Search results for "Network"

showing 10 items of 7718 documents

Probabilistic Logic under Coherence: Complexity and Algorithms

2005

In previous work [V. Biazzo, A. Gilio, T. Lukasiewicz and G. Sanfilippo, Probabilistic logic under coherence, model-theoretic probabilistic logic, and default reasoning in System P, Journal of Applied Non-Classical Logics 12(2) (2002) 189---213.], we have explored the relationship between probabilistic reasoning under coherence and model-theoretic probabilistic reasoning. In particular, we have shown that the notions of g-coherence and of g-coherent entailment in probabilistic reasoning under coherence can be expressed by combining notions in model-theoretic probabilistic reasoning with concepts from default reasoning. In this paper, we continue this line of research. Based on the above sem…

conditional probability assessmentSettore MAT/06 - Probabilita' E Statistica MatematicaDivergence-from-randomness modelalgorithmsprobabilistic logicConditional probability assessments; probabilistic logic; g-coherence; g-coherent entailment; complexity and algorithms.Artificial IntelligenceProbabilistic logic networkprobabilistic logic under coherenceConditional probability assessmentsProbabilistic analysis of algorithmsNon-monotonic logicconditional constraintMathematicsg-coherent entailmentConditional probability assessments probabilistic logic g-coherence g-coherent entailment complexity and algorithms.Reasoning systemcomputational complexitymodel-theoretic probabilistic logicApplied Mathematicscomplexity and algorithmsProbabilistic logiclogical constraintProbabilistic argumentationg-coherenceconditional probability assessment logical constraint conditional constraint probabilistic logic under coherence model-theoretic probabilistic logic g-coherence g-coherent entailment computational complexity algorithmsProbabilistic CTLalgorithms; computational complexity; conditional constraint; conditional probability assessment; g-coherence; g-coherent entailment; logical constraint; model-theoretic probabilistic logic; probabilistic logic under coherenceAlgorithmAnnals of Mathematics and Artificial Intelligence
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Information Transfer in Linear Multivariate Processes Assessed through Penalized Regression Techniques: Validation and Application to Physiological N…

2020

The framework of information dynamics allows the dissection of the information processed in a network of multiple interacting dynamical systems into meaningful elements of computation that quantify the information generated in a target system, stored in it, transferred to it from one or more source systems, and modified in a synergistic or redundant way. The concepts of information transfer and modification have been recently formulated in the context of linear parametric modeling of vector stochastic processes, linking them to the notion of Granger causality and providing efficient tools for their computation based on the state&ndash

conditional transfer entropyInformation transferlinear predictionDynamical systems theoryComputer scienceState–space modelsGeneral Physics and Astronomylcsh:AstrophysicsNetwork topologycomputer.software_genrenetwork physiology01 natural sciencesArticle03 medical and health sciences0302 clinical medicinepenalized regression techniquelcsh:QB460-4660103 physical sciencesEntropy (information theory)Statistics::Methodologylcsh:Science010306 general physicspartial information decompositionmultivariate time series analysisinformation dynamics; partial information decomposition; entropy; conditional transfer entropy; network physiology; multivariate time series analysis; State–space models; vector autoregressive model; penalized regression techniques; linear predictionState–space modellcsh:QC1-999multivariate time series analysiInformation dynamicData pointpenalized regression techniquesAutoregressive modelSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaParametric modelOrdinary least squaresvector autoregressive modellcsh:QData mininginformation dynamicsentropycomputerlcsh:Physics030217 neurology & neurosurgery
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An Optimized Architecture for CGA Operations and Its Application to a Simulated Robotic Arm

2022

Conformal geometric algebra (CGA) is a new geometric computation tool that is attracting growing attention in many research fields, such as computer graphics, robotics, and computer vision. Regarding the robotic applications, new approaches based on CGA have been proposed to efficiently solve problems as the inverse kinematics and grasping of a robotic arm. The hardware acceleration of CGA operations is required to meet real-time performance requirements in embedded robotic platforms. In this paper, we present a novel embedded coprocessor for accelerating CGA operations in robotic tasks. Two robotic algorithms, namely, inverse kinematics and grasping of a human-arm-like kinematics chain, ar…

conformal geometric algebraSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioniapplication-specific processorsComputer Networks and CommunicationsHardware and ArchitectureControl and Systems EngineeringSignal Processingcomputational geometryFPGA-based prototypingElectrical and Electronic Engineeringapplication-specific processors; Clifford Algebra; computational geometry; conformal geometric algebra; FPGA-based prototyping; grasping; human-like robotic arms; inverse kinematics
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Questions and controversies in the study of time-varying functional connectivity in resting fMRI.

2020

The brain is a complex, multiscale dynamical system composed of many interacting regions. Knowledge of the spatiotemporal organization of these interactions is critical for establishing a solid understanding of the brain’s functional architecture and the relationship between neural dynamics and cognition in health and disease. The possibility of studying these dynamics through careful analysis of neuroimaging data has catalyzed substantial interest in methods that estimate time-resolved fluctuations in functional connectivity (often referred to as “dynamic” or time-varying functional connectivity; TVFC). At the same time, debates have emerged regarding the application of TVFC analyses to re…

confound regression strategiesComputer scienceBrain networksRest1.1 Normal biological development and functioningdynamic connectivityReviewDynamical systemlcsh:RC321-57103 medical and health sciencesFunctional connectivity0302 clinical medicineArtificial IntelligenceUnderpinning researchBehavioral and Social Sciencestate fmricognitive controlmotion correctionReview Articleslcsh:Neurosciences. Biological psychiatry. Neuropsychiatry030304 developmental biologyindividual-differencesRest (physics)0303 health sciencesApplied MathematicsGeneral NeuroscienceResting fmriFunctional connectivitytest-retest reliabilityfMRINeurosciencesComputer Science ApplicationsMental HealthNeurologicalwhole-brainNeurosciencedefault mode030217 neurology & neurosurgeryBrain dynamics
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One-Dimensional Convolutional Neural Networks Combined with Channel Selection Strategy for Seizure Prediction Using Long-Term Intracranial EEG

2022

Seizure prediction using intracranial electroencephalogram (iEEG) has attracted an increasing attention during recent years. iEEG signals are commonly recorded in the form of multiple channels. Many previous studies generally used the iEEG signals of all channels to predict seizures, ignoring the consideration of channel selection. In this study, a method of one-dimensional convolutional neural networks (1D-CNN) combined with channel selection strategy was proposed for seizure prediction. First, we used 30-s sliding windows to segment the raw iEEG signals. Then, the 30-s iEEG segments, which were in three channel forms (single channel, channels only from seizure onset or free zone and all c…

convolutional neural network (CNN)channel selectionintracranial electroencephalogram (iEEG)signaalinkäsittelyseizure predictionsairauskohtauksetsignaalianalyysineuroverkotEEGepilepsia
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One and Two Dimensional Convolutional Neural Networks for Seizure Detection Using EEG Signals

2021

Deep learning for the automated detection of epileptic seizures has received much attention during recent years. In this work, one dimensional convolutional neural network (1D-CNN) and two dimensional convolutional neural network (2D-CNN) are simultaneously used on electroencephalogram (EEG) data for seizure detection. Firstly, using sliding windows without overlap on raw EEG to obtain the definite one-dimension time EEG segments (1D-T), and continuous wavelet transform (CWT) for 1D-T signals to obtain the two-dimension time-frequency representations (2D-TF). Then, 1D-CNN and 2D-CNN model architectures are used on 1D-T and 2D-TF signals for automatic classification, respectively. Finally, t…

convolutional neural networks (CNN)Computer scienceseizure detection02 engineering and technologyneuroverkotElectroencephalographyConvolutional neural network0202 electrical engineering electronic engineering information engineeringmedicineEEGContinuous wavelet transformSignal processingArtificial neural networkmedicine.diagnostic_testbusiness.industryelectroencephalogram (EEG)signaalinkäsittelyDeep learningtime-frequency representationtideep learningsignaalianalyysi020206 networking & telecommunicationsPattern recognitionkoneoppiminenBenchmark (computing)020201 artificial intelligence & image processingArtificial intelligencebusinessepilepsia
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A Cooperative Multi-Agent System for Crowd Sensing Based Estimation in Smart Cities

2020

The concept of Smart City has spread as a solution to ensure better access to information and services to citizens, but also as a means to reduce the environmental footprint of cities. To this end, a continuous and wide observation of the environment is necessary to analyze information that enables government bodies to act on the environment appropriately. Moreover, a diffused acquisition of information requires adequate infrastructure and proper devices, which results in relevant installation and maintenance costs. Our proposal enables reducing the number of necessary sensors to be deployed while ensuring that information is available at any time and anywhere. We present the HybridIoT syst…

cooperative multi-agent systemsGeneral Computer ScienceComputer scienceContext (language use)02 engineering and technologycomputer.software_genre[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]missing information estimationIntelligent sensorSmart city11. Sustainability0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceComputingMilieux_MISCELLANEOUSGovernmentSmart cityEcological footprintMulti-agent systemGeneral Engineering020206 networking & telecommunicationsRisk analysis (engineering)13. Climate actionheterogeneous data integration020201 artificial intelligence & image processinglcsh:Electrical engineering. Electronics. Nuclear engineeringcomputerlcsh:TK1-9971Data integrationIEEE Access
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StateOS : A Memory-Efficient Hybrid Operating System for IoT Devices

2023

The increasing significance of operating systems (OSs) in the development of the internet of things (IoT) has emerged in the last decade. An event-driven OS is memory efficient and suitable for resource-constrained IoT devices and wireless sensors, although the program’s control flow, which is determined by events, is not always obvious. A multithreaded OS with sequential control flow is often considered clearer. However, this approach is memory-consuming. A hybrid OS seeks to combine the strengths of the event-driven approach with multithreaded approach. An event-driven cooperative threaded OS represents a hybrid approach that supports concurrency by explicitly yielding control to another …

cooperative programmingkäyttöjärjestelmätComputer Networks and Communicationsinternet of thingsComputer Science Applicationshybrid operating systemHardware and ArchitectureIoT OSSignal ProcessingWSN OSesineiden internetohjelmointitietoverkotwireless sensor network operating systemInformation Systems
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Il contratto di rete: una fattispecie dalle "maglie" troppo larghe?

2014

Il contratto di rete – introdotto nel nostro ordinamento giuridico dalla l. n. 33 del 2009 – si caratterizza per un’ampia flessibilità modulare e l’assenza di connotati tipizzanti ben definiti. L’articolo analizza i tratti più significativi di tale disciplina – peraltro a più riprese integrata e modificata –, mettendo in particolare evidenza l’eccessiva ampiezza della fattispecie contrattuale dalla stessa delineata, tale da determinare evidenti sovrapposizioni con i contratti associativi tipici già esistenti.

cooperazione imprenditorialecontrattoretinetworkimpreseSettore IUS/04 - Diritto Commerciale
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Cell degradation detection based on an inter-cell approach

2017

Fault management is a crucial part of cellular network management systems. The status of the base stations is usually monitored by well-defined key performance indicators (KPIs). The approaches for cell degradation detection are based on either intra-cell or inter-cell analysis of the KPIs. In intra-cell analysis, KPI profiles are built based on their local history data whereas in inter-cell analysis, KPIs of one cell are compared with the corresponding KPIs of the other cells. In this work, we argue in favor of the inter-cell approach and apply a degradation detection method that is able to detect a sleeping cell that could be difficult to observe using traditional intra-cell methods. We d…

correlation based cell degradation detectionreal LTE networknetwork management automationself-healinglong term evolution (LTE)network managementself-organizing networks (SON)fault managementinter-cell analysissiirrokset
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