Search results for "Receiver"

showing 10 items of 308 documents

Control subsystem design for wireless power transfer

2014

Recently, the wireless power transfer has been increasingly employed. Particularly for the electric vehicles, the wireless solution is attractive for contactless battery charging, based on the Inductive Power Transfer (IPT). In this paper, a 150W prototype for IPT-based battery charging is presented and design criteria are reported. In addition to the power stage analysis, a proper control strategy is proposed. Simulation and experimental results are shown. The proposed control method aims at regulating the load current against variations in the magnetic coupling, so that the required amount of power can be supplied despite of unexpected decreases in the coupling efficiency.

Battery (electricity)control subsystem designEngineeringControl (management)IPT-based battery chargingWireless communicationwireless power transfermagnetic couplingCoilSettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciSettore ING-INF/01 - ElettronicaBatterieReceiverCouplingcontactless battery charginginductive power transmissioncontrol system synthesiWirelessMaximum power transfer theoremWireless power transferinductive power transferInductancepower stage analysiecondary cellbusiness.industryElectrical engineeringTransmittercoupling efficiencyInductive couplingPower (physics)power flow controlInductancebusinessload current regulation
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Design and validation of a wireless Body Sensor Network for integrated EEG and HD-sEMG acquisitions

2022

Sensorimotor integration is the process through which the human brain plans the motor program execution according to external sources. Within this context, corticomuscular and corticokinematic coherence analyses are common methods to investigate the mechanism underlying the central control of muscle activation. This requires the synchronous acquisition of several physiological signals, including EEG and sEMG. Nevertheless, physical constraints of the current, mostly wired, technologies limit their application in dynamic and naturalistic contexts. In fact, although many efforts were made in the development of biomedical instrumentation for EEG and High Density-surface EMG (HD-sEMG) signal ac…

Biomedical Engineeringevoked potentialsWireless communicationSynchronizationReceiversBody sensor networkswireless body sensor networkmittauslaitteetInternal MedicineHumansEEGsensorimotor integrationBiopotential acquisition systemsHD-sEMGElectromyographyGeneral NeuroscienceRehabilitationsensoriverkotBrainSignal Processing Computer-AssistedElectroencephalographyelektromyografiahermo-lihastoimintaBiopotential acquisition systems; Body sensor networks; EEG; Electroencephalography; Electromyography; evoked potentials; HD-sEMG; Instruments; Receivers; sensorimotor integration; Synchronization; wireless body sensor network; Wireless communicationInstrumentsWireless Technologylangattomat verkot
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Diagnostic efficacy of panoramic mandibular index to identify postmenopausal women with low bone mineral densities

2011

Objectives: The aim of the study was to compare and assess the accuracy of panoramic mandibular index (PMI) and antegonial index (AI) in the panoramic radiographs of postmenopausal women with normal and low skeletal bone mineral densities( BMD) diagnosed by using dual energy x-ray absorptiometry ( DXA). Study Design: In panoramic radiographs obtained from 40 post menopausal women( 20 normal and 20 osteoporo tic) aged between 50-75 who’s BMD has already been assessed by a DXA, the mean was calculated for PMI and AI index values measured in the right and left mandibles. The PMI and AI index values were evaluated using the student’s t test. The correlation between the observers for indices was…

Bone mineralIndex (economics)Receiver operating characteristicbusiness.industryRadiographyOsteoporosisDentistryOdontología:CIENCIAS MÉDICAS [UNESCO]medicine.diseaseCiencias de la saludConfidence intervalPearson product-moment correlation coefficientsymbols.namesakeStandard errorUNESCO::CIENCIAS MÉDICASsymbolsmedicinebusinessGeneral DentistryJournal of Clinical and Experimental Dentistry
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3D DCE-MRI Radiomic Analysis for Malignant Lesion Prediction in Breast Cancer Patients

2022

Rationale and Objectives: To develop and validate a radiomic model, with radiomic features extracted from breast Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) from a 1.5T scanner, for predicting the malignancy of masses with enhancement. Images were acquired using an 8-channel breast coil in the axial plane. The rationale behind this study is to show the feasibility of a radio-mics-powered model that could be integrated into the clinical practice by exploiting only standard-of-care DCE-MRI with the goal of reducing the required image pre-processing (ie, normalization and quantitative imaging map generation).Materials and Methods: 107 radiomic features were extracted from a …

Breast cancer Dynamic contrast-enhanced magnetic resonance imagingSupport Vector MachineComputer scienceNormalization (image processing)Breast NeoplasmsFeature selectionBreast cancerBreast cancerDiscriminative modelmedicineHumansRadiology Nuclear Medicine and imagingBreastRetrospective StudiesDynamic contrast-enhanced magnetic resonance imagingRadiomicsSupport vector machinesReceiver operating characteristicbusiness.industryPattern recognitionmedicine.diseaseMagnetic Resonance Imagingmachine learning Radiomics unsupervised feature selection Support vector machinesSupport vector machinemachine learningROC CurveFeature (computer vision)Test setFemaleArtificial intelligenceSettore MED/36 - Diagnostica Per Immagini E Radioterapiabusinessunsupervised feature selectionBreast cancer Dynamic contrast-enhanced magnetic resonance imaging; machine learning Radiomics unsupervised feature selection Support vector machinesAcademic Radiology
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Preoperative CT-Based Deep Learning Model for Predicting Risk Stratification in Patients With Gastrointestinal Stromal Tumors.

2021

ObjectiveTo develop and evaluate a deep learning model (DLM) for predicting the risk stratification of gastrointestinal stromal tumors (GISTs).MethodsPreoperative contrast-enhanced CT images of 733 patients with GISTs were retrospectively obtained from two centers between January 2011 and June 2020. The datasets were split into training (n = 241), testing (n = 104), and external validation cohorts (n = 388). A DLM for predicting the risk stratification of GISTs was developed using a convolutional neural network and evaluated in the testing and external validation cohorts. The performance of the DLM was compared with that of radiomics model by using the area under the receiver operating char…

Cancer Researchmedicine.medical_specialtyReceiver operating characteristicbusiness.industryDeep learningClass activation mappingNeoplasms. Tumors. Oncology. Including cancer and carcinogensrisk assessmentdeep learningX-ray computedtomographyConfidence intervalprediction modelgastrointestinal stromal tumorsOncologyRisk stratificationCohortMedicineIn patientRadiologyArtificial intelligencebusinessRisk assessmentRC254-282Original ResearchFrontiers in oncology
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Evaluation of stroke volume variation obtained by arterial pulse contour analysis to predict fluid responsiveness intraoperatively

2009

Background Fluid management guided by oesophageal Doppler monitor has been reported to improve perioperative outcome. Stroke volume variation (SVV) is considered a reliable clinical predictor of fluid responsiveness. Consequently, the aim of the present trial was to evaluate the accuracy of SVV determined by arterial pulse contour (APCO) analysis, using the FloTrac™/Vigileo™ system, to predict fluid responsiveness as measured by the oesophageal Doppler. Methods Patients undergoing major abdominal surgery received intraoperative fluid management guided by oesophageal Doppler monitoring. Fluid boluses of 250 ml each were administered in case of a decrease in corrected flow time (FTc) to 10%. …

Cardiac outputAnesthesiology and Pain MedicineReceiver operating characteristicbusiness.industryAnesthesiaMedicineHemodynamicsBlood flowPerioperativeStroke volumebusinessConfidence intervalAbdominal surgeryBritish Journal of Anaesthesia
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La première rencontre du corps malade en contexte de soins infirmiers : la relation de soin : une expérience ultime, du sensible au social

2016

Our study focuses on nursing care with a first approach based on human body and emotions through the teaching context in the sensitive hospital environment. The nursing student is a central point of our research as he lives a unique sensitive and interpersonal experience within his own body in a social setting imbued with symbolism. He perceives health care community through his five senses which inform and direct him, but also may destabilize him. We decided to base our study on the information and communication sciences thanks to a sensitive, sensorial and symbolic problematisation and through a multidisciplinary conceptualization based on different theoretical approaches, symbolic intera…

Caregiver and care-receiver relationshipSoins infirmiers[SHS.INFO]Humanities and Social Sciences/Library and information sciencesSymbolicSensorialNursing careSymbolique[SHS.INFO] Humanities and Social Sciences/Library and information sciencesSensitiveRelation soignant-soignéSensibleHuman bodyCorps[ SHS.INFO ] Humanities and Social Sciences/Library and information sciencesSensorielÉmotions
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Child abuse/neglect risk assessment under field practice conditions: Tests of external and temporal validity and comparison with heart disease predic…

2015

AbstractObjectives (1) Identify validation design and accuracy assessment standards for medical prognostic models applicable to evaluation of child abuse/neglect (CA/N) risk assessment models. (2) Assess the accuracy of the California Family Risk Assessment (CFRA) in predicting CA/N using the foregoing standards. (3) Compare the prediction accuracy of the CFRA with the prediction accuracy of coronary heart disease (CHD) prediction models. Questions addressed (1) What validation design and accuracy assessment standards are used to evaluate medical prognostic models? (2) What is the evidence for the accuracy of the CFRA using those standards? (3) How does the accuracy of the CFRA in predictin…

Child abusePediatricsmedicine.medical_specialtyFramingham Risk ScoreSociology and Political ScienceReceiver operating characteristicbusiness.industryPoison controlCoronary heart diseaseEducationStatisticsDevelopmental and Educational PsychologymedicineRisk assessmentbusinessChild Abuse & NeglectPredictive modellingChildren and Youth Services Review
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Modelling and Analysis of Non-Stationary Multipath Fading Channels with Time-Variant Angles of Arrival

2017

In mobile radio channel modelling, it is generally assumed that the angles of arrival (AOAs) are independent of time. This assumption does in general not agree with real-world channels in which the AOAs vary with the position of a moving receiver. In this paper, we first present a mathematical model for the time-variant AOAs. This model serves as the basis for the development of two non-stationary multipath fading channels models. The statistical properties of both channel models are analysed with emphasis on the time-dependent autocorrelation function (ACF), time-dependent mean Doppler shift, time-dependent Doppler spread, and the Wigner-Ville spectrum. It is shown that these characteristi…

Computer scienceAutocorrelation020302 automobile design & engineering020206 networking & telecommunications02 engineering and technologyDelay spreadsymbols.namesakeFading distribution0203 mechanical engineering0202 electrical engineering electronic engineering information engineeringsymbolsRake receiverFadingStatistical physicsDoppler effectMultipath propagationCommunication channelComputer Science::Information Theory
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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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