Search results for " Network"

showing 10 items of 6428 documents

NeuronAlg: An Innovative Neuronal Computational Model for Immunofluorescence Image Segmentation

2023

Background: Image analysis applications in digital pathology include various methods for segmenting regions of interest. Their identification is one of the most complex steps and therefore of great interest for the study of robust methods that do not necessarily rely on a machine learning (ML) approach. Method: A fully automatic and optimized segmentation process for different datasets is a prerequisite for classifying and diagnosing indirect immunofluorescence (IIF) raw data. This study describes a deterministic computational neuroscience approach for identifying cells and nuclei. It is very different from the conventional neural network approaches but has an equivalent quantitative and qu…

neuron physiology networksSettore INF/01 - Informaticabiomedical imaging; explainable ai; neuron physiology networks; computer-aided analysis; image segmentation; pattern analysispattern analysisElectrical and Electronic Engineeringbiomedical imagingcomputer-aided analysisimage segmentationBiochemistryInstrumentationAtomic and Molecular Physics and Opticsexplainable aiAnalytical ChemistrySensors
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Unsupervised representation learning of spontaneous MEG data with nonlinear ICA

2023

Funding Information: We wish to thank the reviewers and editors for the useful comments to improve the paper a lot. We thank Dr. Hiroshi Morioka for the useful discussion at the beginning of the project. L.P. was funded in part by the European Research Council (No. 678578 ). A.H. was supported by a Fellowship from CIFAR, and the Academy of Finland. The authors acknowledge the computational resources provided by the Aalto Science-IT project, and also wish to thank the Finnish Grid and Cloud Infrastructure (FGCI) for supporting this project with computational and data storage resources. | openaire: EC/H2020/678578/EU//HRMEG Resting-state magnetoencephalography (MEG) data show complex but stru…

neuropalautenon-stationarityMEGsignaalinkäsittelyCognitive Neurosciencesyväoppiminensignaalianalyysineurofeedbackunsupervised learningdeep generative modelkoneoppiminenNeurologyresting-state networkmagnetoencephalography (MEG)nonlinear independent component analysis (ICA)NeuroImage
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Ghost stochastic resonance in FitzHugh–Nagumo circuit

2014

International audience; The response of a neural circuit submitted to a bi-chromatic stimulus and corrupted by noise is investigated. In the presence of noise, when the spike firing of the circuit is analysed, a frequency not present at the circuit input appears. For a given range of noise intensities, it is shown that this ghost frequency is almost exclusively present in the interspike interval distribution. This phenomenon is for the first time shown experimentally in a FitzHugh-Nagumo circuit.

noise[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingInterval distribution[ NLIN.NLIN-CD ] Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD][ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingStochastic ResonanceComputer Science::Hardware ArchitectureComputer Science::Emerging Technologies[NLIN.NLIN-PS]Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingElectronic engineering[ NLIN.NLIN-PS ] Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS]Electrical and Electronic EngineeringMathematicsCircuit noiseQuantitative Biology::Neurons and CognitionArtificial neural networkStochastic processMathematical analysisneural networksFitzhugh nagumo[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsHarmonics[NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD]Nonlinear network analysis[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingElectronics Letters
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Experimental on-demand recovery of entanglement by local operations within non-Markovian dynamics

2015

In many applications entanglement must be distributed through noisy communication channels that unavoidably degrade it. Entanglement cannot be generated by local operations and classical communication (LOCC), implying that once it has been distributed it is not possible to recreate it by LOCC. Recovery of entanglement by purely local control is however not forbidden in the presence of non-Markovian dynamics, and here we demonstrate in two all-optical experiments that such entanglement restoration can even be achieved on-demand. First, we implement an open-loop control scheme based on a purely local operation, without acquiring any information on the environment; then, we use a closed-loop s…

non-Markovian dynamicsComputer scienceFOS: Physical sciencesMarkov processQuantum entanglementquantum entanglementTopologyArticleSettore FIS/03 - Fisica Della MateriaMultidisciplinary; quantum information; quantum entanglement; open quantum systemsEntanglementsymbols.namesakeNon Markovian dynamicsquantum informationOn demandquantum opticsQuantumQuantum networkLOCCQuantum PhysicsEntanglement entanglement recovery non-Markovian dynamicsMultidisciplinaryHidden entanglementTheoryofComputation_GENERALQuantum Physicsopen quantum systemsOutcome (probability)Dynamics (music)Hidden entanglement non-Markovian dynamics quantum optics quantum informationsymbolsQuantum Physics (quant-ph)entanglement recoveryScientific Reports
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Neural Classification of Compost Maturity by Means of the Self-Organising Feature Map Artificial Neural Network and Learning Vector Quantization Algo…

2019

Self-Organising Feature Map (SOFM) neural models and the Learning Vector Quantization (LVQ) algorithm were used to produce a classifier identifying the quality classes of compost, according to the degree of its maturation within a period of time recorded in digital images. Digital images of compost at different stages of maturation were taken in a laboratory. They were used to generate an SOFM neural topological map with centres of concentration of the classified cases. The radial neurons on the map were adequately labelled to represent five suggested quality classes describing the degree of maturation of the composted organic matter. This enabled the creation of a neural separator classify…

non-parametric classificationComputer science020209 energyHealth Toxicology and Mutagenesislcsh:Medicine02 engineering and technology010501 environmental sciencesengineering.material01 natural sciencesArticleDigital imageSoftwareArtificial Intelligence0202 electrical engineering electronic engineering information engineeringLearningTopological map0105 earth and related environmental sciencesLVQ algorithmLearning vector quantizationArtificial neural networkSOFM neural networkCompostbusiness.industryCompostinglcsh:RPublic Health Environmental and Occupational Health<i>LVQ</i> algorithmengineeringNeural Networks ComputerbusinessClassifier (UML)AlgorithmAlgorithmsSoftwareInternational Journal of Environmental Research and Public Health
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Four essays on IT users' psychological states and behaviors

2016

This dissertation is intended to study information technology (IT) users’ psychological states and behaviors. It consists of four essays. The first essay examines how people react to social networking services (SNS). In this essay, we attempted to extend the existing model, which includes dedication- and constraint-based mechanisms, by additionally including the obligation-based mechanism underlying SNS-related behavior. The second essay is designed to investigate individuals’ smartphone use. In particular, we focused on the role of smartphone addiction in shaping individuals’ perceptions about their smartphone. The third essay is about online community behavior. Drawing on the model of eng…

non-work-related computingverkkoyhteisötsosiaalinen mediasitoutuminennettiriippuvuusonline communitiesälypuhelimetsmartphone addictionsocial networking services (SNS)käyttäytymismallitriippuvuusajankäyttötyytyväisyystyöntekijätkäyttäytyminen
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Wiener-Granger Causality in Network Physiology with Applications to Cardiovascular Control and Neuroscience

2016

Since the operative definition given by C. W. J. Granger of an idea expressed by N. Wiener, the Wiener–Granger causality (WGC) has been one of the most relevant concepts exploited by modern time series analysis. Indeed, in networks formed by multiple components, working according to the notion of segregation and interacting with each other according to the principle of integration, inferring causality has opened a window on the effective connectivity of the network and has linked experimental evidences to functions and mechanisms. This tutorial reviews predictability improvement, information-based and frequency domain methods for inferring WGC among physiological processes from multivariate…

nonlinear dynamicComputer scienceReliability (computer networking)Biomedical signal processingPhysiologyCardiovascular controldynamical systemdirectionalityGranger causalitymultivariate regression modelingtime series analysiPredictabilityTime seriesElectrical and Electronic EngineeringStatistical hypothesis testingbusiness.industryheart rate variabilitytransfer entropypartial directed coherencepredictioncoupling strengthCausalityconditional mutual informationFrequency domainspectral decompositionSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaArtificial intelligencebusinesscomplexityNeuroscience
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Theoretical and experimental study of two discrete coupled Nagumo chains

2001

We analyze front wave (kink and antikink) propagation and pattern formation in a system composed of two coupled discrete Nagumo chains using analytical and numerical methods. In the case of homogeneous interaction among the chains, we show the possibility of the effective control on wave propagation. In addition, physical experiments on electrical chains confirm all theoretical behaviors.

nonlinear dynamicsNagumoneural network[NLIN.NLIN-PS] Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][SPI.TRON] Engineering Sciences [physics]/Electronics[PHYS.COND.CM-DS-NN] Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn]
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Impact of Status and Meme Content on the Spread of Memes in Virtual Communities

2015

We examined the influence of meme consistency (vs. inconsistency) and intragroup status on the spread of memes in virtual communities. Prior research suggests that information consistent with the theme of the group is remembered better and that ideas threatening to the group identity are rejected. In addition, previous research shows that low-status group members mimic high-status members and communicate with them to seek information and approval. We analyzed social interactions among members of four online forums from January 1, 2010, to February 21, 2014. Contrary to our prediction, our results show that memes initiated by low-status members spread faster than memes started by high- or mo…

norminfluencesocial networkmemecomputer-mediated communicationstatus
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A note on normalization schemes: The case of generalized forecast error variance decompositions

2016

The aim of this paper is to propose new normalization schemes for the values obtained from the generalized forecast error variance decomposition, in order to obtain more reliable net spillover measures. We provide a review of various matrix normalization schemes used in different application domains. The intention is to contribute to the financial econometrics literature aimed at building a bridge between different approaches able to detect spillover effects, such as spatial regressions and network analyses. Considering DGPs characterized by different degrees of correlation and persistence, we show that the popular row normalization scheme proposed by Diebold and Yilmaz (2012), as well as t…

normalization schemes forecast error variance decomposition spillover networks spatial econometrics VARspatial econometricsspillovernetworksSettore SECS-P/05 - Econometrianormalization schemes forecast error variance decomposition spillover networksforecast error variance decompositionVARnormalization schemes
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