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68 results for “bike”
BIKE Key-Recovery: Combining Power Consumption Analysis and Information-Set Decoding
<p>Data used in the paper: "BIKE Key-Recovery: Combining Power Consumption Analysis and Information-Set Decoding". The paper has been accepted at <a href="https://sulab-sever.u-aizu.ac.jp/ACNS2023/">ACNS-2023</a>.</p> <p>The available dataset contains a file with a few power consumption curves taken from a Cortex-M4 (STM32F4) on a CW308 board.</p> <p>The file is a numpy array stored using the np.save API.<br> The file can be directly used for running the notebooks provided in the <a href="https://github.com/benoitgerard/sca-bike">publication github</a>.</p>
bike
<p>This data contains the “bike” example from Automatically finding the control variables for complex system behavior, Gregory Gay, Tim Menzies, Misty Davies, Karen Gundy-Burlet , Automated Software Engineering May 2010.</p> <p>Contributed by Misty Davies, NASA AMES, misty.davies AT gmail.com</p> <p>The last two columns are derived from the others. The second last column is the noise (variance) on the power and should be minimized. The last column shows a cluster number for each row (and these clusters were generated via an unsupervised learning, working on all columns except the last two).</p>
Model output from 'Modelling the circular economy potential of micromobility: A Finnish case study for e-scooters and e-bikes'
<p>These two files include the results for e-scooters and e-bikes. The dynamics of the BAU scenario is shown in the first few columns, then follow the sensitivity analyses. The column names should be self-explanatory, subject to reading the paper.</p>
Data Used in [~Re] Setting Inventory Levels in a Bike Sharing Network
<p>Data used to reproduce the publication "Setting an Inventory Levels in a Bike Sharing Network" by Datner et al.</p> <p>This data correspond to the scenarios generated from the parameters given by the authors.</p>
Bike Racks in the city of Trento
<p>Bike racks in the Limited Traffic Zone of Trento, Italy, collected with the <a href="https://doi.org/10.5281/zenodo.3540843">Virtual City Explorer </a>. Crowdworkers were recruited through the FigureEight platform.</p> <p>Data is provided as OnStreetParking elements from teh <a href="https://github.com/FIWARE/data-models/tree/master/specs/Parking">FiWare data model for parkings</a> </p> <p>Provenance and task description information (following the <a href="https://doi.org/10.5281/zenodo.3531962">crowd-voc vocabulary</a>) is included.</p>
NYC Bike Sharing Network: Time-Series Enhanced Nodes and Edges Dataset
<p>This dataset presents a comprehensive graph representation of the New York City Bike Sharing system, structured with nodes representing stations and edges delineating trips between these stations. The dataset is distinctive in integrating dynamic properties as time series data, which are meticulously updated using historical records (csv files) and live data feeds (gbfs files) provided by<a href="https://citibikenyc.com/system-data" target="_blank" rel="noopener"> NYC Bike sharing system</a>. </p> <ul> <li> <p><strong>Nodes</strong>:</p> <ul> <li><strong>Source</strong>: Data is collected from the New York City Bike Station Information API.</li> <li><strong>Attributes</strong>: <ul> <li><strong>ID</strong>: Unique identifier for each station.</li> <li><strong>Name</strong>: Name of the station.</li> <li><strong>Capacity</strong>: Number of bikes the station can accommodate.</li> <li><strong>Short ID</strong>: A condensed identifier used internally.</li> </ul> </li> <li><strong>Time Series Data</strong>: <ul> <li>Updated every 5 minutes from the Station Status API.</li> <li>Captures changes in bike availability, recording values only when they differ from previous data points.</li> </ul> </li> </ul> </li> <li> <p><strong>Edges</strong>:</p> <ul> <li><strong>Source</strong>: Compiled from trip data provided in CSV format specific to NYC Bike Sharing.</li> <li><strong>Attributes</strong>: <ul> <li><strong>Trip Counter</strong>: Total number of trips recorded.</li> <li><strong>Bike Type Counter</strong>: Counts trips made with electric versus classic bikes.</li> <li><strong>Trip Type Counter</strong>: Separates trips made by members versus casual riders.</li> <li><strong>Active Trips Tracker</strong>: Tracks the number of active trips at any given moment.</li> </ul> </li> <li><strong>Aggregation</strong>: Trip data between identical start and end points, in the same direction, are aggregated into a single edge, with time-series tracking the frequency of these trips.</li> </ul> </li> </ul>
Data of 14 participants in the RCT titled Acute effects of virtual reality exercise bike games on psychophysiological outcomes in college North-African adolescents with cerebral palsy: A randomized clinical trial
<p>It is an Excel file including the numerical data of the 14 participants included in the study titled: <a name="_Hlk151119211"></a><span>Acute effects of virtual reality exercise bike games on psychophysiological outcomes in college North-African adolescents with cerebral palsy: A randomized clinical trial</span></p>
Santander bike network usage week 15 April 2019
<p>Dataset of Dock availability of Santander BSS used in the paper "Genetic Hybrid Optimization of a Real Bike Sharing System" MDPI September 2021. </p> <p>The data used in this paper are distributed under the Open Licence from Etalab and were collected using the connector provided by JCDecaux.(JCDecaux. JCDecaux Developer. Open Data. 2021.). This connector’s API provides, for a certain city, an extensive set of attributes in real-time. We have selected and retrieved the number of stations, capacity and occupation every 5 min, in order to figure out the dynamic of users. Within this interval, we will transform the occupation into requests of bikes or docks by means of subtracting consecutive occupation values.</p>
"I was the class teacher at that time. It was a class trip, usually organized near the end of the schoolterm in summer. The pupils went there by bike to have a barbecue at the sandy banks of the river Rhine near Dusseldorf. The landscape around is mostly dominated by agriculture and glasshouse cultures. You find a mixture of former villages nowadays completely suburbanized. The population finds jobs in the nearby urban centers like Dusseldorf, Neuss and other big cities. The reason why Irecorded the scene is simply because Iam interested in collecting sounds in general by doing recordings in different surroundings like nature, cities and everything between. My memories about the event are that it was a relaxing and funny atmosphere, which is not always the case while teaching in a classroom" [Reinhard/reinsamba]15 in Collecting Sounds. Online Sharing of Field Recordings as Cultural Practice
"I was the class teacher at that time. It was a class trip, usually organized near the end of the schoolterm in summer. The pupils went there by bike to have a barbecue at the sandy banks of the river Rhine near Dusseldorf. The landscape around is mostly dominated by agriculture and glasshouse cultures. You find a mixture of former villages nowadays completely suburbanized. The population finds jobs in the nearby urban centers like Dusseldorf, Neuss and other big cities. The reason why Irecorded the scene is simply because Iam interested in collecting sounds in general by doing recordings in different surroundings like nature, cities and everything between. My memories about the event are that it was a relaxing and funny atmosphere, which is not always the case while teaching in a classroom" [Reinhard/reinsamba]15
Bike Post - "Lies and Ignorance Rot Your Soul"
This decal-covered bike post sits outside the former location of Hamilton's Tavern on 30th Street in San Diego, California. The tavern closed following a 2020 kitchen fire. 📍 [San Diego, CA](https://scaniver.se/L32.72183,-117.13016) Made with [Scaniverse](https://scaniverse.com) on an iPhone 12 Pro. I'm posting one scan each day in June. See the [entire collection](https://skfb.ly/ouVY8)! Source: Objaverse 1.0 / Sketchfab
rusty bike #AgisoftNatureChallenge
a rusty bike in nature for the Sketchfab June Challenge 2021: 3D Scanning - Nature. #AgisoftNatureChallenge Work in progress - will optimize this scan the next 4-6 weeks, when I got more RAM and more knowledge on how to better handle Metashape settings. Here the Metashape Editing view, which looks much better.  Source: Objaverse 1.0 / Sketchfab
Survey Data for Multicriteria Satisfaction Analysis of Cargo Bike Last-Mile Delivery in European Cities
<p>SSH CENTRE (Social Sciences and Humanities for Climate, Energy aNd Transport Research Excellence) is a Horizon Europe project, engaging directly with stakeholders across research, policy, and business (including citizens) to strengthen social innovation, SSH-STEM collaboration, transdisciplinary policy advice, inclusive engagement, and SSH communities across Europe, accelerating the EU’s transition to carbon neutrality. <br>SSH CENTRE is based in a range of activities related to Open Science, inclusivity and diversity – especially with regards Southern and Eastern Europe and different career stages – including: development of novel SSH-STEM collaborations to facilitate the delivery of the EU Green Deal; SSH knowledge brokerage to support regions in transition; and the effective design of strategies for citizen engagement in EU R&I activities. Outputs include action-led agendas and building stakeholder synergies through regular Policy Insight events.<br>This is captured in a high-profile virtual SSH CENTRE generating and sharing best practice for SSH policy advice, overcoming fragmentation to accelerate the EU’s journey to a sustainable future.<br>The documents uploaded here are part of WP2 whereby novel, interdisciplinary teams were provided funding to undertake activities to develop a policy recommendation related to EU Green Deal policy. Each of these policy recommendations, and the activities that inform them, will be written-up as a chapter in an edited book collection. Three books will make up this edited collection - one on climate, one on energy and one on mobility. <br>As part of writing a chapter for the SSH CENTRE book on ‘Strengthening European mobility policy - Governance recommendations from innovative interdisciplinary collaborations’, we elicit the opinions of citizens in urban logistics policymaking through a series of surveys in different European cities. The files attached to this Zenodo webpage are therefore the dataset contains raw survey data from a study utilizing Multicriteria Satisfaction Analysis (MUSA) to evaluate public perceptions of cargo bike last-mile delivery in London, Paris, Rome, Dublin, and Warsaw. The data encompasses over 2,000 responses, detailing participants' satisfaction levels with various aspects of cargo bike delivery services, including CO2 emissions, noise, traffic, safety, and shipping costs. This dataset supports comprehensive analyses of urban logistics policies aimed at sustainable mobility solutions in these specific cities.</p>
Dataset of bike-sharing Demand Prediction model based on Spatio-Temporal Graph Convolutional Networks
<p>Dataset of bike-sharing Demand Prediction model based on Spatio-Temporal Graph Convolutional Networks</p>
Occupancy history of Seville's bike-sharing network. January-June 2021
<p>Occupancy history of Seville's bike-sharing network and station coordinates. January-June 2021 </p>
An orally angiotensin - (1 – 7) inclusion compound reduce time to reaction in 2 stroop task and modify heart rate variability after continuous test in mountain 3 bike cyclists
<p>data for An orally angiotensin - (1 – 7) inclusion compound reduce time to reaction in 2 stroop task and modify heart rate variability after continuous test in mountain 3 bike cyclists,<br> </p> <p>Recently our group showed that hydroxypropyl β-cyclodextrin (HPβ-CD)-Angiotensin-(1-7) (HPβ-CD-Ang-[1-7]) oral formulation affects performance and decreases the perceived effort of mountain bike (MTB) athletes.</p> <p>Twenty-one male MTB practitioners were divided into a continuous protocol time trial and repeated sprint groups. Three hours before a 20-km cycling time trial or 4×30-s repeated all-out sprints on a leg cycle ergometer, the athletes received HPβ-CD-Ang-(1-7) (0.8 mg) or HPβ-CD-placebo (only HPβ-CD) oral capsules over a 7-day interval randomized crossover design. At rest and immediately after the exercise protocol, the ratings of perceived recovery and the visual analog scale were assessed, and the volunteers completed the Stroop task (ST). Heart rate variability was measured at rest and peak effort. There were no differences in the perceived variables. The ST showed that HPβ-CD-Ang-(1-7) supplementation reduced the reaction time (rest 1032±331 ms vs. after protocol 902±286 ms, p=0.05) after the continuous time trial. The withdrawal of the parasympathetic components in the peak effort to the continuous protocol was not different from that of rest in the HPβ-CD-Ang-(1-7) condition. The results are pioneering, especially in humans, but indicate that Angiotensin-(1-7) potentially affects reaction time and the parasympathetic withdrawal after continuous protocol time trial.</p>
E-Bike Commuting and Health in Overweight College Students
ClinicalTrials.gov study NCT07114991. IPD Sharing: YES. Countries: 1. Publications: 3.
Edinburgh Bike Sharing Data
<p>Accompanying datasets for the simulation study found here: <a href="https://doi.org/10.5281/zenodo.3702267">doi</a> / <a href="https://github.com/justinnk/bss-simulation-study">GitHub</a></p> <p>Please note the restricted usecases defined in the LICENSE.</p>
Bike-sharing data Berlin from Nextbike and Call-a-Bike for 2019 and 2022
<p>This includes various data sets used to estimate cycling volume in Berlin. It contains the raw bike-sharing data as well as a routed and cleaned version thereof.</p><p> </p><p>The data is based on free-floating bike-sharing systems and is available in the form of individual trips, for each departure and starting point as well as the respective times at the minute level are known. The bike-sharing data comprises the months of April until December 2019 for the providers Nextbike and Call-a-Bike (provided by City Lab Berlin). Additionally, we web scrap the equivalent data for the months of June until December 2022 from Nextbike (web scraped data).</p><p> </p>
iris diaphragm transmission bike
a simple way to improve the bike Source: Objaverse 1.0 / Sketchfab
Supplementary material for publication "Optimizing combined tours: The truck-and-cargo-bike case"
<p>Supplementary material for publication "Optimizing combined tours: The truck-and-cargo-bike case" in OR Spectrum.</p> <p>Includes datasets I_1, I_2_W and I_2_M for different values of delta and n and results for the MIP formulations and heuristics.</p> <p> </p> <p> </p> <p>https://doi.org/10.1007/s00291-024-00754-2</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.