Search results for "multiagent system"

showing 10 items of 108 documents

Edge-Based Missing Data Imputation in Large-Scale Environments

2021

Smart cities leverage large amounts of data acquired in the urban environment in the context of decision support tools. These tools enable monitoring the environment to improve the quality of services offered to citizens. The increasing diffusion of personal Internet of things devices capable of sensing the physical environment allows for low-cost solutions to acquire a large amount of information within the urban environment. On the one hand, the use of mobile and intermittent sensors implies new scenarios of large-scale data analysis

010504 meteorology & atmospheric sciencesComputer scienceDistributed computingUrban sensingMobile sensingContext (language use)Information technology02 engineering and technology01 natural sciences[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Smart cityEdge intelligence11. Sustainability0202 electrical engineering electronic engineering information engineeringLeverage (statistics)Edge computingVoronoi tessellation0105 earth and related environmental sciencesSmart cityOut-of-order executionSettore INF/01 - InformaticaMulti-agent systemMissing data imputation020206 networking & telecommunicationsT58.5-58.64Variety (cybernetics)Multi-agent system[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Mobile deviceInformation Systems
researchProduct

Evaluation of chloroplast genome annotation tools and application to analysis of the evolution of coffee species.

2018

International audience; Chloroplast sequences are widely used for phylogenetic analysis due to their high degree of conservation in plants. Whole chloroplast genomes can now be readily obtained for plant species using new sequencing methods, giving invaluable data for plant evolution However new annotation methods are required for the efficient analysis of this data to deliver high quality phylogenetic analyses. In this study, the two main tools for chloroplast genome annotation were compared. More consistent detection and annotation of genes were produced with GeSeq when compared to the currently used Dogma. This suggests that the annotation of most of the previously annotated chloroplast …

0106 biological sciences0301 basic medicineChloroplastsPlant GenomesPlant SciencePlant Genetics01 natural sciencesGenomeCoffeeDatabase and Informatics MethodsPlant GenomicsPlastidsPhylogenyData Management2. Zero hungerPlant evolutionMultidisciplinarybiologyPhylogenetic treeQRfood and beveragesPhylogenetic AnalysisGenome projectGenomicsPhylogenetics[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]MedicineEngineering and Technology[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Cellular Structures and OrganellesCellular TypesSequence AnalysisResearch ArticleBiotechnologyComputer and Information SciencesBioinformaticsSciencePlant Cell BiologyBioengineering[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]Coffea canephoraGenes PlantResearch and Analysis Methods010603 evolutionary biology[INFO.INFO-IU]Computer Science [cs]/Ubiquitous ComputingEvolution Molecular[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]03 medical and health sciencesPhylogeneticsChloroplast GenomePlant CellsGeneticsEvolutionary SystematicsGenome ChloroplastTaxonomyEvolutionary BiologyCoffea arabicaCoffeafungiBiology and Life SciencesComputational BiologyMolecular Sequence AnnotationSequence Analysis DNACell Biology15. Life on landbiology.organism_classificationGenome Analysis[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationGenome Annotation030104 developmental biologyEvolutionary biology[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Plant BiotechnologySequence AlignmentPloS one
researchProduct

Coupling agent-based with equation-based models to study spatially explicit megapopulation dynamics

2018

International audience; The incorporation of the spatial heterogeneity of real landscapes into population dynamics remains extremely difficult. We propose combining equation-based modelling (EBM) and agent-based modelling (ABM) to overcome the difficulties classically encountered. ABM facilitates the description of entities that act according to specific rules evolving on various scales. However, a large number of entities may lead to computational difficulties (e.g., for populations of small mammals, such as voles, that can exceed millions of individuals). Here, EBM handles age-structured population growth, and ABM represents the spreading of voles on large scales. Simulations applied to t…

0106 biological sciencesHybrid modellingTheoretical computer scienceComputer sciencePopulation[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]010603 evolutionary biology01 natural sciences[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]Travelling waveArvicolaPopulation growtheducation[SDV.EE]Life Sciences [q-bio]/Ecology environmenteducation.field_of_studySpatial contextual awareness010604 marine biology & hydrobiologyEcological ModelingDispersal15. Life on land[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationSpatial heterogeneityCoupling (computer programming)[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Biological dispersalMontane ecology[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC][SDE.BE]Environmental Sciences/Biodiversity and EcologyHybrid modelHybrid modelEcological Modelling
researchProduct

Distributed adaptive leader–follower and leaderless consensus control of a class of strict-feedback nonlinear systems : a unified approach

2020

In this paper, distributed adaptive consensus for a class of strict-feedback nonlinear systems under directed topology condition is investigated. Both leader–follower and leaderless cases are considered in a unified framework. To design distributed controller for each subsystem, a local compensatory variable is generated based on the signals collected from its neighbors. Such a technique enables us to solve the leader–follower consensus and leaderless consensus problems in a unified framework. And it further allows us to treat the leaderless consensus as a special case of the leader–follower consensus. For leader–follower consensus, the assumption that the leader trajectory is linearly para…

0209 industrial biotechnologyClass (computer programming)Computer science020208 electrical & electronic engineeringParameterized complexity02 engineering and technologyComputer Science::Multiagent SystemsVariable (computer science)Nonlinear systemAdaptive Control020901 industrial engineering & automationControl and Systems EngineeringControl theory0202 electrical engineering electronic engineering information engineeringTrajectory:Electrical and electronic engineering [Engineering]Uniform boundednessElectrical and Electronic EngineeringSpecial caseDistributed Consensus Control
researchProduct

Reliable diagnostics using wireless sensor networks

2019

International audience; Monitoring activities in industry may require the use of wireless sensor networks, for instance due to difficult access or hostile environment. But it is well known that this type of networks has various limitations like the amount of disposable energy. Indeed, once a sensor node exhausts its resources, it will be dropped from the network, stopping so to forward information about maybe relevant features towards the sink. This will result in broken links and data loss which impacts the diagnostic accuracy at the sink level. It is therefore important to keep the network's monitoring service as long as possible by preserving the energy held by the nodes. As packet trans…

0209 industrial biotechnologyGeneral Computer ScienceComputer science[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]02 engineering and technologyData loss[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]Network topology[SPI.AUTO]Engineering Sciences [physics]/Automatic[INFO.INFO-IU]Computer Science [cs]/Ubiquitous ComputingPrognostics and health management[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]020901 industrial engineering & automation0202 electrical engineering electronic engineering information engineeringAdaBoostElectroniquebusiness.industryNetwork packetGeneral Engineering[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationWireless sensor networksRandom forest[SPI.TRON]Engineering Sciences [physics]/Electronics[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Sensor node020201 artificial intelligence & image processing[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Gradient boosting[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]businessWireless sensor networkComputer networkComputers in Industry
researchProduct

Ensuring the Reliability of an Autonomous Vehicle

2017

International audience; In automotive applications, several components, offering different services, can be composed in order to handle one specific task (autonomous driving for example). Nevertheless, component composition is not straightforward and is subject to the occurrence ofbugs resulting from components or services incompatibilities for instance. Hence, bugs detection in component-based systems at thedesign level is very important, particularly, when the developed system concerns automotive applications supporting critical services.In this paper, we propose a formal approach for modeling and verifying the reliability of an autonomous vehicle system, communicatingcontinuously with of…

021110 strategic defence & security studiesFocus (computing)021103 operations researchComputer sciencebusiness.industryDistributed computingReliability (computer networking)0211 other engineering and technologiesAutomotive industry[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]02 engineering and technology[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationTask (project management)[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR][INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Systems Modeling LanguageComponent (UML)Systems architectureTime constraint[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]businessProceedings of the 20th ACM International Conference on Modelling, Analysis and Simulation of Wireless and Mobile Systems
researchProduct

SpCLUST: Towards a fast and reliable clustering for potentially divergent biological sequences

2019

International audience; This paper presents SpCLUST, a new C++ package that takes a list of sequences as input, aligns them with MUSCLE, computes their similarity matrix in parallel and then performs the clustering. SpCLUST extends a previously released software by integrating additional scoring matrices which enables it to cover the clustering of amino-acid sequences. The similarity matrix is now computed in parallel according to the master/slave distributed architecture, using MPI. Performance analysis, realized on two real datasets of 100 nucleotide sequences and 1049 amino-acids ones, show that the resulting library substantially outperforms the original Python package. The proposed pac…

0301 basic medicineComputer science[INFO.INFO-SE] Computer Science [cs]/Software Engineering [cs.SE]Health Informatics[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE][INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing03 medical and health sciences[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]0302 clinical medicineSoftware[INFO.INFO-ET] Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-DC] Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Cluster AnalysisHumansCluster analysis[INFO.INFO-CR] Computer Science [cs]/Cryptography and Security [cs.CR]computer.programming_languagebusiness.industry[INFO.INFO-IU] Computer Science [cs]/Ubiquitous ComputingSimilarity matrixPattern recognitionDNAGenomicsSequence Analysis DNAPython (programming language)Mixture model[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationSpectral clusteringComputer Science Applications030104 developmental biologyComputingMethodologies_PATTERNRECOGNITION[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-MA] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-MO] Computer Science [cs]/Modeling and SimulationArtificial intelligence[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]businesscomputerAlgorithmsSoftware030217 neurology & neurosurgery
researchProduct

Global emergence of the widespread Pseudomonas aeruginosa ST235 clone

2018

Abstract Objectives Despite the non-clonal epidemic population structure of Pseudomonas aeruginosa , several multi-locus sequence types are distributed worldwide and are frequently associated with epidemics where multidrug resistance confounds treatment. ST235 is the most prevalent of these widespread clones. In this study we aimed to understand the origin of ST235 and the molecular basis for its success. Methods The genomes of 79 P. aeruginosa ST235 isolates collected worldwide over a 27-year period were examined. A phylogenetic network was built, using a Bayesian approach to find the Most Recent Common Ancestor, and we identified antibiotic resistance determinants and ST235-specific genes…

0301 basic medicineMost recent common ancestorClone (cell biology)[ SDV.MP.BAC ] Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriologymedicine.disease_causeGlobal HealthGenome[ SDV.MP ] Life Sciences [q-bio]/Microbiology and ParasitologyPrevalenceCluster Analysis[ SDV.BIBS ] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]High-risk clonesPhylogenyComputingMilieux_MISCELLANEOUSMolecular EpidemiologyGeneral Medicine3. Good healthInfectious Diseases[SDV.MP]Life Sciences [q-bio]/Microbiology and Parasitology[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA][ SDV.BBM.GTP ] Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]Pseudomonas aeruginosaEfflux[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]FluoroquinolonesMicrobiology (medical)Genotype030106 microbiologyEpidemic[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]BiologyBacterial resistanceMicrobiology[INFO.INFO-IU]Computer Science [cs]/Ubiquitous ComputingEvolution Molecular03 medical and health sciences[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]Antibiotic resistanceDrug Resistance BacterialmedicinePseudomonas InfectionsGenePseudomonas aeruginosaPathogenInternational clones[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationMultiple drug resistanceGenes Bacterial[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Multilocus Sequence Typing
researchProduct

A clustering package for nucleotide sequences using Laplacian Eigenmaps and Gaussian Mixture Model.

2018

International audience; In this article, a new Python package for nucleotide sequences clustering is proposed. This package, freely available on-line, implements a Laplacian eigenmap embedding and a Gaussian Mixture Model for DNA clustering. It takes nucleotide sequences as input, and produces the optimal number of clusters along with a relevant visualization. Despite the fact that we did not optimise the computational speed, our method still performs reasonably well in practice. Our focus was mainly on data analytics and accuracy and as a result, our approach outperforms the state of the art, even in the case of divergent sequences. Furthermore, an a priori knowledge on the number of clust…

0301 basic medicineNematoda01 natural sciencesGaussian Mixture Model[STAT.ML]Statistics [stat]/Machine Learning [stat.ML][MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]ComputingMilieux_MISCELLANEOUScomputer.programming_language[STAT.AP]Statistics [stat]/Applications [stat.AP]Phylogenetic treeDNA ClusteringGenomicsHelminth ProteinsComputer Science Applications[STAT]Statistics [stat]010201 computation theory & mathematics[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Data analysisEmbeddingA priori and a posteriori[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Health Informatics0102 computer and information sciences[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]Biology[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing03 medical and health sciences[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]Laplacian EigenmapsAnimalsCluster analysis[SDV.GEN]Life Sciences [q-bio]/GeneticsModels Geneticbusiness.industryPattern recognitionNADH DehydrogenaseSequence Analysis DNAPython (programming language)Mixture model[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationVisualization030104 developmental biologyComputingMethodologies_PATTERNRECOGNITIONPlatyhelminths[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Programming LanguagesArtificial intelligence[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]businesscomputerComputers in biology and medicine
researchProduct

panISa: ab initio detection of insertion sequences in bacterial genomes from short read sequence data.

2018

Abstract Motivation The advent of next-generation sequencing has boosted the analysis of bacterial genome evolution. Insertion sequence (IS) elements play a key role in prokaryotic genome organization and evolution, but their repetitions in genomes complicate their detection from short-read data. Results PanISa is a software pipeline that identifies IS insertions ab initio in bacterial genomes from short-read data. It is a highly sensitive and precise tool based on the detection of read-mapping patterns at the insertion site. PanISa performs better than existing IS detection systems as it is based on a database-free approach. We applied it to a high-risk clone lineage of the pathogenic spec…

0301 basic medicineStatistics and ProbabilityLineage (genetic)Computer scienceAb initioComputational biologyBacterial genome size[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]BiochemistryGenome[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing03 medical and health sciences[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR][SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]Insertion sequenceMolecular BiologyGenomic organizationHigh-Throughput Nucleotide SequencingSequence Analysis DNA[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM][SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/BacteriologyPipeline (software)[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationComputer Science ApplicationsComputational Mathematics030104 developmental biologyComputational Theory and Mathematics[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]DNA Transposable Elements[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Genome BacterialSoftwareBioinformatics (Oxford, England)
researchProduct