Search results for "Information science"

showing 10 items of 3627 documents

Latvijas Universitātes Bibliotēkas jaunumi, 2015

2015

Dabaszinātņu akadēmiskais centrsKerkoviusa namsEiropas Dokumentācijas centru seminārsAugstskolas bibliotēkaPar Bibliotēkunenovērtēta vai pārvērtēta” [Zinātniskā konference „LU Rakstu nozīmība]Projekts „Latviešu centra Minsterē bibliotēkas krājuma speciālās kolekcijas – nozīmīgs kultūrvēstures izpētes avots’’.Projekts OpenAIRE2020:SOCIAL SCIENCES::Other social sciences::Library and information science [Research Subject Categories]Bibliotēkas nedēļaNotikumu kalendārsTiešsaistes e-pakalpojumiIlona Vēliņa-ŠvilpeApmācības BibliotēkāKonference „Atvērtā zinātne – pētnieku ieguvums 21. gadsimtā”Izstādes un pasākumiDigitalizācija - Žurnāls „Ceļš”Latvijas Universitātes bibliotyēka - Viļņas Universitātes bibliotēka - Tartu universitātes bibliotēka [Sadarbība]LU darbinieku sporta spēles
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Mana pieredze jeb gads digitalizācijā

2017

Rakstā izklāstīta LU Bibliotēkas darbinieces digitalizācijas darba pieredze.

Darba procesi - LU BibliotēkaLU Bibliotēkas darbiniekiDigitalizācija:SOCIAL SCIENCES::Other social sciences::Library and information science [Research Subject Categories]
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Criminal networks analysis in missing data scenarios through graph distances.

2021

Data collected in criminal investigations may suffer from: (i) incompleteness, due to the covert nature of criminal organisations; (ii) incorrectness, caused by either unintentional data collection errors and intentional deception by criminals; (iii) inconsistency, when the same information is collected into law enforcement databases multiple times, or in different formats. In this paper we analyse nine real criminal networks of different nature (i.e., Mafia networks, criminal street gangs and terrorist organizations) in order to quantify the impact of incomplete data and to determine which network type is most affected by it. The networks are firstly pruned following two specific methods: …

Data AnalysisFOS: Computer and information sciencesComputer and Information SciencesScienceIntelligenceSocial SciencesTransportationCriminologyCivil EngineeringSocial NetworkingComputer Science - Computers and SocietyLaw EnforcementSociologyComputers and Society (cs.CY)PsychologyHumansComputer NetworksSocial and Information Networks (cs.SI)Algorithms; Humans; Terrorism; Criminals; Data Analysis; Social NetworkingSettore INF/01 - InformaticaQCognitive PsychologyRBiology and Life SciencesEigenvaluesComputer Science - Social and Information NetworksCriminalsTransportation InfrastructurePoliceRoadsProfessionsAlgebraLinear AlgebraPeople and PlacesPhysical SciencesEngineering and TechnologyCognitive ScienceMedicineLaw and Legal SciencesPopulation GroupingsTerrorismCrimeCriminal Justice SystemMathematicsNetwork AnalysisAlgorithmsResearch ArticleNeurosciencePLoS ONE
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Analyzing big datasets of genomic sequences: fast and scalable collection of k-mer statistics

2019

Abstract Background Distributed approaches based on the MapReduce programming paradigm have started to be proposed in the Bioinformatics domain, due to the large amount of data produced by the next-generation sequencing techniques. However, the use of MapReduce and related Big Data technologies and frameworks (e.g., Apache Hadoop and Spark) does not necessarily produce satisfactory results, in terms of both efficiency and effectiveness. We discuss how the development of distributed and Big Data management technologies has affected the analysis of large datasets of biological sequences. Moreover, we show how the choice of different parameter configurations and the careful engineering of the …

Data AnalysisFOS: Computer and information sciencesTime FactorsTime FactorComputer scienceStatistics as TopicBig dataApache Spark; distributed computing; performance evaluation; k-mer countinglcsh:Computer applications to medicine. Medical informaticsBiochemistryDomain (software engineering)Databases03 medical and health sciences0302 clinical medicineStructural BiologyComputer clusterStatisticsSpark (mathematics)Molecular Biologylcsh:QH301-705.5030304 developmental biology0303 health sciencesGenomeSettore INF/01 - InformaticaBase SequenceNucleic AcidApache Sparkbusiness.industryResearchApache Spark; Distributed computing; k-mer counting; Performance evaluation; Algorithms; Base Sequence; Software; Time Factors; Data Analysis; Databases Nucleic Acid; Genome; Statistics as TopicApplied Mathematicsk-mer countingDistributed computingComputer Science ApplicationsAlgorithmData AnalysiComputer Science - Distributed Parallel and Cluster Computinglcsh:Biology (General)030220 oncology & carcinogenesisScalabilityPerformance evaluationlcsh:R858-859.7Algorithm designDistributed Parallel and Cluster Computing (cs.DC)Databases Nucleic AcidbusinessAlgorithmsSoftware
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Global data on earthworm abundance, biomass, diversity and corresponding environmental properties

2021

Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ec…

Data DescriptorDistribuição GeográficaPlan_S-Compliant-OASoilBiomassbiodiversityDiversityEcologyBiodiversidadeQBiodiversityeliöyhteisötmaaperäeliöstöPE&RCComputer Science ApplicationsMultidisciplinary SciencesBiogeographyinternational1181 Ecology evolutionary biologyEcosystem engineersScience & Technology - Other TopicsStatistics Probability and UncertaintyInformation SystemsStatistics and ProbabilitylierotScienceInvertebradosLibrary and Information Sciences[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil studyEcology and EnvironmentEducationeliömaantiede[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsMinhocaServiço ambientalBIODIVERSITY CHANGELife ScienceEcosystem servicesEarthwormsDatasetsAnimalsSpatial distributionCommunity ecologyOligochaetaLaboratorium voor NematologieEcosystem1172 Environmental sciencesbiogeographyScience & TechnologyLAND-USEBiology and Life SciencesPLATFORMBodemfysica en LandbeheerEcologíaEcossistemabiodiversiteettiSoil Physics and Land ManagementSoloBiologia do Solomaaperäeläimistö570 Life sciences; biologyeartworm ; abundance ; biomass ; diversityLaboratory of Nematology[SDE.BE]Environmental Sciences/Biodiversity and EcologyCOMMUNITIEScommunity ecology
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21ST CENTURY SKILLS IN THE CONTEXT OF LIFE QUALITY

2020

The article addresses comparative qualitative content analysis as a part of the grounded theory research to explore the relationship between English language proficiency of economically active adults and their quality of life. Using comparative qualitative content analysis of the policy documents in respect of lifelong learning as main data collection method, the authors of the article aim to identify the relationship between the 21st century skills and indicators of life quality by comparing the sources that define the 21st century skills and analysing them in the context of the “8+1” dimensions of life quality offered by the European Union. The following research questions have been propo…

Data collection21st century skillsParliamentbusiness.industrymedia_common.quotation_subjectLifelong learningPublic relationsGrounded theoryQuality of lifemedia_common.cataloged_instanceProfiling (information science)SociologyEuropean union21st century skills; adult learning; lifelong learning; the dimensions of life qualitybusinessmedia_commonSOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference
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Industrial Environment Mapping Using Distributed Static 3D Sensor Nodes

2018

This paper presents a system architecture for mapping and real-time monitoring of a relatively large industrial robotic environment of size 10 m × 15 m × 5 m. Six sensor nodes with embedded computing power and local processing of the 3D point clouds are placed close to the ceiling. The system architecture and data processing is based on the Robot Operating System (ROS) and the Point Cloud Library (PCL). The 3D sensors used are the Microsoft Kinect for Xbox One and point cloud data is collected at 20 Hz. A new manual calibration procedure is developed using reflective planes. The specified range of the used sensor is 0.8 m to 4.2 m, while depth data up to 9 m is used in this paper. Despite t…

Data processingComputer scienceReal-time computingPoint cloud0102 computer and information sciences02 engineering and technologyCeiling (cloud)01 natural sciences020202 computer hardware & architecture010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineeringBenchmark (computing)Systems architectureCalibrationMetreReflection mapping2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)
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Analysis of multi-source metabolomic data using joint and individual variation explained (JIVE).

2015

Metabolic profiling is increasingly being used for understanding biological processes but there is no single analytical technique that provides a complete quantitative or qualitative profiling of the metabolome. Data fusion (i.e. joint analysis of data from multiple sources) has the potential to circumvent this issue facilitating knowledge discovery and reliable biomarker identification. Another field of application of data fusion is the simultaneous analysis of metabolomic changes through several biofluids or tissues. However, metabolomics typically deals with large datasets, with hundreds to thousands of variables and the identification of shared and individual factors or structures acros…

Data sourceComputer scienceAnalytical techniqueStatistics as TopicAnalytical chemistryUrinalysisSensor fusioncomputer.software_genreBiochemistryAnalytical ChemistryMultiple dataMetabolomicsKnowledge extractionElectrochemistryEnvironmental ChemistryProfiling (information science)HumansMetabolomicsData miningcomputerSpectroscopyMulti-sourceBlood Chemical AnalysisSoftwareThe Analyst
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Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties – A review

2015

Abstract: Forthcoming superspectral satellite missions dedicated to land monitoring, as well as planned imaging spectrometers, will unleash an unprecedented data stream. The processing requirements for such large data streams involve processing techniques enabling the spatio-temporally explicit quantification of vegetation properties. Typically retrieval must be accurate, robust and fast. Hence, there is a strict requirement to identify next-generation bio-geophysical variable retrieval algorithms which can be molded into an operational processing chain. This paper offers a review of state-of-the-art retrieval methods for quantitative terrestrial bio-geophysical variable extraction using op…

Data streamEconomicsComputer scienceOperational variable retrievalcomputer.software_genreLaboratory of Geo-information Science and Remote SensingMachine learningPhysicalLaboratorium voor Geo-informatiekunde en Remote SensingBio-geophysical variablesComputers in Earth SciencesParametricEngineering (miscellaneous)Parametric statisticsRemote sensingData stream miningPhysicsTransparency (human–computer interaction)VegetationPE&RCNon-parametricHybridAtomic and Molecular Physics and OpticsComputer Science ApplicationsVariable (computer science)SatelliteData miningEngineering sciences. TechnologyRetrievabilitycomputerISPRS Journal of Photogrammetry and Remote Sensing
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Distributed Real-Time Sentiment Analysis for Big Data Social Streams

2014

Big data trend has enforced the data-centric systems to have continuous fast data streams. In recent years, real-time analytics on stream data has formed into a new research field, which aims to answer queries about "what-is-happening-now" with a negligible delay. The real challenge with real-time stream data processing is that it is impossible to store instances of data, and therefore online analytical algorithms are utilized. To perform real-time analytics, pre-processing of data should be performed in a way that only a short summary of stream is stored in main memory. In addition, due to high speed of arrival, average processing time for each instance of data should be in such a way that…

Data streamFOS: Computer and information sciencesComputer Science - Computation and LanguageComputer sciencebusiness.industryData stream miningSentiment analysisBig dataMachine Learning (stat.ML)Databases (cs.DB)Data structurecomputer.software_genreField (computer science)Computer Science - Information RetrievalTree (data structure)Computer Science - DatabasesComputer Science - Distributed Parallel and Cluster ComputingAnalyticsStatistics - Machine LearningData miningDistributed Parallel and Cluster Computing (cs.DC)businesscomputerComputation and Language (cs.CL)Information Retrieval (cs.IR)
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