cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.08554
title: DeepJiandu dataset for character detection and recognition on Jiandu manuscript
title: 简牍文字检测识别数据集

description: In ancient China, bamboo and wooden slips referred to as "Jiandu" served as primary mediums for documenting historical events prior to the advent of paper. These artifacts are rich in historical data and cultural significance. Accurate identification of characters on Jiandu is essential for deciphering the historical narratives they contain and plays a vital role in processing Jiandu manuscripts. We introduce the DeepJiandu dataset, specifically designed for the detection and recognition of Jiandu characters. Comprising 7,416 images annotated with 99,888 characters across 2,272 categories, this dataset addresses a variety of complex challenges encountered in Jiandu character recognition, including character degradation, diverse layouts, and variable forms and shapes. The authenticity and reliability of the DeepJiandu dataset render it an effective tool for training and evaluating models geared towards Jiandu character recognition.
description: In ancient China, bamboo and wooden slips referred to as "Jiandu" served as primary mediums for documenting historical events prior to the advent of paper. These artifacts are rich in historical data and cultural significance. Accurate identification of characters on Jiandu is essential for deciphering the historical narratives they contain and plays a vital role in processing Jiandu manuscripts. We introduce the DeepJiandu dataset, specifically designed for the detection and recognition of Jiandu characters. Comprising 7,416 images annotated with 99,888 characters across 2,272 categories, this dataset addresses a variety of complex challenges encountered in Jiandu character recognition, including character degradation, diverse layouts, and variable forms and shapes. The authenticity and reliability of the DeepJiandu dataset render it an effective tool for training and evaluating models geared towards Jiandu character recognition.
DOI: 10.57760/sciencedb.16464
title: Bibliometric Data for Islamic Management
title: Bibliometric Data for Islamic Management

description: These data is for "Unveiling the Conceptual, Social and Intellectual Structures of Islamic Management: A Bibliometric Approach" research.
description: These data is for "Unveiling the Conceptual, Social and Intellectual Structures of Islamic Management: A Bibliometric Approach" research.
DOI: 10.6084/m9.figshare.22715158.v25
title: Matbench Discovery - Data Files

description: These are the v1 data files for Matbench Discovery, a benchmark for machine learning energy models on inorganic crystal stability prediction from unrelaxed structures. It contains relaxed structures of the MP training set, initial+relaxed structures of the WBM test set, plus several checkpoints for models trained on this data specifically for this benchmark.For a description of each file, see https://matbench-discovery.materialsproject.org/data#--direct-download.The full MPtrj training set containing 1.3M structures along with their energies, forces, stresses and magmons is available at https://figshare.com/articles/dataset/23713842.
DOI: 10.57760/sciencedb.08088
title: Digital Economy and Manufacturing Data
title: 数字经济指数与制造业数据

description: The digital economy index is measured by constructing an index system by the entropy method, manufacturing data is the data of A-share manufacturing listed companies, and measuring total factor productivity.
description: The digital economy index is measured by constructing an index system by the entropy method, manufacturing data is the data of A-share manufacturing listed companies, and measuring total factor productivity.
DOI: 10.5281/zenodo.10060549
title: TroDSIF: an improved spatially downscaled solar-induced chlorophyll fluorescence product of TROPOMI dataset

description: TroDSIF is an improved spatially downscaled solar-induced chlorophyll fluorescence product of TROPOMI dataset at far-red band (wavelength at 740 nm), with a spatial resolution of 500 m and a temporal resolution of 16 days under clear-sky condition.The original TROPOMI SIF was retrieved by Guanter et al., which was available at https://doi.org/10.5270/esa-s5p_innovation-sif-20180501_20210320-v2.1-202104.
DOI: 10.57760/sciencedb.j00052.00010
title: Metaphorical representation of the concepts of poverty and wealth in the dimensions of space, color and body posture——database
title: 贫困富裕的隐喻表征 －空间、颜色和身体姿态等维度——数据集

description: Data generation: E-Prime program Data processing: repeated measurement ANOVA, one-way ANOVA, paired sample t-test and other methods are used in SPSS software. Data rejection criteria: delete the test data whose accuracy rate is less than 70%, delete the test data whose reaction time is less than 300 ms or more than 10000 MS, the test data of wrong reaction, and the test data whose reaction time exceeds three standard deviations (Hill & Lapsley, 2009; Meier & Robinson, 2004).
description: 数据产生：E-prime 程序数据处理过程：SPSS软件中运用重复测量方差分析、单因素方差分析、配对样本t检验等方法。数据剔除标准：删除正确率低于70%的被试数据，删除反应时小于300 ms或者大于10000 ms的试次数据、错误反应的试次数据，以及反应时超过三个标准差以外的试次数据(Hill & Lapsley, 2009; Meier & Robinson, 2004)。
DOI: 10.57760/sciencedb.18769
title: Control and knock out mutant of individual silk gland tissue of silkworm at prepupa stage Raw sequence reads
title: Control and knock out mutant of individual silk gland tissue of silkworm at prepupa stage Raw sequence reads

description: To Explore the changes of transcriptom after GS or GOGAT or AS or GOT1 knock out in the silk gland of silkworm at prepupa stage.
description: To Explore the changes of transcriptom after GS or GOGAT or AS or GOT1 knock out in the silk gland of silkworm at prepupa stage.
DOI: 10.57760/sciencedb.j00001.00490
title: Grape multimodal image dataset
title: 葡萄多模态图像数据集

description: Current research on grape picking point detection mainly relies on grape detection and segmentation using visible RGB images. As we know, the accuracy of grape detection and segmentation is very helpful in improving the recognition result and localization accuracy of grape picking points. However, there are significant differences in background saliency among different varieties of grapes (green, purple), and their recognition rate and segmentation accuracy are usually rather poor in natural scenarios, because of leaf occlusion, overlapping fruits, complex background, and ever-changing illumination. Additionally, the grapes differ greatly from the morphological characteristics of other fruits such as apples and pears, making it more difficult for the existing dataset to meet the research requirements of the detection and segmentation of bunch-shaped grape fruits. To this end, the construction of visible, depth and infrared-based multimodal image datasets of grapes is crucial to explore higher recognition rates and stronger generalization capabilities for grape detection and semantic segmentation models. This dataset offers high-quality multimodal image data of two grape varieties with the colors of green (white Rose) and purple (Giant Peak) under different lighting and shading conditions. The number of images is 300 and 500 each for green and purple grapes, with a total of 3938 targets and approximately 2.97 GB. By means of rotation, deflation, mis-slicing, panning, and Gaussian blur, the dataset can be augmented for training implementation of mainstream deep learning models. The dataset can provide valuable basic image data resources for multimodal image data fusion, grape semantic segmentation, and object detection, which has important practical application value for promoting research in the field of agricultural machinery and equipment intelligence.
description: 目前有关葡萄果实采摘点检测的研究主要聚焦于可见光RGB图像下的检测与分割任务，高质量的葡萄果实检测和分割有利于提高葡萄果实采摘点识别成功率和定位准确率。不同品种葡萄（青色、紫色）的背景显著性存在明显差异，在树叶遮挡、果实重叠、背景复杂和光照多变等自然场景下，其目标识别准确率和分割精度往往不高。此外，葡萄与苹果、梨子等果实形态特征差异较大，现有的相关数据集难以满足针对葡萄串形果实检测和分割的研究需求。因此，构建基于可见光、深度、红外的葡萄多模态图像数据集，对于探索更高识别率和更强泛化能力的葡萄果实目标检测和语义分割模型至关重要。本数据集收集了白玫瑰（青色）、巨峰（紫色）两个不同颜色品种的葡萄在不同光照和遮挡条件下的高质量多模态图像数据，其中青色、紫色葡萄的样本量各为300个、500个，共含3938个目标，约2.97 GB。在使用旋转、缩放、错切、平移，以及高斯模糊等图像增强手段下，可满足主流深度学习模型训练需要。本数据集可为多模态图像数据融合、葡萄果实语义分割和目标检测等领域提供宝贵的基础图像数据资源，对促进农机装备智能化领域研究具有重要的实际应用价值。
DOI: 10.57760/sciencedb.14002
title: Chinese Cultural Values and Happiness: the Composition and Expanse of Happiness Circle
title: Chinese Cultural Values and Happiness: the Composition and Expanse of Happiness Circle

description: In Experienment1, 450 participants were recruited and surveyed to examine the levels of happiness amongst Chinese undergraduates with diverse cultural values. The results showed that individuals with both traditional and modern psychological orientations had high levels of happiness. Those with higher psychological traditionality showed more satisfaction with family relationships and social happiness, while those with higher psychological modernity demonstrated a higher level of relational happiness. In Experienment2, 280 participants were recruited, and a "happiness token distribution" and "happiness importance survey" were employed to draw a 'happiness circle' for Chinese undergraduates. The results revealed that those with a higher degree of psychological traditionality assigned a greater proportion of their happiness to ascribed relationships. In contrast, those with a higher degree of psychological modernity allocated a larger share of their happiness to interactive relationships and social relationships. Individuals with lower values of both traditionality and modernity perceived themselves as the most important component in their happiness circle.
description: In Experienment1, 450 participants were recruited and surveyed to examine the levels of happiness amongst Chinese undergraduates with diverse cultural values. The results showed that individuals with both traditional and modern psychological orientations had high levels of happiness. Those with higher psychological traditionality showed more satisfaction with family relationships and social happiness, while those with higher psychological modernity demonstrated a higher level of relational happiness. In Experienment2, 280 participants were recruited, and a "happiness token distribution" and "happiness importance survey" were employed to draw a 'happiness circle' for Chinese undergraduates. The results revealed that those with a higher degree of psychological traditionality assigned a greater proportion of their happiness to ascribed relationships. In contrast, those with a higher degree of psychological modernity allocated a larger share of their happiness to interactive relationships and social relationships. Individuals with lower values of both traditionality and modernity perceived themselves as the most important component in their happiness circle.
DOI: 10.5281/zenodo.3470354
title: ai-matrix CNN_Tensorflow

description: Large files in ai-matrix.
DOI: 10.57760/sciencedb.j00001.01159
title: VLF to MF Band Classified Lightning Electric Field Change Waveform Dataset
title: VLF至MF频段雷电电场变化波形分类数据集

description: The dataset includes a total of 4 folders, where: the folder labeled as 0 contains Cloud-to-ground lightning flash waveform data, with a total of 5613 cases, including *.csv and *.png files, each *.csv corresponding to a *.png; the folder labeled as 1 contains preliminary breakdown process waveform data, with a total of 2978 cases; the folder labeled as 2 contains narrow bipolar pulse event waveform data, with a total of 2928 cases; the folder labeled as 3 contains general intracloud flash waveform data, with a total of 3059 cases.
description: The dataset includes a total of 4 folders, where: the folder labeled as 0 contains Cloud-to-ground lightning flash waveform data, with a total of 5613 cases, including *.csv and *.png files, each *.csv corresponding to a *.png; the folder labeled as 1 contains preliminary breakdown process waveform data, with a total of 2978 cases; the folder labeled as 2 contains narrow bipolar pulse event waveform data, with a total of 2928 cases; the folder labeled as 3 contains general intracloud flash waveform data, with a total of 3059 cases.
DOI: 10.57760/sciencedb.12539
title: Data of article for HPLSE2023(close-range coupling propagation)
title: HPLSE2023论文数据(近距耦合传输)

description: Including outcomes of comsol and results from propagation code
description: Including outcomes of comsol and results from propagation code
DOI: 10.5281/zenodo.3463717
title: ai-matrix SSD_VGG16_Caffe

description: Large files in ai-matrix.
DOI: 10.57760/sciencedb.07535
title: XRD data
title: XRD data

description: Three geopolymers prepared from solid waste incinerator fly ash under varying sodium silicate: sodium hydroxide ratios
description: Three geopolymers prepared from solid waste incinerator fly ash under varying sodium silicate: sodium hydroxide ratios
DOI: 10.57760/sciencedb.02918
title: Gansu Tourist Attraction Review Text Dataset
title: 甘肃旅游景点评论文本数据集

description: After crawling and processing, the Gansu tourism text dataset includes scenic spot name and user comment text, which maximizes the site information and evaluation views implied in user comments, such as scenic spot health environment, dining facilities and transportation tools.Users' opinions were manually annotated, and the subjective emotions of the review text were divided into positive, neutral and negative emotions, and the emotion confidence was calculated.The missing data set has been processed, and the processed data set has no missing data and data errors.
description: After crawling and processing, the Gansu tourism text dataset includes scenic spot name and user comment text, which maximizes the site information and evaluation views implied in user comments, such as scenic spot health environment, dining facilities and transportation tools.Users' opinions were manually annotated, and the subjective emotions of the review text were divided into positive, neutral and negative emotions, and the emotion confidence was calculated.The missing data set has been processed, and the processed data set has no missing data and data errors.
DOI: 10.57760/sciencedb.14046
title: Conservation priorities for reef-building coral biodiversity across multiple dimensions in the South China Sea
title: Conservation priorities for reef-building coral biodiversity across multiple dimensions in the South China Sea

description: Coral survey data for the South China Sea in 2022
description: Coral survey data for the South China Sea in 2022
DOI: 10.6084/m9.figshare.23909766.v1
title: Marginal land suitable for energy plants _ China

description: The spatial resolution of this dataset is 5 km, and the time step is 5 years. There are seventeen phases from 2020 to 2100. All data are stored in the commonly used geo-tiff format, and the coordinate system is WGS-84, which can be easily obtained using ARCGIS, ENVI, MATLAB and other tools. Within each geo-tiff file, there are different socioeconomic and climatic scenarios: SSP3-RCP7.0, SSP2-RCP4.5, SSP1-RCP2.6, SSP4-RCP6.0, SSP4-RCP3.4, and SSP1-RCP1.9. Within each geo-tiff file, there are eight energy plants mainly <i>Manihot esculenta</i>, <i>Ricinus communis</i>, <i>Jatropha curcas</i>, <i>Miscanthus giganteus</i>, <i>Pistacia chinensis</i>, <i>Sorghum bicolor</i>, <i>Saccharum officinarum</i>, and <i>Panicum virgatum</i>. Each geo-tiff file is named "Year".tif, where "Year" indicates the year of the data.
DOI: 10.5281/zenodo.6301079
title: Software and data release for Fermi Pulsar Timing Array

description: The archive include photon data from the Fermi Large Area Telescope, processed to enable its use for pulsar timing. It includes Python code for performing pulsar timing using Poisson likelihood and for producing pulse time-of-arrival measurements. It further includes code and scripts for constraining noise processes in the data, including the a signal from the nanohertz gravitational wave background. See README for more information.
DOI: 10.5281/zenodo.1198655
title: Front-End System2

description: This is the system which uses traditional source separation methods. It's different from system1.
DOI: 10.5281/zenodo.54764
title: Binary Pulsar Psr B1913+16 Arrival Time And Associated Files. Ref: Weisberg & Huang Apj 2016

description: These files contain arrival time and associated data for PSR B1913+16, which are usable as input to the tempo software program.  They were used for the paper "Relativistic Measurements from Timing the Binary Pulsar PSR B1913+16," Weisberg & Huang, Astrophysical Journal, 2016, in press.
description: See  the ReadMe file for details, and Weisberg & Huang,2016,  Astrophysical Journal, in press, for background.  The data are formatted for use with the tempo computer program, which is maintained on sourceforge.
description: {"references": ["Weisberg & Huang, Astrophysical Journal, in press, 2016"]}
DOI: 10.57760/sciencedb.j00001.00815
title: A dataset of arid surface water in the middle and lower reaches of the Yangtze River during extreme high-temperature in 2022
title: 长江中下游强高温期干旱水体数据集(2022年）

description: As global warming and climate change, in the summer of 2022, the Yangtze River basin in China was affected by climate anomalies and experienced the strongest high-temperature process since the complete meteorological observation records in 1961, which led to the continuous low water level of the Yangtze River tributaries and the rare phenomenon of "anti-depletion of flood season" in Poyang Lake and Dongting Lake, which were affected by climate. Lakes are indicators of global climate change, and water area changes in lakes have become one of the sensitive indicators of regional ecological environment and climate change. In this study, the GEE cloud computing platform was used to call Sentienl-1 SAR data to calculate the sentinel-1 dual-polarized water index(SDWI), and the optimal threshold value was calculated by the OTSU algorithm. The final water change monitoring data at 10m resolution for the main body of Poyang Lake, Dongting Lake and surrounding areas during the strong heat period in 2022 were obtained. This dataset is validated to have an overall accuracy of over 96% and a Kappa coefficient of 0.92. The dataset includes spatiotemporal variations in arid water bodies of the middle and lower reaches of the Yangtze River during strong high temperatures in 2022, which can provide data support and scientific basis for sustainable utilization of lake water resources in extreme weather and global climate change research and ecological evolution of lakes studies.
description: As global warming and climate change, in the summer of 2022, the Yangtze River basin in China was affected by climate anomalies and experienced the strongest high-temperature process since the complete meteorological observation records in 1961, which led to the continuous low water level of the Yangtze River tributaries and the rare phenomenon of "anti-depletion of flood season" in Poyang Lake and Dongting Lake, which were affected by climate. Lakes are indicators of global climate change, and water area changes in lakes have become one of the sensitive indicators of regional ecological environment and climate change. In this study, the GEE cloud computing platform was used to call Sentienl-1 SAR data to calculate the sentinel-1 dual-polarized water index(SDWI), and the optimal threshold value was calculated by the OTSU algorithm. The final water change monitoring data at 10m resolution for the main body of Poyang Lake, Dongting Lake and surrounding areas during the strong heat period in 2022 were obtained. This dataset is validated to have an overall accuracy of over 96% and a Kappa coefficient of 0.92. The dataset includes spatiotemporal variations in arid water bodies of the middle and lower reaches of the Yangtze River during strong high temperatures in 2022, which can provide data support and scientific basis for sustainable utilization of lake water resources in extreme weather and global climate change research and ecological evolution of lakes studies.
DOI: 10.5281/zenodo.3463677
title: ai-matrix CNN_Caffe

description: Large files in AI Matrix.
DOI: 10.5281/zenodo.3470355
title: ai-matrix CNN_Tensorflow

description: Large files in ai-matrix.
DOI: 10.5281/zenodo.3463683
title: ai-matrix DIEN

description: Large files in ai-matrix.
DOI: 10.6073/pasta/5b441f39c0876ef901068709df8f3e50
title: SBC LTER: Time series of quarterly NetCDF files of kelp biomass in the canopy from Landsat 5, 7 and 8, since 1984 (ongoing)

description: This data file represents a time series of canopy area of giant
 kelp, Macrocystis pyrifera, and bull kelp,
 Nereocystis luetkeana, and canopy biomass of
 giant kelp derived from Landsat 5 Thematic Mapper (TM), Landsat 7
 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land
 Imager (OLI), and Landsat 9 Operational Land Imager 2 satellite
 imagery, along with relevant metadata. The kelp canopy is composed
 of the portions of fronds and stipes floating on the surface of
 the water. Canopy area (m) data are given for individual 30 x 30
 meter pixels for all coastal areas of Baja California, Mexico,
 California, Oregon, and the outer coast of Washington (including
 offshore islands). Biomass data (wet weight, kg) are given for
 individual 30 x 30 meter pixels in the coastal areas extending
 from near Ano Nuevo, CA through the southern range limit in Baja
 California (including offshore islands), representing the range
 where giant kelp is the dominant canopy forming species.
 
 
 Data were derived from the three Landsat sensors listed above.
 Observations are made on a 16 day repeat cycle, for each
 instrument, but the temporal coverage is irregular because of
 cloud cover, instrument failure, and the mission length of each
 sensor (TM: 1984 – 2011, ETM+: 1999 – present, OLI: 2013 –
 present). Estimates of canopy area are derived from the fractional
 cover of kelp canopy determined from satellite surface
 reflectance. Estimates of kelp canopy biomass are derived from the
 relationship between giant kelp fractional cover determined from
 satellite surface reflectance and empirical measurements of giant
 kelp canopy biomass in long-term SBC LTER study plots obtained
 using SCUBA. The different Landsat sensors were calibrated to each
 other using simulated Landsat data derived from hyperspectral
 imagery. Missing data due to the ETM+ scan line corrector error
 were filled using a synchrony-based gap filling method.
 
 
 Data are organized into a single NetCDF file and contain the
 quarterly area and biomass means for each Landsat pixel across the
 three sensors. Relevant metadata such as number of Landsat
 estimates from which the mean was derived, the number of estimates
 from each sensor, standard error for each quarterly estimate,
 spatial coordinates, and date are all included in the file. For
 assistance with the data, please contact sbclter@msi.ucsb.edu.
DOI: 10.5281/zenodo.3463682
title: ai-matrix DIEN

description: Large files in ai-matrix.
DOI: 10.5281/zenodo.2708302
title: TROTS - The Radiotherapy Optimisation Test Set

description: The Radiotherapy Optimisation Test Set (TROTS) is an extensive set of problems originating from radiotherapy (radiation therapy) treatment planning. This dataset is created for 2 purposes: (1) to supply a large-scale dense dataset to measure performance and quality of mathematical solvers, and (2) to supply a dataset to investigate the multi-criteria optimisation and decision-making nature of the radiotherapy problem. The dataset contains 120 problems (patients), divided over 6 different treatment protocols/tumour types. Each problem contains numerical data, a configuration for the optimisation problem, and data required to visualise and interpret the results. The data is stored as HDF5 compatible Matlab files, and includes scripts to work with the dataset.

 

The set as present in this version is of date 13 May 2019. Updated versions of the Scripts and other extensions can be found at the following pages:

 

Persistent page with links: Erasmus University Rotterdam Library

Mirror project page: TROTS Mirror

Main publication: S. Breedveld & B. Heijmen, Data for TROTS - The Radiotherapy Optimisation Test Set, Data in Brief 12 (2017) 143-149