Search
Filters
total: 975
filtered: 45
Search results for: ACCIDENT PREVENTION
-
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):
-
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):
-
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):
-
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):
-
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):
-
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):
-
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):
-
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):
-
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):
-
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):
-
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):
-
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):
-
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):
-
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):
-
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):
-
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):
-
Nuts 51 (voj. dolnoslaskie). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. dolnoslaskie (Poland, nuts 71).
-
Nuts 81 (voj. lubelskie). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. lubelskie (Poland, nuts 81)
-
Nuts 61 (voj. kujawsko-pomorskie). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. kujawsko-pomorskie (Poland, nuts 61)
-
Nuts 92 (mazowiecki regionalny region). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in mazowiecki regionalny region (Poland, nuts 92)
-
Nuts 43 (voj. lubuskie). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. lubuskie (Poland, nuts 43)
-
Nuts 62 (voj. warminsko-mazurskie). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. warminsko-mazurskie (Poland, nuts 62)
-
Nuts 42 (voj. zachodniopomorskie). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. zachodniopomorskie (Poland, nuts 42)
-
Nuts 52 (voj. opolskie). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. opolskie (Poland, nuts 52)
-
Nuts 22 (voj. slaskie). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. slaskie (Poland, nuts 22)
-
Nuts 71 (voj. lodzkie). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. lodzkie (Poland, nuts 71)
-
Nuts 21 (voj. malopolskie). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. malopolskie (Poland, nuts 21)
-
Nuts 82 (voj. podkarpackie). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. podkarpackie(Poland, nuts 82)
-
Nuts 84 (voj. podlaskie). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. podlaskie (Poland, nuts 84)
-
Nuts 63 (voj. pomorskie). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. pomorskie (Poland, nuts 63)
-
Nuts 41 (voj. wielkopolskie). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. wielkopolskie (Poland, nuts 41)
-
Nuts 91 (woj. warszawski - stoleczny). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in warszawski - stoleczny region (Poland, nuts 91)
-
Nuts 72 (voj. swietokrzyskie). Number of accidents, injuries, seriously Injured and fatalities
Open Research DataThe data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. swietokrzyskie (Poland, nuts 72)
-
Terrestrial Laser Scan and Survey Images - 3D Model - Simulated Car Accident - MP1 - Reigl
Open Research DataDataset description: Raw images from photogrammetric and terresttial laser scaning survey. Object: Simulated Car AccidentLocation: Puck Pomorskie, PolandDrone type: DJI Mavic Pro 1Flight plan: Circle | Point Of InterestTarget Product: 3D ModelDate: 07.07.2017Direct georeferencing: yesMetadata data: Yes/GPSGCP: Yes - some targets on the object are marked...
-
Employment structure by enterprise size in Poland in 2010-2014
Open Research DataMicro, small and medium-sized enterprises employ in total nearly 70% of all employees working in the corporate sector. Micro enterprises play a decisive role in this respect, accounting for nearly 40% of all employees. This dataset contains data showing the structure of the number of employees in enterprises in 2010-2014.
-
SEM images of dewetted gold films
Open Research DataGold nanostructures were prepared on silicon - Si(111) as a substrate. as a result of dewetting process. Thin golds films were deposited using a table-top dc magnetron sputtering coater under pure Ar plasma conditions . The Au target had 99.99% purity, the rate of Au layer deposition was about 0.4 nm·s−1 and the incident power was 32 W. The thickness...
-
Oxidation of silver nanostructures
Open Research DataSilver nanostructures were prepared on Si substrate. Thin Ag films (2 and 6 nm thickness) were deposited using a tabletop dc magnetron sputtering coater (EM SCD 500, Leica) in pure Ar plasma. The Ag target was of 99.99% purity, the rate of layer deposition was about 0.4 nm·s−1 , and the incident power was in the range of 30–40 W. The layer thickness...
-
Comparison of XPS spectra of Ag3d for silver nanostructures and bulk material
Open Research DataAg nanostructures were prepared on borosilicate glass (Corning 1737F) and Si substrates. In both cases, the substrateswere cleaned with acetylacetone and then rinsed in ethanol. Thin Ag films (2 and 6 nm thickness) were deposited using a tabletop dc magnetron sputtering coater (EM SCD 500, Leica) in pure Ar plasma (argon, Air Products 99.999%). The...
-
Rhetoric at school - a selection of the syllabi from the Academic Gymnasium in Gdańsk - transcription and photographs
Open Research DataThe following data set comprises a transcription (in txt and docx formats) and photographs (in jpg format) of the selected records from the Latin-language teaching syllabi termed 'Typus' or 'Catalogus lectionum' (an abbreviated title). Rhetoric is the main thematic criterion behind this choice. Various topics related to rhetoric have been taught not...
-
SEM images of tge gold nanostructures on silicon
Open Research DataAu nanostructures were prepared on Si(111) as a substrate. The substrates (1 × 1 cm2 of area) were cleaned with acetylacetone and then rinsed in ethanol. Thin Au films (with thicknesses in a range of 1.7–5.0 nm) were deposited using a table-top dc magnetron sputtering coater (EM SCD 500, Leica) under pure Ar plasma conditions (Argon, Air Products 99.999%)....
-
Investigation of plasmon resonance in a silver nanoparticles
Open Research DataSilver nanostructures were prepared on borosilicate glass (Corning 1737F) substrates. Thin Ag films (1–9 nm thickness) were deposited using a table-top dc magnetron sputtering coater (EM SCD 500, Leica) in pure Ar plasma (argon, Air Products 99.999%). The Ag target was of 99.99% purity, the rate of layer deposition was about 0.4 nm·s−1, and the incident...
-
Formation of gold anostructures detected by SEM microscope
Open Research DataGold nanostructures were prepared on silicon - Si(111) as a substrate. The substrates (1 × 1 cm2 of area) were cleaned with acetylacetone and then rinsed in ethanol. Thin Au films (with thicknesses in a range of 1.7–5.0 nm) were deposited using a table-top dc magnetron sputtering coater (EM SCD 500, Leica) under pure Ar plasma conditions (Argon, Air...
-
Wernsdorf - a biography of an 18th century scholar - transcription, photographs and partial translation
Open Research DataThe data set contains the transcription of a large passage of the Latin biography of the eighteenth-century philologist and theologian Gottlieb Wernsdorf (1717-1774), as well as photos of the entire print. A translation from Latin into English and Polish was added to the data set as well (that is, excerpts on the education of both Gottlieb himself,...
-
Simulations of wave propagation and attenuation in fields of colliding ice floes
Open Research DataThis dataset contains results of numerical smulations of sea ice-wave interactions, corresponding to laboratory experiments conducted at the Large Ice Model Basin (LIMB) at the Hamburg Ship Model Basin (HSVA) as part of the LS-WICE ("Loads on Structure and Waves in Ice"; https://zenodo.org/record/1067170#.XrLt_dhpxhE) project. THe simulations were conducted...
-
Plasmon resonance in a TiO2-Au NPs structures
Open Research DataInvestigated structures were deposited on a pre cleaned Corning 1737 glass substrates, which provided flat optical transmission characteristics and high transmission coefficient in a visible light range. Plasmonic nanostructures were formed as a result of thermal annealing. For gold films with thickness of 2.8 nm depiction a table-top dc magnetron sputtering...