show that both SampEn and ApEn enable a clear distinction between control and epileptic signals, but SampEn shows a more robust performance over a wide range of sample loss ratios. MSE exhibits a poor behavior for ratios over a 40% of sample loss. The EEG non-stationary and random trends are kept even when a great number of samp…

Computer scienceEntropyInformation Storage and RetrievalData lossElectroencephalographySensitivity and SpecificityApproximate entropyMultiscale entropyEntropy (classical thermodynamics)SeizuresStatisticsmedicineHumansEntropy (information theory)Entropy (energy dispersal)Entropy (arrow of time)medicine.diagnostic_testbusiness.industryEntropy (statistical thermodynamics)Reproducibility of ResultsElectroencephalographyPattern recognitionSample entropyArtificial intelligenceArtifactsbusinessAlgorithmsEntropy (order and disorder)2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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Group Nonnegative Matrix Factorization with Sparse Regularization in Multi-set Data

2021

Constrained joint analysis of data from multiple sources has received widespread attention for that it allows us to explore potential connections and extract meaningful hidden components. In this paper, we formulate a flexible joint source separation model termed as group nonnegative matrix factorization with sparse regularization (GNMF-SR), which aims to jointly analyze the partially coupled multi-set data. In the GNMF-SR model, common and individual patterns of particular underlying factors can be extracted simultaneously with imposing nonnegative constraint and sparse penalty. Alternating optimization and alternating direction method of multipliers (ADMM) are combined to solve the GNMF-S…

Computer scienceGroup (mathematics)020206 networking & telecommunications02 engineering and technologySparse approximationNon-negative matrix factorizationSet (abstract data type)Constraint (information theory)Computer Science::Computer Vision and Pattern Recognition0202 electrical engineering electronic engineering information engineeringSource separation020201 artificial intelligence & image processingJoint (audio engineering)Sparse regularizationAlgorithm2020 28th European Signal Processing Conference (EUSIPCO)
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Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology

2021

[EN] Background and objective: Magnetic resonance imaging is the most reliable imaging technique to assess the heart. More specifically there is great importance in the analysis of the left ventricle, as the main pathologies directly affect this region. In order to characterize the left ventricle, it is necessary to extract its volume. In this work we present a neural network architecture that is capable of directly estimating the left ventricle volume in short axis cine Magnetic Resonance Imaging in the end-diastolic frame and provide a segmentation of the region which is the basis of the volume calculation, thus offering explain-ability to the estimated value. Methods: The network was des…

Computer scienceHeart VentriclesMagnetic Resonance Imaging CineHealth InformaticsWeak supervisionTECNOLOGIA ELECTRONICAsymbols.namesakeMagnetic resonance imagingSegmentationApproximation errorImage Processing Computer-AssistedHumansSegmentationBasis (linear algebra)Artificial neural networkbusiness.industryDeep learningPattern recognitionHeartDeep learningLeft ventricleExplainabilityPearson product-moment correlation coefficientComputer Science ApplicationsTest setsymbolsArtificial intelligenceNeural Networks ComputerbusinessSoftwareVolume (compression)
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The Use of Easily Computed Checks as a Trigger for Error Elimination

1970

Several checks have been inserted in the three main programs in order to learn about their correlation to the average relative error.

Computer scienceOrder (business)Approximation errorAlgorithm
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Classification of Melanoma Lesions Using Sparse Coded Features and Random Forests

2016

International audience; Malignant melanoma is the most dangerous type of skin cancer, yet it is the most treatable kind of cancer, conditioned by its early diagnosis which is a challenging task for clinicians and dermatologists. In this regard, CAD systems based on machine learning and image processing techniques are developed to differentiate melanoma lesions from benign and dysplastic nevi using dermoscopic images. Generally, these frameworks are composed of sequential processes: pre-processing, segmentation, and classification. This architecture faces mainly two challenges: (i) each process is complex with the need to tune a set of parameters, and is specific to a given dataset; (ii) the…

Computer scienceSparse codingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-invariant feature transformImage processingDermoscopy02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineHistogram0202 electrical engineering electronic engineering information engineeringmedicineComputer visionSegmentationMelanoma[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingbusiness.industryMelanomaCancerPattern recognitionImage segmentationSparse approximationRandom forestsmedicine.diseaseClassificationRandom forest020201 artificial intelligence & image processingArtificial intelligenceSkin cancerNeural codingbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Free-standing 2D metals from binary metal alloys

2020

Recent experiment demonstrated the formation of free-standing Au monolayers by exposing Au-Ag alloy to electron beam irradiation. Inspired by this discovery, we used semi-empirical effective medium theory simulations to investigate monolayer formation in 30 different binary metal alloys composed of late d-series metals Ni, Cu, Pd, Ag, Pt, and Au. In qualitative agreement with the experiment, we find that the beam energy required to dealloy Ag atoms from Au-Ag alloy is smaller than the energy required to break the dealloyed Au monolayer. Our simulations suggest that similar method could also be used to form Au monolayers from Au-Cu alloy and Pt monolayers from Pt-Cu, Pt-Ni, and Pt-Pd alloys.

Condensed Matter - Materials ScienceCondensed Matter - Mesoscale and Nanoscale PhysicsalloysMesoscale and Nanoscale Physics (cond-mat.mes-hall)effective medium approximationMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesmetalliseokset2D materialslcsh:Physicslcsh:QC1-999electron beam irradiation
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Quantum Mechanical Modelling of Pure and Defective KNbO3 Perovskites

2000

Ab initio electronic structure calculations using the density-functional theory (DFT) are performed for KNbO3 with and without defects. Ferroelectric distortive transitions involve very small changes in energies and are therefore sensitive to DFT-approximations. This is discussed by comparing results obtained with the local density approximation (LDA) to those where generalized gradient approximations (GGA) are used. The results of ab initio calculations for F-type centers and bound hole polarons are compared to those obtained by a semiempirical method of the Intermediate Neglect of the Differential Overlap (INDO), based on the HartreeFock formalism. Supercells with 40 and 320 atoms were us…

Condensed Matter::Materials ScienceCondensed matter physicsAb initio quantum chemistry methodsPhysics::Atomic and Molecular ClustersAb initioDensity functional theoryElectronic structureLocal-density approximationPolaronMolecular physicsFerroelectricityQuantumMathematics
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Electrical transport with temperature-induced spin disorder in NiMnSb

2019

Abstract We investigate theoretically the combined effect of phonons and magnons caused by finite temperatures on the electrical resistivity of nonstoichiometric half-Heusler NiMnSb alloy. The coherent potential approximation within the alloy analogy model is employed for an efficient treatment of chemical impurities, atomic displacements, and magnetic disorder. Spin fluctuations of local Mn moments are described by two models: (i) uncompensated disordered local moment approach and (ii) tilting of the moments. The calculated resistivity agrees with experimental data, the agreement is good up to 600 K. We show that a strong magnetic disorder leads to a violation of the Matthiessen’s rule for…

Condensed Matter::Materials ScienceMaterials scienceSpin polarizationCondensed matter physicsElectrical resistivity and conductivityPhononImpurityMagnonCoherent potential approximationCurie temperatureCondensed Matter PhysicsSpin (physics)Electronic Optical and Magnetic MaterialsJournal of Magnetism and Magnetic Materials
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First-Principles Simulation of Substitutional Defects in Perovskites

2000

The results of supercell calculations of electronic structure and related properties of substitutional impurities in perovskite oxides KNbO3 and KTaO3 are discussed. For Fe impurities in KNbO3, the results obtained in the local density approximation (LDA) and in the LDA+U approach (that allows an ad hoc treatment of nonlocality in exchange-correlation) are compared, and different impurity charge configurations are discussed. The study of off-centre Li defects in incipient ferroelectric KTaO3 have been done by the appropriately parametrized Intermediate Neglect of Differential Overlap (INDO) method. The interaction energies of two off-centre impurities in different relative configurations ar…

Condensed Matter::Materials ScienceQuantum nonlocalityMaterials scienceCondensed matter physicsImpurityCondensed Matter::SuperconductivitySupercell (crystal)Condensed Matter::Strongly Correlated ElectronsCharge (physics)Electronic structureLocal-density approximationFerroelectricityPerovskite (structure)
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Iron-based Heusler compounds Fe2YZ: Comparison with theoretical predictions of the crystal structure and magnetic properties

2013

The present work reports on the new soft ferromagnetic Heusler phases Fe${}_{2}$NiGe, Fe${}_{2}$CuGa, and Fe${}_{2}$CuAl, which in previous theoretical studies have been predicted to exist in a tetragonal Heusler structure. Together with the known phases Fe${}_{2}$CoGe and Fe${}_{2}$NiGa these materials have been synthesized and characterized by powder x-ray diffraction, ${}^{57}$Fe M\"ossbauer spectroscopy, superconducting quantum interference device, and energy-dispersive x-ray measurements. In particular M\"ossbauer spectroscopy was used to monitor the degree of local atomic order/disorder and to estimate magnetic moments at the Fe sites from the hyperfine fields. It is shown that in con…

Condensed Matter::Materials ScienceTetragonal crystal systemMaterials scienceMagnetic momentFerromagnetismCondensed matter physicsAb initioCoherent potential approximationInverseElectronic structureCondensed Matter PhysicsHyperfine structureElectronic Optical and Magnetic MaterialsPhysical Review B
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