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4,763 results for “mobility”
Mobile temperature measurements and surrounding canopy characteristics in downtown Madison, WI, summer 2023
This dataset includes temperature and solar radiation measurements collected by a bicycle-mounted mobile sensor. Measurements were collected along four different transects in downtown neighborhoods in Madison, Wisconsin, over the course of five days during the 2023 summer. In addition to the measurements made by the mobile sensor, this dataset includes attributes of surrounding street trees, impervious cover, and overhead canopy cover, within 15 m, 25 m, and 35 m radii of each measurement location.
National Severe Storms Laboratory Mobile Soundings during Lapse-Rate (CLAMPS trailer)
<p>This dataset includes files from the National Severe Storms Laboraory mobile sounding units operated during the LAPSE-RATE field campaign. The files contained here are for each individual sounding launched from the CLAMPS trailer owned and operated by the University of Oklahoma, along with a readme file explaining the data format and processing.</p>
National Severe Storms Laboratory Mobile Mesonet data files from Lapse-Rate
<p>This dataset includes files from the National Severe Storms Laboratory mobile mesonets operated during the LAPSE-RATE field campaign. Daily files from each operation day are uploaded, along with a readme file explaining the format and processing.</p> <p>Version 2 Notes: The original version of this upload contained files with incorrect QC flags. While the core data is correct, the QC flags can be useful for determining specific areas of interest or problems. After identifying this issue, the files were reprocessed to include the correct QC flags and were uploaded to the archive as Version 2. Any questions should be directed to sean.waugh@noaa.gov.</p>
Number of genes per function within mobile genetic elements in Martinez Arbas, Narayanasamy et. al. (2020)
<p>This repository contains a set of tables separated by COG functional categories and the type of mobile genetic element, i.e. phage or plasmid. Each table contains predicted gene functions for each COG category and information on protospacer-containing contigs (PSCCs) and non-PSCCs</p> <p>This repository is related to the work published in Martinez Arbas, Narayanasamy et. al. (2020).</p>
Data from: Arm waving in stylophoran echinoderms: three-dimensional mobility analysis illuminates cornute locomotion
<p>The locomotion strategies of fossil invertebrates are typically interpreted on the basis of morphological descriptions. However, it has been shown that homologous structures with disparate morphologies in extant invertebrates do not necessarily correlate with differences in their locomotory capability. Here, we present a new methodology for analysing locomotion in fossil invertebrates with a rigid skeleton through an investigation of a cornute stylophoran, an extinct fossil echinoderm with enigmatic morphology that has made its mode of locomotion difficult to reconstruct. We determined the range of motion of a stylophoran arm based on digitized three-dimensional morphology of an early Ordovician form, <i>Phyllocystis crassimarginata</i>. Our analysis showed that efficient arm-forward epifaunal locomotion based on dorsoventral movements, as previously hypothesized for cornute stylophorans, was not possible for this taxon; locomotion driven primarily by lateral movement of the proximal aulacophore was more likely. 3D digital modelling provides an objective and rigorous methodology for illuminating the movement capabilities and locomotion strategies of fossil invertebrates.</p>
Figure 4 in Patterns of spatial variability of mobile macro-invertebrate assemblages within a Posidonia oceanica meadow
Figure 4. Non-metric multidimensional scaling (nMDS) ordination on macro-invertebrate assemblages of Pianosa Island. S = shallow, I = intermediate, D = deep; e = east, s = south, w = west.
Figure 3 in Patterns of spatial variability of mobile macro-invertebrate assemblages within a Posidonia oceanica meadow
Figure 3. (a) Mean species number and (b) number of individuals per sample of mobile macroinvertebrate assemblages of Posidonia oceanica meadow (mean ± standard error, SE; n = 24).
Figure 2 in Patterns of spatial variability of mobile macro-invertebrate assemblages within a Posidonia oceanica meadow
Figure 2. (a) Shoot density and (b) mean leaf length of Posidonia oceanica meadow of Pianosa Island (mean ± standard error, SE; n = 120).
SmartUpLab- Co-Creation in sustainable mobility research - Systematic Reviews and Case Studies
<p>The current dataset presents the results of systematic reviews and case studies about co-creation tools best practice for sustainable mobility, carried out in the context of the research project SmartUpLab (funded by EFRE).</p>
A Study on Organizational IT Security in Mobile Software Ecosystems Literature
<p>Information security is a key topic for most organizations. With the digital revolution, smartphones have become popular not only for personal use but also within organizations where many employees use them for business purposes. As smartphones are increasingly present in organizations, it is necessary to understand what recommendations the literature provides for the safe use of such devices, helping organizations to protect themselves from threats. ISO 27000 is a well-known standard for information security in a business context. It provides a set of controls that must be observed to ensure more secure organizational information. Therefore, the goal of this study is to identify which controls presented in ISO 27000, more specifically ISO 27001, are present in the Mobile Software Ecosystem (MSECO) literature. To do so, we conducted a systematic mapping review supplemented by a snowballing process to identify studies in the field of MSECO that have addressed any subject that is present in ISO 27001. We found that 34 out of the 114 ISO 27001 controls are covered by the MSECO literature. Also, some of the ISO sections (e.g., Asset Management) have not yet been explored in the MSECO literature. Our results can inspire future and further studies on the topic of MSECO information security.</p>
University of Nebraska-Lincoln Mobile Mesonet files from LAPSE-RATE
<p>This dataset includes files from the University of Nebraska-Lincoln mobile mesonets operated during the LAPSE-RATE field campaign. </p>
UI Dark Patterns and Where to Find Them: A Study on Mobile Applications and User Perception
<p>UI Dark Patterns and Where to Find Them: A Study on Mobile Applications and User Perception</p> <p> </p> <p>This dataset contains:</p> <ul> <li>survey_data.xlsx: Read-only spreadsheet containing the answers of 541 participants of our online survey (48 participants opted to not make their answers publicly available);</li> <li>classification_data.xlsx: Read-only spreadsheet containing the overall and the individual categorization of 240 mobile apps with respect to the presence of dark patterns; and,</li> <li>Videos.zip: videos of 15 apps (10 minutes each) used to classify the apps. The complete set of videos is considerably large and can be provided upon request.</li> </ul>
Virtual VRU protection of Mobile Cooperative safety function in SAFE STRIP
<p>An example dataset containing log files of Use Case ES1.1 "Virtual Vulnerable Road User (VRU) protection of Mobile Cooperative safety function". The log files contain information about the messages exchanged during the specific use case trial, between the different entities of SAFE STRIP. These messages are logged on the MQTT broker and on the HMI device used. The dataset also contains a file created post processing with details about the sequence of events over time for this particular example. In this way, the timing sequence of messages is displayed together with a brief description of the actual event that triggered the message creation.</p>
Dataset and Jupyter worksheet interpreting the (results from) small- and wide-angle scattering data from a series of boehmite/epoxy nanocomposites. Accompanies the publication "Competition of nanoparticle-induced mobilization and immobilization effects on segmental dynamics of an epoxy-based nanocomposite"
<p>Dataset and Jupyter worksheet interpreting the (results from) small- and wide-angle scattering data from a series of boehmite/epoxy nanocomposites. Accompanies the publication "Competition of nanoparticle-induced mobilization and immobilization effects on segmental dynamics of an epoxy-based nanocomposite", by Paulina Szymoniak, Brian R. Pauw, Xintong Qu, and Andreas Schönhals.</p> <p>Datasets are in three-column ascii (processed and azimuthally averaged data) from a Xenocs NanoInXider SW instrument. Monte-Carlo analyses were performed using McSAS 1.3.1, other analyses are in the Python 3.7 worksheet. Graphics and result tables are output by the worksheet. </p>
Putative mobilized colistin resistance (mcr) genes co-occurring with other antibiotic resistance genes are widespread in the human gut microbiome
<p><strong>The dataset from the article </strong><strong>Putative mobilized colistin resistance (mcr) genes co-occurring with other antibiotic resistance genes are widespread in the human gut microbiome</strong></p>
Dataset for Millimeter-wave Mobile Sensing and Environment Mapping: Models, Algorithms and Validation
<p>Dataset of paper "Millimeter-wave Mobile Sensing and Environment Mapping: Models, Algorithms and Validation".</p> <p>The measurement data contains indoor mapping results using millimeter-wave 5G NR signals at 28 GHz. The measurement campaign was conducted in an indoor office environment in Hervanta Campus of Tampere University. Six different sets of measurements contain the range profiles after the proposed radar processing. The shared data contains the IQ data of both transmit and receive signals used during the measurement campaign.</p> <p>The file "main.m" shows how to process and plot the shared data.</p>
MONROE_Profiling_Mobile_Broadband_Coverage
<p>Dataset for TMA'16 paper Profiling Mobile Broadband Coverage. </p> <p>The dataset consists of grid blocks traversed by the train routes me measure in Norway, more specifically Oslo-Stavanger, Oslo-Voss, Oslo-Trondheim, Trondheim- Bodø.</p> <p>For each of the grids and for each run on a route, we measure the Radio Access Technology an end-user could access while in the train for two different Mobile Broadband providers, namely Telenor and Netcom (Telia) in Norway. The dataset csv files we upload here are organized per operator and per route. </p> <p>Each row in one file consists of:</p> <p>grid_id = unique ID of the grid block that delimits a portion of the route</p> <p>lat1 = latitude of the grid </p> <p>lon1 = longitude of the grid </p> <p>avg_speed = average speed of the train when traversing the grid block </p> <p>start = timestamp of when the train enters the grid</p> <p>end = timestamp when the train exits the grid </p> <p>ccu_desig = unique ID of the NSB passenger train </p> <p>total = total number of datapoints within the grid block </p> <p>4G = number of points within the grid where the RAT is 4G </p> <p>3G = number of points within the grid where the RAT is 3G </p> <p>2G = number of points within the grid where the RAT is 2G </p> <p>nos = number of points within the grid where the RAT is No Service </p> <p>4gd = 4G distribution in the grid block </p> <p>3gd = 3G distribution in the grid block </p> <p>2gd = 2G distribution in the grid block</p> <p>nosd = No Service distribution in the grid block </p> <p>run_id = the ID of the run</p> <p>static = 1 if the train stops at any point in the grid, 0 is the train doesn't stop in the grid</p> <p>mobile = 1 if the train is mobile, 0 is it is not</p> <p>full_mobile = 1 if the train is moving at all times, 0 if it is not </p> <p>tunnel = 1 if the train traverses a tunnel within the grid block, 0 if there are no tunnels</p> <p>full_tunnel = 1 if the train is in train the whole time it is in the respective grid block </p> <p>way = route direction </p> <p>route = train route </p> <p> </p>
Scene camera movies from mobile eye tracker
<p>These are the full recorded scene camera scenes. Eye position data for each scene can also be found here as well as an excel file detailing which parts of the clips we used.</p>
Mobile broadband speedtest traces
<p>The goal of this research is to collect a wide range speedtest traces for the mobile broadband (MBB) networks, as seen from actual users while moving around the city using public or private vehicles. For collecting this dataset we ask students to participate and run Mobile BroadBand speedtest. You can find the instruction of our test here. Traces were mostly collected in the city of Torino in Italy, and refer to three technologies (WiFi, 3G, and 4G), and multiple Mobile Network Operators (MNO). The networks were in normal operating conditions (and unaware of our tests). Our terminals (both Android and iOS smartphones) accessed the mobile networks to upload data to a server on campus, using both TCP and UDP at the transport layer.<br> <br> We used a hybrid method in the trace collection process: we run repetitive active measurements from mobile terminals using iperf2, and we collect passive traces on server side using tcpdump. In each experiment, the mobile terminal runs iperf2 in the upload direction for 600 seconds while tcpdump captures packets at the server.<br> We collected traces for different MNOs in Italy (Tim, Wind, and Vodafone). For WiFi, we considered the open WiFi community WoW-Fi offered automatically by Fastweb customers that share their DLS or FTTH home network via the access gateway. Mobile phones automatically authenticate using IEEE 802.1x with no action from the user. Traces shorter than 300 seconds are iperf2 experiments run from the stationary MONROE nodes or failed experiments.<br> </p>
Taxonomy for Connected Cooperative and Automated Mobility (CCAM)
<p>As part of the FAME project this taxonomy has been created with its main goal to establish a standardized and harmonized classification system for CCAM-related terms, enhancing the comparability, complementarity, and expansion of research, development, and testing in the world of CCAM-enabled solutions and services. Due to its strong links with the EU-CEM handbook multiple terms from the Common Evaluation Methodology (CEM) have been included. The taxonomy is publicly available via the knowledge base and can be accessed here; <a title="Taxonomy for Connected Cooperative and Automated Mobility (CCAM)" href="https://taxonomy.connectedautomateddriving.eu/">https://taxonomy.connectedautomateddriving.eu/</a></p> <p> </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.