Search results for " Applications"

showing 10 items of 4541 documents

Earth's Surface Displacements from the GPS Time Series

2015

The GPS observations of both Latvian permanent GNSS networks - EUPOS®-Riga and LatPos, have been collected for a period of 8 years - from 2007 to 2014. Local surface displacements have been derived from the obtained coordinate time series eliminating different impact sources. The Bernese software is used for data processing. The EUREF Permanent Network (EPN) stations in the surroundings of Latvia are selected as fiducial stations. The results have shown a positive tendency of vertical displacements in the western part of Latvia - station heights are increasing, and negative velocities are observed in the central and eastern parts. Station vertical velocities are ranging in diapason of 4 mm/…

Data processingGeographybusiness.industryGNSS applicationsGlobal Positioning SystemRangingGeodesyCoordinate timeFiducial markerbusinessPrecise Point PositioningEUREF Permanent NetworkIOP Conference Series: Materials Science and Engineering
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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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Technology-Supported Guidance Models Stimulating the Development of Critical Thinking in Clinical Practice: Protocol for a Mixed Methods Systematic R…

2020

BackgroundCritical thinking is an essential skill that nursing students need to develop. Technological tools have opened new avenues for technology-supported guidance models, but the challenges and facilitators of such guidance models, as well as how they stimulate the development of critical thinking, remain unclear.ObjectiveWe developed a protocol for a mixed methods systematic review to investigate the use of technology-supported guidance models that stimulate the development of critical thinking in nursing education clinical practice.MethodsA convergent integrated design following the Joanna Briggs Institute Manual for Evidence Synthesis will be employed. A pair of authors will select t…

Data transformationComputer applications to medicine. Medical informaticsguidance modelsR858-859.703 medical and health sciences0302 clinical medicineProtocolcritical thinking030212 general & internal medicineNurse educationProtocol (science)Medical education030504 nursingClinical study designnursing educationRGeneral Medicineclinical practiceClinical PracticeCritical thinkingData extractiontechnologyMedicine0305 other medical sciencePsychologyEvidence synthesisJMIR Research Protocols
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Guiding the modeller: organizing and selecting experimental data for single cell models using the CoCoDat database

2003

Collating, organizing and selecting quantitative experimental data are time-consuming tasks necessary for building and constraining biophysically realistic neuronal models. The CoCoDat (Collation of Cortical Data) database has been designed as an advanced environment for storing, organizing and retrieving detailed, uninterpreted quantitative data on morphology, electrophysiology and connectivity from the published literature according to neurophysiological concepts. All experimental data are linked to exact bibliographical references and detailed records of procedures used in the experiments that produced the data. We demonstrate the usefulness of CoCoDat for implementation of an example mo…

DatabaseArtificial IntelligenceComputer sciencePyramidal NeuronCognitive NeuroscienceExperimental dataMODELLERNeurophysiologyLayer (object-oriented design)Barrel cortexcomputer.software_genrecomputerComputer Science ApplicationsNeurocomputing
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PyCellBase, an efficient python package for easy retrieval of biological data from heterogeneous sources.

2019

Background Biological databases and repositories are incrementing in diversity and complexity over the years. This rapid expansion of current and new sources of biological knowledge raises serious problems of data accessibility and integration. To handle the growing necessity of unification, CellBase was created as an integrative solution. CellBase provides a centralized NoSQL database containing biological information from different and heterogeneous sources. Access to this information is done through a RESTful web service API, which provides an efficient interface to the data. Results In this work we present PyCellBase, a Python package that provides programmatic access to the rich RESTfu…

Databases FactualComputer scienceAnnotationBiological databaseRESTfulcomputer.software_genreNoSQLlcsh:Computer applications to medicine. Medical informaticsBiochemistryDatabase03 medical and health sciencesAnnotationUser-Computer Interface0302 clinical medicineInstallationStructural BiologyVariantMolecular Biologylcsh:QH301-705.5030304 developmental biologycomputer.programming_language0303 health sciencesBiological dataDatabaseApplied MathematicsRepositoryComputational BiologyPython (programming language)CellBaseComputer Science Applicationslcsh:Biology (General)Scripting language030220 oncology & carcinogenesislcsh:R858-859.7Web servicecomputerSoftwarePython
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Local dimensionality reduction and supervised learning within natural clusters for biomedical data analysis

2006

Inductive learning systems were successfully applied in a number of medical domains. Nevertheless, the effective use of these systems often requires data preprocessing before applying a learning algorithm. This is especially important for multidimensional heterogeneous data presented by a large number of features of different types. Dimensionality reduction (DR) is one commonly applied approach. The goal of this paper is to study the impact of natural clustering--clustering according to expert domain knowledge--on DR for supervised learning (SL) in the area of antibiotic resistance. We compare several data-mining strategies that apply DR by means of feature extraction or feature selection w…

Databases FactualComputer scienceFeature extractionInformation Storage and RetrievalFeature selectionMachine learningcomputer.software_genreModels BiologicalPattern Recognition AutomatedImmune systemArtificial IntelligenceDrug Resistance BacterialCluster AnalysisHumansComputer SimulationElectrical and Electronic EngineeringRepresentation (mathematics)Cluster analysisCross Infectionbusiness.industryDimensionality reductionSupervised learningGeneral MedicineAnti-Bacterial AgentsComputer Science ApplicationsData pre-processingData miningArtificial intelligenceMultidimensional systemsbusinesscomputerAlgorithmsBiotechnology
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FABC: Retinal Vessel Segmentation Using AdaBoost

2010

This paper presents a method for automated vessel segmentation in retinal images. For each pixel in the field of view of the image, a 41-D feature vector is constructed, encoding information on the local intensity structure, spatial properties, and geometry at multiple scales. An AdaBoost classifier is trained on 789 914 gold standard examples of vessel and nonvessel pixels, then used for classifying previously unseen images. The algorithm was tested on the public digital retinal images for vessel extraction (DRIVE) set, frequently used in the literature and consisting of 40 manually labeled images with gold standard. Results were compared experimentally with those of eight algorithms as we…

Databases FactualComputer scienceFeature vectorFeature extractionNormal DistributionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingModels BiologicalEdge detectionArtificial IntelligenceImage Processing Computer-AssistedHumansSegmentationComputer visionAdaBoostFluorescein AngiographyElectrical and Electronic EngineeringTraining setPixelContextual image classificationSettore INF/01 - Informaticabusiness.industryReproducibility of ResultsRetinal VesselsWavelet transformBayes TheoremPattern recognitionGeneral MedicineImage segmentationComputer Science ApplicationsComputingMethodologies_PATTERNRECOGNITIONROC CurveTest setAdaBoost classifier retinal images vessel segmentationArtificial intelligencebusinessAlgorithmsBiotechnology
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Convolutional Neural Network With Shape Prior Applied to Cardiac MRI Segmentation.

2019

In this paper, we present a novel convolutional neural network architecture to segment images from a series of short-axis cardiac magnetic resonance slices (CMRI). The proposed model is an extension of the U-net that embeds a cardiac shape prior and involves a loss function tailored to the cardiac anatomy. Since the shape prior is computed offline only once, the execution of our model is not limited by its calculation. Our system takes as input raw magnetic resonance images, requires no manual preprocessing or image cropping and is trained to segment the endocardium and epicardium of the left ventricle, the endocardium of the right ventricle, as well as the center of the left ventricle. Wit…

Databases FactualComputer scienceHealth InformaticsImage processingConvolutional neural network030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineHealth Information ManagementSørensen–Dice coefficientImage Processing Computer-AssistedHumansElectrical and Electronic EngineeringArtificial neural networkbusiness.industryMedical image computingCenter (category theory)Pattern recognitionHeartImage segmentationMagnetic Resonance ImagingComputer Science ApplicationsCardiac Imaging TechniquesHausdorff distancecardiovascular systemArtificial intelligenceNeural Networks Computerbusiness030217 neurology & neurosurgeryIEEE journal of biomedical and health informatics
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Increasing the Coverage of Medicinal Chemistry-Relevant Space in Commercial Fragments Screening

2014

Analyzing the chemical space coverage in commercial fragment screening collections revealed the overlap between bioactive medicinal chemistry substructures and rule-of-three compliant fragments is only ∼25%. We recommend including these fragments in fragment screening libraries to maximize confidence in discovering hit matter within known bioactive chemical space, while incorporation of nonoverlapping substructures could offer novel hits in screening libraries. Using principal component analysis, polar and three-dimensional substructures display a higher-than-average enrichment of bioactive compounds, indicating increasing representation of these substructures may be beneficial in fragment …

Databases PharmaceuticalChemistry PharmaceuticalGeneral Chemical EngineeringDrug Evaluation PreclinicalCompound managementLibrary and Information Sciences01 natural sciencesMedicinal chemistryArticle03 medical and health sciencesDrug Discovery030304 developmental biologyPrincipal Component Analysis0303 health sciencesMolecular StructureDrug discoveryChemistryModels CardiovascularComputational BiologyGeneral ChemistryCombinatorial chemistryChemical space0104 chemical sciencesComputer Science Applications010404 medicinal & biomolecular chemistryDatabases ChemicalJournal of Chemical Information and Modeling
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Evaluation of Terra/MODIS atmospheric profiles product (MOD07) over the Iberian Peninsula: a comparison with radiosonde stations

2014

Remote sensing techniques are a useful tool for continuous observation of the Earth at global scale. However, products derived from remote sensing data require a rigorous validation using in situ data. Moderate Resolution Imaging Spectroradiometer (MODIS) is not really a sounding instrument, but it does have 16 infrared bands (bands 20–36 covering the spectral range from 3 µm to 14 µm) that allow the retrieval of temperature and moisture profiles as well as total column integrated magnitudes. In this paper we show the results obtained in the evaluation of MOD07 daytime and nighttime products over the Iberian Peninsula during the decade from 2000 to 2010 using nine radiosonde stations. Altho…

DaytimeMoistureMeteorologyStandard deviationComputer Science Applicationslaw.inventionDepth soundingGeographyDew pointlawRadiosondeGeneral Earth and Planetary SciencesModerate-resolution imaging spectroradiometerSoftwareWater vaporRemote sensingInternational Journal of Digital Earth
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