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StreetSurfaceVis: a dataset of crowdsourced street-level imagery annotated by road surface type and quality.
Sci Data
January 2025
Hochschule für Technik und Wirtschaft Berlin (HTW Berlin), Berlin, Germany.
Road unevenness significantly impacts the safety and comfort of traffic participants, especially vulnerable groups such as cyclists and wheelchair users. To train models for comprehensive road surface assessments, we introduce StreetSurfaceVis, a novel dataset comprising 9,122 street-level images mostly from Germany collected from a crowdsourcing platform and manually annotated by road surface type and quality. By crafting a heterogeneous dataset, we aim to enable robust models that maintain high accuracy across diverse image sources.
View Article and Find Full Text PDFEMS3D-KITTI: Synthetic 3D dataset in KITTI format with a fair distribution of Emergency Medical Services vehicles for autodrive AI model training.
Data Brief
February 2025
North Carolina Agricultural and Technical State University, 1601 E Market St, Greensboro, NC 27411, United States.
Contemporary research in 3D object detection for autonomous driving primarily focuses on identifying standard entities like vehicles and pedestrians. However, the need for large, precisely labelled datasets limits the detection of specialized and less common objects, such as Emergency Medical Service (EMS) and law enforcement vehicles. To address this, we leveraged the Car Learning to Act (CARLA) simulator to generate and fairly distribute rare EMS vehicles, automatically labelling these objects in 3D point cloud data.
View Article and Find Full Text PDFThis study introduces a high-resolution wind nowcasting model designed for aviation applications at Madeira International Airport, a location known for its complex wind patterns. By using data from a network of six meteorological stations and deep learning techniques, the produced model is capable of predicting wind speed and direction up to 30-minute ahead with 1-minute temporal resolution. The optimized architecture demonstrated robust predictive performance across all forecast horizons.
View Article and Find Full Text PDFStudy on the effect of water content on physical properties of bentonite.
PLoS One
January 2025
Lecturer College of Civil and Traffic Engineering, Henan University of Urban Construction, Ping Dingshan, China.
Moisture content profoundly influences the engineering properties of expansive soil, a critical consideration in various geotechnical applications. This study delves into the intricate relationship between water content and the physical properties of bentonite, a key constituent of expansive soil. Through a comprehensive analysis encompassing fundamental physical properties, rheological characteristics, permeability behavior, and microscopic features, we elucidate the complex interplay between water content and bentonite behavior.
View Article and Find Full Text PDFA hydrothermal coupling model for permafrost subgrade considering temperature gradient and its application.
Sci Rep
January 2025
Department of Mining and Geological Engineering, University of Arizona, Tucson, AZ, 85721, USA.
The thermodynamic properties of frozen soil depend on its temperature state and ice content. Additionally, the permeability coefficient significantly affects both the temperature distribution and water movement. In this study, the dynamic variation of soil permeability coefficient with temperature is considered, the permeability coefficient is defined as a piecewise function with temperature as independent variable, and the hydrothermal coupling equation is established.
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