Search results for " Network"

showing 10 items of 6428 documents

On-line tools for microscopic and macroscopic monitoring of microwave processing

2007

International audience; Direct monitoring of temperature, chemistry and microstructure is required to understand microwave heating in more detail, in order to fully exploit the unique features this non-equilibrium processing method can offer. In this paper, we show first that microwave radiometry can be used to follow volumetrically the thermal trajectory of microwave-heated aluminium powder. In-situ Raman spectroscopy is then shown to evidence thermal gradients between diamond and silicon grains in a binary powder mixture. Finally, perspectives and preliminary results of microstructural analysis obtained from X-ray microtomography are presented.

SiliconRadiometerschemistry.chemical_element02 engineering and technologyengineering.materialMicrowave radiation interactions with condensed matter[SPI]Engineering Sciences [physics]symbols.namesakeCondensed Matter::Materials ScienceOpticsAluminium0202 electrical engineering electronic engineering information engineeringRaman spectroscopy in condensed matterElectrical and Electronic EngineeringComputed tomographyPowder mixtureSynchrotron radiationbusiness.industryDiamond020206 networking & telecommunications[CHIM.MATE]Chemical Sciences/Material chemistry021001 nanoscience & nanotechnologyCondensed Matter PhysicsMicrostructureElectronic Optical and Magnetic MaterialschemistryengineeringsymbolsAluminium powder0210 nano-technologybusinessRaman spectroscopyMicrowave
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Structural and dynamical properties of sodium silicate melts: An investigation by molecular dynamics computer simulation

2001

We present the results of large scale computer simulations in which we investigate the static and dynamic properties of sodium disilicate and sodium trisilicate melts. We study in detail the static properties of these systems, namely the coordination numbers, the temperature dependence of the Q^(n) species and the static structure factor, and compare them with experiments. We show that the structure is described by a partially destroyed tetrahedral SiO_4 network and the homogeneously distributed sodium atoms which are surrounded on average by 16 silicon and other sodium atoms as nearest neighbors. We compare the diffusion of the ions in the sodium silicate systems with that in pure silica a…

SiliconStatistical Mechanics (cond-mat.stat-mech)Coordination numberSodiumDiffusionInorganic chemistrychemistry.chemical_elementFOS: Physical sciencesGeologySodium silicateDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksMolecular dynamicschemistry.chemical_compoundchemistryGeochemistry and PetrologyChemical physicsAtomPhysics::Atomic and Molecular ClustersStructure factorCondensed Matter - Statistical Mechanics
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Generalized singly-implicit Runge-Kutta methods with arbitrary knots

1985

The aim of this paper is to derive Butcher's generalization of singly-implicit methods without restrictions on the knots. Our analysis yields explicit computable expressions for the similarity transformations involved which allow the efficient implementation of the first phase of the method, i.e. the solution of the nonlinear equations. Furthermore, simple formulas for the second phase of the method, i.e. computation of the approximations at the next nodal point, are established. Finally, the matrix which governs the stability of the method is studied.

Similarity (geometry)Computer Networks and CommunicationsGeneralizationApplied MathematicsComputationMathematical analysisStability (learning theory)Computational MathematicsMatrix (mathematics)Runge–Kutta methodsNonlinear systemSimple (abstract algebra)SoftwareMathematicsBIT
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Anam-Net: Anamorphic Depth Embedding-Based Lightweight CNN for Segmentation of Anomalies in COVID-19 Chest CT Images.

2021

Chest computed tomography (CT) imaging has become indispensable for staging and managing coronavirus disease 2019 (COVID-19), and current evaluation of anomalies/abnormalities associated with COVID-19 has been performed majorly by the visual score. The development of automated methods for quantifying COVID-19 abnormalities in these CT images is invaluable to clinicians. The hallmark of COVID-19 in chest CT images is the presence of ground-glass opacities in the lung region, which are tedious to segment manually. We propose anamorphic depth embedding-based lightweight CNN, called Anam-Net, to segment anomalies in COVID-19 chest CT images. The proposed Anam-Net has 7.8 times fewer parameters …

Similarity (geometry)Coronavirus disease 2019 (COVID-19)Computer Networks and CommunicationsComputer scienceComputed tomography02 engineering and technologyDeep LearningArtificial Intelligence0202 electrical engineering electronic engineering information engineeringMedical imagingmedicineImage Processing Computer-AssistedHumansSegmentationComputer visionLung regionLungmedicine.diagnostic_testbusiness.industryDeep learningVDP::Technology: 500COVID-19Image segmentationComputer Science ApplicationsEmbedding020201 artificial intelligence & image processingArtificial intelligenceNeural Networks ComputerbusinessTomography X-Ray ComputedSoftwareIEEE transactions on neural networks and learning systems
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Predicting Next Dialogue Action in Emotionally Loaded Conversation

2021

This paper reports on creating a neural network model for prediction of the next action in a dialogue considering conversation history, i.e. entities, context variables and emotion indicators marking emotionally loaded user utterances. Several experiments were performed to see how the information about emotions affects the accuracy of the model. For the purposes of these experiments, a dataset containing 206 dialogs in Latvian in the transport inquiry domain was created containing both neutral and emotionally loaded utterances. To see if the proposed next dialogue action prediction model architecture is suitable for other languages, the original Latvian utterances were translated into Engli…

Single modelArtificial neural networkComputer sciencebusiness.industrymedia_common.quotation_subjectLatviancomputer.software_genrelanguage.human_languageDomain (software engineering)Model architectureAction (philosophy)languageConversationArtificial intelligencebusinesscomputerNatural language processingmedia_commonTransformer (machine learning model)
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A proof of bistability for the dual futile cycle

2014

Abstract The multiple futile cycle is an important building block in networks of chemical reactions arising in molecular biology. A typical process which it describes is the addition of n phosphate groups to a protein. It can be modelled by a system of ordinary differential equations depending on parameters. The special case n = 2 is called the dual futile cycle. The main result of this paper is a proof that there are parameter values for which the system of ODE describing the dual futile cycle has two distinct stable stationary solutions. The proof is based on bifurcation theory and geometric singular perturbation theory. An important entity built of three coupled multiple futile cycles is…

Singular perturbationBistabilityFutile cycleMolecular Networks (q-bio.MN)Quantitative Biology::Molecular NetworksApplied MathematicsGeneral EngineeringOdeDynamical Systems (math.DS)General MedicineDual (category theory)Computational MathematicsBifurcation theoryMathematics - Classical Analysis and ODEsFOS: Biological sciencesOrdinary differential equationClassical Analysis and ODEs (math.CA)FOS: MathematicsApplied mathematicsQuantitative Biology - Molecular NetworksMathematics - Dynamical SystemsSpecial caseGeneral Economics Econometrics and FinanceAnalysisMathematicsNonlinear Analysis: Real World Applications
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Monitoring wireless sensor networks through logical deductive processes

2006

This paper proposes a distributed multi-agent architecture for wireless sensor networks management, which exploits the dynamic reasoning capabilities of the Situation Calculus in order to emulate the reactive behavior of a human expert to fault situations. The information related to network events is generated by tunable agents installed on the network nodes and is collected by a logical entity for network managing where it is merged with general domain knowledge, with the aim of identifying the root causes of faults, and deciding on reparative actions. The logical inference system has being devised to carry out automated isolation, diagnosis, and, whenever possible, repair of network anoma…

Situation CalculuSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniEngineeringbusiness.industryMulti-agent systemDistributed computingReliability (computer networking)Network nodeInformation securityScalabilityWireless sensor networks managementDomain knowledgeSituation calculusbusinessLogical deductive processeWireless sensor networkWireless sensor networkNetwork management stationComputer networkMILCOM 2005 - 2005 IEEE Military Communications Conference
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Social Media Data in an Augmented Reality System for Situation Awareness Support in Emergency Control Rooms

2021

AbstractDuring crisis situations, emergency operators require fast information access to achieve situation awareness and make the best possible decisions. Augmented reality could be used to visualize the wealth of user-generated content available on social media and enable context-adaptive functions for emergency operators. Although emergency operators agree that social media analytics will be important for their future work, it poses a challenge to filter and visualize large amounts of social media data. We conducted a goal-directed task analysis to identify the situation awareness requirements of emergency operators. By collecting tweets during two storms in Germany we evaluated the usefu…

Situation awarenessComputer Networks and CommunicationsComputer sciencebusiness.industryInterface (computing)05 social sciencesInternet privacyInformation access02 engineering and technologyFilter (software)VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420Social media analyticsTheoretical Computer ScienceAngewandte Kognitionswissenschaft020204 information systems0202 electrical engineering electronic engineering information engineeringTask analysis0501 psychology and cognitive sciencesSocial mediaAugmented realitybusiness050107 human factorsSoftwareInformation Systems
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An attention-based weakly supervised framework for spitzoid melanocytic lesion diagnosis in whole slide images

2021

[EN] Melanoma is an aggressive neoplasm responsible for the majority of deaths from skin cancer. Specifically, spitzoid melanocytic tumors are one of the most challenging melanocytic lesions due to their ambiguous morphological features. The gold standard for its diagnosis and prognosis is the analysis of skin biopsies. In this process, dermatopathologists visualize skin histology slides under a microscope, in a highly time-consuming and subjective task. In the last years, computer-aided diagnosis (CAD) systems have emerged as a promising tool that could support pathologists in daily clinical practice. Nevertheless, no automatic CAD systems have yet been proposed for the analysis of spitzoi…

Skin NeoplasmsComputer scienceBiopsyMedicine (miscellaneous)CADInductive transfer learningConvolutional neural networkInductive transferArtificial IntelligenceTEORIA DE LA SEÑAL Y COMUNICACIONESBiopsyAttention convolutional neural networkmedicineHumansDiagnosis Computer-AssistedMelanomaMicroscopymedicine.diagnostic_testbusiness.industryMultiple instance learningMelanomaDeep learningHistopathological whole-slide imagesPattern recognitionGold standard (test)medicine.diseaseSpitzoid lesionsArtificial intelligenceSkin cancerbusinessArtificial Intelligence in Medicine
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Automatic recognition of rapid eye movement (REM) sleep by artificial neural networks.

1995

Artificial neural networks are well known for their good performance in pattern recognition. Their suitability for detecting REM sleep periods on the basis of preprocessed EEG data in humans under clinical conditions was tested and their performance compared with the manual evaluation. A single channel of the EEG signal was analysed in time periods of 20 s and preprocessed into a vector of six real numbers, which served as input to the network. EOG and EMG information was ignored. Backpropagation was used as a learning rule for the network, which consisted of 12 neurons and 39 synapses. Training datasets were put together from the input vectors and the corresponding sleep stages were scored…

Sleep StagesCommunicationArtificial neural networkmedicine.diagnostic_testbusiness.industryCognitive NeuroscienceEye movementPattern recognitionGeneral MedicineElectroencephalographyBackpropagationBehavioral NeuroscienceLearning rulePattern recognition (psychology)medicineSleep (system call)Artificial intelligencePsychologybusinessJournal of sleep research
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