cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.j00133.00545
title: AI face-swap fraud experimental data
title: AI换脸诈骗实验数据

description: 该数据集包括从通信视频中提取伪造人脸视频帧特征FFV、从网络流量中提取流量描述特征NT_D、流量负载数据特征序列PD和流量定时特征NT_T。
description: 该数据集包括从通信视频中提取伪造人脸视频帧特征FFV、从网络流量中提取流量描述特征NT_D、流量负载数据特征序列PD和流量定时特征NT_T。
DOI: 10.57760/sciencedb.j00133.00544
title: Accident case information extraction data
title: 事故案例信息抽取数据

description: The annotated dataset contains 4399 chemical accident case data, and each case document is composed of 315 characters on average.
description: The annotated dataset contains 4399 chemical accident case data, and each case document is composed of 315 characters on average.
DOI: 10.57760/sciencedb.23579
title: Zhou Jie, Wang Dongyi, Dai Qinquan, Xia Sudi. Data on Q Analysis Results of Generative AI Prompt Strategies
title: [6]周洁,王东毅,代沁泉,夏苏迪.生成式AI提示词策略Q分析结果数据

description: This dataset contains the results of Q analysis on generative AI prompt strategies.
description: This dataset contains the results of Q analysis on generative AI prompt strategies.
DOI: 10.57760/sciencedb.23577
title: Zhou Jie, Wang Dongyi, Dai Qinquan, Xia Sudi. Demographic Distribution Data of P Samples Involved in Three Types of Strategies
title: 周洁,王东毅,代沁泉,夏苏迪.三种策略类型所涉及P样本的人口统计学分布数据

description: This dataset provides information on the demographic distribution of P samples involved in three types of strategies. It offers detailed insights into how these samples are distributed across various demographic categories, providing researchers with an in-depth understanding of the diversity and representativeness of the samples.
description: This dataset provides information on the demographic distribution of P samples involved in three types of strategies. It offers detailed insights into how these samples are distributed across various demographic categories, providing researchers with an in-depth understanding of the diversity and representativeness of the samples.
DOI: 10.57760/sciencedb.23574
title: Zhou Jie, Wang Dongyi, Dai Qinquan, Xia Sudi. Data on the Demographic Distribution of Valid P Sample
title: 周洁,王东毅,代沁泉,夏苏迪.有效P样本的人口统计学分布数据

description: This dataset provides information on the demographic distribution of valid P samples. It offers detailed insights into how the samples are distributed across categories such as gender, age, and educational level.
description: This dataset provides information on the demographic distribution of valid P samples. It offers detailed insights into how the samples are distributed across categories such as gender, age, and educational level.
DOI: 10.57760/sciencedb.23572
title: Zhou Jie, Wang Dongyi, Dai Qinquan, Xia Sudi. Data on the Effectiveness Scores of Generative AI Prompt Strategies Sorted by Efficacy.
title: 周洁,王东毅,代沁泉,夏苏迪.生成式AI的提示词策略的有效性得分排序数据

description: This dataset contains information on the effectiveness scores of generative AI prompt strategies sorted by their efficacy. It provides insights into the relative effectiveness of different prompt strategies in generative AI applications.
description: This dataset contains information on the effectiveness scores of generative AI prompt strategies sorted by their efficacy. It provides insights into the relative effectiveness of different prompt strategies in generative AI applications.
DOI: 10.57760/sciencedb.23571
title: Zhou Jie, Wang Dongyi, Dai Qinquan, Xia Sudi. Factor Loading Table (Complete) Data
title: 周洁,王东毅,代沁泉,夏苏迪.因子负荷表（全部）数据

description: This dataset contains the complete data of the factor loading table, which is a crucial component in factor analysis. The factor loading table illustrates the relationship between the observed variables and the underlying factors, indicating how much each variable loads on each factor. This information is essential for understanding the structure of the data and the relative importance of each variable in relation to the factors.
description: This dataset contains the complete data of the factor loading table, which is a crucial component in factor analysis. The factor loading table illustrates the relationship between the observed variables and the underlying factors, indicating how much each variable loads on each factor. This information is essential for understanding the structure of the data and the relative importance of each variable in relation to the factors.
DOI: 10.57760/sciencedb.23570
title: Zhou Jie, Wang Dongyi, Dai Qinquan, Xia Sudi. Data on Generative AI Prompt Strategies
title: 周洁,王东毅,代沁泉,夏苏迪.生成式AI提示词策略数据

description: Interviewees' Statements for Factor Analysis
description: Interviewees' Statements for Factor Analysis
DOI: 10.57760/sciencedb.j00133.00542
title: EM-FCJS Factual Consistency Review and FC-JDSM Model Experimental Dataset
title: EM-FCJS事实一致性评测和FC-JDSM模型实验数据集

description: EM-FCJS Factual Conformance Evaluation Model experimentation process on CAIL2020 dataset, and on FC-JDSM model experimentation and results
description: EM-FCJS Factual Conformance Evaluation Model experimentation process on CAIL2020 dataset, and on FC-JDSM model experimentation and results
DOI: 10.57760/sciencedb.j00133.00539
title: DOD_Contract
title: DOD_Contract

description: The procurement contract data publicly released by the US DOD in 2021~2023 were processed, and 9096 valid data were obtained.
description: The procurement contract data publicly released by the US DOD in 2021~2023 were processed, and 9096 valid data were obtained.
DOI: 10.57760/sciencedb.j00133.00538
title: Evaluation of the Patent Similarity Measurement
title: 专利相似度评价

description: Patent similarity evaluation and comparison evaluation dataset, including the target patent and its comparison patent set
description: Patent similarity evaluation and comparison evaluation dataset, including the target patent and its comparison patent set
DOI: 10.57760/sciencedb.j00133.00537
title: Multidimensional Personality Calculation and Analysis Dataset
title: 多维人格计算与分析数据集

description: This data is used for multi-personality computation and analysis based on narrative texts, taking Romance of the Three Kingdoms as an example, and the data contains data and results from all stages of the whole experimental process.
description: This data is used for multi-personality computation and analysis based on narrative texts, taking Romance of the Three Kingdoms as an example, and the data contains data and results from all stages of the whole experimental process.
DOI: 10.57760/sciencedb.j00133.00532
title: ACL anthology network and chart source files
title: ACL anthology network and chart source files

description: This file mainly contains the main experimental data and related chart source files of this paper。The AAN dataset encompasses 49 years of data from 1965 to 2014, including original papers from ACL (Association for Computational Linguistics) journals, conferences, and workshops. Each paper contains various information such as title, author, publication year, venues, and citations.
description: This file mainly contains the main experimental data and related chart source files of this paper。The AAN dataset encompasses 49 years of data from 1965 to 2014, including original papers from ACL (Association for Computational Linguistics) journals, conferences, and workshops. Each paper contains various information such as title, author, publication year, venues, and citations.
DOI: 10.57760/sciencedb.22738
title: Replication Data for TDN Model
title: TDN模型的公开数据

description: The public data of the TDN model contains six types of data sources in the United States from 2018 to 2022, including strategic planning, scientific and technological reports, fund projects, conference papers, journal papers and patent documents.
description: The public data of the TDN model contains six types of data sources in the United States from 2018 to 2022, including strategic planning, scientific and technological reports, fund projects, conference papers, journal papers and patent documents.
DOI: 10.57760/sciencedb.j00133.00524
title: The top 2000 films and derivatives data set released in Chinese Mainland from 1998 to 2023
title: 1998年到2023年在中国大陆上映票房排名前2000的电影及衍生品数据集

description: The data on the top 2000 films released in Chinese Mainland from 1998 to 2023 are gathered. The data used for modeling comes from various heterogeneous data sources, including movie information data, movie IP information data, and movie IP derivative information data, on data platforms such as the original warehouse IP data network, EPS platform, and Yi'en Entertainment data network.
description: The data on the top 2000 films released in Chinese Mainland from 1998 to 2023 are gathered. The data used for modeling comes from various heterogeneous data sources, including movie information data, movie IP information data, and movie IP derivative information data, on data platforms such as the original warehouse IP data network, EPS platform, and Yi'en Entertainment data network.
DOI: 10.57760/sciencedb.j00133.00519
title: The Vehicle Trajectory Data of Shenzhen
title: The Vehicle Trajectory Data of Shenzhen

description: The study utilizes vehicle trajectory data from Shenzhen in August 2020, released by DiDi Chuxing for the ACM SIGSPATIAL GISCUP 2021 competition. The dataset contains over 8.6 million travel trajectories along with detailed road network topology information. To ensure experimental reliability while controlling the computational cost of spatio-temporal graph neural networks, we selected 20,000 high-frequency road segments during peak hours (7:00-23:00) to build a representative small-scale dataset for experimental analysis.
description: The study utilizes vehicle trajectory data from Shenzhen in August 2020, released by DiDi Chuxing for the ACM SIGSPATIAL GISCUP 2021 competition. The dataset contains over 8.6 million travel trajectories along with detailed road network topology information. To ensure experimental reliability while controlling the computational cost of spatio-temporal graph neural networks, we selected 20,000 high-frequency road segments during peak hours (7:00-23:00) to build a representative small-scale dataset for experimental analysis.
DOI: 10.57760/sciencedb.19800
title: Research on Integrating Temporal Information and Dynamic Structural Evolution for Knowledge Graph Completion Models-The source file of the chart
title: 融合时态信息和图结构动态演化的知识图谱补全模型研究-图表源文件

description: Research on the related experimental charts of the knowledge graph completion model that integrates temporal information and the dynamic evolution of graph structure
description: Research on the related experimental charts of the knowledge graph completion model that integrates temporal information and the dynamic evolution of graph structure
DOI: 10.57760/sciencedb.22636
title: APP Privacy Policy Compliance Analysis Dataset
title: APP隐私政策合规性分析数据集

description: The Xiaomi App Store includes 140 privacy policies across 14 fields. These fields are:Finance and Wealth Management, Home Life, Chat and Social, Travel and Transportation, Practical Tools, Video and Audio, Sports and Fitness, Reading, Logistics and Shopping, Office Efficiency, News, Education, Healthcare, and Gaming and Entertainment.
description: The Xiaomi App Store includes 140 privacy policies across 14 fields. These fields are:Finance and Wealth Management, Home Life, Chat and Social, Travel and Transportation, Practical Tools, Video and Audio, Sports and Fitness, Reading, Logistics and Shopping, Office Efficiency, News, Education, Healthcare, and Gaming and Entertainment.
DOI: 10.57760/sciencedb.j00133.00518
title: Dataset of U.S. congressional hearings
title: 美国国会听证会数据集

description: This dataset contains part of the text data from the hearings of the 118th Congress. We selected and annotated the texts of hearings from 8 committees closely related to China, which includes 4 House committees, 3 Senate committees, and 1 joint committee, totaling 63 hearings and 143,041 sentences.
description: This dataset contains part of the text data from the hearings of the 118th Congress. We selected and annotated the texts of hearings from 8 committees closely related to China, which includes 4 House committees, 3 Senate committees, and 1 joint committee, totaling 63 hearings and 143,041 sentences.
DOI: 10.57760/sciencedb.j00133.00516
title: Chinanews.com Instant News Dataset from 2021 to 2023
title: 中国新闻网2021年至2023年即时新闻数据集

description: News titles, channels and release times of Chinanews.com's instant news from 2021 to 2023.
description: News titles, channels and release times of Chinanews.com's instant news from 2021 to 2023.
DOI: 10.57760/sciencedb.22518
title: Supervised Multi-Domain Scientific and Technology Entities in Short Texts
title: 科技短文本中有监督的多领域科技实体

description: Technology short texts mainly consist of three parts: briefings on domestic and international strategic trends, policy and frontier updates, and a global technology map. The time span covers from January 2019 to June 2024. Three master's students in information management manually annotated the multi-domain technology entities contained within, resulting in a total of 4,416 supervised data entries.
description: Technology short texts mainly consist of three parts: briefings on domestic and international strategic trends, policy and frontier updates, and a global technology map. The time span covers from January 2019 to June 2024. Three master's students in information management manually annotated the multi-domain technology entities contained within, resulting in a total of 4,416 supervised data entries.
DOI: 10.57760/sciencedb.j00133.00514
title: Preprocessed CMU-MOSEI dataset for Multi-modal Sentiment Analysis
title: Preprocessed CMU-MOSEI dataset for Multi-modal Sentiment Analysis

description: The preprocessed CMU-MOSEI dataset is a comprehensive dataset for multi-modal bridge-based social media multi-label sentiment analysis. This dataset covers user-generated content with various emotional and sentiment expressions. The processing of the dataset includes extracting video subtitle text, audio features, and visual features from the video, and these data are cleaned and preprocessed for sentiment analysis tasks.The dataset includes a collection of 2,199 opinion video clips. Each video clip contains three forms of content: verbal text-based language, visual content through perceived gestures and facial expressions, and auditory content through intonation and prosody. Each video clip is labeled with an emotional score.
description: The preprocessed CMU-MOSEI dataset is a comprehensive dataset for multi-modal bridge-based social media multi-label sentiment analysis. This dataset covers user-generated content with various emotional and sentiment expressions. The processing of the dataset includes extracting video subtitle text, audio features, and visual features from the video, and these data are cleaned and preprocessed for sentiment analysis tasks.The dataset includes a collection of 2,199 opinion video clips. Each video clip contains three forms of content: verbal text-based language, visual content through perceived gestures and facial expressions, and auditory content through intonation and prosody. Each video clip is labeled with an emotional score.
DOI: 10.57760/sciencedb.06581
title: ACE2005 Event Detection English Data Set
title: ACE2005 Event Detection English Data Set

description: The ACE2005 English dataset contains 599 English documents, including 8 event types, 33 subtypes, and 35 parameter role annotations.
description: The ACE2005 English dataset contains 599 English documents, including 8 event types, 33 subtypes, and 35 parameter role annotations.
DOI: 10.57760/sciencedb.j00133.00503
title: A smart water quality monitoring dataset for interdisciplinary literature recognition
title: A smart water quality monitoring dataset for interdisciplinary literature recognition

description: This dataset was mainly obtained through literature search tools such as Web of Science and Research Rabbit. The process of data acquisition includes two steps. Firstly, by constructing retrieval equations, partial literature data (referred to as raw data) from three fields, namely smart water quality monitoring (interdisciplinary field), artificial intelligence (non interdisciplinary field), and traditional water quality analysis (non interdisciplinary field), were retrieved separately in Web of Science. Then, based on the DOI of the raw data, literature search was conducted in the Research Rabbit system to obtain the references and citations of each raw data. The dataset contains a total of 5826 articles, including 2436 interdisciplinary articles and 3390 non interdisciplinary articles.
description: This dataset was mainly obtained through literature search tools such as Web of Science and Research Rabbit. The process of data acquisition includes two steps. Firstly, by constructing retrieval equations, partial literature data (referred to as raw data) from three fields, namely smart water quality monitoring (interdisciplinary field), artificial intelligence (non interdisciplinary field), and traditional water quality analysis (non interdisciplinary field), were retrieved separately in Web of Science. Then, based on the DOI of the raw data, literature search was conducted in the Research Rabbit system to obtain the references and citations of each raw data. The dataset contains a total of 5826 articles, including 2436 interdisciplinary articles and 3390 non interdisciplinary articles.
DOI: 10.5281/zenodo.15593164
title: Supporting data - Physics-guided machine learning for wind-farm power prediction: Toward interpretability and generalizability

description: Supporting data for the publication:






Title: Physics-Guided Machine Learning for Wind-Farm Power Prediction: Toward Interpretability and Generalizability

Authors: Navid Zehtabiyan-Rezaie, Alexandros Iosifidis, Mahdi Abkar

PRX Energy 2, 013009 – Published 30 March 2023

DOI: https://doi.org/10.1103/PRXEnergy.2.013009





 

Intro: Here, we provide datasets containing turbine-level efficiencies for seven wind farm cases, based on the layouts of operational wind farms, such as the Horns Rev 1 (HR1) offshore wind farm in Denmark and the Lillgrund offshore wind farm in Sweden. Details on the specifications of turbines, farms, and the characteristics of the inflow in each case are provided in Table I in our PRX paper.

Structures of the datasets: The datasets include efficiency values for all turbines in each case for different incoming wind directions, with a step of 2 degrees. The turbine efficiency is the ratio of its power to the extracted power if it were standing upstream. Turbine-level data for Cases 1-4 contain 28,800 data points. Case 5 adds 14,400 data points, and Cases 6 and 7 add 17,280 data points to the dataset (60,480 data points in total).  

The datasets include 11 different features of data for each turbine:

- Turbine's ID- Turbine's x coordinate- Turbine's y coordinate- Turbine's rotor diameter- Turbine's hub height- Turbine's thrust coefficient- Turbine's power coefficient- Inflow velocity at the hub height- Inflow turbulence level at the hub height- Wind direction- Turbine's efficiency

How to cite: To cite our datasets, please use the following Bibtex records:@article{PRXEnergy.2.013009,  title = {Physics-Guided Machine Learning for Wind-Farm Power Prediction: Toward Interpretability and Generalizability},  author = {Zehtabiyan-Rezaie, Navid and Iosifidis, Alexandros and Abkar, Mahdi},  journal = {PRX Energy},  volume = {2},  issue = {1},  pages = {013009},  numpages = {17},  year = {2023},  month = {Mar},  publisher = {American Physical Society},  doi = {10.1103/PRXEnergy.2.013009},  url = {https://link.aps.org/doi/10.1103/PRXEnergy.2.013009}}
DOI: 10.5281/zenodo.15593163
title: Supporting data - Physics-guided machine learning for wind-farm power prediction: Toward interpretability and generalizability

description: Supporting data for the publication:






Title: Physics-Guided Machine Learning for Wind-Farm Power Prediction: Toward Interpretability and Generalizability

Authors: Navid Zehtabiyan-Rezaie, Alexandros Iosifidis, Mahdi Abkar

PRX Energy 2, 013009 – Published 30 March 2023

DOI: https://doi.org/10.1103/PRXEnergy.2.013009





 

Intro: Here, we provide datasets containing turbine-level efficiencies for seven wind farm cases, based on the layouts of operational wind farms, such as the Horns Rev 1 (HR1) offshore wind farm in Denmark and the Lillgrund offshore wind farm in Sweden. Details on the specifications of turbines, farms, and the characteristics of the inflow in each case are provided in Table I in our PRX paper.

Structures of the datasets: The datasets include efficiency values for all turbines in each case for different incoming wind directions, with a step of 2 degrees. The turbine efficiency is the ratio of its power to the extracted power if it were standing upstream. Turbine-level data for Cases 1-4 contain 28,800 data points. Case 5 adds 14,400 data points, and Cases 6 and 7 add 17,280 data points to the dataset (60,480 data points in total).  

The datasets include 11 different features of data for each turbine:

- Turbine's ID- Turbine's x coordinate- Turbine's y coordinate- Turbine's rotor diameter- Turbine's hub height- Turbine's thrust coefficient- Turbine's power coefficient- Inflow velocity at the hub height- Inflow turbulence level at the hub height- Wind direction- Turbine's efficiency

How to cite: To cite our datasets, please use the following Bibtex records:@article{PRXEnergy.2.013009,  title = {Physics-Guided Machine Learning for Wind-Farm Power Prediction: Toward Interpretability and Generalizability},  author = {Zehtabiyan-Rezaie, Navid and Iosifidis, Alexandros and Abkar, Mahdi},  journal = {PRX Energy},  volume = {2},  issue = {1},  pages = {013009},  numpages = {17},  year = {2023},  month = {Mar},  publisher = {American Physical Society},  doi = {10.1103/PRXEnergy.2.013009},  url = {https://link.aps.org/doi/10.1103/PRXEnergy.2.013009}}