Search results for "Emerging technologies"

showing 10 items of 317 documents

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
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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
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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
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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
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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
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Food Processing at a Crossroad

2019

Recently, processed foods received negative images among consumers and experts regarding food-health imbalance. This stresses the importance of the food processing—nutrition interface and its relevance within the diet-health debates. In this review, we approach the related questions in a 3-fold way. Pointing out the distinguished role food processing has played in the development of the human condition and during its 1.7 million year old history, we show the function of food processing for the general design principles of food products. Secondly, a detailed analysis of consumer related design principles and processing reveals questions remaining from the historical transformation from basic…

0301 basic medicineProcess (engineering)Computer scienceEmerging technologiesEndocrinology Diabetes and Metabolismmedia_common.quotation_subjectlcsh:TX341-641030209 endocrinology & metabolismFood technologyReviewnutrient profiling03 medical and health sciences0302 clinical medicinefood processingultra-processed foodsFunction (engineering)NutritionGrand Challengesmedia_commonfood process-structure-function relationship030109 nutrition & dieteticsNutrition and Dieteticsbusiness.industrydigestive oral and skin physiologyData sciencePAN principlesemerging technologiesfood system changesParadigm shiftFood processingFood systemsbusinesslcsh:Nutrition. Foods and food supplyFood ScienceFrontiers in Nutrition
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Proteomics Standards Initiative: Fifteen Years of Progress and Future Work.

2017

Abstract: The Proteomics Standards Initiative (PSI) of the Human Proteome Organization (HUPO) has now been developing and promoting open community standards and software tools in the field of proteomics for 15 years. Under the guidance of the chair, co-chairs, and other leadership positions, the PSI working groups are tasked with the development and maintenance of community standards via special workshops and ongoing work. Among the existing, ratified standards, the PSI working groups continue to update PSI-MI XML, MITAB, mzML, mzIdentML, mzQuantML, mzTab, and the MIAPE (Minimum Information About a Proteomics Experiment) guidelines with the advance of new technologies and techniques. Furthe…

0301 basic medicineProteomicsprotein quantificationEmerging technologiesComputer sciencecomputer.internet_protocolGuidelines as Topiccomputer.software_genreBiochemistry03 medical and health sciencesprotein identificationHuman proteome projectHumansCommunity standardsquality controlDatabases ProteinBiologydatabasemass spectrometryComputer. Automation030102 biochemistry & molecular biologyApplication programming interfaceProteomics Standards InitiativeGeneral ChemistryReference StandardsData sciencemetabolomicsChemistry030104 developmental biologyPerspectivedata standardWeb servicebioinformatics softwareWorking groupcomputerXMLSoftwaremolecular interactionsJournal of proteome research
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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)
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Simulation-based estimation of branching models for LTR retrotransposons

2017

Abstract Motivation LTR retrotransposons are mobile elements that are able, like retroviruses, to copy and move inside eukaryotic genomes. In the present work, we propose a branching model for studying the propagation of LTR retrotransposons in these genomes. This model allows us to take into account both the positions and the degradation level of LTR retrotransposons copies. In our model, the duplication rate is also allowed to vary with the degradation level. Results Various functions have been implemented in order to simulate their spread and visualization tools are proposed. Based on these simulation tools, we have developed a first method to evaluate the parameters of this propagation …

0301 basic medicineStatistics and ProbabilitySource codeTheoretical computer scienceRetroelementsmedia_common.quotation_subjectRetrotransposon[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]BiologyBiochemistryGenomeChromosomesBranching (linguistics)[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing03 medical and health sciences[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]SoftwareAnimalsComputer SimulationMolecular BiologyComputingMilieux_MISCELLANEOUSmedia_commoncomputer.programming_languageGeneticsGenomeModels Geneticbusiness.industry[SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE]Python (programming language)[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM][INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationComputer Science ApplicationsVisualizationComputational Mathematics030104 developmental biologyDrosophila melanogasterComputational Theory and Mathematics[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Programming Languages[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Mobile genetic elements[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]businesscomputerSoftware
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Methods for RNA Modification Mapping Using Deep Sequencing: Established and New Emerging Technologies

2019

New analytics of post-transcriptional RNA modifications have paved the way for a tremendous upswing of the biological and biomedical research in this field. This especially applies to methods that included RNA-Seq techniques, and which typically result in what is termed global scale modification mapping. In this process, positions inside a cell`s transcriptome are receiving a status of potential modification sites (so called modification calling), typically based on a score of some kind that issues from the particular method applied. The resulting data are thought to represent information that goes beyond what is contained in typical transcriptome data, and hence the field has taken to use …

0301 basic medicinelcsh:QH426-470Computer scienceProcess (engineering)Emerging technologieschemical treatmentNext Generation Sequencingengineered Reverse Transcriptase enzymesRNA-SeqReviewcomputer.software_genreDeep sequencingField (computer science)deep sequencing03 medical and health sciences0302 clinical medicineepitranscriptome[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]GeneticsAnimalsHumansRNA-SeqRNA Processing Post-TranscriptionalComputingMilieux_MISCELLANEOUSGenetics (clinical)Sequence Analysis RNAbusiness.industryScale (chemistry)High-Throughput Nucleotide Sequencing[SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular biologyRNA modificationTerm (time)lcsh:Genetics030104 developmental biologyAnalyticsRNAData miningbusinesscomputer030217 neurology & neurosurgeryGenes
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