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13,017 results for “Positioning”
POLCAND_ELEC (Allocation of Seats on Electoral Lists: A Dynamic Analysis of Candidate Positioning in Parliamentary Elections from 1991 to 2023)
<p>The aim of the study was to supplement and expand the data contained in the EAST PaC database (Joshua Kjerulf Dubrow: East European Parliamentarian and Candidate Data (EAST PaC), 1985 - 2015 [dane]. Institute of Philosophy and Sociology, Polish Academy of Sciences [producent], Warsaw, 2016. PADS21320. Polish Social Data Archive [dystrybutor], Repozytorium Danych Społecznych [wydawca], 2021. <a href="https://doi.org/10.18150/LSBNLO" target="_blank" rel="noopener">https://doi.org/10.18150/LSBNLO</a>, V1).</p> <p>Currently, an open-access database called EAST PaC (with a data structure similar to panel data, which allows for identifying candidates each time they participate in subsequent elections) contains information on all candidates who have ever run in elections to the Sejm in Poland, from the last elections in the People's Republic of Poland in 1985 to the elections in 2015.</p> <p>This study allowed for the expansion of previous analyses regarding the ways of forming political representation and the associated quality of political elites. This is essential for conducting a dynamic analysis of candidate positioning on electoral lists, which enables tracing the electoral activity of all candidates in elections from 1991 to 2023. It allows for illustrating the occurrence of events over time by tracking candidates' electoral activities. Many previous empirical studies on the course and consequences of parliamentary elections have significant gaps, as they are limited to analyzing the situation of parliamentarians (often focusing on only selected categories). They lack the history of candidacies in elections, even though voters' final decisions are based on the assessment of previous results of candidates and the political entities they represent.These analyses are significant for explaining the dynamics of the political system and assessing the quality of democracy. They also enable empirical verification of hypotheses concerning the periodization of the institutionalization of the electoral system in Poland from 1991 to 2023.</p>
CCE LTER process cruise, in the California Current region, event log records including date, time, position and activity for use in post-cruise data integration based on co-sampling indexes. From 2006 to 2019 CCE LTER used a locally developed event logging system. During P2107, CCE LTER started to utilize the R2R Event Logger on UNOL ships, 2006 - 2024 (ongoing).
The event logger program developed and maintained by the California Cooperative Oceanic Fisheries Investigations, SIO, program is used aboard CCE LTER process cruises to create indexes with temporal, spatial and activity information for post-cruise data integration. The event log is configured aboard the ship for the recording of sampling events by both ship crew personnel on the bridge, and research personnel in the lab. The event log is processed post-cruise to correct for various errors.
Stomach contents (1977-1981) and stable isotopes (1994) from the Everglades, Florida, USA from the publication "Fishes in a seasonally pulsed wetland show spatiotemporal shifts in diet and trophic niche but not shifts in trophic position"
Stomach contents of fishes (1977-1981) and stable isotopes of fishes, invertebrates, and basal resources (1994) were collected from spikerush marsh, sawgrass ridge, and alligator pond habitats in Shark River Slough, Everglades National Park, Florida, USA. These data were used to quantify diet, trophic niche area, trophic position, basal resource use and how these metrics vary among size classes, seasons, and habitats. Data collection is complete. These data support Flood et al. (2023). Associated R code will be made available through Peter Flood's GitHub: https://github.com/pjflood/historic_everglades_aquatic_food_web. References: Flood, Peter J., William F. Loftus, and Joel C. Trexler. "Fishes in a seasonally pulsed wetland show spatiotemporal shifts in diet and trophic niche but not shifts in trophic position." Food Webs 34 (2023): e00265. https://doi.org/10.1016/j.fooweb.2022.e00265
AMC01 Growing season microclimate by topographic position for annually-burned and 4-yr burned watersheds at Konza Prairie
Dataset contains 30min averages of many variables used to record changes in microclimatic conditions. Microclimate sensor stations were arrayed in discrete topographic positions (upland, slope, lowland) in 4 watersheds: 1D, 1B, 4B, 4F. No microclimate sensor stations were present in upland-1D or lowland-4B because eddy flux towers are present in these locations. Similar microclimate data is available from these flux towers during the time period of this study.
MCR LTER: Coral Reef: Biodiversity has a positive but saturating effect on imperiled coral reefs; data for Clements and Hay 2021, Science Advances
Species loss threatens ecosystems worldwide, but the ecological processes and thresholds that underpin positive biodiversity effects among critically important foundation species, such as corals on tropical reefs, remain inadequately understood. In field experiments, we manipulated coral species richness and intraspecific density to test whether, and how, biodiversity affects coral productivity and survival. Corals performed better in mixed species assemblages. Improved performance was unexplained by competition theory alone, suggesting that positive effects exceeded agonistic interactions during our experiments. Peak coral performance occurred at intermediate species richness and declined thereafter. Positive effects of coral diversity suggest that species’ losses on degraded reefs make recovery more difficult and further decline more likely. Harnessing these positive interactions may improve ecosystem conservation and restoration in a changing ocean. This material is based upon work supported by the U.S. National Science Foundation under Grant No. OCE 16-37396 (and earlier awards) as well as a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2022). This work represents a contribution of the Moorea Coral Reef (MCR) LTER Site. Datasets used in this study are available online from the BCO-DMO data system. Data for this paper can be found at (https://www.bco-dmo.org/project/837802).
Additional TAU datasets for Wi-Fi fingerprinting-based positioning
<p><strong>1. Contents</strong></p> <p>This document describes two datasets collected at Tampere University facilities with samples taken from a Wi-Fi network interface for experiments with indoor positioning based on Wi-Fi fingerprinting.</p> <p>To reference this dataset, please use</p> <p>E.S. Lohan et al. “Additional TAU datasets for Wi-Fi fingerprinting-based positioning” 10.5281/zenodo.3819917</p> <p>Additional reference using these datasets</p> <p><em>Torres-Sospedra, J.; Quezada-Gaibor, D.; Mendoza-Silva, G. M.; Nurmi, J.; Koucheryavy, Y. and Huerta, J. New Cluster Selection and Fine-grained Search for k-Means Clustering and Wi-Fi Fingerprinting Proceedings of the Tenth International Conference on Localization and GNSS (ICL-GNSS), 2020.</em></p> <p><strong>Dataset format</strong></p> <p>Two independent datasets are provided, they are in different folders, namely “Database_Building01” and “Database_Building02” respectively. Each dataset includes two sets of samples:</p> <ul> <li>radio map – a set of Wi-Fi samples collected at a grid of points (reference points);</li> <li>evaluation – a set of Wi-Fi samples randomly collected in the evaluation area.</li> </ul> <p>Two files are provided for each set that include the rss vectors and the coordinates. For the radio map, the provided files have their names starting with “rm_”; for the evaluation, the evaluation files have their names starting with “eval_”. For instance, for the radio map they are:</p> <ul> <li>rm_crd.csv: holds coordinates (x,y)and floor identifier (z) where the samples were collected;</li> <li>rm_rss.csv: holds the measured RSSI values from each of the Access Points (AP) detected in each sample;</li> </ul> <p>All the file are described in the same format, and all files are CSV – Comma Separated Values plain text (UTF-8).</p> <p><strong>Coordinates:</strong> Each sample is associated to a pair of coordinates in a 2D Euclidean reference system. The origin of the reference system was chosen arbitrarily for convenience. The units are meters. Therefore, distances between points can be easy calculated. Moreover, the floor identifier is included to enable 3D positioning.</p> <p><strong>RSSI values:</strong> The RSSI values provided as read from the Wi-Fi network interface through the Android API. In each sample, a value of +100 was assigned to each AP not detected during a measurement. No information is provided about the MAC addresses of the APs. However, in the files, the same order is used for all samples, meaning that the values in each column are all associated to the same AP.</p> <p>Both datasets are independent and none of the provided files include an identifier for each sample. The values in the two provided files are associated by the line number, meaning that the coordinates and RSSI values in the same line, in each file, refer to the same sample.</p>
Surface electromyogram (sEMG) dataset recorded from forearm for 9 hand movements and three electrode array positions
<p>This repository contains raw surface Electromyography signals termed surface Electromyograms (<a href="https://en.wikipedia.org/wiki/Electromyography">sEMG</a>) recorded with 8 circular surface Ag/AgCl pairs of electrodes placed circumferentially around the forearm of the dominant arm in 10 able-bodied individuals (5 Females and 5 Males). The proposed method for processing sEMG data with subjects' characteristics and protocol can be found in <a href="https://doi.org/10.1016/j.bspc.2020.102292">Miljković & Isaković 2021</a>.</p> <p>For each subject, sEMG was recorded from <strong>three recording electrode array positions</strong> termed P1, P2, and P3 for 9 hand movements. We provide a compressed .7z folder with 10 sub-folders for each subject named by <strong>subject ID</strong> (ID1, ID2, ... ID10). Each sub-folder contains 27 .txt data files (for 9 movements × 3 electrode array positions), except for subject ID7 (there are 24 .txt records, since three records for wrist extension EX in P1, P2, and P3 positions got corrupted in subject ID7). Average size of 10 sub-folders is 167.50 ± 27.02 MB with maximum of 194 MB and minimum of 117 MB.</p> <p>The subjects performed following hand movements from the reference resting position –relaxation, R (explained in-detail in <a href="https://doi.org/10.1016/j.bspc.2020.102292">Miljković & Isaković 2021</a>): (1) spherical power grasp, PS, (2) three finger sphere grasp, 3F, (3) two finger prismatic grasp, PP, (4) wrist flexion, FL, (5) wrist extension, EX, (6) radial deviation, RD, (7) ulnar deviation, UD, and then forearm rotation i.e. (8) pronation, PR, and (9) supination, SU. PS, 3F, PP, FL, EX, RD, UD, PR, and SU correspond to <strong>type of hand movement</strong> in naming convention for .txt data files.</p> <p><a href="https://www.youtube.com/playlist?list=PLI3SYeiSufnBo6UDAZt9NJO9ecb-InJqb">Hand movements YoutTube playlist</a> contains explanatory videos for 9 hand movements recorded in this study, and we also provide corresponding .wmv here in the "movies hand movements.7z". Naming convention for .wmv files is <strong>type of hand movement</strong> with both full name and abbreviation for the movement (for example "radialDeviation-RD.wmv").</p> <p>Naming convention for .txt data files within 10 sub-folders is: <strong>subjects ID _ type of hand movement _ recording electrode array position</strong> (for example: "ID1_3F_P1.txt" in sub-folder ID1, "ID9_RD_P3.txt" in sub-folder ID9).</p> <p><strong>Dataset contents</strong></p> <ol> <li><a href="https://zenodo.org/record/4039550/files/EMG%20dataset.7z?download=1">EMG dataset.7z</a>, 267 .txt data files, text format</li> <li><a href="https://zenodo.org/record/4039550/files/movies%20hand%20movements.7z?download=1">movies hand movements.7z</a>, 9 .wmv files, explanatory hand movement videos (also available on <a href="https://www.youtube.com/playlist?list=PLI3SYeiSufnBo6UDAZt9NJO9ecb-InJqb">YouTube</a>)</li> <li><a href="https://zenodo.org/record/4039550/files/README.txt?download=1">README.txt</a>, metadata for data files, text format</li> </ol> <p><strong>Data files contain numerical values with decimal point* according to the following structure</strong></p> <ol> <li>column - CH1** (recorded samples from channel 1)</li> <li>column - CH2** (recorded samples from channel 2)</li> <li>column - CH3** (recorded samples from channel 3)</li> <li>column - CH4** (recorded samples from channel 4)</li> <li>column - CH5** (recorded samples from channel 5)</li> <li>column - CH6** (recorded samples from channel 6)</li> <li>column - CH7** (recorded samples from channel 7)</li> <li>column - CH8** (recorded samples from channel 8)</li> </ol> <p>* For subjects ID1 and ID2 three decimal places are provided, while for other subjects 6 decimal places in .txt data files are provided.</p> <p>** Each data file contains at least 10 repetitions of the corresponding movement. In cases where file contains >10 repetitions (overall 162 .txt data files), we used the first or the last ten for the analysis (except for two files where short and strong artifact appeared during the measurement procedure, and corresponding movement repetitions were discarded) presented in <a href="https://doi.org/10.1016/j.bspc.2020.102292">Miljković & Isaković 2021</a>.</p> <p>Sample rate was set at 1000 Hz and <a href="https://en.wikipedia.org/wiki/Analog-to-digital_converter">A/D card</a> had 16 bits resolution. Gain of the amplifier was set at 1000. For more in-detail explanations of electrode array assemble and positioning for sEMG channels CH1, CH2, ... CH8, please refer to <a href="https://doi.org/10.1016/j.bspc.2020.102292">Miljković & Isaković 2021</a>.</p> <p>If you find these signals useful for your own research or teaching class, please cite both relevant preprint and dataset as:</p> <ol> <li> <p>Miljković, N. and Isaković, M.S., 2021. Effect of the sEMG electrode (re) placement and feature set size on the hand movement recognition. <em>Biomedical signal processing and control</em>, 64:102292. <em><a href="https://doi.org/10.1016/j.bspc.2020.102292">10.1016/j.bspc.2020.102292</a></em></p> </li> <li> <p>Miljković, N. and Isaković, M.S., 2020. Surface electromyogram (sEMG) dataset recorded from forearm for 9 hand movements and three electrode array positions. [Data set]. <em>Zenodo</em> <em><a href="https://zenodo.org/record/4039550">10.5281/zenodo.4039550</a></em>.</p> </li> </ol> <p><strong>ACKNOWLEDGEMENTS</strong> (from <a href="https://doi.org/10.1016/j.bspc.2020.102292">Miljković & Isaković 2021</a>): "Special appreciation the authors owe to Professor Mirjana B. Popović from the University of Belgrade for her kind support,precious guidance, and advice regarding this research which significantly improved the manuscript. Also, the authors would like to thank Dr Matija Štrbac from Tecnalia Serbia Ltd. for providing advice throughout the study.The authors thank all volunteers for their participation."</p>
Analysing the data-driven approach of dynamically estimating positioning accuracy (data)
<p>The train/validation/test sets used in the study <strong>"<em>Analysing the data-driven approach of dynamically estimating positioning accuracy</em>"</strong>.</p> <p>Preprint: <a href="https://arxiv.org/abs/2011.10478">https://arxiv.org/abs/2011.10478</a></p> <p>Published paper: <a href="https://ieeexplore.ieee.org/document/9500369">https://ieeexplore.ieee.org/document/9500369</a></p> <p>-----------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p>The full dataset used in this study, is the public dataset <em>lorawan_dataset_antwerp.csv </em> (and its related file <em>lorawan_antwerp_gateway_locations.json)</em> which can be access here:</p> <pre><a href="https://zenodo.org/record/3904158#.X4_h7y8RpQI">https://zenodo.org/record/3904158#.X4_h7y8RpQI</a></pre> <p>The above link is related to the following publication, in which the original dataset was published:</p> <p><a href="http://www.mdpi.com/2306-5729/3/2/13">http://www.mdpi.com/2306-5729/3/2/13</a></p> <p>The credit for the creation of the dataset goes to Aernouts, Michiel; Berkvens, Rafael; Van Vlaenderen, Koen; and Weyn, Maarten.</p>
Position Data in the Biographical Dictionary of Republican China
<p>This dataset contains records of positions of the 589 historical figures in the Biographical Dictionary of Republican China.</p>
Data and code for the paper "Macroscopic parameterization of positive streamer heads in air"
<p>This dataset contains the following:</p> <ul> <li><strong>ODE_solutions_no_photoi</strong>: the simulation results corresponding to figure 3 (see the README in the folder)</li> <li><strong>ODE_solutions_photoi</strong>: the simulation results corresponding to figure 6 (see the README in the folder)</li> <li><strong>input</strong>: the electron transport data used in the simulations (ionization coefficient, attachment coefficient, electron mobility) as a function of electric field strength</li> <li><strong>ODE_model.py</strong>: The version of the ODE model used in the paper</li> </ul> <p>The most recent version of the ODE model can be found at <a href="https://github.com/MD-CWI/streamer-head-ode">https://github.com/MD-CWI/streamer-head-ode</a></p>
Most bacterial gene families are biased toward specific chromosomal positions
<p><span>The arrangement of genes along bacterial chromosomes influences their expression through growth rate-dependent gene copy number changes during DNA replication. While translation and transcription genes often cluster near the origin of replication, the extent of positional biases across gene families remains unclear. We hypothesized that natural selection broadly favors specific chromosomal positions to optimize growth rate-dependent expression. Analyzing 910 bacterial species and proteomics data from <em>Escherichia coli</em> and <em>Bacillus subtilis</em>, we find that about two-thirds of bacterial gene families are positionally biased, mainly near the origin or terminus of replication, with the strongest natural selection in fast-growing species. Our findings reveal chromosomal positioning as a fundamental mechanism for coordinating gene expression with growth rate, highlighting evolutionary constraints on bacterial genome architecture.</span></p> <p> </p>
Audio recordings of COVID-19 positive individuals from the prospective Predi-COVID cohort study with their ageusia and anosmia status
<p>We uploaded 1636 audio recordings originating from 259 distinct participants in the prospective Predi-COVID cohort study recruited between May 2020 and May 2021. The audios have been converted from their original format into WAV files. The audio name structure integrates the participant ID, the recording date and time of the audio recording, the type of audio (Type 1: reading of a text, Type2: hold the [a] vowel), the original audio format, and the symptomatic status for ageusia and anosmia (1: symptomatic, 0: asymptomatic) as such:</p> <p>predi-covid_{participant}{recording date and time}{type of audio}{original format}{sympyomatic status}.wav</p>
The DR-Train dataset: dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh
<p><strong>Note: Downloading the large data file could have a timeout issue. If you cannot directly download it here, please use the following link as a complementary method for getting the data. </strong></p> <p><a href="https://drive.google.com/drive/folders/1oKn7IN7zznQuhwjDCDdjq8r9wHJYBEhj?usp=sharing">https://drive.google.com/drive/folders/1oKn7IN7zznQuhwjDCDdjq8r9wHJYBEhj?usp=sharing</a></p> <p> </p> <p>This dataset contains the dynamic responses (acceleration records) of two passenger trains with corresponding GPS positions, environmental conditions and track maintenance schedules for a light rail network in the city of Pittsburgh, Pennsylvania in the United States of America.</p> <p>In particular, two light rail vehicles were instrumented (identified as LRV4306 and LRV4313): <br> LRV 4306 has 5 acceleration channels, corresponding to the two uni-axial accelerometers inside the train and the three channels of the tri-axial accelerometer on the wheel truck.</p> <p><em>- The last digit of each acceleration file: 1, 2, 3, 4, 5<br> - Corresponding sensor channels: tri-axial x, tri-axial y, tri-axial z, front cabinet uni-axial, back cabinet uni-axial</em></p> <p><br> LRV 4313 has 8 acceleration channels, corresponding to the two uni-axial accelerometer and the two tri-axial accelerometers inside the train.</p> <p><em>- The last digit of each acceleration file: 1, 2, 3, 4, 5, 6, 7, 8<br> - Corresponding sensor channels: front cabinet uni-axial, back cabinet uni-axial, front tri-axial x, front tri-axial y, front tri-axial z, back tri-axial x, back tri-axial y, back tri-axial z.<br> - x longitudinal (vehicle moving direction); y-axis, transverse; z-axis, vertical.</em></p> <p>The dataset contained in this repository is a condensed version of the original raw data. While the accelerometers on the train were sampled continuously, this dataset contains only those measurements for when the train was actually moving along the track (i.e. not idling at a terminal).</p> <p>The data is stored in binary MAT-files (a MATLAB/Octave data format). These files contain MATLAB objects of the class "pass", which is defined in the file pass.m that can be found in the "code" folder. Specifically, two MAT-files named "obj_dic.mat", and found in the "LRV4306" and "LRV4313" folders, contain the "pass" objects of the two trains, respectively.</p> <p>Each category is described in detail. For more detail on the regions of the track, refer to the 'region.fig' file in this folder. The track was divided into distinct regions so that the data over specific sections of track could be compared. These regions were chosen for two reasons: <br> (1) within a region, the train always followed the same track and <br> (2) there are no tunnels in them so the GPS data is relatively consistent. </p> <p>To get started, using MATLAB or Octave try running "main_script.m" in the "code" folder.</p> <p>A data descriptor paper with details of the data collection process was published.</p> <p>Please cite as</p> <p><strong>Liu, J., Chen, S., Lederman, G., Kramer, D. B., Noh, H. Y., Bielak, J., Garrett, J. H., Kovačević, J., & Berges, M. Dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh. Scientific Data, 6, 146. <a href="https://doi.org/10.1038/s41597-019-0148-9">https://doi.org/10.1038/s41597-019-0148-9</a>(2019)</strong></p> <p><strong>Liu, J., Chen, S., Lederman, G., Kramer, D. B., Noh, H. Y., Bielak, J., Garrett, J. H., Kovačević, J., & Berges, M. The DR-Train dataset: dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh. Zenodo, <a href="https://doi.org/10.5281/zenodo.1432702">https://doi.org/10.5281/zenodo.1432702</a>(2018).</strong></p> <p>For questions or suggestions please e-mail Jingxiao Liu <liujx@stanford.edu></p>
Piezoresistive sensor fiber composites based on silicone elastomers for the monitoring of the position of a robot arm
<p>Combining conductive fillers like carbon black with elastomers allows the development of soft elastomer strain sensors that can reach very large elongations, an important requirement for many robotic applications. However, when the conductive filler is introduced in the polymer, significant stiffening occurs, affecting the mechanical properties, e.g. Young’s Modulus, of the soft structure. In this attempt, single piezoresistive fiber composites were successfully fabricated, without drastically increasing the stiffness. Two silicone elastomers that are widely used in robotic applications were examined as matrix materials. Furthermore, modeling the stresses exerted on the fiber inside the composite was successfully used to predict the detachment of fiber inside the matrix, observed by visual inspection. For the PDMS based composite, pre-straining improved sensor properties, which could be confirmed for the monitoring of the movement of the crane robot. The results showed that the pre-strained piezoresistive sensor fiber-matrix composites positions of the robot crane can be monitored even at low strains.</p>
La force des positions vulnerables : hégémonie financière et potentiel disruptif
<p>Dataset and R script related to the paper <a href="https://arcs.episciences.org/9233">La force des positions vulnérables : Hégémonie financière et potentiel disruptif</a>, <em>ARCS</em>, 2018.</p>
Dataset for "A robust tip-less positioning device for near-field investigations: Press and Roll Scan (PROscan)"
<p>The dataset contains the data relevant for the publication "A robust tip-less positioning device for near-field investigations: Press and Roll Scan (PROscan)". The data has been acquired using optical measurement techniques as described in detail in the publication https://arxiv.org/abs/2203.05527. The data is structured according to Figures presented in the publication.</p> <p>The authors acknowledge financial support by the Max Planck Society and by the QuantERA project RouTe through the Federal Ministry of Education and Research (BMBF) (13N14839). This project has also received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska Curie Grant Agreement No. 101025918.</p>
New dataset obtained from 2D positioning system with distributed control
<p>The dataset contains the obtained trajectory (encoder measurements) of the 2D positioning system, as well as the reference (commanded) trajectory. The control task is distributed to the low-level controllers for x and y axes synchronized using IEEE 1588 Precision Time Protocol (PTP), where the movement of the axes is realized based on the data that the low-level controllers receive from the high-level controller. The dataset includes 60 signals (30 measurements for x and y axis) that represent obtained trajectories and 2 signals (x and y axes) that represent commanded trajectory, where the length of each signal is 61,000 samples. The system was designed and built by the Cyber-Physical Systems Lab at the Pratt School of Engineering, Duke University, where it is located. Table 1 shows the list of collected signals, whereas a detailed description of the system can be found in [1]. For more information, see [2, 3].</p>
Continuous Long-term Wi-Fi Fingerprinting Dataset for Indoor Positioning (full version)
<p>Database with Wi-Fi samples (RSSI measurements) collected from several Raspberry Pi (RPi) 3B+ devices continuously over 2+ years. The database includes the long-term dataset from the RPi devices (with 7,435,398 Wi-Fi samples), as well as 12 site-survey datasets (with 11,140 Wi-Fi samples) conducted in this period. The site-surveys were also conducted with a RPi 3B+.</p> <p>The measurements obtained from the RPi 3B+ Wi-Fi interface include the list of detected APs, their signal strength (RSSI) and transmission channel. The list has APs from the 2.4GHz and 5GHz bands because it supports IEEE 802.11.b/g/n/ac wireless LAN. </p> <p>These data were collected at a university building, between 19 Feb. 2019 and 25 Mar. 2021.</p> <p>The supporting material includes the Python scripts to parse and analyse the data by generating various plots. It also includes the locations of the monitoring devices and the list of reference points considered in the site-surveys.</p> <p> </p> <p>A detailed description of this dataset and the data collection process can be found here:</p> <p>Silva I, Pendão C, Moreira A. Collection of a Continuous Long-Term Dataset for the Evaluation of Wi-Fi-Fingerprinting-Based Indoor Positioning Systems. <em>Sensors</em>. <strong>2022</strong>; 22(22):8585. <a href="https://doi.org/10.3390/s22228585">https://doi.org/10.3390/s22228585</a></p> <p> </p> <p>When using this dataset, please add a citation to the paper above or this citation:</p> <p>Silva, I., Pendão, C., & Moreira, A. (2022). Continuous Long-term Wi-Fi Fingerprinting Dataset for Indoor Positioning (full version) (1.1.0) [Data set]. Zenodo. <a href="Silva, I., Pendão, C., & Moreira, A. (2022). Continuous Long-term Wi-Fi Fingerprinting Dataset for Indoor Positioning (full version) (1.1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6928554">https://doi.org/10.5281/zenodo.6928554</a> </p> <p> </p> <p>The following papers have used this dataset for quantifying radio map degradation and overcoming radio map degradation in Wi-Fi fingerprinting:</p> <ul> <li>I. Silva, C. Pendão, J. Torres-Sospedra and A. Moreira, "Quantifying the Degradation of Radio Maps in Wi-Fi Fingerprinting," <em>2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN)</em>, Lloret de Mar, Spain, 2021, pp. 1-8, doi: 10.1109/IPIN51156.2021.9662558.</li> <li>I. Silva, C. Pendão, J. Torres-Sospedra and A. Moreira, "Overcoming Radio Map Degradation in Wi-Fi-based Positioning Systems," <em>2023 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN)</em>, Nuremberg, Germany, 2023, pp. 1-6, doi: 10.1109/IPIN57070.2023.10332545.</li> </ul>
Positions for "First insights into migration routes and nonbreeding sites used by Red-rumped Swallows (Cecropis daurica rufula) breeding in the Iberian Peninsula"
<p><strong>Abstract</strong></p> <p>Using EURING data and geolocation, we describe migration routes and nonbreeding range of Red-rumped Swallows breeding in the Western Palearctic. One bird ringed in southern Spain and recovered in southern Morocco indicates southwestern migration; geolocator data from five birds from central and eastern Iberian Peninsula confirm migration to various nonbreeding sites in sub-Saharan west Africa between Senegal/Mauritania and Ghana. Two swallows showed non-breeding site itinerancy by using more than one nonbreeding site per season. Despite wide ranges in departure for autumn (August- October) and spring migration (February-March), all birds arrived at nonbreeding and breeding sites within ±1-week from each other.</p> <p><strong>Zusammenfassung</strong></p> <p>Erste Einblicke in Zugrouten und Überwinterungsgebiete von Rötelschwalben (<em>Cecropis daurica rufula</em>) der Iberischen Halbinsel.<br> In dieser Studie beschreiben wir Zugrouten und Überwinterungsgebiete westpaläarktischer Rötelschwalben basierend auf EURING- und Geolokations-Daten. Eine Rötelschwalbe, die in Südspanien beringt und im südlichen Marokko wiedergefunden wurde, spricht für einen südwestlichen Zug. Geolokalisation von fünf Vögeln der zentralen und östlichen Iberischen Halbinsel zeigen Überwinterungsorte im sub-Saharischen Westafrika zwischen Senegal/Mauretanien und Ghana. Zwei der getrackten Rötelschwalben nutzten mehrere Überwinterungsplätze pro Saison. Trotz der großen Schwankungsbreite der Abzugszeiten im Herbst (August-Oktober) und im Frühjahr (Februar-März) erreichten die getrackten Vögel ihre Nichtbrut- bzw. Brutplätze innerhalb von 1–2 Wochen.</p>
Accuracy or positions and parallaxes
<p>Two figures from a report soon to be placed on arXiv: </p> <p><strong>Astrometric Accuracy of Positions</strong></p> <p>Erik Høg, Niels Bohr Institute, Copenhagen University</p> <p><span>Figure 1. <span>The </span></span><span>accuracy of observed star positions for 2000 years, marked with red color for observations from the ground and with blue from space. The accuracy was greatly improved shortly before 1600 AD by the Landgrave in Kassel and by Tycho Brahe in Denmark. The following 400 years brought even larger but much more gradual improvement before space techniques with the European Hipparcos satellite started a new era of astrometry. Catalogs before 1900 are plotted at the mean epoch of observation, but after 1900 at the time of publication. – The 17 million brightest stars in the sky have accuracies of 0.014 milliarcsec </span></p> <p>Figure 1b. Astrometric accuracy, update of Fig.5 from 1995 to our 2024 knowledge, including both parallaxes and positions. Gaia produces millions of accurate proper motions and parallaxes in addition to the positions shown in this diagram, see Gaia DR3 (2022). The important astrometry from space obtained with the HST should also be mentioned, and the very accurate astrometry by interferometry with radio telescopes.</p>
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
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.