Search results for "NETWORKS"

showing 10 items of 3260 documents

Noise-tolerant efficient inductive synthesis of regular expressions from good examples

1997

We present an almost linear time method of inductive synthesis restoring simple regular expressions from one representative (good) example. In particular, we consider synthesis of expressions of star-height one, where we allow one union operation under each iteration, and synthesis of expressions without union operations from examples that may contain mistakes. In both cases we provide sufficient conditions defining precisely the class of target expressions and the notion of good examples under which the synthesis algorithm works correctly, and present the proof of correctness. In the case of expressions with unions the proof is based on novel results in the combinatorics of words. A genera…

Class (set theory)CorrectnessComputer programComputer Networks and CommunicationsComputer scienceComputer experimentTheoretical Computer ScienceHardware and ArchitectureSimple (abstract algebra)Regular expressionTime complexityAlgorithmSoftwareProgram synthesisNew Generation Computing
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Disorder and interactions in systems out of equilibrium : the exact independent-particle picture from density functional theory

2017

Density functional theory (DFT) exploits an independent-particle-system construction to replicate the densities and current of an interacting system. This construction is used here to access the exact effective potential and bias of non-equilibrium systems with disorder and interactions. Our results show that interactions smoothen the effective disorder landscape, but do not necessarily increase the current, due to the competition of disorder screening and effective bias. This puts forward DFT as a diagnostic tool to understand disorder screening in a wide class of interacting disordered systems.

Class (set theory)Current (mathematics)Non-equilibrium thermodynamicsFOS: Physical sciences02 engineering and technologyCondensed Matter::Disordered Systems and Neural Networks01 natural sciencesCondensed Matter - Strongly Correlated ElectronsInformationSystems_GENERALdisordered systems0103 physical sciencesMesoscale and Nanoscale Physics (cond-mat.mes-hall)strongly correlated systemsDisorder screeningStatistical physics010306 general physicsdensity functional theoryPhysicsta114Condensed Matter - Mesoscale and Nanoscale PhysicsStrongly Correlated Electrons (cond-mat.str-el)tiheysfunktionaaliteoriaDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural Networks021001 nanoscience & nanotechnologynonequilibrium Green's functionParticleDensity functional theory0210 nano-technology
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Assessing the impact of copy number variants on miRNA genes in autism by Monte Carlo simulation.

2014

Autism Spectrum Disorders (ASDs) are childhood neurodevelopmental disorders with complex genetic origins. Previous studies have investigated the role of de novo Copy Number Variants (CNVs) and microRNAs as important but distinct etiological factors in ASD. We developed a novel computational procedure to assess the potential pathogenic role of microRNA genes overlapping de novo CNVs in ASD patients. Here we show that for chromosomes # 1, 2 and 22 the actual number of miRNA loci affected by de novo CNVs in patients was found significantly higher than that estimated by Monte Carlo simulation of random CNV events. Out of 24 miRNA genes over-represented in CNVs from these three chromosomes only …

Clinical PathologyDNA Copy Number Variationsendocrine system diseasesChromosomes Human Pair 22ScienceGene regulatory networkGenomicsDevelopmental and Pediatric NeurologyBiologyPathology and Laboratory MedicinePediatricsGenomeMolecular GeneticsmiRNA Genes Monte Carlo Simulation AutismDiagnostic Medicinemental disordersGeneticsMedicine and Health SciencesmedicineHumansComputer SimulationGene Regulatory NetworksCopy-number variationAutistic DisorderGeneGeneticsMultidisciplinaryGenome HumanQRBiology and Life SciencesComputational BiologyGenomicsGenome Analysismedicine.diseaseSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)MicroRNAsNeurologyChromosomes Human Pair 1Genetic LociAutism spectrum disorderChromosomes Human Pair 2AutismMedicineStructural GenomicsHuman genomeMonte Carlo MethodResearch ArticlePLoS ONE
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On the chromatic number of disk graphs

1998

Colorings of disk graphs arise in the study of the frequency-assignment problem in broadcast networks. Motivated by the observations that the chromatic number of graphs modeling real networks hardly exceeds their clique number, we examine the related properties of the unit disk (UD) graphs and their different generalizations. For all these graphs including the most general class of the double disk (DD) graphs, it is shown that X(G) ≤ c.ω(G) for a constant c. Several coloring algorithms are analyzed for disk graphs, aiming to improve the bounds on X(G). We find that their worst-case performance expressed in the number of used colors is indeed reached in some instances.

Clique-sumComputer Networks and CommunicationsTrapezoid graph1-planar graphMetric dimensionCombinatoricsIndifference graphPathwidthHardware and ArchitectureChordal graphMaximal independent setSoftwareMathematicsofComputing_DISCRETEMATHEMATICSInformation SystemsMathematicsNetworks
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Using Cloud Computing to Implement a Security Overlay Network

2012

This article proposes and analyzes a general cloud-based security overlay network that can be used as a transparent overlay network to provide services such as intrusion detection systems, antivirus and antispam software, and distributed denial-of-service prevention. The authors analyze each of these in-cloud security services in terms of resiliency, effectiveness, performance, flexibility, control, and cost.

Cloud computing securityComputer Networks and CommunicationsComputer scienceNetwork securitybusiness.industryOverlay networkDenial-of-service attackCloud computingIntrusion detection systemElectronic mailNetwork Access ControlElectrical and Electronic EngineeringbusinessLawComputer networkIEEE Security & Privacy Magazine
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Comparative analysis of architectures for monitoring cloud computing infrastructures

2015

The lack of control over the cloud resources is one of the main disadvantages associated to cloud computing. The design of efficient architectures for monitoring such resources can help to overcome this problem. This contribution describes a complete set of architectures for monitoring cloud computing infrastructures, and provides a taxonomy of them. The architectures are described in detail, compared among them, and analysed in terms of performance, scalability, usage of resources, and security capabilities. The architectures have been implemented in real world settings and empirically validated against a real cloud computing infrastructure based on OpenStack. More than 1000 virtual machin…

Cloud computing securityComputer Networks and Communicationsbusiness.industryComputer scienceDistributed computingCloud computingcomputer.software_genreSet (abstract data type)Utility computingHardware and ArchitectureVirtual machineScalabilitybusinesscomputerSoftwareFuture Generation Computer Systems
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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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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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Data for: Secondary Users Selection and Sparse Narrow-band Interference Mitigation in Cognitive Radio Networks

2018

Spectrum scarcity is a critical problem that may reduce the effectiveness of wireless technologies and services. To address this problem, different spectrum management techniques have been proposed such as overlay cognitive radio (CR) where the unlicensed users can share the same spectrum with the licensed users. The main challenges in overlay CR networks are the identification and detection of the Primary User (PU) signals in a multi-source narrow-band interference (NBI) scenario. Therefore, in this paper, we investigate the performance of an orthogonal frequency division multiplexing (OFDM) overlay CR network with Secondary Users (SUs) and subcarriers selection schemes. Three approaches f…

Cognitive Radio NetworkForward NetworksInterdisciplinary sciencesOtherInterference
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