cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6784358
title: Diabetic Macular Edema VQA Dataset

description: Medical VQA dataset built from the IDRiD and eOphta datasets. The dataset contains both healthy and unhealthy fundus images. For each image, a set of pre-defined questions is generated, including questions about regions (e.g. are there hard exudates in this region?), for which an associated mask denotes the location of the region. The motivation for this dataset includes the lack of public medical VQA datasets with related questions. In our dataset, questions are related because there is a high-level question about the DME grade of the image, and associated low-level questions that can lead to the answer of the high-level question. This allows to study the consistency of a VQA model i.e. how often the model produces contradictory answers to questions about a given image. Questions about regions are also a novel feature of this dataset. The dataset can be used for general VQA purposes, and also for the more specific purpose of consistency improvement. Number of images : Train: 433 Val: 112 Test: 134 Number of QA pairs: Train: 9779 Val: 2380 Test: 1311 More details can be found here. If you use this dataset, please make sure you cite our paper: <em>@inproceedings{tascon2022consistency,<br> title={Consistency-Preserving Visual Question Answering in Medical Imaging},<br> author={Tascon-Morales, Sergio and Márquez-Neila, Pablo and Sznitman, Raphael},<br> booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},<br> pages={386--395},<br> year={2022},<br> organization={Springer}<br> }</em> Do you need annotations about logical relations? No problem; check out our DME VQA dataset with logical relations.
DOI: 10.5281/zenodo.4552919
title: The dataset of photovoltaic power plant distribution in China by 2020

description: Photovoltaic (PV) technology, as an efficient solution for mitigating impacts of climate change, has been increasingly used across the world to replace fossil-fuel power to minimize greenhouse gas emissions. With the world's highest cumulative and fastest built PV capacity, China needs to assess the environmental and social impacts of these established photovoltaic (PV) power plants. However, a comprehensive map regarding the locations and extent of the PV power plants remains to be scarce at the country scale. This study developed a workflow combining machine learning and visual interpretation methods with big satellite data to map the PV power plants in China. We applied a pixel-based Random Forest (RF) model to classify the PV power plants from composite images in 2020 with 30-meter spatial resolution on Google Earth Engine (GEE). The result classification map was further improved by a visual interpretation approach. Eventually, we established a map of PV power plants in China by 2020, covering a total area of 2917 km<sup>2</sup>. Based on the derived national PV map, we found that most PV power plants were sited on cropland, followed by barren land and grassland. In addition, the installation of PV power plants has generally decreased the vegetation cover. This new dataset is expected to be conducive to policy management, environmental assessment, and further classification of PV power plants.
DOI: 10.15468/dl.83q6zp
title: Occurrence Download

description: A dataset containing 1254 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Year is 2020",
 "TaxonKey is Ardeotis australis (J.E.Gray, 1829)"
 ]
}

 The dataset includes 1254 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048068-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.3642405
title: Water Segmentation Dataset

description: The dataset is composed of 490 images and their labelled ground truth, which consists of binary masks where zero is assigned to the background pixels and one to the water pixels. You can get the full dataset of 11900 images with their mask at the following link: https://drive.google.com/file/d/1Tm0p7XLzpLlXycSxxu2X7WENTYHh97qC/view?usp=sharing
DOI: 10.5281/zenodo.4467759
title: Dataset related to "Girth analysis and design of periodically time-varying SC-LDPC codes"

description: This archive contains the parity-check matrices of the codes considered in the paper "Girth analysis and design of periodically time-varying SC-LDPC codes". Two representations are given: the exponent matrix in time-varying form and the transposed syndrome former matrix in the "alist" format, described in http://www.inference.org.uk/mackay/codes/alist.html. The archive also contains the following MATLAB support functions:<br> <br> - "expTIfromexpTV.m" returns the exponent matrix in time-invariant form, given the exponent matrix in time-varying form<br> - "expTVfromexpTI.m" returns the exponent matrix in time-varying form, given the exponent matrix in time-invariant form<br> - "alist2sparse.m" returns a sparse binary matrix variable, given a string containing the name of the alist format file<br> - "sparse2alist.m" writes the alist format file for the input sparse binary matrix, with file name specified as second input<br>
DOI: 10.5281/zenodo.5148268
title: Parkinson-CBD

description: The database includes the raw data of the article “Neuroprotective and Symptomatic Effects of Cannabidiol in an Animal Model of Parkinson’s Disease” (doi.org/10.3390/ijms22168920). The aim of this study was to evaluate the effects of chronic treatment with cannabidiol (CBD) on Parkinson’s disease-associated neurodegenerative and neuroinflammatory processes, and motor deficits in the 6-hydroxydopamine (6-OHDA) model. Moreover, the potential mechanisms by which CBD exerted its effects in this model has been investigated. The database contains the data obtained by the following evaluations: a) immunohistochemical analysis of the extent of nigrostriatal lesion, b) motor performance assessment by cylinder test (at baseline and after 28days), apomorphine-induced rotation test and rotarod test, c) immunohistochemical analysis of neuroinflammatory response - involving microglia and astrocytes - in the substantia nigra pars compacta, investigating both cell activation and polarization, d)co-localization analysis of transient receptor potential cation channel subfamily V member 1 (TRPV1) and ciliary neurotrophic factor (CNTF) expression in astrocytes. CBD-treated animals showed a reduction of nigrostriatal degeneration accompanied by a damping of the neuroinflammatory response and an improvement of motor performance. In particular, CBD exhibited a preferential action on astrocytes, by activating TRPV1 and enhancing the endogenous neuroprotective response of CNTF. These results overall support the potential therapeutic utility of CBD in PD, as both neuroprotective and symptomatic agent.
description: Funding: This research was funded by Linnea SA
DOI: 10.5281/zenodo.6502311
title: Passive RFID indoor location dataset

description: We use four monostatic UHF antennas that operate in the frequency range from 902 to 928 MHz with a 6 dBi gain (isotropic antenna gain) for the implementation environment preparation. The equipment we used to perform the readings was the ThingMagic Mercury 6, a high-performance UHF RFID reader, supporting up to four monostatic antennas, digital inputs and outputs, and a Wi-Fi connection. Both devices are commercially available. We affixed 400 labels to objects placed side by side on the shelves in an auto parts store. The distance between the antennas and tags was 115 cm, and the distance between the antenna group was 250 cm. The reader interrogates the tags every 5 seconds and organizes the input information in a data collection formed by TagID, RSSI, Read Count (RC), True_x, and True_y. This interrogation time was defined by the minimum limit at which all tags were identified at least once by the antenna. In order to carry out data collection, the objects were placed in known positions. We performed 100 readings on each target tag, measuring the RSSI and the RC of each of the four antennas, totaling 40,000 readings.
DOI: 10.5281/zenodo.3642406
title: Water Segmentation Dataset

description: The dataset is composed of 490 images and their labelled ground truth, which consists of binary masks where zero is assigned to the background pixels and one to the water pixels. You can get the full dataset of 11900 images with their mask at the following link: https://drive.google.com/file/d/1Tm0p7XLzpLlXycSxxu2X7WENTYHh97qC/view?usp=sharing
DOI: 10.5281/zenodo.4525643
title: YOLO/Darknet BACH model foraging area

description: Trained YOLO/Darknet model to use with BACH. Detecting ants in the foraging section of experimental nests.
DOI: 10.5281/zenodo.4579982
title: Moonshine Context-Based Authentication Harvested Data

description: This is a placeholder description for the dataset to accompany our Moonshine paper at IPSN 2021.
DOI: 10.5281/zenodo.4923011
title: Dataset for gait-based authentication

description: This dataset can be used for identifying and authenticating people according to their way of walking. Information contained in the dataset is especially suitable as train and test data for machine learning models. The data for this dataset has been gathered in a corridor with a RGB (Red, Blue and Green) camera at 30 FPS (Frames Per Second). The dataset is composed by videos of 14 people walking through a 4 meter distance in the most natural way. This dataset contains 10523 JSON files composed by 2D coordinates for each point of the body provided by OpenPose. 14 people were recorded walking These keypoints are: nose, neck, right shoulder, right elbow, right wrist, left shoulder, left elbow, left wrist, right hip, right knee, right ankle, left hip, left knee, left ankle, right eye, left eye, right ear, left ear, left big toe, left small toe, left heel, right big toe, right small toe and right heel. JSON files are named as follows: Subject_XX_YY_ZZZZZZZZZZZZ_keypoints.json XX: Person ID YY: Video ID ZZZZZZZZZZZZ: Frame ID
DOI: 10.5281/zenodo.6517279
title: List of wind power projects in Vietnam

description: Historical inventory of wind power projects in Vietnam updated 2022-05-04 "post FIT race" This release is complete for projects with COD or PPA at the end of the FIT period. The number of records is 548, of which 360 refer to active projects phases, and 215 have investment costs. Each record describes a wind project phase. The table includes projects at all stages of the lifecycle. Some have been mentioned years ago and are now of historical interest only. Some have just a signed exploration MoU. All records are referenced to one or several public sources. Fields: Record status, Project stage, Project name, Owner, Location (hamlet, commune, province, region, longitude, latitude), Location type (onshore/nearshore/offshore), Capacity (MWp), Connection plan, Turbines, Investment (VND or USD), dates (MoU, Investment Licence,, Groundbreaking), Note and sources. The dataset also include: Descriptive data paper. A CSV export of the table. Python module to read the data from the CSV and python script to print the descriptive statistics.
description: Public sources only. Lacks visibility on the offshore zones proposed by Provinces for inclusion in the PDP8.
DOI: 10.5281/zenodo.4281165
title: MuSe: The Musical Sentiment Dataset

description: The MuSe (Music Sentiment) dataset contains sentiment information for 90,408 songs. We computed scores for the affective dimensions of <em>valence</em>, <em>dominance</em> and <em>arousal</em>, based on the user-generated tags that are available for each song via Last.fm. In addition, we provide artist and title metadata as well as a Spotify ID and a MusicBrainz ID, which allow researchers to extend the dataset with further metadata, such as genre or year. Though the tags themselves cannot be included in the dataset, we include a jupyter notebook in our accompanying Github repository that demonstrates how to fetch the tags of a given song from the Last.fm API (Last.fm_API.ipynb) We further include a jupyter notebook in the same repository that demonstrates how one might enrich the dataset with audio features using different endpoints of the Spotify API using the included Spotify IDs (spotify_API.ipynb). Please note that in its current form, the dataset only contains tentative spotify IDs for a subset (around 68%) of the songs.
DOI: 10.5281/zenodo.4643806
title: Dataset related to the paper "Effects of dose and duration of Robot-Assisted Gait Training on walking ability of children affected by cerebral palsy"

description: This dataset is related to the paper "Peri E, Turconi AC, Biffi E, Maghini C, Panzeri D, Morganti R, Pedrocchi A, Gagliardi C. Effects of dose and duration of Robot-Assisted Gait Training on walking ability of children affected by cerebral palsy. Technol Health Care. 2017 Aug 9;25(4):671-681. doi: 10.3233/THC-160668. PMID: 28436398." Specifically, the dataset reports GMFM-88, GMFM-D, GMFM-E and 6MWT pre and post treatment for group 1 (4 TOP sessions/week x 10 weeks) and 2 (4 RAGT sessions/week x 10 weeks). Age and GMFCS level are also reported.
DOI: 10.5281/zenodo.6533850
title: IODP Expedition 374 Photomicrographs

description: Microscopic images of discrete samples were acquired using stereo and upright light microscopes and captured on digital cameras. Image files were uploaded along with a brief description and a record of the microscopic and lighting conditions when the image was taken.
DOI: 10.5281/zenodo.4267995
title: ESC Dataset

description: ESC Dataset presented in the paper <strong>Elastic Smart Contracts in Blockchains</strong> (10.1109/JAS.2021.1004222) IEEE/CAA Journal of Automatica Sinica ( Volume: 8, Issue: 12, December 2021 In this paper, we deal with questions related to blockchains in complex Internet of Things (IoT)-based ecosystems. Such ecosystems are typically composed of IoT devices, edge devices, cloud computing software services, as well as people, who are decision makers in scenarios such as smart cities. Many decisions related to analytics can be based on data coming from IoT sensors, software services, and people. However, they are typically based on different levels of abstraction and granularity. This poses a number of challenges when multiple blockchains are used together with smart contracts. This work proposes to apply our concept of elasticity to smart contracts and thereby enabling analytics in and between multiple blockchains in the context of IoT. We propose a reference architecture for Elastic Smart Contracts and evaluate the approach in a smart city scenario, discussing the benefits in terms of performance and self-adaptability of our solution.
DOI: 10.5281/zenodo.4738404
title: Supplementary Materials for 'Smartphone Distance Estimation Based on RSSI-Fuzzy Classification Approach'

description: Supplementary Materials for 'Smartphone Distance Estimation Based on RSSI-Fuzzy Classification Approach'
DOI: 10.1594/pangaea.807488
title: Total flux, particulate carbon and nitrogen flux measured on water bottle samples during Sagar Kanya cruise SK91
DOI: 10.5281/zenodo.3753552
title: Stable psychological traits predict perceived stress related to the COVID-19 outbreak

description: This repository contains the raw dataset associated to the scientific article "Stable psychological traits predict psychological perceived stress to COVID-19 outbreak”, by L. Flesia, V. Fietta, B. Segatto, M. Monaro. Data are contained in the excel file and organized as follows: - the entire dataset used by the authors to perform statistical analysis - the training set used by the authors to train and validate ML models - the test set used by the authors to test the ML models The "Legend" file contains the description of each variable in the excel file. The step by step instructions to replicate the results of ML classification models, which are reported in the paper, including two .arff files containing the training and test set od data that can be directly run in WEKA software 3.9. The "COVID-19 QUESTIONNAIRE" file contains the English version of the questions administered to participants.
DOI: 10.5281/zenodo.4312780
title: Variation of texture anisotropy and hardness with build parameters and wall height in directed-energy-deposited 316L steel

description: Raw data associated with a paper submission.<br> " Variation of texture anisotropy and hardness with build parameters and wall height in directed-energy-deposited 316L steel" submitted to Additive Manufacturing. Contained are all the raw images used in figures, as well as csv's of any data pltoted in graphs. Raw images captured during printing of various processing parameters<br> EBSD scans (.ctf) of all disucssed samples Wall definitions (EBSD compared to paper)<br> Wall 1 - Wall A1 300 W 2750 mm/s<br> Wall 2 - Wall D 500 W 2250 mm/s<br> Wall 3 - Wall B 300 W 2250 mm/s<br> Wall 4 - Wall C 500 W 2750 mm/s<br> Wall 5 - Wall A2 300 W 2750 mm/s
DOI: 10.5281/zenodo.5130673
title: Surface Water Area Variations of Global Lakes and Reservoirs

description: Monthly surface area timeseries of large lakes and reservoirs generated from Sentinel-1 SAR backscatter data from January 2017 through December 2019.
DOI: 10.5281/zenodo.3625223
title: Water, energy and carbon fluxes and ancillary meteorological measurements of four different urban landscapes in Phoenix, AZ during 2015

description: Water, energy and carbon fluxes and ancillary meteorological measurements of four different urban landscapes in Phoenix, AZ during 2015. The measurements were done in three temporal not continuous deployment and in a permanent site as a reference. The urban landscape sites consisted in: A xeric landscape (XL), with measurements from 01/20/2015 to 03/13/2015. A parking lot (PL), with measurements from 05/19/2015 to 06/30/2015. A mesic landscape (ML), with measurements from 07/08/2015 to 09/18/2015. A reference suburban neighbourhood (REF), with measurements from 01/01/2015 to 12/13/2015. Water energy and carbon fluxes were processed using the software EdiRe. If additional data or information is needed, please contact the authors. The use of the datasets requires the citation of the next papers: - Templeton, N.P., Vivoni, E.R., Wang, Z-H., and Schreiner-McGraw, A.P. 2018. Quantifying Water and Energy Fluxes over Different Urban Land Covers in Phoenix, Arizona. Journal of Geophysical Research - Atmospheres. 123(4): 2111-2128. -Pérez-Ruiz, E. R., Vivoni, E. R. and Templeton, N. P. 2020. Urban land cover type determines the sensitivity of carbon dioxide fluxes to precipitation in Phoenix, Arizona. PLoS ONE 15(2): e0228537. https://doi.org/10.1371/journal.pone.0228537
description: Funding was provided by the U.S. Army Research Office (grant 65962‐EVII) and the National Science Foundation through grant EF1049251 "Assessing Decadal Climate Change Impacts on Urban Populations in the Southwestern United States" and grant DEB‐1026865 "CAPIV: Central Arizona‐Phoenix Long‐term Ecological Research Program."
DOI: 10.5281/zenodo.3369237
title: Validity of accelerometry in step detection and gait speed measurement in orthogeriatric patients (DATASET)

description: see README.txt for descriptions of files and formats<br>
DOI: 10.5281/zenodo.3703172
title: Gas Geochemistry of Hot Springs at the Tengchong Field, Southwest China

description: This is a dataset of the abundances and isotopic compositions for the gases discharged from Tengchong volcanic field,
DOI: 10.5281/zenodo.4584774
title: Future global land datasets with a 1-km resolution based on the SSP-RCP scenarios

description: The continuous strengthening of human activities and intensification of climate change have jointly affected global land cover changes. Scenario-based land change simulation has been widely used as a powerful tool that can assess the impact of potential land changes. However, the current future land projection products at a global scale generally suffer from deficiencies such as low resolution, unsuitable scenarios, and few types of land. Therefore, we propose a series global land projection datasets with a resolution of 1-km from 2015 to 2100, which uses the latest IPCC coupling scenarios of socioeconomic and climate change, SSP-RCP.<br> Actually, there are two subdatasets: 1) the 1-km global LULC dataset containing seven land types; 2) the 1-km global PFT-based land dataset containing 20 land types. The production of the LULC dataset combines the top-down land demand constraints provided by the official dataset of CMIP6 and the bottom-up spatial simulation executed by cellular automata (CA). The land demand from official data sources ensures the authority of the land trajectories under different SSP-RCP scenarios. The CA model is executed separately in different regions of the world to reflect spatial heterogeneity. Based on the LULC dataset, we further subdivide the its land types into 20 types according to climate data. The results show that our global land simulation achieves a satisfactory accuracy. The spatial change of various land types in each scenario appropriately reflects the storyline of the corresponding scenario. We believe that our dataset can provide stronger data support for climate research, including climate models, due to its advantages in resolution, scenarios, and land types. Please cite the corresponding paper: Chen, G., Li, X. & Liu, X. Global land projection based on plant functional types with a 1-km resolution under socio-climatic scenarios. <em>Sci Data</em> 9, 125 (2022).
DOI: 10.5281/zenodo.6477788
title: OSM buildings noisy labels dataset

description: This dataset contains tile imagery from the OpenStreetMap project alongside label masks for buildings from OpenStreetMap. Besides the original clean label set, additional noisy label sets for random noise, removed and added buildings are provided. The purpose of this dataset is to provide training data for analysing the impact of noisy labels on the performance of models for semantic segmentation in Earth observation. The code for downloading and creating the datasets as well as for performing some preliminary analyses is also provided, however it is necessary to have access to a tile server where OpenStreetMap tiles can be downloaded in sufficient amounts. To reproduce the dataset and perform analysis on it, do the following: unzip data.zip and code.zip create the folder structure from data Build and activate a python environment from environment.yml Insert the url of a suitable tile server for OSM tiles in line 76 of utils.py Execute download_OSM_dataset.py to download OSM image tiles alongside OSM labels Execute create_noisy_labels.py for the OSM dataset to create noisy label sets Divide the images and labels into train and test data. split_data.py can be used as a baseline for this, but pathnames have to be adjusted and the corresponding directories have to be created first. Call train_model.py to train a model on the data. Specify the data size and the label set by giving command line arguments as shown in train_model.sh
DOI: 10.5281/zenodo.3572834
title: Quantifying Fatigue-Damage and Failure-Precursors using Ultrasonic Coda Wave Interferometry

description: Data sets for the Publication "Quantifying Fatigue-Damage and Failure-Precursors using Ultrasonic Coda Wave Interferometry".
DOI: 10.5281/zenodo.4073071
title: SAL-Autarkic-Localization-RSSI-BLE-Dataset: SAL-RB-Dataset

description: The SAL-Autarkic-Localization-RSSI-BLE-Dataset (SAL-RB-Dataset) is a set of more than 20 000 labeled Received Signal Strength Indicator (RSSI) measurements for indoor localization with Bluetooth Low Energy (BLE)
DOI: 10.1594/pangaea.807489
title: Total flux, particulate carbon and nitrogen flux measured on water bottle samples during Sagar Kanya cruise SK99
DOI: 10.5281/zenodo.2387103
title: Underwater database

description: Underwater database
DOI: 10.5281/zenodo.4555588
title: Sentiment analysis of Dutch tweets: a comparison of automatic and manual sentiment analysis

description: This dataset was used for the bachelor thesis of Lynette Joosten, where Dutch-language tweets were analyzed using NLP for sentiment analysis