cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7424460
title: Image Dataset and Trained Detection Models (based on YOLOv5 and EfficientNet) of Mangrove Crabs of China

description: A manually annotated image dataset of crabs collected from 16 mangrove forests in China, and a set of trained detection models based on YOLOv5 and EfficientNet. We provide a simple UI that is designed by us, please cite it if helpful.
description: {"references": ["Ultralytics-YOLOv5 (2022). https://github.com/ultralytics/yolov5", "Tzutalin (2015) LabelImg. Git code. https://github.com/tzutalin/labelImg", "R-Core-Team (2022) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/", "Kuhn, M. (2022) caret: classification and regression training. https://CRAN.R-project.org/package=caret", "Wickham et al., (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686, https://doi.org/10.21105/joss.01686", "Hadley Wickham (2007). Reshaping Data with the reshape Package. Journal of Statistical Software, 21(12), 1-20. URL http://www.jstatsoft.org/v21/i12/", "Xiao N (2018). _ggsci: Scientific Journal and Sci-Fi Themed Color Palettes for 'ggplot2'_. R package version 2.9, ", "L\u00fcdecke et al., (2021). see: An R Package for Visualizing Statistical Models. Journal of Open Source Software, 6(64), 3393. https://doi.org/10.21105/joss.03393", "Oksanen J, Simpson G, Blanchet F, Kindt R, Legendre P, Minchin P, O'Hara R, Solymos P, Stevens M, Szoecs E, Wagner H, Barbour M, Bedward M, Bolker B, Borcard D, Carvalho G, Chirico M, De Caceres M, Durand S, Evangelista H, FitzJohn R, Friendly M, Furneaux B, Hannigan G, Hill M, Lahti L, McGlinn D, Ouellette M, Ribeiro Cunha E, Smith T, Stier A, Ter Braak C, Weedon J (2022). _vegan: Community Ecology Package_. R package version 2.6-2, ", "Dray S, Bauman D, Blanchet G, Borcard D, Clappe S, Guenard G, Jombart T, Larocque G, Legendre P, Madi N, Wagner HH (2022). _adespatial: Multivariate Multiscale Spatial Analysis_. R package version 0.3-16, ", "Tan, M. & Le, Q.V. (2019) EfficientNet: Rethinking model scaling for convolutional neural networks. 36th International Conference on Machine Learning, ICML 2019, 2019-June, 10691-10700. https://doi.org/10.48550/arXiv.1905.11946", "Liang, G., Chen, J., Xie, J., Deng, Z. & Cui, Y. (2021) Classification of fine-grained species of marine organisms based on multi-scale fusion. ACM International Conference Proceeding Series, 94-100. https://doi.org/10.1145/3485314.3485321", "Hou, Q., Zhou, D. & Feng, J. (2021) Coordinate attention for efficient mobile network design. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 13708-13717. https://doi.org/10.1109/CVPR46437.2021.01350"]}
DOI: 10.5281/zenodo.7435630
title: Image Dataset and Trained Detection Models (based on YOLOv5 and EfficientNet) of Mangrove Crabs of China

description: A manually annotated image dataset of crabs collected from 16 mangrove forests in China, and a set of trained detection models based on YOLOv5 and EfficientNet. We provide a simple UI that is designed by us, please cite it if helpful.
description: {"references": ["Ultralytics-YOLOv5 (2022). https://github.com/ultralytics/yolov5", "Tzutalin (2015) LabelImg. Git code. https://github.com/tzutalin/labelImg", "R-Core-Team (2022) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/", "Kuhn, M. (2022) caret: classification and regression training. https://CRAN.R-project.org/package=caret", "Wickham et al., (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686, https://doi.org/10.21105/joss.01686", "Hadley Wickham (2007). Reshaping Data with the reshape Package. Journal of Statistical Software, 21(12), 1-20. URL http://www.jstatsoft.org/v21/i12/", "Xiao N (2018). _ggsci: Scientific Journal and Sci-Fi Themed Color Palettes for 'ggplot2'_. R package version 2.9, ", "L\u00fcdecke et al., (2021). see: An R Package for Visualizing Statistical Models. Journal of Open Source Software, 6(64), 3393. https://doi.org/10.21105/joss.03393", "Oksanen J, Simpson G, Blanchet F, Kindt R, Legendre P, Minchin P, O'Hara R, Solymos P, Stevens M, Szoecs E, Wagner H, Barbour M, Bedward M, Bolker B, Borcard D, Carvalho G, Chirico M, De Caceres M, Durand S, Evangelista H, FitzJohn R, Friendly M, Furneaux B, Hannigan G, Hill M, Lahti L, McGlinn D, Ouellette M, Ribeiro Cunha E, Smith T, Stier A, Ter Braak C, Weedon J (2022). _vegan: Community Ecology Package_. R package version 2.6-2, ", "Dray S, Bauman D, Blanchet G, Borcard D, Clappe S, Guenard G, Jombart T, Larocque G, Legendre P, Madi N, Wagner HH (2022). _adespatial: Multivariate Multiscale Spatial Analysis_. R package version 0.3-16, ", "Tan, M. & Le, Q.V. (2019) EfficientNet: Rethinking model scaling for convolutional neural networks. 36th International Conference on Machine Learning, ICML 2019, 2019-June, 10691-10700. https://doi.org/10.48550/arXiv.1905.11946", "Liang, G., Chen, J., Xie, J., Deng, Z. & Cui, Y. (2021) Classification of fine-grained species of marine organisms based on multi-scale fusion. ACM International Conference Proceeding Series, 94-100. https://doi.org/10.1145/3485314.3485321", "Hou, Q., Zhou, D. & Feng, J. (2021) Coordinate attention for efficient mobile network design. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 13708-13717. https://doi.org/10.1109/CVPR46437.2021.01350"]}
DOI: 10.34740/kaggle/dsv/4854359
title: Rotten Tomatoes Film Dataset
DOI: 10.5281/zenodo.7538371
title: Intervention design and details.

description: <strong>The supplemental material of "Digital Addiction Intervention for Children: A Scoping Review"</strong> <strong>Appendix A</strong> Table S1: Intervention design and details.
DOI: 10.5281/zenodo.7538370
title: Intervention design and details.

description: <strong>The supplemental material of "Digital Addiction Intervention for Children: A Scoping Review"</strong> <strong>Appendix A</strong> Table S1: Intervention design and details.
DOI: 10.6084/m9.figshare.21901377.v1
title: Data S1.xlsx

description: In situ Raman detection of the vent fluid at the Onsen site and diffuse fluid at the Faxian site based on a RiP-Hv probe
DOI: 10.6084/m9.figshare.21901380
title: bus driver driving style

description: data attached to article Predictive validity of the Multidimensional Driving Style Inventory in bus drivers’ accident involvement: a follow-up study
DOI: 10.34740/kaggle/dsv/4854461
title: Rotten Tomatoes Series Dataset
DOI: 10.5281/zenodo.4650822
title: CCG Starter Data Kit: Cameroon

description: A starter data kit for Cameroon
DOI: 10.5281/zenodo.4650823
title: CCG Starter Data Kit: Cameroon

description: A starter data kit for Cameroon
DOI: 10.5281/zenodo.4756738
title: CCG Starter Data Kit: Cameroon

description: A starter data kit for Cameroon
DOI: 10.5281/zenodo.6542300
title: CCG Starter Data Kit: Cameroon

description: A starter data kit for Cameroon
DOI: 10.5281/zenodo.7526331
title: CCG Starter Data Kit: Cameroon

description: A starter data kit for Cameroon
DOI: 10.6084/m9.figshare.21387471.v1
title: testdata1.sql

description: this database for Pre-trained model based feature envy
DOI: 10.6084/m9.figshare.21387471
title: testdata1.sql

description: this database for Pre-trained model based feature envy
DOI: 10.5281/zenodo.7538432
title: Renta media por persona y nivel de formación en los 21 distritos del Ayuntamiento de Madrid (2016-2019)

description: Este conjunto de datos ha sido utilizado en el proyecto REFOMAD. Incluye información sobre la renta media por persona, el nivel de formación educativa de los residentes mayores de 25 años y el número de centros educativos en cada uno de los 21 distritos del Ayuntamiento de Madrid durante los años 2016-2019. El nivel de formación tiene 6 niveles: no sabe leer ni escribir, bachiller elemental, formación profesional, titulados medios, estudios universitarios y nivel de estudios no consta. Los centros educativos se clasifican también en 6 niveles: escuelas infantiles municipales, escuelas infantiles públicas de la Comunidad Autónoma de Madrid, escuelas infantiles privadas, colegios públicos infantil/primaria, institutos públicos de educación secundaria y colegios privados infantil/primaria. Los datos de renta fueron proporcionados por el INE, los datos sobre la formación fueron obtenidos mediante encuestas propias realizadas por el equipo REFOMAD y los datos de los centros educativos fueron solicitados al portal de datos abiertos del Ayuntamiento de Madrid. Los datos están en formato XLSX y tienen un tamaño de 109.6 kB. Los datos fueron prepreocesados y curados utilizando herramientas de software libre como NumPy y pandas en Python versión 3.10.6.
DOI: 10.5281/zenodo.7538431
title: Renta media por persona y nivel de formación en los 21 distritos del Ayuntamiento de Madrid (2016-2019)

description: Este conjunto de datos ha sido utilizado en el proyecto REFOMAD. Incluye información sobre la renta media por persona, el nivel de formación educativa de los residentes mayores de 25 años y el número de centros educativos en cada uno de los 21 distritos del Ayuntamiento de Madrid durante los años 2016-2019. El nivel de formación tiene 6 niveles: no sabe leer ni escribir, bachiller elemental, formación profesional, titulados medios, estudios universitarios y nivel de estudios no consta. Los centros educativos se clasifican también en 6 niveles: escuelas infantiles municipales, escuelas infantiles públicas de la Comunidad Autónoma de Madrid, escuelas infantiles privadas, colegios públicos infantil/primaria, institutos públicos de educación secundaria y colegios privados infantil/primaria. Los datos de renta fueron proporcionados por el INE, los datos sobre la formación fueron obtenidos mediante encuestas propias realizadas por el equipo REFOMAD y los datos de los centros educativos fueron solicitados al portal de datos abiertos del Ayuntamiento de Madrid. Los datos están en formato XLSX y tienen un tamaño de 109.6 kB. Los datos fueron prepreocesados y curados utilizando herramientas de software libre como NumPy y pandas en Python versión 3.10.6.
DOI: 10.5281/zenodo.4725467
title: CCG Starter Data Kit: Chad

description: A starter data kit for Chad
DOI: 10.5281/zenodo.4725466
title: CCG Starter Data Kit: Chad

description: A starter data kit for Chad
DOI: 10.5281/zenodo.4729555
title: CCG Starter Data Kit: Chad

description: A starter data kit for Chad
DOI: 10.5281/zenodo.4756761
title: CCG Starter Data Kit: Chad

description: A starter data kit for Chad
DOI: 10.5281/zenodo.7526333
title: CCG Starter Data Kit: Chad

description: A starter data kit for Chad
DOI: 10.34740/kaggle/dsv/4854628
title: YouTube Daily
DOI: 10.34740/kaggle/dsv/4854640
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.34740/kaggle/dsv/4854479
title: MyDramaList Movies & Drama's
DOI: 10.34740/kaggle/dsv/4854227
title: cyclistic_historical_trip_data
DOI: 10.5281/zenodo.7415103
title: Synthetic dataset used for validating MDSPACE method for analyzing continuous conformational variability of biomolecules in cryo-EM single particle images

description: Synthetic dataset used for validating MDSPACE method for analyzing continuous conformational variability of biomolecules in cryo-EM single particle images. A README file with the contents of the dataset is included.
DOI: 10.5281/zenodo.7415104
title: Synthetic dataset used for validating MDSPACE method for analyzing continuous conformational variability of biomolecules in cryo-EM single particle images

description: Synthetic dataset used for validating MDSPACE method for analyzing continuous conformational variability of biomolecules in cryo-EM single particle images. A README file with the contents of the dataset is included.
DOI: 10.5281/zenodo.5498087
title: CCG Starter Data Kit: Chile

description: A starter data kit for Chile
DOI: 10.5281/zenodo.5498088
title: CCG Starter Data Kit: Chile

description: A starter data kit for Chile
DOI: 10.5281/zenodo.7526334
title: CCG Starter Data Kit: Chile

description: A starter data kit for Chile
DOI: 10.5281/zenodo.5718819
title: Synthetic cryo electron subtomograms containing biomolecular complexes with continuous conformational variability, used for validating TomoFlow method

description: Two datasets used for validating TomoFlow method, an optical-flow based approach for analyzing continuous conformational variability of biomolecular complexes in cryo electron subtomograms. The TomoFlow method and the methods used to synthesize the two test datasets have been fully described in the following article: "M. Harastani, M. Eltsov, A. Leforestier, S. Jonic, TomoFlow: Analysis of continuous conformational variability of macromolecules in cryogenic subtomograms based on 3D dense optical flow, Journal of Molecular Biology (2021), doi: https://doi.org/10.1016/j.jmb.2021.167381". Additionally, this article describes a test of TomoFlow using one experimental cryo electron tomography dataset (available in EMPIAR and EMDB databases under the accession codes EMPIAR-10679 and EMD-12699).
description: {"references": ["M. Harastani, M. Eltsov, A. Leforestier, S. Jonic, TomoFlow: Analysis of continuous conformational variability of macromolecules in cryogenic subtomograms based on 3D dense optical flow, Journal of Molecular Biology (2021), doi: https://doi.org/10.1016/j.jmb.2021.167381"]}
DOI: 10.5281/zenodo.5718820
title: Synthetic cryo electron subtomograms containing biomolecular complexes with continuous conformational variability, used for validating TomoFlow method

description: Two datasets used for validating TomoFlow method, an optical-flow based approach for analyzing continuous conformational variability of biomolecular complexes in cryo electron subtomograms. The TomoFlow method and the methods used to synthesize the two test datasets have been fully described in the following article: "M. Harastani, M. Eltsov, A. Leforestier, S. Jonic, TomoFlow: Analysis of continuous conformational variability of macromolecules in cryogenic subtomograms based on 3D dense optical flow, Journal of Molecular Biology (2021), doi: https://doi.org/10.1016/j.jmb.2021.167381". Additionally, this article describes a test of TomoFlow using one experimental cryo electron tomography dataset (available in EMPIAR and EMDB databases under the accession codes EMPIAR-10679 and EMD-12699).
description: {"references": ["M. Harastani, M. Eltsov, A. Leforestier, S. Jonic, TomoFlow: Analysis of continuous conformational variability of macromolecules in cryogenic subtomograms based on 3D dense optical flow, Journal of Molecular Biology (2021), doi: https://doi.org/10.1016/j.jmb.2021.167381"]}
DOI: 10.5281/zenodo.6891965
title: A Priority Map for Vision-Language Navigation - Datasets

description: This archive contains full versions of the datasets and additional data presented in the following paper: A Priority Map for Vision-and-Language Navigation with Trajectory Plans and Feature-Location Cues A priority map module (PM-VLN) boosts the performance of transformer-based architectures in navigation tasks by combining temporal sequence alignment and feature-level localisation in cross-modal inputs. The module is pretrained on trajectory estimation and a multi-objective task that pairs location estimation with cross-modal sentence prediction. Two datasets are introduced for the auxiliary tasks: - TR-NY-PIT-central - a set of path traces for routes in two urban locations. - MC-10 - a set of samples with multimodal inputs representing landmarks in 10 US cities. Full details and links for this research are available at the following link: https://jasonarmitage-res.github.io/projects/priority_map/ Additional data comprising path traces for routes in Manhattan and language tokens for the Touchdown task are provided for training and evaluating the PM-VLN and framework on the Touchdown benchmark. Please refer to the following link for details on the Touchdown dataset and StreetLearn environment: https://sites.google.com/view/streetlearn/touchdown
description: This research is supported by the Digital Visual Studies program at the University of Zurich and funded by the Max Planck Society.
DOI: 10.5281/zenodo.6891964
title: A Priority Map for Vision-Language Navigation - Datasets

description: This archive contains full versions of the datasets and additional data presented in the following paper: A Priority Map for Vision-and-Language Navigation with Trajectory Plans and Feature-Location Cues A priority map module (PM-VLN) boosts the performance of transformer-based architectures in navigation tasks by combining temporal sequence alignment and feature-level localisation in cross-modal inputs. The module is pretrained on trajectory estimation and a multi-objective task that pairs location estimation with cross-modal sentence prediction. Two datasets are introduced for the auxiliary tasks: - TR-NY-PIT-central - a set of path traces for routes in two urban locations. - MC-10 - a set of samples with multimodal inputs representing landmarks in 10 US cities. Full details and links for this research are available at the following link: https://jasonarmitage-res.github.io/projects/priority_map/ Additional data comprising path traces for routes in Manhattan and language tokens for the Touchdown task are provided for training and evaluating the PM-VLN and framework on the Touchdown benchmark. Please refer to the following link for details on the Touchdown dataset and StreetLearn environment: https://sites.google.com/view/streetlearn/touchdown
description: This research is supported by the Digital Visual Studies program at the University of Zurich and funded by the Max Planck Society.
DOI: 10.34740/kaggle/dsv/4854872
title: 2021 World Population (updated daily)
DOI: 10.5281/zenodo.7308281
title: Instituições Estaduais Ambientais - BR: Mapeamento do conteúdo dos sites

description: As instituições estaduais ambientais no Brasil tratam de diversas matérias em razão da multidisciplinaridade própria da temática ligada ao meio ambiente. A diversidade de atribuições dessas organizações públicas também deriva dos encargos estabelecidos pela legislação. A planilha indica as opções de conteúdo disponibilizadas nas primeiras páginas dos sites das instituições estaduais ambientais brasileiras, a fim de contribuir para o conhecimento desta variedade de conteúdo organizacional de caráter público.
DOI: 10.5281/zenodo.7308282
title: Instituições Estaduais Ambientais - BR: Mapeamento do conteúdo dos sites

description: As instituições estaduais ambientais no Brasil tratam de diversas matérias em razão da multidisciplinaridade própria da temática ligada ao meio ambiente. A diversidade de atribuições destas organizações públicas também deriva dos encargos estabelecidos pela legislação. A planilha indica as opções de conteúdo disponibilizadas nas primeiras páginas dos sites das instituições estaduais ambientais brasileiras, a fim de contribuir para o conhecimento desta variedade de conteúdo organizacional de caráter público.
DOI: 10.5281/zenodo.7538540
title: Instituições Estaduais Ambientais - BR: Mapeamento do conteúdo dos sites

description: As instituições estaduais ambientais no Brasil tratam de diversas matérias em razão da multidisciplinaridade própria da temática ligada ao meio ambiente. A diversidade de atribuições dessas organizações públicas também deriva dos encargos estabelecidos pela legislação. A planilha indica as opções de conteúdo disponibilizadas nas primeiras páginas dos sites das instituições estaduais ambientais brasileiras, a fim de contribuir para o conhecimento desta variedade de conteúdo organizacional de caráter público.
DOI: 10.25919/5shc-5209
title: Parkes observations for project P1162 semester 2022OCTS_04

description: Pulsar timing is a powerful tool in studying pulsar physics. Discovering more exotic pulsar systems or timing pulsars with higher precision is an essential part of pulsar astronomy. As a recently discovered millisecond pulsar, PSR J1402+13 is an interesting source for follow-up timing observations. First, its spin-down rate is the highest among known millisecond pulsars according to initial data. This spin-down rate, if confirmed, will place stringent constraints on the spin-up process predicted by pulsar recycling theories. Second, and more importantly, J1402+13 is a very promising candidate for pulsar timing arrays, with an achievable precision at the level of 6 nanoseconds for 60 minutes observation with Parkes. We thus apply for 18.7 hours to conduct dedicated timing observations of J1402+13 over the period of half a year (and more observations in the future semesters). This project will derive an ephemeris of the system, which is valuable to understand its formation and evolution history. Furthermore, the observations will allow us to evaluate the timing performance of J1402+13 and its suitability to be included in pulsar timing arrays.
DOI: 10.34740/kaggle/dsv/4854960
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.5498091
title: CCG Starter Data Kit: Colombia

description: A starter data kit for Colombia
DOI: 10.5281/zenodo.5498092
title: CCG Starter Data Kit: Colombia

description: A starter data kit for Colombia
DOI: 10.5281/zenodo.7526335
title: CCG Starter Data Kit: Colombia

description: A starter data kit for Colombia
DOI: 10.6084/m9.figshare.21901464
title: Appendix_F_on_SCW.pdf

description: The appendix to the paper "The Structural Complexity of Chinese Words and Its Relationship with Word Frequency"
DOI: 10.6084/m9.figshare.21901464.v1
title: Appendix_F_on_SCW.pdf

description: The appendix to the paper "The Structural Complexity of Chinese Words and Its Relationship with Word Frequency"
DOI: 10.57967/hf/0274
title: hatebr
DOI: 10.25919/r2s6-2h50
title: Parkes observations for project P1166 semester 2022OCTS_04

description: Observationally, there are two basic types of Fast Radio Bursts (FRBs): repeating and non-repeating ones. In the southern sky, there are very limited number of repeaters we can monitor unless more are confirmed to repeat. Large sample of FRBs released by the CHIME telescope seems to tell us the morphology difference between repeater and non-repeaters, that is, repeating FRBs tend to exhibit more complex pulse profile but more narrowband radio emission. Using this dichotomy, we may be able to find more repeaters from the known sample. In this project, we select FRB 20180923B, which has not been followed up to date, as the target of this proposed observation. The source has a quite broad pulse width of 20 ms and its brightness is close with most repeaters of with similar dispersion. We request 16-hour observing with the Parkes ultra-wide-bandwidth receiver (UWL) to search for possible repeating events. Even non-detection can still constrain that most of FRBs are not active repeaters.
DOI: 10.21227/3vrm-vc05
title: Tracking data of Multi-robot formation controll(sztu2023)

description: This data package（.zip） includes data of follower robots'  motion track、errors  and velocities in five simulatd experimental cases：(1),(2): set obstacle range on 0.8m and 1.0m，2 groups；(3):  oneside situation,  and the number of follower robots rises to 5.   (4)：complex environment, which we place more obstacles.   （5): change the lead-follower formation  （6),(7)：two types of formation tracks, circle and straight line，compare follower1，2.Each file contains all data of each case: except .jpg and .png, .m file contains the simulated experiment's code associated with the article which links to the Dataset.
DOI: 10.34740/kaggle/dsv/4855019
title: Divorce Rates Data: Should You Get Married?
DOI: 10.6084/m9.figshare.21431733
title: Type of home-school cooperation

description: The database recorded information on the parents of 3,509 primary school students from grade 1 to grade 5 (average age range 34.5±1.26 years) in Jiangsu Province, Sichuan Province and Shanxi Province, China, were investigated using the Home-School Cooperation
DOI: 10.6084/m9.figshare.21431733.v2
title: GENERATED.xlsx

description: The database recorded information on childhood abuse, self-esteem, coping styles and depression levels among 409 male inmates