Search results for " Integra"

showing 10 items of 2527 documents

The Athena X-ray Integral Field Unit: a consolidated design for the system requirement review of the preliminary definition phase

2023

The Athena X-ray Integral Unit (X-IFU) is the high resolution X-ray spectrometer, studied since 2015 for flying in the mid-30s on the Athena space X-ray Observatory, a versatile observatory designed to address the Hot and Energetic Universe science theme, selected in November 2013 by the Survey Science Committee. Based on a large format array of Transition Edge Sensors (TES), it aims to provide spatially resolved X-ray spectroscopy, with a spectral resolution of 2.5 eV (up to 7 keV) over an hexagonal field of view of 5 arc minutes (equivalent diameter). The X-IFU entered its System Requirement Review (SRR) in June 2022, at about the same time when ESA called for an overall X-IFU redesign (i…

X-IFU: The X-ray Integral Field UnitCosmology and Nongalactic Astrophysics (astro-ph.CO)The X-ray Integral Field Unit [X-IFU]Solar and stellar astrophysicsFOS: Physical sciences/dk/atira/pure/sustainabledevelopmentgoals/responsible_consumption_and_production[PHYS.ASTR.CO]Physics [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO]Settore FIS/05 - Astronomia E AstrofisicaX-raysSDG 7 - Affordable and Clean EnergyInstrumentation and Methods for Astrophysics (astro-ph.IM)Solar and Stellar Astrophysics (astro-ph.SR)High Energy Astrophysical Phenomena (astro-ph.HE)/dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energyAstrophysics of GalaxiesAthena: the advanced telescope for high energy astrophysicsAstronomy and AstrophysicsAstrophysics - Astrophysics of GalaxiesAstrophysical phenomenaSpace instrumentationAstrophysics - Solar and Stellar AstrophysicsHigh energySpace and Planetary ScienceAstrophysics of Galaxies (astro-ph.GA)[PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc]the advanced telescope for high energy astrophysics [Athena]Athena: the advanced telescope for high energy astrophysics · X-IFU: The X-ray Integral Field Unit · Space instrumentation · X-rays · ObservatoryObservatoryAstrophysics - Instrumentation and Methods for AstrophysicsAstrophysics - High Energy Astrophysical PhenomenaSDG 12 - Responsible Consumption and ProductionAstrophysics - Cosmology and Nongalactic Astrophysics
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ATHENA X-IFU thermal filters development status toward the end of the instrument phase-A

2018

Copyright 2018 Society of Photo-Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. The X-ray Integral Field Unit (X-IFU) is one of the two instruments of the Athena astrophysics space mission approved by ESA in the Cosmic Vision 2015-2025 Science Programme. The X-IFU consists of a large array of transition edge sensor micro-calorimeters that will operate at 100 mK inside a sophisticated cryostat. A set of thin filters, highly transparent to X-rays, will be m…

X-ray detectorCryostatCosmic VisionPhotonComputer scienceShieldsCondensed Matter Physicmicrocalorimeter01 natural sciences7. Clean energySettore FIS/05 - Astronomia E AstrofisicaX-ray Integral Field Unit (X-IFU)0103 physical sciencesthermal thin-film filterElectrical and Electronic EngineeringAerospace engineering010306 general physics010303 astronomy & astrophysicsbusiness.industryElectronic Optical and Magnetic MaterialDetectorAstrophysics::Instrumentation and Methods for AstrophysicsShot noiseComputer Science Applications1707 Computer Vision and Pattern RecognitionTransition Edge SensorApplied MathematicATHENA X-ray observatoryRadio frequencyTransition edge sensorbusinessSpace Telescopes and Instrumentation 2018: Ultraviolet to Gamma Ray
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First observations of the X-ray transient EXO 2030+375 with IBIS/ISGRI

2003

We present a first INTEGRAL observation of the 42s transient X-ray pulsar EXO 2030+375 with IBIS/ISGRI. The source was detected during Cyg X-1 observations in December 2002. We analyzed observations during the outburst period from 9 to 21 December 2002 with a total exposure time of ~770 kiloseconds. EXO 2030+375 was almost always detected during single ~30 minute exposures in the 18-45 energy bands. The source light curve shows the characteristic outburst shape observed in this source.

X-ray transientFOS: Physical sciencesIndividualAstrophysicsUNESCO::ASTRONOMÍA Y ASTROFÍSICAAstrophysicsGamma rays ; Observations ; X-rays ; Individual ; EXO 2030+375 ; Telescopes ; INTEGRAL ; IBISPulsarX-raysObservations:ASTRONOMÍA Y ASTROFÍSICA::Astronomía óptica [UNESCO]PhysicsIbisEXO 2030+375biologyINTEGRALUNESCO::ASTRONOMÍA Y ASTROFÍSICA::Astronomía ópticaGamma raysAstrophysics (astro-ph)Astronomy and Astrophysicsbiology.organism_classificationLight curveSpace and Planetary ScienceIBIS:ASTRONOMÍA Y ASTROFÍSICA [UNESCO]Telescopes
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HTML - Hypertext Markup Language

1997

XHTMLRuleMLMarkup languageComputer sciencecomputer.file_formatHTMLSynchronized Multimedia Integration LanguageComputer Science ApplicationsWorld Wide WebSGMLcomputerInformation Systemscomputer.programming_languagePCDATACollaborative Application Markup LanguageInformatik-Spektrum
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Analisi integrata tramite XRF e LIBS per lo studio dei materiali pittorici

2011

Lo studio dei materiali pittorici è uno degli obiettivi primari per la caratterizzazione storico- artistica delle opere d’arte poiché fornisce informazioni utili circa i materiali originali e di degrado, la tecnica di esecuzione ed eventuali interventi di restauro pregressi. Tuttavia, la complessità delle indagini archeometriche è legata alla necessità di garantire la salvaguardia del bene culturale che rende essenziale l’uso di tecniche di indagini non o micro invasive. Tra le metodologie d’indagine integrata, l’uso della fluorescenza a raggi X (XRF) e della spettroscopia mediante ablazione laser (LIBS) risponde a tale esigenza e risulta particolarmente utile per la complementarietà delle …

XRF LIBS analisi integrata materiali pittorici
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Adaptive Learning Process for the Evolution of Ontology-Described Classification Model in Big Data Context

2016

International audience; One of the biggest challenges in Big Data is to exploit value from large volumes of variable and changing data. For this, one must focus on analyzing the data in these Big Data sources and classify the data items according to a domain model (e.g. an ontology). To automatically classify unstructured text documents according to an ontology, a hierarchical multi-label classification process called Semantic HMC was proposed. This process uses ontologies to describe the classification model. To prevent cold start and user overload, the classification process automatically learns the ontology-described classification model from a very large set of unstructured text documen…

[ INFO ] Computer Science [cs]Computer scienceMaintenanceBig dataAdaptive learningContext (language use)Multi-label classification02 engineering and technologyOntology (information science)[INFO] Computer Science [cs]Machine learningcomputer.software_genreAdaptive LearningData modeling[SPI.AUTO]Engineering Sciences [physics]/AutomaticMachine LearningCold start020204 information systems[ SPI.AUTO ] Engineering Sciences [physics]/AutomaticMachine learning0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]Multi-Label ClassificationMulti-label classificationbusiness.industryOntologyOntology-based data integration[SPI.AUTO] Engineering Sciences [physics]/Automatic020201 artificial intelligence & image processingAdaptive learningArtificial intelligencebusinesscomputer
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User profile matching in social networks

2010

International audience; Inter-social networks operations and functionalities are required in several scenarios (data integration, data enrichment, information retrieval, etc.). To achieve this, matching user profiles is required. Current methods are so restrictive and do not consider all the related problems. Particularly, they assume that two profiles describe the same physical person only if the values of their Inverse Functional Property or IFP (e.g. the email address, homepage, etc.) are the same. However, the observed trend in social networks is not fully compatible with this assumption since users tend to create more than one social network account (for personal use, for work, etc.) w…

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR]Matching (statistics)Computer science[SCCO.COMP]Cognitive science/Computer science02 engineering and technologySimilarity measurecomputer.software_genreElectronic mail[SCCO.COMP] Cognitive science/Computer science020204 information systemsFOAF0202 electrical engineering electronic engineering information engineeringPattern matchingUser profileSocial networkbusiness.industrycomputer.file_formatProfile MatchingSocial Networks[ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]020201 artificial intelligence & image processingData mining[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]businesscomputerData integration
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Towards a Novel Approach to Multimedia Data Mixed Fragmentation

2009

International audience; Distributed multimedia applications have emerged at an increasing rate during the last decade in several domains (video conferencing, e-health, virtual meeting rooms, etc). This has created several new challenging problems related to the data integration and fragmentation, user-oriented and adaptive interfaces, real time and network performances, etc. In this paper, we focus on the problem of data(base) fragmentation in a multimedia context. We recall in this respect that data fragmentation consists of reducing irrelevant data accesses by grouping data frequently accessed together in dedicated segments. We mainly address the issue of query and predicate implication r…

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-WB] Computer Science [cs]/WebComputer science[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer science02 engineering and technologycomputer.software_genreMultimedia DistanceVideoconferencing[SCCO.COMP] Cognitive science/Computer science020204 information systems0202 electrical engineering electronic engineering information engineering[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Data partitioningData PartitionQuery Implication[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]MultimediaFunctional Dependency[INFO.INFO-WB]Computer Science [cs]/WebFragmentation (computing)[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]Multimedia FragmentationPartition (database)Predicate (grammar)[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ SCCO.COMP ] Cognitive science/Computer science020201 artificial intelligence & image processing[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]computerData integration
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Semantic oriented data structuration for MABS Application to BIM

2013

International audience; This paper presents a multiagent-based simulation approach to qualify the usage of buildings from the design phase. Our approach combines ontology and evolution process based on machine learning algorithms. The ontology relies on semantic data structures for the representation of environment components, agent knowledge and all data generated during the simulation.

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and SimulationComputer scienceProcess (engineering)0211 other engineering and technologies020101 civil engineering02 engineering and technologyOntology (information science)Semantic data modelcomputer.software_genre0201 civil engineering021105 building & constructionUpper ontologyRepresentation (mathematics)business.industryOntology-based data integration[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationDesign phaseBuilding information modeling[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA][ INFO.INFO-MA ] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-MA] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-MO] Computer Science [cs]/Modeling and SimulationData miningbusinessSoftware engineeringcomputer
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Qualifying semantic graphs using model checking

2011

International audience; Semantic interoperability problems have found their solutions using languages and techniques from the Semantic Web. The proliferation of ontologies and meta-information has improved the understanding of information and the relevance of search engine responses. However, the construction of semantic graphs is a source of numerous errors of interpretation or modeling and scalability remains a major problem. The processing of large semantic graphs is a limit to the use of semantics in current information systems. The work presented in this paper is part of a new research at the border of two areas: the semantic web and the model checking. This line of research concerns t…

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation[INFO.INFO-WB] Computer Science [cs]/WebComputer science[ INFO.INFO-WB ] Computer Science [cs]/Web0102 computer and information sciences02 engineering and technologycomputer.software_genre01 natural sciencesSocial Semantic Webtemporal logicSemantic similaritySemantic computing0202 electrical engineering electronic engineering information engineeringSemantic analyticsSemantic integrationSemantic Web StackInformation retrievalbusiness.industry[INFO.INFO-WB]Computer Science [cs]/WebSemantic search020207 software engineeringSemantic interoperability[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationModel-checking010201 computation theory & mathematicsSemantic graphTheoryofComputation_LOGICSANDMEANINGSOFPROGRAMS[INFO.INFO-MO] Computer Science [cs]/Modeling and SimulationArtificial intelligencebusinesscomputerNatural language processing2011 International Conference on Innovations in Information Technology
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