Search results for "Fluid Flow and Transfer Processes"

showing 10 items of 386 documents

Robust Resolution-Enhanced Prostate Segmentation in Magnetic Resonance and Ultrasound Images through Convolutional Neural Networks

2021

[EN] Prostate segmentations are required for an ever-increasing number of medical applications, such as image-based lesion detection, fusion-guided biopsy and focal therapies. However, obtaining accurate segmentations is laborious, requires expertise and, even then, the inter-observer variability remains high. In this paper, a robust, accurate and generalizable model for Magnetic Resonance (MR) and three-dimensional (3D) Ultrasound (US) prostate image segmentation is proposed. It uses a densenet-resnet-based Convolutional Neural Network (CNN) combined with techniques such as deep supervision, checkpoint ensembling and Neural Resolution Enhancement. The MR prostate segmentation model was tra…

Computer scienceMR prostate imagingUS prostate imagingINGENIERIA MECANICAconvolutional neural networklcsh:TechnologyConvolutional neural network030218 nuclear medicine & medical imaginglcsh:Chemistry03 medical and health sciences0302 clinical medicinemedicineGeneral Materials Sciencelcsh:QH301-705.5Instrumentation030304 developmental biologyFluid Flow and Transfer Processes0303 health sciencesmedicine.diagnostic_testlcsh:Tbusiness.industryProcess Chemistry and TechnologyConvolutional Neural NetworksUltrasoundResolution (electron density)General EngineeringMagnetic resonance imagingPattern recognitionProstate Segmentationlcsh:QC1-999Computer Science ApplicationsNeural resolution enhancementlcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040Christian ministryArtificial intelligencelcsh:Engineering (General). Civil engineering (General)Magnetic Resonance and Ultrasound Imagesbusinesslcsh:PhysicsProstate segmentationApplied Sciences
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Deep Convolutional Neural Network for HEp-2 fluorescence intensity classification

2019

Indirect ImmunoFluorescence (IIF) assays are recommended as the gold standard method for detection of antinuclear antibodies (ANAs), which are of considerable importance in the diagnosis of autoimmune diseases. Fluorescence intensity analysis is very often complex, and depending on the capabilities of the operator, the association with incorrect classes is statistically easy. In this paper, we present a Convolutional Neural Network (CNN) system to classify positive/negative fluorescence intensity of HEp-2 IIF images, which is important for autoimmune diseases diagnosis. The method uses the best known pre-trained CNNs to extract features and a support vector machine (SVM) classifier for the …

Computer scienceSVM02 engineering and technologyConvolutional neural networklcsh:TechnologyIIF image030218 nuclear medicine & medical imaginglcsh:Chemistry03 medical and health sciences0302 clinical medicineClassifier (linguistics)Autoimmune disease0202 electrical engineering electronic engineering information engineeringGeneral Materials Scienceautoimmune diseasesReceiver operating characteristic (ROC) curveInstrumentationlcsh:QH301-705.5AccuracyIIF imagesFluid Flow and Transfer ProcessesIndirect immunofluorescencebusiness.industrylcsh:TProcess Chemistry and TechnologyGeneral EngineeringPattern recognitionIIfGold standard (test)Convolutional Neural Network (CNN)lcsh:QC1-999Computer Science ApplicationsIntensity (physics)Support vector machineFluorescence intensitylcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040020201 artificial intelligence & image processingArtificial intelligencebusinesslcsh:Engineering (General). Civil engineering (General)lcsh:Physics
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An Automatic HEp-2 Specimen Analysis System Based on an Active Contours Model and an SVM Classification

2019

The antinuclear antibody (ANA) test is widely used for screening, diagnosing, and monitoring of autoimmune diseases. The most common methods to determine ANA are indirect immunofluorescence (IIF), performed by human epithelial type 2 (HEp-2) cells, as substrate antigen. The evaluation of ANA consist an analysis of fluorescence intensity and staining patterns. This paper presents a complete and fully automatic system able to characterize IIF images. The fluorescence intensity classification was obtained by performing an image preprocessing phase and implementing a Support Vector Machines (SVM) classifier. The cells identification problem has been addressed by developing a flexible segmentati…

Computer scienceSVMKNN02 engineering and technologylcsh:TechnologyIIF imageHough transformlaw.inventionlcsh:Chemistry03 medical and health scienceslawClassifier (linguistics)0202 electrical engineering electronic engineering information engineeringPreprocessorGeneral Materials ScienceSegmentationcell segmentationlcsh:QH301-705.5InstrumentationIIF images030304 developmental biologyFluid Flow and Transfer Processes0303 health sciencesIndirect immunofluorescencelcsh:Tbusiness.industryProcess Chemistry and TechnologyGeneral EngineeringPattern recognitionSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)ROC curvelcsh:QC1-999Computer Science ApplicationsSupport vector machineParameter identification problemFluorescence intensityHough transformlcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040020201 artificial intelligence & image processingArtificial intelligencelcsh:Engineering (General). Civil engineering (General)businesslcsh:Physicsactive contours modelApplied Sciences
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Assessment of Deep Learning Methodology for Self-Organizing 5G Networks

2019

In this paper, we present an auto-encoder-based machine learning framework for self organizing networks (SON). Traditional machine learning approaches, for example, K Nearest Neighbor, lack the ability to be precisely predictive. Therefore, they can not be extended for sequential data in the true sense because they require a batch of data to be trained on. In this work, we explore artificial neural network-based approaches like the autoencoders (AE) and propose a framework. The proposed framework provides an advantage over traditional machine learning approaches in terms of accuracy and the capability to be extended with other methods. The paper provides an assessment of the application of …

Computer scienceintrusion detection5G-tekniikka02 engineering and technologyIntrusion detection systemself-organizing networks (SON)Machine learningcomputer.software_genrelcsh:Technologyk-nearest neighbors algorithmself-organizing networkslcsh:Chemistryautoencoder (AE)deep learning (DL)mobility load balancing0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceInstrumentationlcsh:QH301-705.5Fluid Flow and Transfer ProcessesautoencoderArtificial neural networkbusiness.industrylcsh:Tmobility load balancing (MLB)Process Chemistry and TechnologyDeep learningGeneral Engineeringdeep learning020206 networking & telecommunicationsSelf-organizing networkLoad balancing (computing)021001 nanoscience & nanotechnologyAutoencoderlcsh:QC1-999Computer Science Applicationscell outage detectionlcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040Cellular networkArtificial intelligence0210 nano-technologybusinesslcsh:Engineering (General). Civil engineering (General)computerlcsh:Physics5G
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The Elephant in the Machine: Proposing a New Metric of Data Reliability and its Application to a Medical Case to Assess Classification Reliability

2020

In this paper, we present and discuss a novel reliability metric to quantify the extent a ground truth, generated in multi-rater settings, as a reliable basis for the training and validation of machine learning predictive models. To define this metric, three dimensions are taken into account: agreement (that is, how much a group of raters mutually agree on a single case)

Computer sciencekneeMachine learningcomputer.software_genrelcsh:TechnologyTask (project management)lcsh:Chemistry03 medical and health sciencesMagnetic resonance imaging0302 clinical medicine0504 sociologyGeneral Materials Science030212 general & internal medicinelcsh:QH301-705.5InstrumentationCompetence (human resources)MRNetReliability (statistics)Fluid Flow and Transfer ProcessesGround truthreliabilityBasis (linear algebra)Point (typography)lcsh:Tbusiness.industryComputer Science::Information RetrievalProcess Chemistry and Technology05 social sciencesGeneral Engineering050401 social sciences methodslcsh:QC1-999Computer Science ApplicationsInter-rater reliabilitymachine learninglcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040inter-rater agreementArtificial intelligenceMetric (unit)lcsh:Engineering (General). Civil engineering (General)businessground truthcomputerlcsh:PhysicsApplied Sciences
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Biomechanical analysis of two types of osseointegrated transfemoral prosthesis

2020

In the last two decades, osseointegrated prostheses have been shown to be a good alternative for lower limb amputees experiencing complications in using a traditional socket-type prosthesis

Computer sciencemedicine.medical_treatmentFinite element analysi0206 medical engineeringOPLProsthetic limb02 engineering and technologyProsthesislcsh:TechnologyOsseointegrationlcsh:Chemistry03 medical and health sciencesDistal femur0302 clinical medicineosseointegrated prosthesismedicineGeneral Materials ScienceCADOPL osseointegrated prosthesiSettore ING-IND/15 - Disegno E Metodi Dell'Ingegneria IndustrialeInstrumentationlcsh:QH301-705.5Fluid Flow and Transfer ProcessesOrthodontics030222 orthopedicslcsh:TProcess Chemistry and TechnologyGeneral EngineeringFinite element analysisOPL osseointegrated prosthesisLimitingStress distributionTransfemoral amputeeequipment and supplies020601 biomedical engineeringTransfemoral prosthesislcsh:QC1-999OPRAComputer Science Applicationsbody regionslcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040Implantlcsh:Engineering (General). Civil engineering (General)lcsh:Physics
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Natural Convection Cooling of a Hot Vertical Wall Wet by a Falling Liquid Film

2008

Abstract The system studied is a plane channel in which one of the two vertical walls is kept at an arbitrary temperature profile and may be partially or completely wet by a falling liquid film, while the opposite wall is adiabatic. Air from the environment flows along the channel with a mass flow rate which depends on the balance between hydraulic resistances and buoyancy forces. These latter, in their turn, depend on the distribution of temperature and humidity (hence, density) along the channel and eventually on the heat and mass transferred from wall and film to the humid air. A simplified computational model of the above system was developed and applied to the prediction of relevant qu…

ConvectionBuoyancyMaterials scienceThermodynamicsengineering.materialPhysics::Fluid DynamicsMass flow rateEvaporative CoolingFluid FlowPhysics::Atmospheric and Oceanic PhysicsEngineering & allied operationsSettore ING-IND/19 - Impianti NucleariFluid Flow and Transfer ProcessesNatural convectionNatural ConvectionMechanical Engineeringfree convection liquid film humid air evaporative cooling containment cooling heat and mass transferHumidityMechanicsContainmentCondensed Matter PhysicsHeat TransferPassive CoolingCoolantVolumetric flow rateLiquid FilmNuclear ReactorDecay Heat Removalengineeringddc:620Evaporative cooler
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Coupling between oxidation kinetics and anisothermal oil flow during deep-fat frying

2021

Deep-fat frying is a cooking technique that has been used continuously since prehistoric times. A domestic deep-fryer heated from the bottom develops significant convection inside the bath cavity. It is responsible for very high heat transfer coefficients and the exposure of the deep-frying oil to the atmospheric oxygen. The continuous conversion of gaseous dioxygen into unstable and reactive hydroperoxides and their subsequent advection throughout the bulk volume is at the origin of the main complaints made of frying which includes issues such as odors, fouling, and generation of several toxic compounds. This study analyzes the coupling between natural convection of triacylglycerols and th…

ConvectionComputational MechanicsThermodynamics010402 general chemistry01 natural sciencesEndothermic process0404 agricultural biotechnologyFluid Flow and Transfer ProcessesPhysicsNatural convectionAutoxidationHeating elementAdvectionMechanical Engineering[SPI.FLUID]Engineering Sciences [physics]/Reactive fluid environment04 agricultural and veterinary sciences[SPI.FLUID] Engineering Sciences [physics]/Reactive fluid environmentCondensed Matter Physics040401 food scienceDecomposition0104 chemical sciences[SDV.AEN] Life Sciences [q-bio]/Food and NutritionVolume (thermodynamics)13. Climate actionMechanics of Materials[SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
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Onset of Convection in an Inclined Anisotropic Porous Layer with Internal Heat Generation

2019

The onset of convection in an inclined porous layer which is heated internally by a uniform distribution of heat sources is considered. We investigate the combined effects of inclination, anisotropy and internal heat generation on the linear instability of the basic parallel flow. When the Rayleigh number is sufficiently large, instability occurs and a convective motion is set up. It turns out that the preferred motion at convection onset depends quite strongly on the anisotropy ratio, &xi

ConvectioninclinationMaterials scienceonsetComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyanisotropylcsh:Thermodynamics01 natural sciencesInstability010305 fluids & plasmasPhysics::Fluid Dynamicsporous media0203 mechanical engineeringlcsh:QC310.15-3190103 physical sciencesAstrophysics::Solar and Stellar Astrophysicsheat generationAnisotropyconvectionlcsh:QC120-168.85Fluid Flow and Transfer ProcessesMechanical EngineeringMechanicsRayleigh numberCondensed Matter PhysicsVDP::Matematikk og Naturvitenskap: 400::Matematikk: 410Transverse plane020303 mechanical engineering & transportsTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESHeat generationComputer Science::Programming Languageslcsh:Descriptive and experimental mechanicsAstrophysics::Earth and Planetary AstrophysicsInternal heatingPorous mediumFluids
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Interaction between turbulent structures and particles in roughened channel

2016

Abstract The distribution of inertial particles in turbulent flows is highly non-uniform and is driven by the local dynamics of the turbulent structures of the underlying carrier flow field. In the specific context of dilute particle-laden wall-bounded flows, deposition and resuspension mechanisms are dominated by the interaction between inertial particles and coherent turbulent structures characteristic of the wall region. The macroscopic behavior of these two-phase systems is influenced by particle inertia, which plays a role at the microscale of a single dispersed element. These turbulent structures, which control the turbulent regeneration cycles, are strongly affected by the wall rough…

DNSmedia_common.quotation_subjectDirect numerical simulationGeneral Physics and AstronomyContext (language use)Lagrangian particle trackingInertia01 natural sciencesSettore ICAR/01 - Idraulica010305 fluids & plasmasPhysics::Fluid DynamicsPhysics and Astronomy (all)symbols.namesake0103 physical sciences010306 general physicsDispersion (water waves)media_commonFluid Flow and Transfer ProcessesPhysicsTurbulenceMechanical EngineeringParticle-laden flowReynolds numberMechanicsTurbulenceClassical mechanicssymbolsParticleLagrangian trackingParticle mass fluxRoughneInternational Journal of Multiphase Flow
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