Search results for "cloud computing"

showing 10 items of 327 documents

Pan-cancer analysis of whole genomes

2020

Publisher's version (útgefin grein)

Maletert promoter mutationsCancer development and immune defence Radboud Institute for Molecular Life Sciences [Radboudumc 2]DNA Mutational AnalysisNormal tissuesystematic analysisGermlineTranscriptome0302 clinical medicineAetiologyCàncerCellular SenescenceCancer0303 health sciencesdna-damageMassive parallel sequencingPan cancerREARRANGEMENTSHigh-Throughput Nucleotide SequencingGenomicsSciences bio-médicales et agricolesTelomereCOMPREHENSIVE3. Good healthTERT PROMOTER MUTATIONSsignatures030220 oncology & carcinogenesisScience & Technology - Other TopicsErfðarannsóknirHuman:Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC]EvolutionRNA SplicingGenomicsArticleEvolution MolecularStructural variationRC025403 medical and health sciencesSDG 3 - Good Health and Well-beingGeneticgenomicsSYSTEMATIC ANALYSISGeneticsGenomics--Databases.HumansGenetic TestingMolecular BiologySIGNATURESWhole genome sequencing1000 MultidisciplinaryChromothripsisScience & TechnologyRC0254 Neoplasms. Tumors. Oncology (including Cancer)Information DisseminationResearchInstitutes_Networks_Beacons/mcrcPreventionBiology and Life SciencesMolecularOncogenesCloud Computingmedicine.diseaseGenòmicaCompute cloudsMutation570 Life sciences; biologyCOMPREHENSIVE CHARACTERIZATIONGenèticaWhole Genome Sequencing--methodsBackground informationDNA Mutational Analysis ; Evolution ; Genetic / genetics ; Genome ; Genomics ; Germ-Line Mutation / genetics ; High-Throughput Nucleotide Sequencing ; Human / genetics ; Humans ; ICGC/TCGA Pan-Cancer Analysis of Whole Genomes ConsortiumMedizinGenomeWhole-genomeGenome mappingNeoplasms2.1 Biological and endogenous factorsPromoter Regions GeneticCàncer -- Aspectes genèticsTelomeraseGeneticsWomen's cancers Radboud Institute for Molecular Life Sciences [Radboudumc 17]MultidisciplinaryChromothripsisGenomeManchester Cancer Research Centregenomics cancer profiling3rd-DAS10124 Institute of Molecular Life SciencesWomen's cancers Radboud Institute for Health Sciences [Radboudumc 17]Multidisciplinary SciencesParallel sequencingICGC/TCGA Pan-Cancer Analysis of Whole Genomes ConsortiumFemaleprofilingMedical GeneticsEngineering sciences. TechnologyBiotechnologyGeneral Science & TechnologyThe Cancer Genome Atlas610 Medicine & healthComputational biologyQH426 GeneticsBiologyConsortium of the International Cancer Genome ConsortiumPromoter RegionsGermline mutationPan-cancer analysisKrabbameinsrannsóknirmedicinecancerddc:610QH426Germ-Line MutationMedicinsk genetikKrabbamein030304 developmental biologyCell ProliferationLANDSCAPEGenome Humancomprehensive characterizationPan-cancer analysis of whole genomesPoint mutationHuman GenomeCancerReproducibility of ResultsSOMATIC MUTATIONSEVOLUTIONCancer sequencing Chromothripsis telomereDNA-DAMAGEMutagenesisPATTERNS3111 BiomedicineCHARACTERIZATION
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Multitemporal Cloud Masking in the Google Earth Engine

2018

The exploitation of Earth observation satellite images acquired by optical instruments requires an automatic and accurate cloud detection. Multitemporal approaches to cloud detection are usually more powerful than their single scene counterparts since the presence of clouds varies greatly from one acquisition to another whereas surface can be assumed stationary in a broad sense. However, two practical limitations usually hamper their operational use: the access to the complete satellite image archive and the required computational power. This work presents a cloud detection and removal methodology implemented in the Google Earth Engine (GEE) cloud computing platform in order to meet these r…

Masking (art)010504 meteorology & atmospheric sciencesComputer scienceScienceOptical instrumentReal-time computing0211 other engineering and technologiesCloud detectionCloud computing02 engineering and technologyEarth observation satellite01 natural scienceslaw.inventionmultitemporal analysislawSatellite imageLandsat-8change detection021101 geological & geomatics engineering0105 earth and related environmental sciencesbusiness.industryQGoogle Earth Engine (GEE)cloud maskingPower (physics)General Earth and Planetary Sciencesbusinessimage time seriesChange detectionRemote Sensing
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MODIS probabilistic cloud masking over the Amazonian evergreen tropical forests: a comparison of machine learning-based methods

2019

Amazonian tropical forests play a significant role in global water, carbon and energy cycles. Satellite remote sensing is presented as a feasible means in order to monitor these forests. In particu...

Masking (art)010504 meteorology & atmospheric sciencesbusiness.industryAmazonian0211 other engineering and technologiesProbabilistic logicCloud computing02 engineering and technologyEvergreen01 natural sciencesSatellite remote sensingClimatologyGeneral Earth and Planetary SciencesEnvironmental sciencebusiness021101 geological & geomatics engineering0105 earth and related environmental sciencesInternational Journal of Remote Sensing
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Convolutional Neural Networks for Multispectral Image Cloud Masking

2020

Convolutional neural networks (CNN) have proven to be state of the art methods for many image classification tasks and their use is rapidly increasing in remote sensing problems. One of their major strengths is that, when enough data is available, CNN perform an end-to-end learning without the need of custom feature extraction methods. In this work, we study the use of different CNN architectures for cloud masking of Proba-V multispectral images. We compare such methods with the more classical machine learning approach based on feature extraction plus supervised classification. Experimental results suggest that CNN are a promising alternative for solving cloud masking problems.

Masking (art)FOS: Computer and information sciencesComputer Science - Machine Learning010504 meteorology & atmospheric sciencesContextual image classificationbusiness.industryComputer scienceComputer Vision and Pattern Recognition (cs.CV)Feature extractionMultispectral image0211 other engineering and technologiesComputer Science - Computer Vision and Pattern RecognitionCloud computingPattern recognition02 engineering and technology01 natural sciencesConvolutional neural networkMachine Learning (cs.LG)Artificial intelligenceState (computer science)business021101 geological & geomatics engineering0105 earth and related environmental sciences
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Achieving Fair Load Balancing by Invoking a Learning Automata-Based Two-Time-Scale Separation Paradigm.

2020

Author's accepted manuscript. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. In this article, we consider the problem of load balancing (LB), but, unlike the approaches that have been proposed earlier, we attempt to resolve the problem in a fair manner (or rather, it would probably be more appropriate to describe it as an ε-fair manner because, although the LB…

Mathematical optimizationLearning automataComputer Networks and Communicationsbusiness.industryStochastic processComputer scienceQuality of serviceResource allocationsCloud computingLoad balancing (computing)Continuous learning automatonsComputer Science ApplicationsArtificial IntelligenceServerResource allocationFair load balancingbusinessVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550SoftwareIEEE transactions on neural networks and learning systems
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How to enhance digital support for cross-organisational health care teams? A user-based explorative study

2020

Health care service provision of individualised treatment to an ageing population prone to chronic conditions and multimorbidities is threatened. There is a need for digitally supported care, that is, (1) person-centred, (2) integrated, and (3) proactive. The research project 3P, Patients and Professionals in Productive Teams, aimed to validate and verify the prerequisites for health care systems run with patient-centred service models. This paper presents an explorative study of the digital support of a cross-organisational health care team in Norway, providing services to elderly frail people with multimorbidities in hospital discharge transition. Qualitative research methods were employe…

Medicine (General)Population ageingService (systems architecture)Knowledge management020205 medical informaticsArticle SubjectHealth Services for the AgedFrail Elderlymedia_common.quotation_subjectInteroperabilityBiomedical EngineeringHealth InformaticsCloud computingComorbidity02 engineering and technology03 medical and health sciencesR5-9200302 clinical medicineVDP::Teknologi: 500::Medisinsk teknologi: 620Patient-Centered CareHealth careMedical technology0202 electrical engineering electronic engineering information engineeringHumans030212 general & internal medicineInformation flow (information theory)R855-855.5VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550Qualitative ResearchAgedmedia_commonPatient Care TeamTeamworkComputersNorwaybusiness.industryData CollectionVDP::Medical disciplines: 700::Health sciences: 800Cloud ComputingTelemedicineVDP::Medisinske Fag: 700::Helsefag: 800Models OrganizationalChronic DiseaseSurgerybusinessVDP::Technology: 500::Medical technology: 620Research ArticleBiotechnologyQualitative research
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Impact of cloud processes on aerosol particle properties: results from two ATR-42 flights in an extended stratocumulus cloud layer during the EUCAARI…

2011

Abstract. Within the European Aerosol Cloud Climate and Air Quality Interactions (EUCAARI) project, the Meteo France research aircraft ATR-42 was operated from Rotterdam airport during May 2008, to perform scientific flights dedicated to the investigation of aerosol-cloud interactions. Therein, the objective of this study is to illustrate the impact of cloud processing on the aerosol particles physical and chemical properties. The presented results are retrieved from measurements during a double-flight mission from Rotterdam (Netherlands) to Newcastle (UK) and back using data measured with compact Time of Flight Aerosol Mass Spectrometer (cToF-AMS) and Scanning Mobility Particle Sizer (SMPS…

Meteorologybusiness.industryCloud computingAtmospheric sciencesMarine stratocumulusAerosolchemistry.chemical_compoundchemistryLiquid water contentScanning mobility particle sizerEnvironmental scienceParticleSulfatebusinessSea salt aerosol
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The Cirrus Coupled Cloud-Radiation Experiment-II

2016

A cirrus study has been undertaken during the second Cirrus Cloud-Radiation Experiment field campaign based in Prestwick, Scotland. We report on a case study describing the radiation and microphysics measurements and cloud modelling work.

MicrophysicsMeteorologybusiness.industryEnvironmental scienceCirrusCloud computingRadiationbusinessField campaignLight, Energy and the Environment
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Performance Analysis of Memory Cloning Solutions in Mobile Edge Computing

2018

This paper deals with the problem of service migration in the emerging scenarios of Mobile Edge Computing. Mobile edge computing is achieved by moving the traditional cloud infrastructures, exploited by many today applications, close to the network edge in order to reduce the response times in the so called tactile-internet. However, because of user mobility, such an application architecture may pose the problem of service migration in case of handover from one server site to another. After introducing the current solutions for dealing with service migration and, in particular, the approaches based on service decomposition into multiple layers, we quantify the migration time and the service…

Mobile Edge Computing Internet of Things Live migrationMobile edge computingHandoverEdge deviceComputer sciencebusiness.industrySettore ING-INF/03 - TelecomunicazioniDistributed computingServerApplications architectureCloud computingbusiness
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NFVMon: Enabling Multioperator Flow Monitoring in 5G Mobile Edge Computing

2018

With the advances of new-generation wireless and mobile communication systems such as the fifth-generation (5G) mobile networks and Internet of Things (IoT) networks, demanding applications such as Ultra-High-Definition video applications is becoming ever popular. These applications require real-time monitoring and processing to meet the mission-critical quality of service requirements and are expected to be supported by the emerging fog or edge computing paradigms. This paper presents NFVMon, a novel monitoring architecture to enable flow monitoring capabilities of network traffic in a 5G multioperator mobile edge computing environment. The proposed NFVMon is integrated with the management…

Mobile edge computingArticle SubjectComputer Networks and CommunicationsComputer sciencebusiness.industrylcsh:TQuality of serviceTestbed020206 networking & telecommunicationsCloud computing02 engineering and technologylcsh:Technologylcsh:Telecommunicationlcsh:TK5101-67200202 electrical engineering electronic engineering information engineeringWireless020201 artificial intelligence & image processingElectrical and Electronic EngineeringbusinessInternet of Things5GEdge computingInformation SystemsComputer networkWireless Communications and Mobile Computing
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