Search results for "Event data"

showing 10 items of 10 documents

How important is culture to understand political protest?

2021

Abstract The literature considers nonviolent protests among the most important predictors of transitions towards democracy and democratic reforms. This study addresses the conditionsmaking countries more likely to experience nonviolent instead of violent forms of protest. While the literature emphasizes economic and political predictors of protest at the country level, we expand the study of nonviolent-vs-violent protest by incorporating cultural predictors. To do so, we use a newly developed time-pooled cross-sectional database covering an established set of orientations from the World Values Survey, known as “emancipative values”. Estimating the prevalence of these values at the country l…

Persistence (psychology)Economics and EconometricsSociology and Political Sciencemedia_common.quotation_subjectGeography Planning and DevelopmentCulturePoliticsBuilding and ConstructionDevelopmentDemocracyPoliticsCountry levelEvent dataPolitical sciencePolitical economyPolitical protestWorld Values Survey/dk/atira/pure/core/keywords/549305769Set (psychology)Emancipative valuesmedia_common
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A framework for vertex reconstruction in the ATLAS experiment at LHC

2010

In anticipation of the first LHC data to come, a considerable effort has been devoted to ensure the efficient reconstruction of vertices in the ATLAS detector. This includes the reconstruction of photon conversions, long lived particles, secondary vertices in jets as well as finding and fitting of primary vertices. The implementation of the corresponding algorithms requires a modular design based on the use of abstract interfaces and a common Event Data Model. An enhanced software framework addressing various physics applications of vertex reconstruction has been developed in the ATLAS experiment. Presented in this paper are the general principles of this framework. A particular emphasis is…

HistoryTheoretical computer scienceLarge Hadron Collider010308 nuclear & particles physicsComputer scienceAtlas detectorbusiness.industryATLAS experimentComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONModular designcomputer.software_genre01 natural sciencesComputer Science ApplicationsEducationComputational scienceVertex (geometry)Software frameworkEvent data0103 physical sciences010306 general physicsbusinesscomputerImplementationComputingMethodologies_COMPUTERGRAPHICSJournal of Physics: Conference Series
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Biodiversity surveys of grassland and coastal habitats in 2021 as a documentation of pre-war status in southern Ukraine

2023

This paper presents two sampling-event datasets with occurrences of vascular plants, bryophytes and lichens collected in May-June 2021 in southern Ukraine. We aimed to collect high-quality biodiversity data in an understudied region and contribute it to international databases and networks. The study was carried out during the 15th Eurasian Dry Grassland Group (EDGG) Field Workshop in southern Ukraine and the Dark Diversity Network (DarkDivNet) sampling in the Kamianska Sich National Nature Park. By chance, these datasets were collected shortly before the major escalation of the Russian invasion in Ukraine. Surveyed areas in Kherson and Mykolaiv Regions, including established monitoring plo…

floraEcologybryophytesoccurrence dataSettore BIO/03 - Botanica Ambientale E Applicatasampling-event datavascular plantsdry grasslandslichenssteppeEcology Evolution Behavior and Systematics
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On the use of innovative post-event data for reducing uncertainty in calibrating flood propagation models

2013

Hydraulic models for flood propagation description are an essential tool in many fields and are used, for example, for flood hazard and risk assessments, evaluation of flood control measures, etc. However, the calibration of these models is still underdeveloped in contrast to other models like e.g. hydrological models essentially for lacking of specific data, because extreme flood events occur rarely and very rarely are monitored. Very often calibration data, when available, consist of water depths measure in some scattered points. For an inundation event occurred on November 2011 in Sicily, new sources of data were available due to the availability of many videos recorded by ‘common’ peopl…

Settore ICAR/02 - Costruzioni Idrauliche E Marittime E Idrologiaflood propagation post-event data hydraulic model
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A Time-to-Event Model for Acute Kidney Injury after Reduced-Intensity Conditioning Stem Cell Transplantation Using a Tacrolimus- and Sirolimus-based …

2017

There is a paucity of data evaluating acute kidney injury (AKI) incidence and its relationship with the tacrolimus-sirolimus (Tac-Sir) concentrations in the setting of reduced-intensity conditioning (RIC) after allogeneic stem cell transplantation (allo-HSCT). This multicenter retrospective study evaluated risk factors of AKI defined by 2 classification systems, Kidney Disease Improving Global Outcome (KDIGO) score and "Grade 0-3 staging," in 186 consecutive RIC allo-HSCT recipients with Tac-Sir as graft-versus-host disease prophylaxis. Conditioning regimens consisted of fludarabine and busulfan (n = 53); melphalan (n = 83); or a combination of thiotepa, fludarabine, and busulfan (n = 50). …

MelphalanAdultMalemedicine.medical_specialtyTransplantation ConditioningUrologyReduced intensity conditioningGraft vs Host DiseaseThioTEPAurologic and male genital diseasesTacrolimus03 medical and health sciencesYoung Adult0302 clinical medicineParametric modeling of time-to-event dataRisk Factorshemic and lymphatic diseasesTime-to-event analysisMedicineHumansCumulative incidenceAgedRetrospective StudiesSirolimusTransplantationbusiness.industryAcute kidney injuryHematopoietic Stem Cell TransplantationHematologyAcute Kidney InjuryMiddle Agedmedicine.diseaseFludarabineSurgeryAcute kidney injuryAllogeneic stem cell transplantationTransplantationsurgical procedures operative030220 oncology & carcinogenesisFemalebusinessBusulfan030215 immunologymedicine.drugKidney disease
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Frequentist and Bayesian approaches for a joint model for prostate cancer risk and longitudinal prostate-specific antigen data

2015

The paper describes the use of frequentist and Bayesian shared-parameter joint models of longitudinal measurements of prostate-specific antigen (PSA) and the risk of prostate cancer (PCa). The motivating dataset corresponds to the screening arm of the Spanish branch of the European Randomized Screening for Prostate Cancer study. The results show that PSA is highly associated with the risk of being diagnosed with PCa and that there is an age-varying effect of PSA on PCa risk. Both the frequentist and Bayesian paradigms produced very close parameter estimates and subsequent 95% confidence and credibility intervals. Dynamic estimations of disease-free probabilities obtained using Bayesian infe…

Statistics and ProbabilityPREDICTIONBayesian probabilityurologic and male genital diseasesBayesian inferenceGeneralized linear mixed modelPSAProstate cancerLATENT CLASS MODELSAnàlisi de supervivència (Biometria)Frequentist inference62N01Statisticsprostate cancer screeningSurvival analysis (Biometry)FAILUREMedicineProstate cancer riskTO-EVENT DATAbusiness.industryjoint modelsMORTALITYDISEASE PROGRESSIONmedicine.diseaselinear mixed modelsTIMEProstate-specific antigenProstate cancer screeningshared-parameter models:Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC]62P10SURVIVALStatistics Probability and Uncertaintyrelative risk modelsFOLLOW-UPbusinessJournal of Applied Statistics
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Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data

2020

The statistical analysis of the information generated by medical follow-up is a very important challenge in the field of personalized medicine. As the evolutionary course of a patient's disease progresses, his/her medical follow-up generates more and more information that should be processed immediately in order to review and update his/her prognosis and treatment. Hence, we focus on this update process through sequential inference methods for joint models of longitudinal and time-to-event data from a Bayesian perspective. More specifically, we propose the use of sequential Monte Carlo (SMC) methods for static parameter joint models with the intention of reducing computational time in each…

Statistics and ProbabilityComputer sciencebusiness.industryBayesian probabilitySequential monte carlo methodsMachine learningcomputer.software_genre01 natural sciencesField (computer science)010104 statistics & probability03 medical and health sciences0302 clinical medicineEvent data030220 oncology & carcinogenesisStatistical analysisPersonalized medicineArtificial intelligence0101 mathematicsStatistics Probability and UncertaintybusinessJoint (audio engineering)CartographycomputerStatistical Modelling
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Search for new physics using QUAERO: A general interface to D0 Event data

2001

We describe Quaero, a method that i) enables the automatic optimization of searches for physics beyond the standard model, and ii) provides a mechanism for making high energy collider data generally available. We apply Quaero to searches for standard model WW, ZZ, and ttbar production, and to searches for these objects produced through a new heavy resonance. Through this interface, we make three data sets collected by the D0 experiment at sqrt(s)=1.8 TeV publicly available.

PhysicsHigh energyInformation retrieval010308 nuclear & particles physicsInterface (Java)Physics beyond the Standard ModelGeneral Physics and AstronomyFOS: Physical sciencesQ codeD0 experiment01 natural scienceslaw.inventionHigh Energy Physics - ExperimentHigh Energy Physics - Experiment (hep-ex)Event datalawExperimental High Energy Physics0103 physical sciencesComputingMethodologies_DOCUMENTANDTEXTPROCESSING[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]High Energy Physics::ExperimentStatistical physics010306 general physicsColliderStandard model (cryptography)Physical Review Letters
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Background subtraction and peak search from threefold gamma event data

1990

Abstract A method for subtracting background from triple-coincidence γ events is presented. In our data set it was used to remove 40% of the noise without affecting photopeaks with intensity of >18 counts. An example of performance of Ward's clustering algorithm applied to three-dimensional photopeak searching is also presented. Several standard clustering algorithms were found to be applicable only to background-subtracted data.

Data setPhysicsNuclear and High Energy PhysicsBackground subtractionNoiseEvent databusiness.industryPattern recognitionArtificial intelligenceCluster analysisbusinessInstrumentationIntensity (physics)Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
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Less Data Same Information for Event-Based Sensors: A Bioinspired Filtering and Data Reduction Algorithm

2018

Sensors provide data which need to be processed after acquisition to remove noise and extract relevant information. When the sensor is a network node and acquired data are to be transmitted to other nodes (e.g., through Ethernet), the amount of generated data from multiple nodes can overload the communication channel. The reduction of generated data implies the possibility of lower hardware requirements and less power consumption for the hardware devices. This work proposes a filtering algorithm (LDSI&mdash

bioinspired event filteringComputer sciencedynamic vision sensor02 engineering and technologylcsh:Chemical technology01 natural sciencesBiochemistryArticleAnalytical ChemistryReduction (complexity)0202 electrical engineering electronic engineering information engineeringneuromorphic systemslcsh:TP1-1185Electrical and Electronic EngineeringEnginyeria DissenyInstrumentationEnginyeria elèctricaEvent (computing)Noise (signal processing)010401 analytical chemistryFilter (signal processing)Atomic and Molecular Physics and Optics0104 chemical sciencesevent data reductionFPGA implementationspike-basedLookup table020201 artificial intelligence & image processingevent-based sensorsAlgorithmData reductionSensors
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