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Open Research Data
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3D point cloud as a representation of buildings: the Nanotechnology Center and the Auditorium Novum
Open Research DataThe product presents the point cloud in the collection of a three-dimensional database in spatial order as the representations of the Nanotechnology Center and the Auditorium Novum buildings (located on the campus of the Gdańsk University of Technology) acquired in the laser scanning technology. According to its high accuracy and precision of data acquisition...
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3D point cloud as a representation of silo / tank
Open Research DataThe product presents a point cloud in the set of coordinates X Y Z. The data was obtained by terrestrial laser scanning and its processing for the analysis of tanks geometry. The development process indicates the possibility to obtain the reliable results useful for the evaluation of the tank side surfaces geometry.
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Alcohol and drug accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: Offenders under influence of alcohol or drug - driver or pedestrian. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - All accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Child accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: children - drivers, passengers and . vulnerable road user.. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Cyclist accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: Cyclists. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Elderly people accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: elderly people (65+) - drivers, passengers and . vulnerable road user. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Excessive speed accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, cause of accidents: Excessive speed accidents. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Head-on accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, type of accidents: head-on. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Medium to High and high road sections
Open Research DataData contain road sections with the highest number of accidents and victims on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019. Measures used to assess the level of risk is: minimum 4 accidents or 4 seriously injured or fatalities per one kilometer (5 classes: low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Motorcycle and moped accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: motorcyclists and mopeds. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Night accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, time of accidents: Night. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Pedestrian accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: Pedestrians. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Run off road accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, type of accidents: Run off road. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Side-impact accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, type of accidents: Side-impact. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Young drivers accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: young driver offender. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2019 - Municipality areas
Open Research DataData contain the number of accidents, victims, accident costs divided on municipality areas (119 areas) on regional roads (voivodeship roads) in pomorskie voivodeship in 2019. Measures used to assess the level of social risk are (5 classes: low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2019 - Poviat areas
Open Research DataData contain the number of accidents, victims, accident costs divided on poviat areas (16 areas) on regional roads (voivodeship roads) in pomorskie voivodeship in 2019. Measures used to assess the level of social risk are (5 classes low, low to medium, medium, medium to high, high):
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Analysis of spatial changes in the town of Puck with its surroundings in the years 1926, 1940, 1974, 1985, 2000, 2020 on the basis of topographic maps using the BDOT10K database
Open Research DataSpatial changes over time are extremely valuable due to the possibility of modeling forecasts. This dataset shows how Puck has evolved over a specific period of time. Thanks to this presentation of the data set, it is possible to easily recreate the appearance of the city in particular years.
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A New Adaptive Method for the Extraction of Steel Design Structures from an Integrated Point Cloud
Open Research DataA new automatic and adaptive algorithm for edge extraction from a random point cloud was developed and presented herein. The proposed algorithm was tested using real measurement data. The developed algorithm is able to realistically reduce the amount of redundant data and correctly extract stable edges representing the geometric structures of a studied...