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5 results for “WVC”
Wildlife–vehicle collisions (WVC) on interurban roads in Spain (2016-2021)
<p>CSV that contains 1.000 records of wildlife–vehicle collisions (WVC) on interurban roads in Spain between 2016 and 2021. If you are interested in the whole country dataset, please do not hesitate to <strong>contact me and I will forward it to you</strong>. </p> <p>Data source of each WVC record is the Spanish General Directorate of Traffic (DGT), but the dataset has been enhanced by the integration of other sources: OpenStreetMap (OSM), Global Biodiversity Information Facility (GBIF), the National Geographic Institute of Spain (IGN), State Meteorological Agency (AEMET).Therefore, each record describes an accident by the following fields:</p> <p>• <strong>id_num </strong>(int8): the unique identifier for an accident.<br> • <strong>ind_accda </strong>(int8): a binary variable for property damages involved or not (encoded).<br> • <strong>nombre_ind_accd </strong>(str): a statement for property damages involved or not (decoded).<br> • <strong>ind_acciv </strong>(int8): a binary variable for personal damages involved or not (encoded).<br> • <strong>nombre_ind_acciv </strong>(str): a statement for personal damages involved or not (decoded).<br> • <strong>total_mu30df </strong>(int8): the total number of deaths from the accident.<br> • <strong>total_hg30df </strong>(int8): the total number of injured with hospitalization from the accident.<br> • <strong>total_hl30df </strong>(int8): the total number of injured without hospitalization from the accident.<br> • <strong>fecha_accidente </strong>(date): the reported date of the collision, following ISO 8601 date-time standard. <br> • <strong>hora_accidente </strong>(str): the reported hour of the collision in 24-hour notation. <br> • <strong>mes_1f </strong>(int8): the month as integer of the event date (encoded).<br> • <strong>nombre_mes </strong>(str): the month name of the event date (decoded).<br> • <strong>anyo </strong>(int8): the four-digit year of the event date.<br> • <strong>ccaa_1f </strong>(int8): the autonomous region code from INE where accident is registered (encoded).<br> • <strong>nombre_ccaa </strong>(str): the name of the autonomous region where accident is registered (decoded).<br> • <strong>provincia_1f </strong>(int8): the province code from INE where the accident is registered (encoded).<br> • <strong>nombre_provincia </strong>(str): the province name where the accident is registered (decoded).<br> • <strong>cod_municipio </strong>(int8): the municipality code from INE where the accident is registered (encoded).<br> • <strong>nombre_municipio </strong>(str): the municipality name where the accident is registered (decoded).<br> • <strong>carretera </strong>(str): the road attending to the national road numbering system in Spain where the accident is located.<br> • <strong>km </strong>(float): the kilometre point of the road where the accident is located.<br> • <strong>sentido_1f </strong>(int8): the vehicle’s direction of traffic reported as integer when the accident occurred (encoded).<br> • <strong>nombre_sentido </strong>(str): the vehicle’s direction of traffic reported when the accident occurred (decoded).<br> • <strong>tipo_via_3f </strong>(int8): the type of road as integer attending to the project road classification (encoded).<br> • <strong>nombre_tipo_via </strong>(str): the type of road description attending to the project road classification (decoded).<br> • <strong>titularidad_via_2f </strong>(int8): the road ownership type as integer (encoded).<br> • <strong>nombre_titularidad_via </strong>(str): the road ownership type description (decoded).<br> • <strong>tipo_animal_1f </strong>(int8): the animal species involved in the accident as integer (encoded).<br> • <strong>nombre_tipo_animal_1f </strong>(str): the animal species name involved in the accident (decoded).<br> • <strong>tipo_animal_2f </strong>(int8): the reported animal type of breeding as integer (encoded).<br> • <strong>nombre_tipo_animal_2f </strong>(str): the type of animal breeding description (decoded).<br> • <strong>longitud </strong>(float): the length of the accident location coordinate in decimal degrees.<br> • <strong>latitud </strong>(float): the latitude of the accident location coordinate in decimal degrees.<br> • <strong>geom </strong>(geometry): geometry from latitude and longitude position. Developed for this project.<br> • <strong>dia_semana </strong>(int8): the integer day of the week when the accident occurred (encoded).<br> • <strong>nombre_dia_semana </strong>(str): the name of the day when the accident occurred (decoded).<br> • <strong>tipo_dia </strong>(str): the category name of the day type to separate weekday from weekend (decoded).<br> • <strong>parte_dia </strong>(str): the part name of the day when the accident is registered including day, night and the transitions.<br> • <strong>luna </strong>(int8): the portion of illuminated moon surface represented as an integer value from 0 to 100.<br> • <strong>prec </strong>(float): the daily rainfall measurement of the event day based on pluviometric days.<br> • <strong>tmin </strong>(float): the minimum temperature in Celsius of the event day.<br> • <strong>tmed </strong>(float): the average temperature in Celsius of the event day.<br> • <strong>tmax</strong> (float): the maximum temperature in Celsius of the event day.<br> • <strong>sol </strong>(float): the accumulated sun hours of the event day.<br> • <strong>uso_suelo </strong>(str): the main land usage of the accident area.<br> • <strong>altitud </strong>(float): the altitude in meters above sea level.<br> • <strong>pendiente </strong>(float): the slope median value of a 30 meters buffer around the accident location.<br> • <strong>taxonkey</strong> (str): a taxon key from the GBIF backbone.<br> • <strong>imd_total </strong>(float): the average daily traffic intensity of the accident year.<br> • <strong>maxspeed </strong>(int): the maximum speed of the road section where the reported collision.</p> <p>The context is the Final Master's Degree Project 'Analysis and Predictive Modelling of Wildlife–Vehicle Collision on Interurban Roads in Spain' (Data Science Master’s Degree of Universitat Oberta de Catalunya - UOC).</p> <p>This dataset is the output of the wildlife–vehicle collision analysis and the <a href="https://github.com/alba620/analisis-prediccion-accidentes-trafico-animales">code repository</a> is available on GitHub.</p>
PAN Wikipedia Vandalism Corpus 2010 (PAN-WVC-10)
<p>The PAN Wikipedia Vvandalism Ccorpus 2010 (PAN-WVC-10) is a corpus for the evaluation of automatic vandalism detectors for Wikipedia. For research purposes the corpus can be used free of charge.</p> <p>This corpus is supplemented by the <a href="https://doi.org/10.5281/zenodo.3342157">PAN-WVC-11</a>, which features additional edits in English, Spanish and German. Both corpora should be used to get more representative results.</p> <p>As part of our research on automatic vandalism detection we have compiled a corpus of vandalism cases found in Wikipedia. The corpus compiles 32452 edits on 28468 Wikipedia articles, among which 2391 vandalism edits have been identified. To annotate the corpus we have used Amazon's Mechanical Turk; 753 workers have been recruited who cast more than 150000 votes on the edits, so that each edit was reviewed by at least 3 annotators. The achieved level of agreement was analyzed in order to label an edit as "regular" or "vandalism."</p>
Webis Wikipedia Vandalism Corpus (Webis-WVC-07)
<p>This corpus is outdated. Please use its successors <a href="https://doi.org/10.5281/zenodo.3341488">PAN-WVC-10</a> and <a href="https://doi.org/10.5281/zenodo.3342157">PAN-WVC-11</a>.</p> <p>The Webis Wikipedia Vandalism Corpus (Webis-WVC-07) is a corpus for the evaluation of automatic vandalism detection algorithms for Wikipedia. For research purposes the corpus can be used free of charge.</p> <p>The corpus is the first standardized test collection for the comparison of vandalism detection algorithms. It comprises 940 edits from which 301 are marked as vandalism by human evaluators.</p>
PAN Wikipedia Vandalism Corpus 2011 (PAN-WVC-11)
<p>The PAN Wikipedia Vandalism Corpus 2011 (PAN-WVC-11) is a corpus for the evaluation of automatic vandalism detectors for Wikipedia. For research purposes the corpus can be used free of charge.</p> <p>This corpus supplements the <a href="https://doi.org/10.5281/zenodo.3341488">PAN-WVC-10</a>, which features only English edits. Both corpora should be used to get more representative results.</p> <p>The corpus compiles 29949 edits on 24351 Wikipedia articles, among which 2813 vandalism edits have been identified. The corpus features 9985 English edits, 9990 German edits, and 9974 Spanish edits. To annotate the corpus we have used Amazon's Mechanical Turk; each edit was presented to a number of annotators who were asked to decide whether it is vandalism or regular, and the agreement of the annotators was analyzed in order to label an edit.</p>
Outcome of SBO With Calcium Silicate Sealer vs WVC With Resin Based Sealer
ClinicalTrials.gov study NCT04753138. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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