Search results for " Monitoring"

showing 10 items of 3129 documents

A comparison of three statistical methods for analysing extinction threat status

2013

SUMMARYThe International Union for Conservation of Nature (IUCN) Red List provides a globally-recognized evaluation of the conservation status of species, with the aim of catalysing appropriate conservation action. However, in some parts of the world, species data may be lacking or insufficient to predict risk status. If species with shared ecological or life history characteristics also tend to share their risk of extinction, then ecological or life history characteristics may be used to predict which species may be at risk, although perhaps not yet classified as such by the IUCN. Statistical models may be a means to determine whether there are non-threatened or unclassified species that s…

ExtinctionEcologyHealth Toxicology and MutagenesisStatistical modelManagement Monitoring Policy and LawBiologyLogistic regressionPollutionDiscriminant function analysisAbundance (ecology)Threatened speciesStatisticsConservation statusIUCN Red Listta1181Nature and Landscape ConservationWater Science and TechnologyEnvironmental Conservation
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A rare case of extra-intramedullary dorsal tanycitic ependymoma, radically removed with intraoperative neurophysiological monitoring

2015

Introduction: Tanycitic dorsal extra and intramedullary ependymoma is a rare form of tumor. From the histological point of view, these tumors show several aspects that make difficult the differential diagnosis from schwannomas and pilocytic astrocytomas. Tanycytic variant, often occurs in the thoracic tract of the spinal cord, and it is constituted by tanycites, that are typical elongated and bipolar cells that give to the tumor fibrillary aspects. Tanycitic variant has been recently characterized as a variant of ependymoma, since the 2000 World Health Organization (WHO) system. Case presentation: A 57 years old woman presented with intractable back pain often radiating to the left leg. Neu…

Extramedullary ependymomaTanycitic ependymomaSettore MED/27 - NeurochirurgiaIntraoperative neurophysiological monitoringMedicine (all)Differential diagnosiDifferential diagnosisDifferential diagnosis; Extramedullary ependymoma; Intraoperative neurophysiological monitoring; Tanycitic ependymoma; Medicine (all)
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First Characterization of Novel Silicon Carbide Detectors with Ultra-High Dose Rate Electron Beams for FLASH Radiotherapy

2023

Ultra-high dose rate (UHDR) beams for FLASH radiotherapy present significant dosimetric challenges. Although novel approaches for decreasing or correcting ion recombination in ionization chambers are being proposed, applicability of ionimetric dosimetry to UHDR beams is still under investigation. Solid-state sensors have been recently investigated as a valuable alternative for real-time measurements, especially for relative dosimetry and beam monitoring. Among them, Silicon Carbide (SiC) represents a very promising candidate, compromising between the maturity of Silicon and the robustness of diamond. Its features allow for large area sensors and high electric fields, required to avoid ion r…

FLASH radiotherapy; Silicon Carbide; dosimetry; beam monitoring; UHDRFluid Flow and Transfer Processesbeam monitoringdosimetrySilicon CarbidePhysicsProcess Chemistry and TechnologyGeneral EngineeringSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Computer Science ApplicationsChemistryUHDRFLASH radiotherapyGeneral Materials ScienceHuman medicineInstrumentationApplied Sciences (Switzerland)
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Spectral band selection for vegetation properties retrieval using Gaussian processes regression

2020

Abstract With current and upcoming imaging spectrometers, automated band analysis techniques are needed to enable efficient identification of most informative bands to facilitate optimized processing of spectral data into estimates of biophysical variables. This paper introduces an automated spectral band analysis tool (BAT) based on Gaussian processes regression (GPR) for the spectral analysis of vegetation properties. The GPR-BAT procedure sequentially backwards removes the least contributing band in the regression model for a given variable until only one band is kept. GPR-BAT is implemented within the framework of the free ARTMO's MLRA (machine learning regression algorithms) toolbox, w…

FOS: Computer and information sciences010504 meteorology & atmospheric sciencesComputer Vision and Pattern Recognition (cs.CV)0211 other engineering and technologiesComputer Science - Computer Vision and Pattern Recognition02 engineering and technologyManagement Monitoring Policy and Law01 natural sciencesStatistics - Applicationssymbols.namesakeFOS: Electrical engineering electronic engineering information engineeringApplications (stat.AP)Computers in Earth SciencesGaussian processHyMap021101 geological & geomatics engineering0105 earth and related environmental sciencesEarth-Surface ProcessesRemote sensingGlobal and Planetary ChangeImage and Video Processing (eess.IV)Hyperspectral imagingRegression analysisVegetationSpectral bands15. Life on landElectrical Engineering and Systems Science - Image and Video ProcessingRegressionGeographyGround-penetrating radarsymbolsInternational Journal of Applied Earth Observation and Geoinformation
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Unlocking the potential of deep learning for marine ecology: overview, applications, and outlook

2022

The deep learning revolution is touching all scientific disciplines and corners of our lives as a means of harnessing the power of big data. Marine ecology is no exception. These new methods provide analysis of data from sensors, cameras, and acoustic recorders, even in real time, in ways that are reproducible and rapid. Off-the-shelf algorithms can find, count, and classify species from digital images or video and detect cryptic patterns in noisy data. Using these opportunities requires collaboration across ecological and data science disciplines, which can be challenging to initiate. To facilitate these collaborations and promote the use of deep learning towards ecosystem-based management…

FOS: Computer and information sciences0106 biological sciencesArtificial intelligenceComputer Science - Machine LearningEcologyComputer Science - Artificial IntelligenceComputer Vision and Pattern Recognition (cs.CV)010604 marine biology & hydrobiologyComputer Science - Computer Vision and Pattern RecognitionMarine monitoringMarine bioacousticsAquatic ScienceEcosystem-based managementOceanography010603 evolutionary biology01 natural sciencesMachine Learning (cs.LG)VDP::Teknologi: 500Artificial Intelligence (cs.AI)13. Climate actionMachine learning14. Life underwaterEcology Evolution Behavior and Systematics
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Multilingual Clustering of Streaming News

2018

Clustering news across languages enables efficient media monitoring by aggregating articles from multilingual sources into coherent stories. Doing so in an online setting allows scalable processing of massive news streams. To this end, we describe a novel method for clustering an incoming stream of multilingual documents into monolingual and crosslingual story clusters. Unlike typical clustering approaches that consider a small and known number of labels, we tackle the problem of discovering an ever growing number of cluster labels in an online fashion, using real news datasets in multiple languages. Our method is simple to implement, computationally efficient and produces state-of-the-art …

FOS: Computer and information sciencesComputer Science - Computation and LanguageInformation retrievalComputer scienceInformationSystems_INFORMATIONSTORAGEANDRETRIEVAL02 engineering and technologyClusteringMedia MonitoringComputer Science - Information RetrievalComputingMethodologies_PATTERNRECOGNITIONMultilingual Methods0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingCluster analysisComputation and Language (cs.CL)Information Retrieval (cs.IR)
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Retrieval of aboveground crop nitrogen content with a hybrid machine learning method

2020

Abstract Hyperspectral acquisitions have proven to be the most informative Earth observation data source for the estimation of nitrogen (N) content, which is the main limiting nutrient for plant growth and thus agricultural production. In the past, empirical algorithms have been widely employed to retrieve information on this biochemical plant component from canopy reflectance. However, these approaches do not seek for a cause-effect relationship based on physical laws. Moreover, most studies solely relied on the correlation of chlorophyll content with nitrogen, and thus neglected the fact that most N is bound in proteins. Our study presents a hybrid retrieval method using a physically-base…

FOS: Computer and information sciencesComputer Science - Machine LearningHeteroscedasticity010504 meteorology & atmospheric sciencesMean squared errorEnMAP0211 other engineering and technologiesGaussian processes02 engineering and technologyManagement Monitoring Policy and LawQuantitative Biology - Quantitative Methods01 natural sciencesMachine Learning (cs.LG)symbols.namesakeHomoscedasticityEnMAPAgricultural monitoringComputers in Earth SciencesGaussian processQuantitative Methods (q-bio.QM)021101 geological & geomatics engineering0105 earth and related environmental sciencesEarth-Surface ProcessesMathematicsRemote sensing2. Zero hungerGlobal and Planetary ChangeInversionHyperspectral imagingImaging spectroscopyRadiative transfer modelingRegressionImaging spectroscopyFOS: Biological sciences[SDE]Environmental SciencessymbolsInternational Journal of Applied Earth Observation and Geoinformation
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The IceProd framework: distributed data processing for the IceCube neutrino observatory

2015

IceCube is a one-gigaton instrument located at the geographic South Pole, designed to detect cosmic neutrinos, identify the particle nature of dark matter, and study high-energy neutrinos themselves. Simulation of the IceCube detector and processing of data require a significant amount of computational resources. This paper presents the first detailed description of IceProd, a lightweight distributed management system designed to meet these requirements. It is driven by a central database in order to manage mass production of simulations and analysis of data produced by the IceCube detector. IceProd runs as a separate layer on top of other middleware and can take advantage of a variety of c…

FOS: Computer and information sciencesMonitoringComputer scienceComputer Networks and CommunicationsDistributed computingData managementReal-time computingDistributed managementcomputer.software_genre01 natural sciencesData managementIceCube Neutrino ObservatoryTheoretical Computer ScienceIceCubeArtificial Intelligence0103 physical sciences010306 general physicsData processingData management; Distributed computing; Grid computing; Monitoring010308 nuclear & particles physicsbusiness.industryDistributed computingGrid computingComputer Science - Distributed Parallel and Cluster ComputingHardware and ArchitectureMiddleware (distributed applications)MiddlewareGrid computingParticleDistributed Parallel and Cluster Computing (cs.DC)Neutrinoddc:004businesscomputerSoftware
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A multi-scale area-interaction model for spatio-temporal point patterns

2018

Models for fitting spatio-temporal point processes should incorporate spatio-temporal inhomogeneity and allow for different types of interaction between points (clustering or regularity). This paper proposes an extension of the spatial multi-scale area-interaction model to a spatio-temporal framework. This model allows for interaction between points at different spatio-temporal scales and the inclusion of covariates. We fit the proposed model to varicella cases registered during 2013 in Valencia, Spain. The fitted model indicates small scale clustering and regularity for higher spatio-temporal scales.

FOS: Computer and information sciencesStatistics and ProbabilityScale (ratio)Computer scienceManagement Monitoring Policy and LawMulti-scale area-interaction modelcomputer.software_genreVaricella01 natural sciencesPoint processMethodology (stat.ME)010104 statistics & probability0502 economics and businessStatisticsCovariate60D05 60G55 62M30Point (geometry)0101 mathematicsComputers in Earth SciencesCluster analysisStatistics - Methodology050205 econometrics 05 social sciencesInteraction modelExtension (predicate logic)Gibbs point processesComputingMethodologies_PATTERNRECOGNITIONSpatio-temporal point processesData miningcomputer
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Effect of Short-Term and UV Irradiation Aging on the Behaviour of SBS-Modified Bitumen

2022

To obtain road bitumen with improved temperature and fatigue resistance, polymers and/or rubbers could be added to it. A particularly suitable polymer for bitumen modification is styrene-butadiene-styrene (SBS) copolymer but limited information is available about the ageing behaviour of modified binders. In this work, two neat bitumens, with different penetration grades, and two SBS-modified bitumens, containing different SBS amounts, were selected, and their short-term and UVB ageing behaviour were investigated considering dynamic shear rheometry and Attenuated Total Reflectance-Fourier Transformation InfraRed spectroscopy (ATR-FTIR). Short-time ageing behaviour was investigated performing…

FTIR analysis SBS-modified bitumen short-term ageing UV irradiationSettore ING-IND/22 - Scienza E Tecnologia Dei MaterialiRenewable Energy Sustainability and the EnvironmentGeography Planning and DevelopmentSettore ICAR/04 - Strade Ferrovie Ed AeroportiBuilding and ConstructionManagement Monitoring Policy and LawSBS-modified bitumen; short-term ageing; UV irradiation; FTIR analysis
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