Search results for "ACOUSTIC"

showing 10 items of 1590 documents

Stability criteria, atomization and non-thermal processes in liquids

2008

Analyzing the first equation in the BBGKY chain of equations for an equilibrium liquid-gas system, we derived the analytical expression for the atom work function from liquid into gas. The coupling between the atom work function from liquid into vacuum and the stability criterion of liquid in limiting points of the first type was shown (using I.Z.. Fisher classification). As it turned out, Fisher's criterion corresponds to the condition of atomization. We have expressed the state equation in terms of the atom work function from liquid into vacuum and performed calculations of the limiting line of stability composed of limiting points of the first type for argon. Our model discovers an inter…

Equation of stateAcoustics and UltrasonicsStability criterionmechanism of sonoluminescenceThermodynamicschemistry.chemical_elementInorganic ChemistryPhysics::Fluid DynamicsSonoluminescenceFLUIDSIonizationAtomBUBBLEChemical Engineering (miscellaneous)Environmental ChemistryRadiology Nuclear Medicine and imagingWork functionfluid atomizationequation of stateArgonChemistrystability criteriaOrganic ChemistryMechanism of sonoluminescenceatom work functionAtomic physicsUltrasonics sonochemistry
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The dark side of curvature

2009

Geometrical tests such as the combination of the Hubble parameter H(z) and the angular diameter distance d(A)(z) can, in principle, break the degeneracy between the dark energy equation of state parameter w(z), and the spatial curvature Omega(k) in a direct, model-independent way. In practice, constraints on these quantities achievable from realistic experiments, such as those to be provided by Baryon Acoustic Oscillation (BAO) galaxy surveys in combination with CMB data, can resolve the cosmic confusion between the dark energy equation of state parameter and curvature only statistically and within a parameterized model for w(z). Combining measurements of both H(z) and d(A)(z) up to suffici…

Equation of stateCosmology and Nongalactic Astrophysics (astro-ph.CO)Cosmic microwave backgroundFOS: Physical sciencesAstrophysicsAstrophysics::Cosmology and Extragalactic AstrophysicsCurvature01 natural sciencessymbols.namesakeHigh Energy Physics - Phenomenology (hep-ph)0103 physical sciencesDark energy experiments010303 astronomy & astrophysicsPhysics010308 nuclear & particles physicsAngular diameter distanceAstronomy and AstrophysicsRedshiftCosmological parameters from CMBRHigh Energy Physics - PhenomenologysymbolsDark energyBaryon acoustic-oscillationsBaryon acoustic oscillationsHubble's lawAstrophysics - Cosmology and Nongalactic Astrophysics
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High-speed duetting - latency times of the female acoustic response within the bush-cricket genera

2018

Abstract To find a mate, male and female bush-crickets of the family Phaneropteridae typically engage in duets. The male sings and the female responds. For mutual recognition, the amplitude pattern of the male song and the species-specific timing of the female response have been shown to be very important. In the seven studied species, belonging to the genera Leptophyes and Andreiniimon, these duets are extremely fast and nearly completely in the ultrasonic range. The females produce very short sounds by fast closing movements of the tegmina. They respond with species-specific delays of 20 to 150 ms after the beginning of the male song. The different latency times are probably not important…

Evolutionary BiologyInsectaArthropodaHexapodaduetTettigoniideafemale acoustic signalsEuropeEnsiferakatydidPhaneropterinaeAnimaliaOrthopteraNeogenePhaneropteridaeInvertebrataResearch Articlestridulatory movementZooKeys
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Inclusion ratio based estimator for the mean length of the boolean line segment model with an application to nanocrystalline cellulose

2014

A novel estimator for estimating the mean length of fibres is proposed for censored data observed in square shaped windows. Instead of observing the fibre lengths, we observe the ratio between the intensity estimates of minus-sampling and plus-sampling. It is well-known that both intensity estimators are biased. In the current work, we derive the ratio of these biases as a function of the mean length assuming a Boolean line segment model with exponentially distributed lengths and uniformly distributed directions. Having the observed ratio of the intensity estimators, the inverse of the derived function is suggested as a new estimator for the mean length. For this estimator, an approximation…

Exponential distributionAcoustics and UltrasonicsMaterials Science (miscellaneous)General MathematicsInversevarianceSquare (algebra)exponential length distributionfibresLine segmentStatisticsRadiology Nuclear Medicine and imagingnanocellulose crystallineratio of estimatesInstrumentationnanocelluloseMathematicsplus-samplinglcsh:R5-920lcsh:MathematicsMathematical analysisEstimatorBoolean modelFunction (mathematics)lcsh:QA1-939mean lengthsimulationEfficient estimatorminus-samplingSignal Processinglength distributionComputer Vision and Pattern Recognitionlcsh:Medicine (General)Intensity (heat transfer)line segmentsBiotechnologyImage Analysis and Stereology
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Inspection of additive-manufactured layered components

2015

Laser powder deposition (LPD) is a rapid additive manufacturing process to produce, layer upon layer, 3D geometries or to repair high-value components. Currently there is no nondestructive technique that can guarantee absence of flaws in LPD products during manufacturing. In this paper a laser ultrasonic technique for in-line inspection of LPD components is proposed. Reference samples were manufactured from Inconel and machined flaws were created to establish the sensitivity of the technique. Numerical models of laser-generated ultrasonic waves have been created to gain a deeper understanding of physics, to optimize the set-up and to verify the experimental measurements. Results obtained on…

FEMNDT inspectionAcoustics and UltrasonicsAdditive manufacturingMechanical engineeringNumerical modelsLaserFinite element methodlaw.inventionSettore ING-IND/14 - Progettazione Meccanica E Costruzione Di MacchinelawLaser ultrasoundDeposition (phase transition)Ultrasonic sensorSensitivity (control systems)InconelLayer (electronics)Laser powder depositionUltrasonics
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A 2D-FEM Model of Nonlinear Ultrasound Propagation in Trans-cranial MRgFUS Technique

2022

Magnetic Resonance guided Focused Ultrasound (MRgFUS) is a non-invasive technique based on the thermal ablation of a target using high intensity focused ultrasound. MRgFUS treatment applied to brain is challenging due to the skull presence that attenuates ultrasound, leading to heating effects in bone region. In this study, we simulate trans-cranial nonlinear ultrasound propagation considering the detailed structure of bone tissue. We developed a 2D Finite Element (FE) model that mimics the propagation of focused ultrasound through skin, skull and brain tissue. The skull is represented as a three-layered system with two cortical tables packing a layer of trabecular bone. We assume that the …

FEMNonlinear acousticsBone tissueBrain biomechanicsSettore MED/37 - NeuroradiologiaHigh intensity focused ultrasoundSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)
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Unlocking the potential of deep learning for marine ecology: overview, applications, and outlook

2022

The deep learning revolution is touching all scientific disciplines and corners of our lives as a means of harnessing the power of big data. Marine ecology is no exception. These new methods provide analysis of data from sensors, cameras, and acoustic recorders, even in real time, in ways that are reproducible and rapid. Off-the-shelf algorithms can find, count, and classify species from digital images or video and detect cryptic patterns in noisy data. Using these opportunities requires collaboration across ecological and data science disciplines, which can be challenging to initiate. To facilitate these collaborations and promote the use of deep learning towards ecosystem-based management…

FOS: Computer and information sciences0106 biological sciencesArtificial intelligenceComputer Science - Machine LearningEcologyComputer Science - Artificial IntelligenceComputer Vision and Pattern Recognition (cs.CV)010604 marine biology & hydrobiologyComputer Science - Computer Vision and Pattern RecognitionMarine monitoringMarine bioacousticsAquatic ScienceEcosystem-based managementOceanography010603 evolutionary biology01 natural sciencesMachine Learning (cs.LG)VDP::Teknologi: 500Artificial Intelligence (cs.AI)13. Climate actionMachine learning14. Life underwaterEcology Evolution Behavior and Systematics
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Diffusion map for clustering fMRI spatial maps extracted by Indipendent Component Analysis

2013

Functional magnetic resonance imaging (fMRI) produces data about activity inside the brain, from which spatial maps can be extracted by independent component analysis (ICA). In datasets, there are n spatial maps that contain p voxels. The number of voxels is very high compared to the number of analyzed spatial maps. Clustering of the spatial maps is usually based on correlation matrices. This usually works well, although such a similarity matrix inherently can explain only a certain amount of the total variance contained in the high-dimensional data where n is relatively small but p is large. For high-dimensional space, it is reasonable to perform dimensionality reduction before clustering.…

FOS: Computer and information sciencesDiffusion (acoustics)Computer sciencediffusion mapMachine Learning (stat.ML)02 engineering and technologycomputer.software_genreMachine Learning (cs.LG)Computational Engineering Finance and Science (cs.CE)Correlation03 medical and health sciencesTotal variation0302 clinical medicineStatistics - Machine LearningVoxel0202 electrical engineering electronic engineering information engineeringComputer Science - Computational Engineering Finance and ScienceCluster analysisdimensionality reductionta113spatial mapsbusiness.industryDimensionality reductionfunctional magnetic resonance imaging (fMRI)Pattern recognitionIndependent component analysisSpectral clusteringComputer Science - Learningindependent component analysista6131020201 artificial intelligence & image processingArtificial intelligenceDYNAMICAL-SYSTEMSbusinesscomputer030217 neurology & neurosurgeryclustering
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Resolving gas bubbles ascending in liquid metal from low-SNR neutron radiography images

2021

We demonstrate a new image processing methodology for resolving gas bubbles travelling through liquid metal from dynamic neutron radiography images with an intrinsically low signal-to-noise ratio. Image pre-processing, denoising and bubble segmentation are described in detail, with practical recommendations. Experimental validation is presented—stationary and moving reference bodies with neutron-transparent cavities are radiographed with imaging conditions representative of the cases with bubbles in liquid metal. The new methods are applied to our experimental data from previous and recent imaging campaigns, and the performance of the methods proposed in this paper is compared against our p…

FOS: Computer and information sciencesLiquid metalTechnologyMaterials scienceQH301-705.5low signal-to-noise ratio (SNR)BubbleAcousticsNoise reductionQC1-999Computer Vision and Pattern Recognition (cs.CV)dynamic neutron imagingComputer Science - Computer Vision and Pattern Recognitionmetohydrodynamics (MHD)FOS: Physical sciencesImage processingdenoisingGeneral Materials ScienceSegmentationBiology (General)InstrumentationQD1-999Fluid Flow and Transfer ProcessesProcess Chemistry and TechnologyNeutron imagingTPhysicssegmentationGeneral EngineeringFluid Dynamics (physics.flu-dyn)Experimental dataPhysics - Fluid DynamicsEngineering (General). Civil engineering (General)Computer Science Applicationsimage processingtwo-phase flowChemistryliquid metalComputer Science::Computer Vision and Pattern RecognitionTwo-phase flowTA1-2040bubble flow
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Acoustic Scene Classification with Squeeze-Excitation Residual Networks

2020

Acoustic scene classification (ASC) is a problem related to the field of machine listening whose objective is to classify/tag an audio clip in a predefined label describing a scene location (e. g. park, airport, etc.). Many state-of-the-art solutions to ASC incorporate data augmentation techniques and model ensembles. However, considerable improvements can also be achieved only by modifying the architecture of convolutional neural networks (CNNs). In this work we propose two novel squeeze-excitation blocks to improve the accuracy of a CNN-based ASC framework based on residual learning. The main idea of squeeze-excitation blocks is to learn spatial and channel-wise feature maps independently…

FOS: Computer and information sciencesSound (cs.SD)Computer Science - Machine LearningGeneral Computer ScienceCalibration (statistics)Computer scienceResidualConvolutional neural networkField (computer science)Computer Science - SoundMachine Learning (cs.LG)030507 speech-language pathology & audiology03 medical and health sciencesAudio and Speech Processing (eess.AS)Acoustic scene classificationFeature (machine learning)FOS: Electrical engineering electronic engineering information engineeringGeneral Materials ScienceBlock (data storage)Artificial neural networkbusiness.industrypattern recognitionGeneral Engineeringdeep learningPattern recognitionmachine listeningsqueeze-excitationArtificial intelligencelcsh:Electrical engineering. Electronics. Nuclear engineering0305 other medical sciencebusinesslcsh:TK1-9971Electrical Engineering and Systems Science - Audio and Speech Processing
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