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Katalog
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Filtry wybranego katalogu
Wyniki wyszukiwania dla: LOW-RESOURCE LANGUAGE
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Medium to High and high road sections
Dane BadawczeData 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 - All accidents
Dane BadawczeData 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 - Pedestrian accidents
Dane BadawczeData 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 - Young drivers accidents
Dane BadawczeData 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, 2017-2019 - Motorcycle and moped accidents
Dane BadawczeData 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 - Head-on accidents
Dane BadawczeData 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, 2019 - Municipality areas
Dane BadawczeData 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, 2017-2019 - Side-impact accidents
Dane BadawczeData 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 - Run off road accidents
Dane BadawczeData 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, 2019 - Poviat areas
Dane BadawczeData 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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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Elderly people accidents
Dane BadawczeData 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 - Cyclist accidents
Dane BadawczeData 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 - Night accidents
Dane BadawczeData 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 - Excessive speed accidents
Dane BadawczeData 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 - Child accidents
Dane BadawczeData 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 - Alcohol and drug accidents
Dane BadawczeData 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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The aggregation of objects representing Gdańsk district buildings - scale 1:10000
Dane BadawczeThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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Heart rate PPG signals with acceleration captured at wrist during small and moderate body movements
Dane BadawczeHeart rate PPG signals with acceleration captured at wrist during small and moderate body movements
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The aggregation of objects representing buildings in the Kartuzy district - scale 1:10000
Dane BadawczeThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The aggregation of objects representing Gdańsk district buildings - scale 1:25000
Dane BadawczeThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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Herbarium of Division of Marine Biology and Ecology University of Gdańsk (DMBE)
Dane BadawczeHerbarium of Division of Marine Biology and Ecology University of Gdańsk (DMBE) is a research herbarium encompassing specimens of vascular plants and algae hosted by the Laboratory of Marine Plant Ecology at University of Gdańsk, Poland. The aim of Herbarium is to preserve marine plant and algae collections mostly from the Gulf of Gdańsk, but the herbarium...
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The aggregation of objects representing buildings in the Kartuzy district - scale 1:25000
Dane BadawczeThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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An facile Fortran-95 algorithm to simulate complex instabilities in three-dimensional hyperbolic systems
Dane BadawczeIt is well know that the simulation of fractional systems is a difficult task from all points of view. In particular, the computer implementation of numerical algorithms to simulate fractional systems of partial differential equations in three dimensions is a hard task which has no been solved satisfactorily. Here, we provide a Fortran-95 code to solve...
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Tensile test of 1.4307 / X2CrNi18-9 / AISI 304L grade austenitic steel
Dane BadawczeShip structures and their components are build mainly of steel. Hull steel is used to build the hull structure. Some structural elements, such as RSW (Refrigerated See Water) tanks, or LNG (Liquid Natural Gas) tanks - gas transported at temperatures below -162° C, are build from austenitic steels. Austenitic steels have a different microstructure and...
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Tensile test of 1.4541 / X6CrNi18-10 / AISI 321 grade austenitic steel
Dane BadawczeShip structures and their components are build mainly of steel. Hull steel is used to build the hull structure. Some structural elements, such as RSW (Refrigerated See Water) tanks, or LNG (Liquid Natural Gas) tanks - gas transported at temperatures below -162° C, are build from austenitic steels. Austenitic steels have a different microstructure and...
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Tensile test of 1.4571 / X6CrNiMoTi17-12-2 / AISI 316Ti grade austenitic steel
Dane BadawczeShip structures and their components are build mainly of steel. Hull steel is used to build the hull structure. Some structural elements, such as RSW (Refrigerated See Water) tanks, or LNG (Liquid Natural Gas) tanks - gas transported at temperatures below -162° C, are build from austenitic steels. Austenitic steels have a different microstructure and...
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Electrical and noise responses of graphene/AlGaN/GaN field-effect transistor for nitrogen dioxide, teatrahydrofuran, and acetone sensing
Dane BadawczeThis data set consists of raw and modified data concerning current-voltage characteristics and low-frequency noise spectra measured for graphene/AlGaN/GaN field-effect transistor in the ambiance of selected gases (laboratory air, dry and wet synthetic air, nitrogen dioxide, tetrahydrofuran, and acetone). The data show that sensor responses are enhanced...
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Auditory Brainstem Responses recorded employing Audio ABR device
Dane BadawczeThe dataset consists of ABR measurements employing click, burst and speech stimuli. Parameters of the particular stimuli were as follows:
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The aggregation of objects representing Katowice district buildings - scale 1:25000
Dane BadawczeThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The aggregation of objects representing Katowice district buildings - scale 1:10000
Dane BadawczeThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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MODALITY corpus - SPEAKER 35 - COMMANDS C1
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 21 - SEQUENCE S6
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 21 - COMMANDS C5
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 21 - SEQUENCE S4
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 01 - SEQUENCE S2
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 39 - COMMANDS C1
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 01 - SEQUENCE S3
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 01 - COMMANDS C3
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 21 - SEQUENCE S2
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 33 - SEQUENCE S1
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 01 - COMMANDS C2
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 21 - COMMANDS C3
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 01 - SEQUENCE S4
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 01 - SEQUENCE S6
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 21 - SEQUENCE S5
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 01 - COMMANDS C4
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 21 - COMMANDS C4
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 01 - COMMANDS C5
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 21 - SEQUENCE S3
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
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MODALITY corpus - SPEAKER 01 - COMMANDS C6
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...