Search results for "Neural"

showing 10 items of 2783 documents

Direct activation of zebrafish neurons by ultrasonic stimulation revealed by whole CNS calcium imaging

2020

Abstract Objective. Ultrasounds (US) use in neural engineering is so far mainly limited to ablation through high intensity focused ultrasound, but interesting preliminary results show that low intensity low frequency ultrasound could be used instead to modulate neural activity. However, the extent of this modulatory ability of US is still unclear, as in in vivo studies it is hard to disentangle the contribution to neural responses of direct activation of the neuron by US stimulation and indirect activation due either to sensory response to mechanical stimulation associated to US, or to propagation of activity from neighboring areas. Here, we aim to show how to separate the three effects and…

Ultrasonic Therapy0206 medical engineeringBiomedical EngineeringCalcium imagingStimulationSensory systembrain-stimulation02 engineering and technologysystem03 medical and health sciencesCellular and Molecular NeuroscienceUltrasounds0302 clinical medicineCalcium imagingmedicineAnimalsZebrafishZebrafishNeuronscalcium imaging ultrasonic stimulation ultrasound zebrafishSensory stimulation therapybiologyCalcium imaging; Neuromodulation; Ultrasounds; ZebrafishNeuromodulationneuromodulation; zebrafish; ultrasounds; calcium imagingtranscranial focused ultrasoundNeural engineeringbiology.organism_classification020601 biomedical engineeringNeuromodulation (medicine)cellular resolutionmedicine.anatomical_structureLarvaCalciumNeuronNeuroscience030217 neurology & neurosurgeryneurostimulation
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Bot recognition in a Web store: An approach based on unsupervised learning

2020

Abstract Web traffic on e-business sites is increasingly dominated by artificial agents (Web bots) which pose a threat to the website security, privacy, and performance. To develop efficient bot detection methods and discover reliable e-customer behavioural patterns, the accurate separation of traffic generated by legitimate users and Web bots is necessary. This paper proposes a machine learning solution to the problem of bot and human session classification, with a specific application to e-commerce. The approach studied in this work explores the use of unsupervised learning (k-means and Graded Possibilistic c-Means), followed by supervised labelling of clusters, a generative learning stra…

Unsupervised classificationWeb bot detectionComputer Networks and CommunicationsComputer scienceInternet robot02 engineering and technologyMachine learningcomputer.software_genreWeb trafficWeb serverMachine learning0202 electrical engineering electronic engineering information engineeringArtificial neural networkbusiness.industrySupervised learning020206 networking & telecommunicationsPerceptronWeb application securityWeb botComputer Science ApplicationsSupport vector machineGenerative modelComputingMethodologies_PATTERNRECOGNITIONHardware and ArchitectureSupervised classificationUnsupervised learning020201 artificial intelligence & image processingArtificial intelligencebusinesscomputer
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Effects of deep cervical flexor training on pressure pain thresholds over myofascial trigger points in patients with chronic neck pain.

2012

The purpose of this study was to assess the effects of a low-load training program for the deep cervical flexors (DCFs) on pain, disability, and pressure pain threshold (PPT) over cervical myofascial trigger points (MTrPs) in patients with chronic neck pain.Thirty patients with chronic idiopathic neck pain participated in a 6-week program of specific training for the DCF, which consisted of active craniocervical flexion performed twice per day (10-20 minutes) for the duration of the trial. Perceived pain and disability (Neck Disability Index, 0-50) and PPT over MTrPs of the upper trapezius, levator scapulae, and splenius capitis muscles were measured at the beginning and end of the training…

Upper trapeziusAdultMaleManipulation Spinalmedicine.medical_specialtyPressure painAdolescentFacial NeuralgiaSeverity of Illness IndexCohort StudiesChronic neck painYoung AdultPhysical medicine and rehabilitationNeck MusclesMedicineHumansIn patientProspective StudiesTraining periodPain MeasurementMassageNeck painAnalysis of VarianceReferred painNeck Painbusiness.industryTrigger PointsMiddle AgedTreatment OutcomeSensory ThresholdsPhysical therapyFemaleChiropracticsmedicine.symptomChronic PainTraining programbusinessFollow-Up StudiesJournal of manipulative and physiological therapeutics
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CNN-Based Prostate Zonal Segmentation on T2-Weighted MR Images: A Cross-Dataset Study

2020

Prostate cancer is the most common cancer among US men. However, prostate imaging is still challenging despite the advances in multi-parametric magnetic resonance imaging (MRI), which provides both morphologic and functional information pertaining to the pathological regions. Along with whole prostate gland segmentation, distinguishing between the central gland (CG) and peripheral zone (PZ) can guide toward differential diagnosis, since the frequency and severity of tumors differ in these regions; however, their boundary is often weak and fuzzy. This work presents a preliminary study on deep learning to automatically delineate the CG and PZ, aiming at evaluating the generalization ability o…

Urologic DiseasesComputer scienceContext (language use)32 Biomedical and Clinical Sciences-Convolutional neural networkDeep convolutional neural networks Prostate zonal segmentation Cross-dataset generalizationProstate cancer46 Information and Computing SciencesProstateDeep convolutional neural networksmedicineAnatomical MRISegmentationProstate zonal segmentation; Prostate cancer; Anatomical MRI; Deep convolutional neural networks; Cross-dataset generalization;3202 Clinical SciencesCancerSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniProstate cancerSettore INF/01 - Informaticamedicine.diagnostic_testbusiness.industryDeep learningINF/01 - INFORMATICAMagnetic resonance imagingPattern recognitionmedicine.disease3211 Oncology and Carcinogenesismedicine.anatomical_structureCross-dataset generalizationProstate zonal segmentationBiomedical ImagingArtificial intelligenceDeep convolutional neural networkbusinessT2 weightedAnatomical MRI; Cross-dataset generalization; Deep convolutional neural networks; Prostate cancer; Prostate zonal segmentation
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Modulation of H-reflex and V-wave responses during dynamic balance perturbations

2023

AbstractMotoneuron excitability is possible to measure using H-reflex and V-wave responses. However, it is not known how the motor control is organized, how the H-reflex and V-wave responses modulate and how repeatable these are during dynamic balance perturbations. To assess the repeatability, 16 participants (8 men, 8 women) went through two, identical measurement sessions with ~ 48 h intervals, where maximal isometric plantar flexion (IMVC) and dynamic balance perturbations in horizontal, anterior–posterior direction were performed. Soleus muscle (SOL) neural modulation during balance perturbations were measured at 40, 70, 100 and 130 ms after ankle movement by using both H-reflex and V-…

V-wavehermo-lihastoimintaelektromyografiaGeneral Neurosciencetasapainodynamic balancerefleksitdynamic conditiontasapainoaistineural modulationH-reflexmotoriikkaExperimental Brain Research
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"Table 4" of "Elliptic flow of charged particles in Pb-Pb collisions at 2.76 TeV"

2014

Integrated elliptic flow at sqrt(sNN) = 2.76 TeV for centrality 20-30%.

V2Inclusive2760.0Astrophysics::High Energy Astrophysical PhenomenaComputer Science::Neural and Evolutionary ComputationHigh Energy Physics::PhenomenologyAngular CorrelationHigh Energy Physics::ExperimentNuclear ExperimentPB PB --> CHARGED X
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Investigation of vehicle crash modeling techniques: theory and application

2013

Published version of an article in the journal: The International Journal of Advanced Manufacturing Technology. Also available from the publisher at: http://dx.doi.org/10.1007/s00170-013-5320-3 Creating a mathematical model of a vehicle crash is a task which involves considerations and analysis of different areas which need to be addressed because of the mathematical complexity of a crash event representation. Therefore, to simplify the analysis and enhance the modeling process, in this work, a brief overview of different vehicle crash modeling methodologies is proposed. The acceleration of a colliding vehicle is measured in its center of gravity—this crash pulse contains detailed informati…

VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413Feedforward neural network; Lumped parameter models; Multiresolution analysis; Vehicle crash modeling; Control and Systems Engineering; Software; Mechanical Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Industrial and Manufacturing EngineeringEvent (computing)Computer scienceReliability (computer networking)Mechanical Engineeringvehicle crash modelingVDP::Technology: 500::Mechanical engineering: 570lumped parameter modelsCrashControl engineeringComputer Science Applications1707 Computer Vision and Pattern RecognitionCollisionIndustrial and Manufacturing EngineeringComputer Science Applicationsmultiresolution analysisAutoregressive modelControl and Systems Engineeringfeedforward neural networkRepresentation (mathematics)SimulationSoftwareMotor vehicle crash
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Prediction of dynamic mooring responses of a floating wind turbine using an artificial neural network

2021

Abstract Numerical simulations in coupled aero-hydro-servo-elastic codes are known to be a challenge for design and analysis of offshore wind turbine systems because of the large number of design load cases involved in checking the ultimate and fatigue limit states. To alleviate the simulation burden, machine learning methods can be useful. This article investigates the effect of machine learning methods on predicting the mooring line tension of a spar floating wind turbine. The OC3 Hywind wind turbine with a spar-buoy foundation and three mooring lines is selected and simulated with SIMA. A total of 32 sea states with irregular waves are considered. Artificial neural works with different c…

VDP::Teknologi: 500Artificial neural networkComputer scienceFloating wind turbineMooringMarine engineeringIOP Conference Series: Materials Science and Engineering
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Online Deflection Compensation of a Flexible Hydraulic Loader Crane Using Neural Networks and Pressure Feedback

2022

The deflection compensation of a hydraulically actuated loader crane is presented. Measurement data from the laboratory are used to design a neural network deflection estimator. Kinematic expressions are derived and used with the deflection estimator in a feedforward topology to compensate for the static deflection. A dynamic deflection compensator is implemented, using pressure feedback and an adaptive bandpass filter. Simulations are conducted to verify the performance of the control system. Experimental results showcase the effectiveness of both the static and dynamic deflection compensator while running closed-loop motion control, with a 90% decrease in static deflection.

VDP::Teknologi: 500Control and OptimizationArtificial IntelligenceMechanical EngineeringPhysics::Space Physicsdeflection compensation; kinematics; loader crane; hydraulics; neural networkRobotics
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Forward Kinematic Modelling with Radial Basis Function Neural Network Tuned with a Novel Meta-Heuristic Algorithm for Robotic Manipulators

2022

The complexity of forward kinematic modelling increases with the increase in the degrees of freedom for a manipulator. To reduce the computational weight and time lag for desired output transformation, this paper proposes a forward kinematic model mapped with the help of the Radial Basis Function Neural Network (RBFNN) architecture tuned by a novel meta-heuristic algorithm, namely, the Cooperative Search Optimisation Algorithm (CSOA). The architecture presented is able to automatically learn the kinematic properties of the manipulator. Learning is accomplished iteratively based only on the observation of the input–output relationship. Related simulations are carried out on a 3-Degrees…

VDP::Teknologi: 500Control and OptimizationArtificial IntelligenceMechanical Engineeringrobotics; artificial intelligence; ROS; forward kinematic modelling; radial basis function neural networks; cooperative search optimisation algorithmComputer Science::Neural and Evolutionary ComputationRobotics
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