Search results for "Retrieval"

showing 10 items of 1176 documents

Quantitative Phase Imaging in Microscopy Using a Spatial Light Modulator

2010

In this chapter, we present a new method capable of recovery of the quantitative phase information of microscopic samples. Essentially, a spatial light modulator (SLM) and digital image processing are the basics to extract the sample’s phase distribution. The SLM produces a set of misfocused images of the input sample at the CCD plane by displaying a set of lenses with different power at the SLM device. The recorded images are then numerically processed to retrieve phase information. Computations are based on the wave propagation equation and lead to a complex amplitude image containing information of both amplitude and phase distributions of the input sample diffracted wave front. The prop…

WavefrontSpatial light modulatorOpticsMaterials sciencebusiness.industryMicroscopyDigital image processingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPhase (waves)Digital holographic microscopyPhase retrievalbusinessDigital holography
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Optical phase retrieval using four rotated versions of a single binary amplitude modulating mask

2019

In recent years, phase retrieval methods recovering the phase of an object from coded diffraction patterns have gained popularity. A numerical phase retrieval method called PhaseLift that recovers the phase of an object from a very limited number of coded diffraction patterns was recently proposed. Performance of PhaseLift has been analyzed for different types and the number of masks modulating an object. We present a unique application of PhaseLift that uses four rotations of a single mask, modulating only the amplitude of an object. In simulations, a phase screen with the root-mean-square (RMS) value 0.294  μm was used as the test object. The RMS value of the retrieved phase screen after …

WavefrontZernike polynomialsComputer scienceMechanical EngineeringPhase (waves)Astronomy and AstrophysicsWavefront sensor01 natural sciencesElectronic Optical and Magnetic Materials010309 opticssymbols.namesakeAmplitudeSpace and Planetary ScienceControl and Systems Engineering0103 physical sciencessymbolsPhase retrieval010303 astronomy & astrophysicsInstrumentationAlgorithmSmoothingPhase-shift keyingJournal of Astronomical Telescopes, Instruments, and Systems
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Cobertura y solapamiento de Web of Science y Scopus en el análisis de la actividad científica española de psicología

2013

7 p. - Diversas tablas y figuras

Web of sciencelcsh:BF1-990EspañaScopusLibrary scienceContext (language use)159.9 - PsicologíaBibliotecologíaInformation systemBibliotecología y ciencia de la informaciónPsychologyScopusRelevance (information retrieval)General PsychologyScientific activityInternational levelScientific productionRevistas CientíficasScientific journalsRevistas científicasPsicologíalcsh:PsychologySpainInvestigaciónWeb of Science
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Towards Graphical Query Notation for Semantic Databases

2015

We describe a notation and a tool for schema-enabled visual/diagrammatic creation of SPARQL queries over RDF databases. The notation and the tool support both the standard basic query pattern comprising a main query class and possibly linked condition classes and means for aggregate query definition and placing conditions over aggregates including also aggregation of aggregate results. We discuss the applicability of the tool for ad-hoc query formulation in practical use cases.

Web search queryInformation retrievalComputer scienceInformationSystems_INFORMATIONSTORAGEANDRETRIEVALAggregate (data warehouse)InformationSystems_DATABASEMANAGEMENTcomputer.file_formatQuery languageQuery optimizationNotationSPARQLSargableQuery by Examplecomputercomputer.programming_language
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Post-search query modeling in federated web scenario

2014

As opposed to query reformulation oriented towards changes made by a user to specify the information need more precisely, a post-search query modeling is a technique of exploiting syntax variation of gradually extended query which depending on some other factors like e.g. the resource, database or the key word alignment, facilitates the searching process. The study into modeling query submitted to some search engines that utilize different translation semantic paradigms is motivated by a real-world's challenges to retrieve heterogeneous textual documents from the web. For a couple of language pairs, we develop a user-centered framework for imposing the Hidden Web traffic optimization. In li…

Web search queryInformation retrievalComputer scienceQuery languageQuery optimizationRanking (information retrieval)Human-Computer InteractionQuery expansionWeb query classificationcomponentSearch StrategyHidden WebSargableQuery ModelingTrans-lingual Information RetrievalcomputerRDF query languagecomputer.programming_languageThe Fifth International Conference on the Applications of Digital Information and Web Technologies (ICADIWT 2014)
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Non-Technological Aspects on Web Searching Success

2008

This paper studies the influence of social, cultural and emotional background of typical Web users into the web searching process. Several variables, describing such aspects, are represented and statistically analyzed with well known clustering and classifying algorithms such, as COBWEB, J48, Bayes classification, and Correspondence analysis. Results indicate that the efficiency of the complete process of Information Retrieval will not be fully understood without considering subjectivity and personality facts.

Web standardsBayes' theoremInformation retrievalC4.5 algorithmComputer scienceProcess (engineering)media_common.quotation_subjectPersonalityCluster analysisCorrespondence analysisCategory utilitymedia_common
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A web search methodology for health consumers

2014

Nowadays, many people use the World Wide Web to seek medical and health information but different users, such as providers (e.g., physicians) and consumers (e.g., patients), have different needs and bring different levels of reading ability and prior knowledge. Generic and specific search engines and specialized health sites either do not exploit the whole web or overload users with information. This creates difficulties mainly to consumers who often do not exactly know how to find the desired information. Thus, an information retrieval system for the web that 'drives' the user in finding the relevant information would be very beneficial. This paper describes a web search methodology for he…

Web standardsSettore INF/01 - InformaticaWeb developmentbusiness.industryComputer scienceConsumer Health Information Biomedical Information Retrieval Web Search VocabularyWorld Wide WebWeb Accessibility InitiativeWeb designWeb pageWeb navigationWeb intelligenceWS-PolicybusinessProceedings of the 15th International Conference on Computer Systems and Technologies
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Semantic to intelligent web era

2013

International audience; The Web has known a very fast evolution: going from the Web 1.0, known as Web of Documents where users are merely consumers of static information, to the more dynamic Web 2.0, known as social or collaborative Web where users produce and consume information simultaneously, and entering the more sophisticated Web 3.0, known as the Semantic Web by giving information a well-defined meaning so that it becomes more easily accessible by human users and automated processes. Fostering service intelligence and atomicity (the ability of autonomous services to interact automatically), remains one of the most upcoming challenges of the Semantic Web. This promotes the dawn of a ne…

Web standards[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR]medicine.medical_specialty[INFO.INFO-WB] Computer Science [cs]/WebComputer scienceInternet of Things[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer sciencecomputer.software_genreSPARQLData SemanticsSocial Semantic WebRDFKnowledge baseIntelligent ServicesWorld Wide Web[SCCO.COMP] Cognitive science/Computer sciencemedicine[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Semantic Web StackSemantic WebData WebSemantic WebOWL[ 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]business.industry[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]XMLWeb[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]Web serviceWeb intelligencebusinesscomputerWeb modelingProceedings of the Fifth International Conference on Management of Emergent Digital EcoSystems
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Semantic Multi-agent Architecture to Road Traffic Information Retrieval on the Web of Data

2013

In this paper, we describe a system based on FIPA standards to help the process of advertisement, discovery, invocation and reuse of traffic information on the web of data. The use of semantic web services (SWS) can be exploited to improve the outcomes in the discovery process, allowing end users to specify their need using concepts not keywords. Most of the traffic information is generally recovered by end users through web forms that specify their requirements, and must refill each time the same parameters to obtain the updated value from the web sites. Using agents besides Service Oriented Architecture (SOA), we will achieve interoperability between systems and also automatize the proces…

Web standardsmedicine.medical_specialtyInformation retrievalComputer sciencebusiness.industrycomputer.software_genreSocial Semantic WebWorld Wide WebmedicineSemantic Web StackWeb servicebusinessWS-PolicyWeb modelingcomputerSemantic WebData Web
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Natural Language Processing Agents and Document Clustering in Knowledge Management

2008

While HTML provides the Web with a standard format for information presentation, XML has been made a standard for information structuring on the Web. The mission of the Semantic Web now is to provide meaning to the Web. Apart from building on the existing Web technologies, we need other tools from other areas of science to do that. This chapter shows how natural language processing methods and technologies, together with ontologies and a neural algorithm, can be used to help in the task of adding meaning to the Web, thus making the Web a better platform for knowledge management in general.

Web standardsmedicine.medical_specialtyInformation retrievalKnowledge managementWeb developmentbusiness.industryComputer sciencecomputer.software_genreSocial Semantic WebWorld Wide WebmedicineArtificial intelligenceSemantic Web StackWeb servicebusinessWeb modelingcomputerSemantic WebData WebNatural language processing
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