Search results for " Neural network"

showing 10 items of 1232 documents

OH-related Infrared Absorption Bands in Oxide Glasses

2005

We report the infrared activity, in the spectral region of the OH stretching modes, of different composite silicate glasses whose chemical composition is established by X-ray fluorescence measurements. The analysis of the absorption line profiles is made in terms of different spectral contributions, Gaussian in shape. The comparison with analogous spectra obtained in vitreous silica samples with impurity concentrations < 100 part per million moles is evidence of the effects of the different oxides on the vibrational properties of the OH groups. In particular, for oxide glasses a red shift of the composite band at about 3670 cm(-1), assigned to the OH stretching modes of free Si-OH groups an…

Absorption spectroscopyInfraredFTIR AbsorptionOxide glasseOxideAnalytical chemistryX-ray fluorescenceInfrared spectroscopyCondensed Matter PhysicsCondensed Matter::Disordered Systems and Neural NetworksSylanol groupsSilicateSpectral lineSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Settore FIS/03 - Fisica Della MateriaElectronic Optical and Magnetic Materialschemistry.chemical_compoundchemistryImpurityHydroxyl groupFTIR spectroscopy.Materials ChemistryCeramics and Compositessilicate glasse
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Mini-COVIDNet: Efficient Lightweight Deep Neural Network for Ultrasound Based Point-of-Care Detection of COVID-19

2021

Lung ultrasound (US) imaging has the potential to be an effective point-of-care test for detection of COVID-19, due to its ease of operation with minimal personal protection equipment along with easy disinfection. The current state-of-the-art deep learning models for detection of COVID-19 are heavy models that may not be easy to deploy in commonly utilized mobile platforms in point-of-care testing. In this work, we develop a lightweight mobile friendly efficient deep learning model for detection of COVID-19 using lung US images. Three different classes including COVID-19, pneumonia, and healthy were included in this task. The developed network, named as Mini-COVIDNet, was bench-marked with …

Acoustics and UltrasonicsCoronavirus disease 2019 (COVID-19)Computer sciencePoint-of-Care SystemsLatency (audio)detectionlung ultrasound (US) imaging01 natural sciences0103 physical sciencesImage Interpretation Computer-AssistedComputer-Assisted/methodsHumansElectrical and Electronic Engineering010301 acousticsInstrumentationImage InterpretationPoint of careUltrasonographyArtificial neural networkbusiness.industrySARS-CoV-2Deep learningImage Interpretation Computer-Assisted/methodsVDP::Technology: 500COVID-19deep learningUltrasonography/methodsLung ultrasoundCoronavirusTask (computing)point-of-care testingSoftware deploymentEmbedded systemCOVID-19/diagnostic imagingArtificial intelligencebusiness
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An ASSOM neural network to represent actions performed by an autonomous agent

1997

An ASSOM neural network to describe the action performed by an autonomous reactive agent is proposed. The neural network receives in input the sequences of data acquired by the agent internal sensors and it classifies them by generating the corresponding symbolic assertions. Experimental results performed on a RWI B12 autonomous robot are reported.

Action (philosophy)Artificial neural networkComputer sciencebusiness.industryControl systemAutonomous agentRoboticsComputingMethodologies_GENERALArtificial intelligenceAutonomous robotbusiness
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Rapid developmental switch in the mechanisms driving early cortical columnar networks

2006

The immature cerebral cortex self-organizes into local neuronal clusters long before it is activated by patterned sensory inputs. In the cortical anlage of newborn mammals, neurons coassemble through electrical or chemical synapses either spontaneously or by activation of transmitter-gated receptors. The neuronal network and the cellular mechanisms underlying this cortical self-organization process during early development are not completely understood. Here we show in an intact in vitro preparation of the immature mouse cerebral cortex that neurons are functionally coupled in local clusters by means of propagating network oscillations in the beta frequency range. In the newborn mouse, this…

Action PotentialsSensory systemBiologyReceptors N-Methyl-D-AspartateSynapseMiceSubplatemedicineBiological neural networkAnimalsReceptorNeuronsMultidisciplinaryGap junctionGap JunctionsSomatosensory CortexElectrophysiologyMice Inbred C57BLElectrophysiologymedicine.anatomical_structureBiochemistryAnimals NewbornCerebral cortexSynapsesNMDA receptorCarbacholNeuronCortical columnNeurosciencee-Neuroforum
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Is the nonREM–REM sleep cycle reset by forced awakenings from REM sleep?

2002

In selective REM sleep deprivation (SRSD), the occurrence of stage REM is repeatedly interrupted by short awakenings. Typically, the interventions aggregate in clusters resembling the REM episodes in undisturbed sleep. This salient phenomenon can easily be explained if the nonREM–REM sleep process is continued during the periods of forced wakefulness. However, earlier studies have alternatively suggested that awakenings from sleep might rather discontinue and reset the ultradian process. Theoretically, the two explanations predict a different distribution of REM episode duration. We evaluated 117 SRSD treatment nights recorded from 14 depressive inpatients receiving low dosages of Trimipram…

Activity CyclesMaleSelective REM sleep deprivationPolysomnographyAudiologyBehavioral NeuroscienceNIGHTSleep onset REM episodeDEPRIVATIONSlow-wave sleepmedia_commonDEPRESSIVE PATIENTSmedicine.diagnostic_testDepressionmusculoskeletal neural and ocular physiologyTRIMIPRAMINEMiddle AgedAntidepressive AgentsAnesthesiaLATENCIESFemaleWakefulnessArousalPsychologyAlgorithmspsychological phenomena and processesmedicine.drugVigilance (psychology)Adultmedicine.medical_specialtyREM episodePolysomnographymedia_common.quotation_subjectRapid eye movement sleepSleep REMExperimental and Cognitive PsychologyNon-rapid eye movement sleepmental disordersmedicineHumansWakefulnessMODULATIONUltradian rhythmINTERRUPTIONARTIFICIAL NEURAL NETWORKSRECOGNITIONTrimipramineUltradian processSleep cycleSleepEYE-MOVEMENT SLEEPPhysiology &amp; Behavior
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Combining Benford's Law and machine learning to detect money laundering. An actual Spanish court case.

2017

Abstract Objectives This paper is based on the analysis of the database of operations from a macro-case on money laundering orchestrated between a core company and a group of its suppliers, 26 of which had already been identified by the police as fraudulent companies. In the face of a well-founded suspicion that more companies have perpetrated criminal acts and in order to make better use of what are very limited police resources, we aim to construct a tool to detect money laundering criminals. Methods We combine Benford’s Law and machine learning algorithms (logistic regression, decision trees, neural networks, and random forests) to find patterns of money laundering criminals in the conte…

Actuarial scienceScrutinyArtificial neural networkComputer sciencebusiness.industryDecision treeContext (language use)02 engineering and technologySpace (commercial competition)Money launderingComputer securitycomputer.software_genreMachine learning01 natural sciencesPathology and Forensic MedicineBenford's law010104 statistics & probabilityOrder (business)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligence0101 mathematicsbusinessLawcomputerForensic science international
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Using adaptive fuzzy-neural control to minimize response time in cluster-based web systems

2005

We have developed content-aware request distribution algorithm called FARD which is a client-and-server-aware, dynamic and adaptive distribution policy in cluster-based Web systems. It assigns each incoming request to the server with the least expected response time. To estimate the expected response times it uses the fuzzy estimation mechanism. The system is adaptive as it uses a neural network learning ability for its adaptation. Simulations based on traces from the 1998 World Cup show that when we consider the response time, FARD can be more effective than the state-of-the-art content-aware policy LARD.

Adaptive controlArtificial neural networkComputer sciencebusiness.industryAdaptive systemResponse timeThe InternetFuzzy control systemArtificial intelligenceAdaptation (computer science)businessFuzzy logic
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Type-2 Fuzzy Control of a Bioreactor

2009

Abstract—In this paper the control of a bioprocess using an adaptive type-2 fuzzy logic controller is proposed. The process is concerned with the aerobic alcoholic fermentation for the growth of Saccharomyces Cerevisiae a n d i s characterized by nonlinearity and parameter uncertainty. Three type-2 fuzzy controllers heve been developed and tested by simulation: a simple type-2 fuzzy logic controller with 49 rules; a type-2 fuzzyneuro- predictive controller (T2FNPC); a t y p e -2 selftuning fuzzy controller ( T2STFC). The T2FNPC combines the capability of the type-2 fuzzy logic to handle uncertainties, with the ability of predictive control to predict future plant performance making use of a…

Adaptive neuro fuzzy inference systemSettore ING-IND/26 - Teoria Dello Sviluppo Dei Processi ChimiciAdaptive controlArtificial neural networkNeuro-fuzzyComputer scienceFuzzy setFuzzy control systemEthanol fermentationFuzzy logicDefuzzificationNonlinear systemModel predictive controlControl theoryAdaptive systemAdaptive control Type-2 fuzzy control Non-linear systems UncertaintyProcess controlRobust control
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Dosage individualization of erythropoietin using a profile-dependent support vector regression

2003

The external administration of recombinant human erythropoietin is the chosen treatment for those patients with secondary anemia due to chronic renal failure in periodic hemodialysis. The objective of this paper is to carry out an individualized prediction of the EPO dosage to be administered to those patients. The high cost of this medication, its side-effects and the phenomenon of potential resistance which some individuals suffer all justify the need for a model which is capable of optimizing dosage individualization. A group of 110 patients and several patient factors were used to develop the models. The support vector regressor (SVR) is benchmarked with the classical multilayer percept…

AdultAnemia HemolyticInjections SubcutaneousAutoregressive conditional heteroskedasticityBiomedical EngineeringMachine learningcomputer.software_genreCohort StudiesHemoglobinsRenal DialysisFeature (machine learning)HumansMedicineSensitivity (control systems)Time seriesErythropoietinAgedAged 80 and overArtificial neural networkbusiness.industryMiddle AgedRecombinant ProteinsRegressionDrug Therapy Computer-AssistedRegression PsychologySupport vector machineTreatment OutcomeMultilayer perceptronKidney Failure ChronicNeural Networks ComputerArtificial intelligencebusinesscomputerAlgorithmsBiomedical engineeringIEEE Transactions on Biomedical Engineering
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Criss‐crossing autism spectrum disorder and adult neurogenesis

2021

Autism spectrum disorder (ASD) comprises a group of multifactorial neurodevelopmental disorders primarily characterized by deficits in social interaction and repetitive behavior. Although the onset is typically in early childhood, ASD poses a lifelong challenge for both patients and caretakers. Adult neurogenesis (AN) is the process by which new functional neurons are created from neural stem cells existing in the post-natal brain. The entire event is based on a sequence of cellular processes, such as proliferation, specification of cell fate, maturation, and ultimately, synaptic integration into the existing neural circuits. Hence, AN is implicated in structural and functional brain plasti…

AdultAutism Spectrum DisorderNeurogenesisNeurogenesisCell fate determinationBiologymedicine.diseaseAffect (psychology)BiochemistryFMR1Neural stem cellCellular and Molecular NeuroscienceNeural Stem CellsNeurodevelopmental DisordersAutism spectrum disorderChild Preschoolmental disordersmedicineBiological neural networkAnimalsHumansEarly childhoodNeuroscienceJournal of Neurochemistry
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