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12,237
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Dataset results
12,237 results for “2019”
Survey results: PARALLEL COMP MATH Fall 2019
<p>We introduced GitHub Classroom and other new technology and asked the students for their feedback on these new technolgoies.</p>
Datasets and Supporting Materials for the IPIN 2019 Competition Track 3 (Smartphone-based, off-site)
<p>This package contains the datasets and supplementary materials used in the IPIN 2019 Competition (Pisa, Italy).</p><p><strong>Contents:</strong></p><ol><li>IPIN2019_Call4Competition: Call for competition and main rules</li><li>IPIN2019_Track03_TechnicalAnnex: Technical annex describing the Track 3 of the competition.</li><li>01-Logfiles: This folder contains a subfolder with the 50 (40 + 10) training logfiles, a subfolder with the 9 validation logfiles, and a subfolder with the 1 blind evaluation logfile as provided to competitors.</li><li>02-Supplementary_Materials: This folder contains the Matlab/octave parser, the raster maps, the vector maps and the visualization of the training routes.</li><li>03-Evaluation: This folder contains the scripts used to calculate the competition metric, the 75th percentile on the 99 evaluation points. The ground truth is also provided in MatLab format and as a CSV file. Since the results must be provided with a 2Hz freq. starting from apptimestamp 0, the GT includes the closest timestamp matching the timing provided by competitors.</li></ol><p><strong>Please, cite the following works when using the datasets included in this package:</strong></p><ul><li>Jiménez, A. R.; Perez-Navarro, A.; Crivello, A.; Mendoza-Silva, G.; Ortiz, M.; Perul, J.; Seco, F. and Torres-Sospedra, J. Datasets and Supporting Materials for the IPIN 2019 Competition Track 3 (Smartphone-based, off-site), Zenodo 2019. <a href="http://dx.doi.org/10.5281/zenodo.3606765">http://dx.doi.org/10.5281/zenodo.3606765</a></li><li>Potorti, F.; Park, S.; Palumbo, F.; Girolami, M.; Barsocchi, P.; Lee, S.; Torres-Sospedra, J.; Jimenez Ruiz, A. R.; Perez-Navarro, A.; Mendoza-Silva, G. M.; Seco, F.; Ortiz, M.; Perul, J.; Renaudin, V.; Kang, H.; Park, S. Y.; Lee, J. H.; Park, C. G.; Ha, J.; Han, J.; Park, C.; KIM, K.; Lee, Y.; GYE, S.; Lee, K.; Kim, E.; Choi, J.-S.; Choi, Y.-S.; Talwar, S.; Cho, S. Y.; Ben-Moshe, B.; Sansano, E.; Chidlovskii, B.; Kronenwett, N.; Prophet, S.; Landay, Y.; Marbel, R.; Peng, A.; Wu, B.; MA, C.; Poslad, S.; Selviah, D.; Wu, W.; Ma, Z.; Zhang, W.; Wei, D.; Yuan, H.; Jiang, J.-B.; Liu, J.-W.; Su, K.-W.; Leu, J.-S.; Nishiguchi, K.; Bousselham, W.; Uchiyama, H.; Thomas, D.; Shimada, A.; Taniguchi, R.-I.; Cortés, V.; Lungenstrass, T.; Ashraf, I.; Lee, C.; Usman Ali, M.; Im, Y.; Kim, G.; Eom, J.; Hur, S.; Park, Y.; Opiela, M.; Moreira, A.; Nicolau, M. J.; Pendão, C.; Silva, I.; Meneses, F.; Costa, A.; Trogh, J.; Plets, D.; Chien, Y.-R.; Chang, T.-Y.; Fang, S.-H.; Tsao, Y. The IPIN 2019 Indoor Localisation Competition - Description and Results IEEE Access Vol. 8, pp. 206674-206718, 2020. https://doi.org/10.1109/ACCESS.2020.3037221</li></ul><p><strong>Additional information can be found at:</strong></p><ul><li><a href="http://evaal.aaloa.org/2019/call-for-competitions">http://evaal.aaloa.org/2019/call-for-competitions</a></li></ul><p><strong>For any further questions about the database and this competition track, please contact: </strong></p><ul><li>Joaquín Torres (<a href="mailto:jtorres@uji.es?subject=IPIN%202016%20Competition%20Dataset%20(Zenodo)">jtorres@uji.es</a>,<a href="mailto:torres@ubikgs.com?subject=Contact%20from%20Zenodo%203606765">torres@ubikgs.com</a>) UBIK Geospatial Solutions S.L., Spain<br>Institute of New Imaging Technologies, Universitat Jaume I, Spain.</li><li>Antonio R. Jiménez (<a href="mailto:antonio.jimenez@csic.es?subject=IPIN%202016%20Competition%20Dataset%20(Zenodo)">antonio.jimenez@csic.es</a>) Center of Automation and Robotics (CAR)-CSIC/UPM, Spain.</li></ul>
Base de datos del artículo El Congreso a través de Twitter. El mensaje político ante un parlamento sin mayorías (2019-2020)
<p>Base de datos del artículo <em>El Congreso a través de Twitter. El mensaje político ante un parlamento sin mayorías (2019-2020)</em></p>
AIOSAT datasets for Gent's integration phase in October 2019
<p>Datasets from the two days of integration and testing of the second version of the AIOSAT hardware in Gent, around the parking lot defined as the test scenario in Belgium, hosted by Hulpverleningszone Centrum.</p> <p>This dataset presents the data from 3 firefighter nodes with information about GNSS; UWB interdistance, IMU, Lora and Bluetooth Long Range communication systems</p>
Data for Mouton Atlas of Languages and Cultures (ed. Gerd Carling). Mouton De Gruyter 2019.
<p>These are the basic data sets (.xml), which are used for creating maps, graphs and results of the volume Mouton Atlas of Languages and Cultures (Mouton De Gruyter 2019). Data has been extracted from the database Diachronic Atlas of Comparative Linguistics during 2018 and prepared for publication. Data is printed in the paper and online version of the book. The data is made available by permission from the publishers.</p> <p>NB. In using the data, quoting of the book is required: Carling, Gerd (ed.) 2019. Mouton Atlas of Languages and Cultures. Berlin - New York: Mouton de Gruyter.</p>
Level 2 spectra of the 290 - 500 nm solar irradiance measured at Aosta - Saint Christophe by the Bentham DTMc300 with serial number 5541 in 2006 - 2019
<p>The provided dataset includes the Level 2 spectral measurements (in Watt/m<sup>2</sup>) of the solar irradiance in the range 290 - 500 nm, performed by the Bentham DTMc300 spectroradiometer with serial number 5541. The particular instrument performs automated continuous, high quality measurements at Aosta - Saint Christophe, Italy (45.7° N, 7.4° E, 570 m a.s.l.) since 2006. The Level 2 spectra are re-evaluated and homogenized and are currently available for the period 24 July 2006 - 8 July 2019. Each file contains the spectra for one day. The time (in UTC) for the measurements at 290, 400, and 500 nm is also provided for each spectral scan.</p>
Dataset Versatile Layout Understanding via Conjugate Graph (ICDAR 2019)
<p>Contains the datasets with tables used in the following paper:</p> <p><a href="https://europe.naverlabs.com/research/publications/versatile-layout-understanding-via-conjugate-graph/">Versatile Layout Understanding via Conjugate Graph</a>. Animesh Prasad, Hervé Déjean and Jean-Luc Meunier, International Conference on Document Analysis and Recognition (ICDAR), Sydney, Australia, 20–25 September 2019.</p>
Comparing the numerical results in [Vater S., N. Beisiegel, and J. Behrens, 2019] to results produced by the FLASH implementation in Samoa2
<p>This document contains plots for the results produced by the FLASH implementation in Samoa<sup>2</sup> (<a href="https://gitlab.lrz.de/samoa/samoa">https://gitlab.lrz.de/samoa/samoa</a>), using the scenarios defined in <em>[Vater S., N. Beisiegel, and J. Behrens, 2019]</em>.</p> <p>Initialization data for the okushiri scenario is also provided.</p>
Medical Concept Embeddings for SNOMED-CT (Jan 2019 version)
<p>This dataset contains the SNOMED-CT medical concept embeddings trained using the following text and graph embedding methods.</p> <ul> <li>Averaged Word Embedding (300)</li> <li>ELMo (1024)</li> <li>Universal Sentence Encoder (512)</li> <li>BERT (768)</li> <li>Deepwalk (128)</li> <li>Node2Vec (128)</li> <li>HARP (128)</li> <li>LINE (128)</li> </ul> <p>The tar file contains eight JSON files corresponding to the aforementioned embedding techniques. The number (in parenthesis) besides each embedding method represents the dimensionality of the embedding. Each JSON file contains a python dictionary of the form</p> <p>SNOMED concept ID (String): Embedding (List).</p> <p>If you find this resource useful in your research, please consider citing our paper:</p> <p>"Pattisapu, N., Patil, S., Palshikar, G. and Varma, V., Medical Concept Normalization by Encoding Target Knowledge, Proceedings of Machine Learning Research 116:246–259, 2020 Machine Learning for Health (ML4H) at NeurIPS 2019"</p> <p>Warning: The dataset size is large (~12 GB). Please ensure that you have sufficient network bandwidth and disk space before requesting a download.</p>
TweetsKB (Part 7, April 2018 - April 2019)
<p><strong>TweetsKB</strong><strong> </strong>is a public RDF corpus of anonymized data for a large collection of <strong>annotated </strong>tweets. The dataset currently contains data for more than <strong>1.9 billion tweets</strong>, spanning more than 7 years (February 2013 - April 2020). Metadata information about the tweets as well as extracted <strong>entities</strong>, <strong>sentiments</strong>, <strong>hashtags</strong>, <strong>user mentions</strong> and <strong>URLs </strong>are exposed in RDF using established RDF/S vocabularies*. Example queries and more information are available through TweetsKB's home page: <a href="https://data.gesis.org/tweetskb/">https://data.gesis.org/tweetskb/</a>.</p> <p> </p> <p><em>* For the sake of privacy, we anonymize user IDs and we do not provide the text of the tweets.</em></p>
Chelatna pike suppression in 2018 and 2019
Northern pike are an invasive species in southcentral Alaska and have caused the decline and extirpation of salmonids and other native fish populations across the region. Over the last decade, adaptive management of invasive pike populations has included population suppression, eradication, outreach, angler engagement, and research to mitigate damages from pike where feasible. Pike suppression efforts have been focused in open drainages of the northern and western Cook Inlet areas, and eradication efforts have been primarily focused on the Kenai Peninsula and the municipality of Anchorage. Between 2010 and 2020, almost 40,000 pike were removed from southcentral Alaska waters as a result of suppression programs, and pike have been successfully eradicated from over 20 lakes and creeks from the Kenai Peninsula and Anchorage, nearly completing total eradication of pike from known distributions in those areas. Northern pike control actions are tailored to the unique conditions of waters prioritized for their management, and all efforts support the goal of preventing further spread of this invasive aquatic apex predator to vulnerable waters.
Supplementary materials for Perl et al 2019
<p>Supplementary dataset for Perl et al, 2019, "Human non-olfactory cognition phase-locked with inhalation", published in Nature Human Behavior</p>
DS5_LH_ Lodola et al_Sci Adv_2019_Immunofluorescence
<p>NFKB and ROS immunofluorescence assays. </p>
Input and output data from numerical simulations associated to paper Biggs and Annen (2019)
<p>Input and output files produced by code Heat2D_Car and used to produce the results published in Biggs and Annen (2019)</p>
Datos Scopus USTA ( hasta 2019)
<p>Consolidado de los datos de las publicaciones de autores con filiación USTA (Colombia) en la plataforma Scopus. Parte del servicio de vigilancia tecnológica del Observatorio de Cienciometría de la Universidad Santo Tomás.</p> <p>Ecuación de búsqueda</p> <p>( AFFILORG ( "universidad santo tomás" OR "universidad santo tomas" OR "saint thomas aquinas university" OR "saint thomas university" OR "santo tomás university" OR "santo tomas university" ) ) AND (EXCLUDE ( AF-ID,"Universidad del Norte Santo Tomas de Aquino" 60000851)) AND ( EXCLUDE (AF-ID,"Universidad FASTA de la Fraternidad de Agrupaciones Santo Tomas de Aquino" 60027203)) AND ( EXCLUDE ( AF-ID,"Universidad Santo Tomas, Santiago" 60009128) AND (EXCLUDE ( AF-ID,"University of Santo Tomas Hospital" 60071489)) AND (EXCLUDE ( AF-ID,"St. Thomas University, Miami" 60026192)) AND (EXCLUDE ( AF-ID,"Saint Thomas University, Fredericton" 60018810)) AND (EXCLUDE ( AF-ID,"Saint Thomas University" 119159448)) AND (EXCLUDE ( AF-ID,"Universidad Santo Tomas de Oriente y Medio Día" 115480135)) AND (EXCLUDE ( AF-ID,"Santo Tomas University Hospital" 113845649)) AND (EXCLUDE ( AF-ID,"Family Health Center of Los Lagos" 114163380)) AND (EXCLUDE ( AF-ID,"Universidad Santo Tomás Talca" 120956329)) AND ( EXCLUDE (AF-ID,"Santo Tomas University" 112880585)) AND ( EXCLUDE ( AF-ID,"University of Santo Tomas, Manila" 60071488)) AND ( EXCLUDE (AF-ID,"University of St. Thomas, Minnesota" 60009635)) AND ( EXCLUDE (AF-ID," Saint Thomas Hospital Nashville" 60028779)) AND ( EXCLUDE (AF-ID,"University of St. Thomas - Houston" 60030200)) AND ( EXCLUDE (AF-ID,"Universidad Finis Terrae" 60105368)) AND ( EXCLUDE ( AFFILORG ("Santo Tomas University, Concepción, Chile" OR "Pontificia Universidad Santo Tomas de Aquino, Chile" OR "Escuela de Medicina Veterinaria, Universidad Santo Tomás, Ejercito 146, Santiago de Chile, Chile" OR "Saint Thomas University School of Law, United States" OR "Canadian Citizenship and Human Rights, Saint Thomas University, Fredericton" OR "Saint Thomas University of Florida" OR "Saint Thomas University, United States")) AND ( EXCLUDE ( TITLE-ABS-KEY-AUTH("Santo Tomas University, Concepción, Chile" OR "Pontificia Universidad Santo Tomas de Aquino, Chile" OR "Escuela de Medicina Veterinaria, Universidad Santo Tomás, Ejercito 146, Santiago de Chile, Chile" OR "Saint Thomas University School of Law, United States" OR "Canadian Citizenship and Human Rights, Saint Thomas University, Fredericton" OR "Saint Thomas University of Florida" OR "Saint Thomas University, United States")) </p>
Datos WOS USTA (hasta 2019)
<p>Consolidado de los datos de las publicaciones de autores con filiación USTA (Colombia) en la plataforma WOS. Parte del servicio de vigilancia tecnológica del Observatorio de Cienciometría de la Universidad Santo Tomás.</p> <p>Estrategia de búsqueda:</p> <p>(OO=universidad santo tomas AND CU=COLOMBIA) OR (OO=saint thomas aquinas univer sity AND CU=COLOMBIA) OR (OO=saint thomas university AND CU=COLOMBIA) OR (OO=santo tomás university AND CU=COLOMBIA) OR (OO=santo tomas university AND CU=COLOMBIA) OR (OO= Univ Santo Tomas AND CU=COLOMBIA) NOT ( (OO=Univ Santo Tomas AND CU=Philippines) OR (OO=Univ Santo Tomas Hosp AND CU=Philippines) OR (OO=Univ Santo Tomas AND CU=Chile))</p>
Exploring Societal Impact: global researcher attitudes, raw data from a 2019 survey
<p>This data was generated as part of a global survey with more than 9,000 researchers, conducted in June 2019 by Springer Nature. It investigates the global attitudes of researchers towards societal impact, with specific relation to the UN's sustainable development goals. Associated presentations summarising the findings of this research can be found at <a href="https://www.doi.org/10.5281/zenodo.3964940">https://www.doi.org/10.5281/zenodo.3964940</a>, <a href="https://www.doi.org/10.5281/zenodo.3964942">https://www.doi.org/10.5281/zenodo.3964942</a>, and <a href="https://www.doi.org/10.5281/zenodo.3964944">https://www.doi.org/10.5281/zenodo.3964944</a>. Access the Jupyter notebook: <a href="https://www.doi.org/10.5281/zenodo.3957929">https://www.doi.org/10.5281/zenodo.3957929</a>. </p>
Georeferenced IFC files exported within the GeoBIM benchmark 2019 - Task 2
<p>Result of the georeferencing test performed within the Task 2 - georeferencing IFC of the GeoBIM benchmark 2019, funded as a Scientific Initiative 2019 by the International Society of Photogrammetry and Remote Sensing (ISPRS) and co-funded by the European association for Spatial Data Research (EuroSDR).</p> <p>Full details and additional resources about the project are available in the project website: https://3d.bk.tudelft.nl/projects/geobim-benchmark/</p> <p>The dataset results from the collaboration of the authors with all the participants to the benchmark, listed at https://3d.bk.tudelft.nl/projects/geobim-benchmark/participants.html</p>
Anopheles stephensi occurrence data 1985 - 2019
<p>In 2012, an unusual outbreak of malaria occurred in Djibouti City followed by increasingly severe annual outbreaks. Investigations revealed the presence of an Asian mosquito species; Anopheles stephensi, which thrives in urban environments. Anopheles stephensi has since been identified in Ethiopia and Sudan.</p> <p>By combining data for An. stephensi across its full range (Asia, Arabian Peninsula, Horn of Africa) with spatial models that identify the species' preferred habitat, we provide evidence-based maps predicting the possible African locations where An. stephensi could establish if allowed to spread. </p>
Data sets to all figures in our article Appl. Phys. Lett. 115, 193507 (2019)
<p>Data sets to all figures in our article in Applied Physics Letters:<br> <br> Quartz tuning fork—A potential low temperature thermometer in high magnetic fields<br> Appl. Phys. Lett. <strong>115</strong>, 193507 (2019)<br> doi: 10.1063/1.5124736</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.