Search results for " network"

showing 10 items of 6428 documents

Autonomic Brokerage Service for an End-to-End Cloud Networking Service Level Agreement

2014

8 pages; International audience; Today, cloud networking which is the ability to connect the user with his cloud services and to interconnect these services within an inter-cloud approach, is one of the recent research areas in the cloud computing research communities. The main drawback of cloud networking consists in the lack of Quality of Service (QoS) assurance and management in conformance with a corresponding Service Level Agreement (SLA). In this paper, we propose a framework for self-establishing an end-to-end service level agreement between a Cloud Service User (CSU) and multiple Cloud Service Providers (CSPs) in a cloud networking environment using brokerage service. We focus on Qo…

Cloud computing security[INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI]business.industryService delivery frameworkComputer scienceCloud NetworkingQuality of service[ INFO.INFO-NI ] Computer Science [cs]/Networking and Internet Architecture [cs.NI]Quality of ServiceService level requirementCloud computingAutonomic computingService-level agreement[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]IEEECloud testingService catalogAutonomic ComputingCloudSimScalabilityVideoconferencingService Level AgreementData as a servicebusinessComputer network
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The on-line curvilinear component analysis (onCCA) for real-time data reduction

2015

Real time pattern recognition applications often deal with high dimensional data, which require a data reduction step which is only performed offline. However, this loses the possibility of adaption to a changing environment. This is also true for other applications different from pattern recognition, like data visualization for input inspection. Only linear projections, like the principal component analysis, can work in real time by using iterative algorithms while all known nonlinear techniques cannot be implemented in such a way and actually always work on the whole database at each epoch. Among these nonlinear tools, the Curvilinear Component Analysis (CCA), which is a non-convex techni…

Clustering high-dimensional dataBregman divergenceComputer scienceneural networkprojectionBregman divergenceNovelty detectionSynthetic dataData visualizationArtificial Intelligencebranch and boundComputer visionunfoldingcurvilinear component analysisCurvilinear coordinatesArtificial neural networkbusiness.industryVector quantizationPattern recognitiononline algorithmbearing faultvector quantizationPattern recognition (psychology)Principal component analysisbearing fault; branch and bound; Bregman divergence; curvilinear component analysis; data reduction; neural network; novelty detection; online algorithm; projection; unfolding; vector quantization; Software; Artificial Intelligencedata reductionArtificial intelligencebusinessnovelty detectionSoftware
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ROS/Gazebo Based Simulation of Co-operative UAVs

2019

UAVs can be assigned different tasks such as e.g., rendez-vous and space coverage, which require processing and communication capabilities. This work extends the architecture ROS/Gazebo with the possibility of simulation of co-operative UAVs. We assume UAV with the underlying attitude controller based on the open-source Ardupilot software. The integration of the co-ordination algorithm in Gazebo is implemented with software modules extending Ardupilot with the capability of sending/receiving messages to/from drones, and executing the co-ordination protocol. As far as it concerns the simulation environment, we have extended the world in Gazebo to hold more than one drone and to open a specif…

Co operative0209 industrial biotechnologyComputer sciencebusiness.industryComputer Science (all)Real-time computing020206 networking & telecommunicationsROS/Gazebo02 engineering and technologyPort (computer networking)DroneTheoretical Computer ScienceCo-operative UAVSoftware modulesCo-operative UAVs; ROS/Gazebo; Simulation020901 industrial engineering & automationSoftwareSettore ING-INF/04 - AutomaticaControl theory0202 electrical engineering electronic engineering information engineeringbusinessProtocol (object-oriented programming)SimulationCo-operative UAVs
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Comprehensive analysis of forty yeast microarray datasets reveals a novel subset of genes (APha-RiB) consistently negatively associated with ribosome…

2014

Background The scale and complexity of genomic data lend themselves to analysis using sophisticated mathematical techniques to yield information that can generate new hypotheses and so guide further experimental investigations. An ensemble clustering method has the ability to perform consensus clustering over the same set of genes from different microarray datasets by combining results from different clustering methods into a single consensus result. Results In this paper we have performed comprehensive analysis of forty yeast microarray datasets. One recently described Bi-CoPaM method can analyse expressions of the same set of genes from various microarray datasets while using different cl…

Co-regulation(Binarisation of consensus partition matrices) Bi-CoPaMGene Expression ProfilingStress responseGenes FungalCo-expressionGenome-wide analysisGene Expression Regulation FungalRibosome biogenesisSaccharomycetalesCluster AnalysisGene Regulatory NetworksBudding yeastRibosomesOligonucleotide Array Sequence AnalysisResearch ArticleBMC bioinformatics
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Toll-quality digital secraphone

2002

This paper describes the design and performance of a secraphone that, when plugged between any conventional telephone set and the public telephone network, protects the speech information travelling through the PSTN. The device has a transparent operating mode that does not alter the signal and a secure mode, accessed upon request of any of the speakers, that encrypts the speech with digital techniques, assuring privacy against unwanted listeners. At the transmission branch, voice is sampled, coded with a CELP scheme at 9600 bps (with a slow mode at 7200 bps), encrypted with a proprietary algorithm and interfaced to the line with a V.32 modem chip set. The keys for encryption are establishe…

Code-excited linear predictionPublic-key cryptographyTelephone networkComputer sciencebusiness.industrySpeech codingCryptographyTelephonyEncryptionbusinessLinear predictive codingComputer networkProceedings of 8th Mediterranean Electrotechnical Conference on Industrial Applications in Power Systems, Computer Science and Telecommunications (MELECON 96)
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Using Aerial Platforms in Predicting Water Quality Parameters from Hyperspectral Imaging Data with Deep Neural Networks

2020

In near future it is assumable that automated unmanned aerial platforms are coming more common. There are visions that transportation of different goods would be done with large planes, which can handle over 1000 kg payloads. While these planes are used for transportation they could similarly be used for remote sensing applications by adding sensors to the planes. Hyperspectral imagers are one this kind of sensor types. There is need for the efficient methods to interpret hyperspectral data to the wanted water quality parameters. In this work we survey the performance of neural networks in the prediction of water quality parameters from remotely sensed hyperspectral data in freshwater basin…

Coefficient of determinationArtificial neural networkRemote sensing applicationvesien tilaspektrikuvausHyperspectral imagingneuroverkotvedenlaatuConvolutional neural networkwater qualityPearson product-moment correlation coefficientsymbols.namesakeremote sensinghyperspectralilmakuvakartoitusMultilayer perceptronconvolutional neural networkssymbolsEnvironmental scienceWater qualitykaukokartoitusRemote sensing
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Neural networks with non-uniform embedding and explicit validation phase to assess Granger causality

2015

A challenging problem when studying a dynamical system is to find the interdependencies among its individual components. Several algorithms have been proposed to detect directed dynamical influences between time series. Two of the most used approaches are a model-free one (transfer entropy) and a model-based one (Granger causality). Several pitfalls are related to the presence or absence of assumptions in modeling the relevant features of the data. We tried to overcome those pitfalls using a neural network approach in which a model is built without any a priori assumptions. In this sense this method can be seen as a bridge between model-free and model-based approaches. The experiments perfo…

Cognitive NeuroscienceEntropyFOS: Physical sciencesOverfittingcomputer.software_genreMachine learningGranger causalityArtificial IntelligenceMedicine and Health SciencesEntropy (information theory)Non-uniform embeddingComputer SimulationMathematicsArtificial neural networkbusiness.industryProbability and statisticsModels TheoreticalNeural Networks (Computer)ClassificationNeural networkAlgorithmCausalityPhysics - Data Analysis Statistics and ProbabilitySettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalityEmbeddingA priori and a posterioriTransfer entropyNeural Networks ComputerArtificial intelligenceData miningbusinesscomputerAlgorithmsNeural networksData Analysis Statistics and Probability (physics.data-an)
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Thalamic Network Oscillations Synchronize Ontogenetic Columns in the Newborn Rat Barrel Cortex

2013

Neocortical areas are organized in columns, which form the basic structural and functional modules of intracortical information processing. Using voltage-sensitive dye imaging and simultaneous multi-channel extracellular recordings in the barrel cortex of newborn rats in vivo, we found that spontaneously occurring and whisker stimulation-induced gamma bursts followed by longer lasting spindle bursts were topographically organized in functional cortical columns already at the day of birth. Gamma bursts synchronized a cortical network of 300-400 µm in diameter and were coherent with gamma activity recorded simultaneously in the thalamic ventral posterior medial (VPM) nucleus. Cortical gamma b…

Cognitive NeuroscienceOntogenyThalamusAction PotentialsStimulation610 Medicine & healthStatistics NonparametricElectrolytesCellular and Molecular NeuroscienceBiological ClocksReaction TimeExtracellularmedicineAnimalsAnesthetics Local610 Medicine & healthFeedback PhysiologicalBrain MappingVentral Thalamic NucleiChemistryLidocaineSomatosensory CortexBarrel cortexElectric StimulationVoltage-Sensitive Dye ImagingNetwork activityRatsmedicine.anatomical_structureAnimals NewbornCortical networkVibrissaeNerve NetNeuroscienceNucleus
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Trait impulsivity associated with altered resting-state functional connectivity within the somatomotor network

2020

Knowledge of brain mechanisms underlying self-regulation can provide valuable insights into how people regulate their thoughts, behaviors, and emotional states, and what happens when such regulation fails. Self-regulation is supported by coordinated interactions of brain systems. Hence, behavioral dysregulation, and its expression as impulsivity, can be usefully characterized using functional connectivity methodologies applied to resting brain networks. The current study tested whether individual differences in trait impulsivity are reflected in the functional architecture within and between resting-state brain networks. Thirty healthy individuals completed a self-report measure of trait im…

Cognitive NeuroscienceSensory systemSomatosensory systemImpulsivitylcsh:RC321-57103 medical and health sciencesBehavioral Neuroscience0302 clinical medicineBarratt Impulsiveness Scalemedicineresting statelcsh:Neurosciences. Biological psychiatry. NeuropsychiatryOriginal Research030304 developmental biology0303 health sciencestrait impulsivitymedicine.diagnostic_testResting state fMRIFunctional connectivityfunctional connectivitysomatomotor networkNeuropsychology and Physiological PsychologyTraitBarratt Impulsiveness Scalemedicine.symptomPsychologyFunctional magnetic resonance imagingNeuroscience030217 neurology & neurosurgeryNeuroscience
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Blocking NMDA-receptors in the pigeon's "prefrontal" caudal nidopallium impairs appetitive extinction learning in a sign-tracking paradigm

2015

Extinction learning provides the ability to flexibly adapt to new contingencies by learning to inhibit previously acquired associations in a context-dependent manner. The neural networks underlying extinction learning were mostly studied in rodents using fear extinction paradigms. To uncover invariant properties of the neural basis of extinction learning, we employ pigeons as a model system. Since the prefrontal cortex of mammals is a key structure for extinction learning, we assessed the role of N-methyl-D-aspartate receptors (NMDARs) in the nidopallium caudolaterale, the avian functional equivalent of mammalian prefrontal cortex. Since NMDARs in prefrontal cortex have been shown to be rel…

Cognitive NeuroscienceSpontaneous recoveryStimulus (physiology)contextlcsh:RC321-571Behavioral NeuroscienceSign-trackingmedicinePrefrontal cortexretrievallcsh:Neurosciences. Biological psychiatry. NeuropsychiatryOriginal ResearchrenewalArtificial neural networkExtinction (psychology)social sciencesmusculoskeletal systemhumanitiesNeuropsychology and Physiological Psychologynervous systemDisinhibitionNidopalliumNMDA receptorAPVmedicine.symptomPsychologyNeurosciencegeographic locationsNeuroscience
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