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1,308 results for “Vehicle”
[5G-IANA] UC1 - Vehicle position, speed and angle
<p>Linear and angular movement commands that allow to know position, speed and angle of the vehicle. </p>
SPARCS_WP4_Leipzig_City_Total amount of vehicles in public transport
<p>The number of vehicles used in the city of Leipzig's public transport with annually captured data covering the period between 2016 and 2023.</p>
SPARCS_WP4_Leipzig_City_Total amount of motorised vehicles
<p>The number of motorised vehicles in the city of Leipzig with annually captured data covering the period between 2017 and 2023.</p>
SPARCS_WP4_Leipzig_City_Percentage of people going to work using an own combustion vehicle
<p>The percentage of people in the city of Leipzig who commute to and from their workplace using an own combustion vehicle; data captured annually covering the period from 2016 to 2022</p>
SPARCS-WP3_Espoo_City_Citizens going to work using personal vehicle
<p>Percentage of people using personal vehicle for commuting.</p>
Electric vehicle synthetic trips
<p>This dataset contains four files:</p> <p>- a trip diary that was synthesized for electric vehicle drivers in the area of Westfield Shopping Center, London.</p> <p>- a trip diary that was synthesized for electric vehicle drivers in the area of Canary Wharf, London.</p> <p>- A set of EV charging packages that were used to optimize charging prices for a Charging Service Provider</p> <p>- A readme file with details and variable definitions for the contained datasets</p> <p>The original trip sample that was used for the synthesis of the two travel diaries is part of the London Travel Demand Survey (LTDS) - https://tfl.gov.uk/corporate/about-tfl/how-we-work/planning-for-the-future/consultations-and-surveys</p>
Replication Package: "Simulation-based Test Case Generation for Unmanned Aerial Vehicles in the Neighborhood of Real Flights"
<p><strong>Structure:</strong></p> <p>For each of the experiments, conducted for our Research questions, we include the following:</p> <p>1. An spreadsheet file containing the aggregated experiment results</p> <ul> <li>first tab: aggregated data for all the 10 repetitions, and metrics reported in the paper</li> <li>raw logs for each of 10 repetitions in separate tabs</li> </ul> <p>2. Experiment summary for each of the 10 repetitions</p> <ul> <li>plots of the evaluated solutions at each iteration, and their fitness values</li> <li>the plot of the overall progress of the fitness values over iterations</li> <li>the raw log containing the details of computations for each iteration</li> </ul> <p>3. Experiment simulation logs (raw simulation outputs)</p> <ul> <li>'.ulg' flight logs of the solutions evaluated at each iteration ( 'n' parallel simulations at each iteration)</li> <li>only the repetition with the best final result is included. We exclude the other repetitions since the total space needed is too large (more than 200 GB).</li> </ul>
Dataset of a project entitled "Knowledge of traffic signs among vehicle drivers of Bangladesh"
<p>Road traffic accidents remain a significant public health concern globally, causing a staggering number of fatalities and injuries annually. Our study delves into the knowledge and perceptions of traffic signs among bus drivers in Bangladesh, a country witnessing a notable surge in economic growth and urbanization, leading to increased motorization and road accidents. The research examines the level of traffic sign knowledge and perceptions among 300 licensed bus drivers using a cross-sectional survey approach. The results provide insights regarding the driver's understanding and shed light on key factors contributing to comprehension levels, including age, education, and training.</p>
Unidentified Agriculture Vehicle
This is one of several cool vehicles laying around in my neighborhood. I have fotoscanned it with my DLSR (Canon 70D with 20mm lens), then used Reality Capture, Instant Meshes and Blender to create it. Source: Objaverse 1.0 / Sketchfab
Data for Near-Surface Characterization Using Classified Vehicle-Induced Surface Waves from DAS
<p>In this study, we characterize surface waves generated by vehicles of varying sizes and speeds to provide insights into accurate and efficient near-surface imaging using vehicle-induced DAS data. We employ a specialized Kalman filter algorithm to track vehicle locations and classify them into lightweight, midweight, and heavyweight based on the maximum amplitudes of quasi-static DAS records. Vehicles are also classified by their traveling speed (slow, medium, and fast) using their arrival times at DAS channels. Virtual shot gathers for the same class of vehicles are constructed from their surface wave windows selected using the tracked vehicle trajectories. We analyze the dispersion of the phase velocity to investigate the influence of vehicle characteristics on the induced surface waves.</p> <p><code>Put these pickle files into '/das_diff_veh/data/sw_data/' and run the scripts at https://github.com/jingxiaoliu/das_diff_veh</code></p> <p>If you found this useful, please cite our papers:</p> <blockquote> <p>[1] Liu, J., Li, H., Yuan, S., Noh, H. Y., & Biondi, B. (2024). Characterizing Vehicle-Induced Distributed Acoustic Sensing Signals for Accurate Urban Near-Surface Imaging. <em>arXiv preprint arXiv:2408.14320</em>.</p> <p>[2] Yuan, S., Liu, J., Noh, H. Y., Clapp, R., & Biondi, B. (2024). Using vehicle‐induced DAS signals for near‐surface characterization with high spatiotemporal resolution. <em>Journal of Geophysical Research: Solid Earth</em>, <em>129</em>(4), e2023JB028033.</p> <p>[3] Liu, J., Yuan, S., Dong, Y., Biondi, B., & Noh, H. Y. (2023). TelecomTM: A fine-grained and ubiquitous traffic monitoring system using pre-existing telecommunication fiber-optic cables as sensors. <em>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies</em>, <em>7</em>(2), 1-24.</p> </blockquote>
Clinical Validation of AI-powered Smart Vehicle Assisted Gait Training in Neurodegenerative Disorders
ClinicalTrials.gov study NCT07230366. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Effect of an Exploratory Vehicle on Meibomian Gland Dysfunction in Patients With Demodex
ClinicalTrials.gov study NCT06054217. IPD Sharing: NO. Countries: 1. Publications: 0.
EMDR vs. PC For Motor Vehicle Accident Trauma
ClinicalTrials.gov study NCT03271359. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Phase 3 Study Evaluating Efficacy and Safety of DSC127 Compared With Vehicle and With Standard-of-care in Diabetic Foot Ulcers
ClinicalTrials.gov study NCT01849965. IPD Sharing: Not stated. Countries: 4. Publications: 0.
Efficacy and Safety of Fucicort® Lipid Cream Compared to Combination Treatment With Fucidin® Cream Followed by Betamethasone (Lianbang Beisong®) Cream and Fucicort® Lipid Cream Vehicle in Clinically I
ClinicalTrials.gov study NCT03395132. IPD Sharing: NO. Countries: 1. Publications: 0.
Safety and Efficacy Study Comparing AM001 Cream, 7.5% to Vehicle Cream in the Treatment of Plaque Psoriasis
ClinicalTrials.gov study NCT03005964. IPD Sharing: NO. Countries: 1. Publications: 0.
Double-Blind, Multicenter, Study Comparing the Efficacy and Safety of OMS103HP With Vehicle Irrigation Solution in Subjects Undergoing Meniscectomy
ClinicalTrials.gov study NCT00624845. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Double-Masked Comparison of FID 123320 Ophthalmic Solution to Vehicle for the Reduction of Ocular Redness
ClinicalTrials.gov study NCT06444529. IPD Sharing: NO. Countries: 1. Publications: 0.
An Exploratory Psoriasis Plaque Test Study With Different Dose Combinations of Calcipotriol Plus Betamethasone Dipropionate in the Daivobet® Gel Vehicle in Psoriasis Vulgaris
ClinicalTrials.gov study NCT01837576. IPD Sharing: NO. Countries: 1. Publications: 0.
The Effect of Electronic Cigarette (ECIG) Liquid Vehicles on ECIG Acute Effects
ClinicalTrials.gov study NCT02500615. IPD Sharing: Not stated. Countries: 1. Publications: 0.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.