cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/rvfxvxy94b.1
title: Stand-Up Comedy Data

description: Researchers and comedy enthusiasts seeking more profound insights into Indonesian stand-up comedy can leverage a rich dataset from Kompas TV's YouTube channel. This dataset, brimming with user interactions and remarks on stand-up comedy videos, is a comprehensive archive reflecting audience engagement and perceptions of various comedic performances. By meticulously analyzing this trove of user-generated content, researchers can unravel prevailing trends, identify standout comedians, and discern cultural nuances influencing audience preferences. Such an endeavor facilitates a profound understanding of the Indonesian comedic landscape, shedding light on evolving tastes, emerging comedic styles, and the reception of specific comedy specials. Ultimately, this dataset emerges as a valuable tool for academic inquiry and a guiding compass for comedians and content creators, informing their craft and enabling them to better connect with their audience.
DOI: 10.17632/xd74wbskxg.1
title: Coding of Data Cleaning and Processing

description: The specific process was mainly implemented through the MySQL database. Some invalid data was removed. The first part of the removed data was incomplete and error data. Because these data could cause mistakes to the results. The second part of removed data was the trip over 60 minutes and 14 kilometers because these trips were considered personal use such as shopping instead of commuting. Finally, this research used a total of 437,053 trip records about public bike systems and 7,051 trip records about bike sharing systems as the dataset.
DOI: 10.17632/f58j9j8zyx.1
title: Problems And Prospects Of Primary Healthcare:A Case Study Of Odo-owa Oke-Ero Local Government Kwara State 

description: The research topic "Prospects of Primary Health Care: A Case Study of Odo-owa Oke-Ero Local" explores the potential outcomes and challenges associated with the primary health care system within the specific context of Odo-owa Oke-Ero Local. The study aims to uncover critical insights into the effectiveness, accessibility, and impact of primary health care services on the local community's health and well-being.Hypothesis: The central hypothesis of this research is that an improved and well-functioning primary health care system has the potential to significantly enhance the overall health outcomes and quality of life for residents in Odo-owa Oke-Ero Local. Specifically, the research hypothesizes that:Accessible and comprehensive primary health care services directly correlate with reduced incidence of preventable diseases and improved health indicators among the local population.Community engagement and awareness-building initiatives positively influence the utilization of primary health care services, resulting in more timely and appropriate healthcare-seeking behavior.Adequate training, staffing, and resources allocated to the primary health care facilities lead to higher patient satisfaction and improved healthcare delivery, subsequently contributing to better health outcomes.Identification of existing gaps and challenges within the primary health care system can inform targeted interventions that have the potential to enhance its efficacy and impact.Through rigorous data collection, analysis, and comparison with existing literature, this study seeks to either validate or refute these hypotheses, contributing to a deeper understanding of the prospects of primary health care services in Odo-owa Oke-Ero Local. The findings could offer valuable insights for policy recommendations, resource allocation, and community-based initiatives aimed at strengthening primary health care delivery and improving overall health outcomes in similar contexts.
DOI: 10.17632/gd85f25pdw.1
title: Cryptocurrency

description: This data is about green finance and cryptocurrency market dynamics
DOI: 10.17632/p3hfgr5j3m.1
title: INDONESIAN HOAX NEWS DETECTION DATASET

description: This dataset is part of this study: I. Y. R. Pratiwi, R. A. Asmara and F. Rahutomo, "Study of hoax news detection using naïve bayes classifier in Indonesian language," 2017 11th International Conference on Information & Communication Technology and System (ICTS), Surabaya, 2017, pp. 73-78. doi: 10.1109/ICTS.2017.8265649 keywords: {Bayes methods;Internet;natural language processing;pattern classification;Web sites;naïve bayes classifier;Indonesian language;online news articles;internet;websites;hoax recall;hoax precision;hoax news article detection;automatic hoax news detection;fake news article;search news;Information and communication technology;Google;Uniform resource locators;Hoax news detection;dataset;naïve bayes classifier}, URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8265649&isnumber=8265591 The dataset contains five files: 1. 250 news with valid hoax label.csv The file contains 250 Indonesian news texts with hoax/ valid label 2. 250 news labelling process.xlsx The file contains information on the labelling process of 10 news topics. The news links are labelled by three referees wether it is hoax or valid. The final label is derived by voting procedure of the three referees. 3. 250 news experiment documentation.xlsx The file contains experiments documentation on the dataset by NBC classifier. The experiments were conducted three times with different training/ testing size. The schemes of training-testing are: 60-40, 70-30, and 80-20. 4. 600 news with valid hoax label.csv The file contains 600 Indonesian news texts with hoax/ valid label 5. 600 news labelling process.xlsx The file contains information on the labelling process of 12 news topics. The news links are labelled by three referees wether it is hoax or valid. The final label is derived by voting procedure of the three referees.
DOI: 10.17632/drgg7v5zjx.1
title: Cross-modal thalamocortical plasticity

description: Data used for generating figures in Rodriguez et al. paper.
DOI: 10.17632/wzjv88gftp.1
title: Python & R Scripts

description: The six scripts used to execute the quantitative CT workflow. Script 1 to 5 are made in Python, 6 in R.
DOI: 10.17632/rjj84brk2p.1
title: Transactional Retail

description: The statistical details of this dataset were provided below:

Database size (total no of transactions) : 88125
Number of items : 16469
Minimum Transaction Size : 1
Average Transaction Size : 10.305497872340425
Maximum Transaction Size : 76
Standard Deviation Transaction Size : 8.162050490723274
Variance in Transaction Sizes : 66.61982418275215
Sparsity : 0.9993742487174485

Please cite the following reference:

Rage Uday Kiran, Masaru Kitsuregawa: Efficient discovery of correlated patterns using multiple minimum all-confidence thresholds. J. Intell. Inf. Syst. 45(3): 357-377 (2015)

URL: https://link.springer.com/article/10.1007/s10844-014-0314-7

Disclaimer: This dataset was downloaded from fimi repository - http://fimi.uantwerpen.be/data/
DOI: 10.17632/32d6r6r6zk.4
title: Big Data acquired by Internet of Things-enabled Industrial Multichannel Wireless Sensors Networks for Active Monitoring and Control in the Smart Grid Industry 4.0.

description: • The data provided in this paper provides can be used for efficient monitoring and control of the power generation and distribution processes in the smart grid. • The data provided in this paper can be used for the integration of distributed power generation sources into the power transmission and distribution systems within realistic network scenarios. • It can also support reliable and dynamic data capacity requirements of different types of advanced cyber-physical systems equipped with sensors and devices to operate them optimally, either manual or automatic controls, and provide information about their operations to the utilities. • In case of faults, the designed scheme intelligently monitoring and identifies the faulty systems located in a remote position and notifies the user in real-time, so that appropriate actions can be taken to supply steady electricity to the customers.
DOI: 10.17632/vygnwb6b2p.3
title: AI Skin Cancer Systematic Review

description: AI Skin Cancer Databases
DOI: 10.17632/yvnv94jym6.1
title: Emotional intelligence and teamwork results of university students

description: The dataset explores the relationship between emotional intelligence and teamwork results of university students.
DOI: 10.17632/3fkbbw9w36.2
title: CRYPTOCURRENCY IN MODERN DAYS: PROSPECTS AND CHALLENGES

description: Cryptocurrency is a non-regulated form of currency that has gained popularity due to its potential to disrupt traditional financial systems and provide greater financial inclusion. The cryptocurrency market is much more volatile and riskier than traditional markets, and there are various risks associated with it, such as hacking and fraud. The lack of clear guidelines and regulations from governments and financial institutions is a major challenge for the cryptocurrency market. Despite the challenges, the cryptocurrency market has the potential to revolutionize the financial landscape. This paper examines the overall impression of Cryptocurrency in the market, including the lack of clear guidelines and regulations from governments and financial institutions and tries to explore the prospects, risks and drawbacks of crypto market, including the impact on market stability and innovation.
DOI: 10.17632/59rv9y5y2f.1
title: Waste generation in Malaysia (states under Act 672), GHG emissions, land use, and health risk assessment. 

description: The secondary data sets of MSW (tonnes) from the year 2014 to 2018 were obtained from the Domestic Waste and Public Cleansing Division of Solid Waste and Public Cleansing Corporation (SWCorp), Malaysia. The data was structured in Microsoft Excel by the area, state, year, and category and analysed by using mathematical equations and the SPSS software.
DOI: 10.17632/cvv5rzymhd.1
title: Single-cell analysis of embryoids reveals lineage diversification roadmaps of early human development. Zheng et al.

description: Raw data for the plots in the figures and extra experimental results.
DOI: 10.17632/mvyd3bgjv7.1
title: Raw data of the antisaccade task in patients with obsessive-compulsive disorder (EEG, eyetracking, vegetatics)

description: The eyetracking dataset consists of raw eyetracking data (EYE1_OCD) recorded in 32 OCD (obsessive-compulsive disorder) participants, preprocessing and analyses of eyetracking data (code_grant)*, detailed information of preprocessing and analyses (Methods_OCD), general information with descriptive table with age, scores of Y-BOCS, STAI-test, Beck test and Barrat test and sheet with subtypes of OCD (General_info_OCD). The EEG and vegetatics data dataset consists of raw data recorded in 31 OCD participants (EEG_vegetatics_OCD.rar).

* The R-script for reprocessing and analyses of eyetracking data (code_grant.R) both for the control group and for the group with patients with obsessive-compulsive disorder (OCD). The data for the control group can be found here: Khayrullina, Guzal; Liaukovich, Krystsina; Portnova, Galina; Martynova, Olga (2024), “Raw data of the antisaccade task in healthy volunteers (EEG, eyetracking, vegetatics)”, Mendeley Data, V1, doi: 10.17632/h8xrwrmttj.1
DOI: 10.15468/dl.tcgnwe
title: Occurrence Download

description: A dataset containing 1592 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pinus cembroides Zucc.",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 1592 records from 96 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009200-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/468ynm7rfz.1
title: Data for: Predictive Maintenance Scheduling Optimization of Building Heating, Ventilation, and Air Conditioning Systems

description: Data for the two case studies.
DOI: 10.17632/jkvk97nfjc.1
title: Nucleation phenomena and extreme vulnerability of spatial k-core systems

description: This dataset contains experimental data related to spatial k-core percolation, a process used to analyze the robustness of spatial k-core systems under random and localized attacks. The dataset includes both network structures and numerical simulation results obtained from experiments conducted on various spatial networks.

Network Structures
This dataset comprises the link sequences, network structures utilized in numerical simulations of spatial k-core percolation, and edgelist of toy model as a demonstration in the paper. These structures represent networks where nodes correspond to spatial coordinates and edges denote connections between nodes. The link sequences and networks were generated using the zeta model with specific parameters, including a system size of L=1000, characteristic link lengths ranging from zeta = 3 to 1000, and an average degree of k=10. Each file is labeled with a unique identifier (e.g., Link Sequences: "NetID0_avgk10_links_zeta4.pkl", Network Structure: "NetID0_avgk10_zeta3_spatialNet.pkl").

Numerical Simulation Results
This dataset includes multiple subdirectories, each representing different experimental configurations and setups. Within each subdirectory, the numerical simulation results are stored in serialized format files. These files are labeled with descriptive names indicating the specific parameters and conditions used in the simulations. 

Useage: Each file is stored in a serialized format (e.g., Pickle). Some large files are compressed into RAR format; after downloading, these files need to be uncompressed. By loading the serialized files into computational environments (e.g. python or other language), researchers can utilize this network structure dataset to investigate the impact of link length on network resilience under random and localized attacks, and utilize these numerical simulation results to reproduce the figures presented in academic papers or conduct further analyses. 

For detailed information about the experimental methodology and code implementation, please refer to the associated GitHub code repository (https://github.com/LeyangXue/SpatialKcorePercolation.git) and paper titled “Nucleation phenomena and extreme vulnerability of spatial k-core systems” (https://arxiv.org/abs/2311.13579).
DOI: 10.17632/m9n4f6prn4.1
title: Multi-Environment Object Detection Dataset for Improved Indoor Navigation: Focusing on the Importance of Different Door Handle Types

description: The object detection dataset consists of 3,292 images captured from various environments using a simple data collection system. Images were taken from different perspectives, including handheld and camera-mounted on an EPW (Environmental Process Workstation), to ensure diversity and varied perspectives. The dataset was divided into 60% for training (1,975 images), 10% for validation (330 images), and 30% for testing (987 images). The image resolution is 512x512x3 pixels, which is lower than a proposed semantic segmentation dataset but still comparable to standard datasets. The dataset contains annotations on the bounding box level and includes eight object categories such as doors, fire extinguishers, key slots, switches, ID readers, and various types of door handles. The dataset addresses the absence of infrequent objects found in other publicly available datasets. Unclassifiable objects are left unannotated.


Folders description:
- images -> dataset images.

Files descriptions:
- AllDataTable -> All the images and the corresponding bounding boxes in a Matlab table format.

- trainingData_datastore.mat -> training datastore in Matlab format. The combined datastore has the images file path and the corresponding bounding boxes.

- testingData_datastore.mat -> testing datastore in Matlab format. The combined datastore has the images file path and the corresponding bounding boxes.

- validationData_datastore.mat -> validation datastore in Matlab format. The combined datastore has the images file path and the corresponding bounding boxes.

Note: files path in the training, validation and testing Matlab files need to be modified to point to the location where the images locate.

Classes:
- Classes -> 
	'door'
	'pull door handle'
	'push button'
	'moveable door handle'
	'push door handle'
	'fire extinguisher'
	'key slot'
	'id_reader'
	

Paper:
Mohamed, E.; Sirlantzis, K.; Howells, G.; Hoque, S. Optimisation of Deep Learning Small-Object Detectors with Novel Explainable Verification. Sensors 2022, 22, 5596. https://doi.org/10.3390/s22155596
DOI: 10.17632/g7whxvncn3.3
title: Dataset for study on Patient-Reported Outcomes in non-English African Languages

description: Dataset for study on the availability and psychometric properties of patient-reported outcomes in non-English African languages.
DOI: 10.17632/g8392fw2k4.1
title: Species identified in NMCs and their volatilome

description: Species identified in NMCs and their volatilome
DOI: 10.17632/py4hhv3rb8.1
title: KEEL dataset repository

description: KEEL (Knowledge Extraction based on Evolutionary Learning) is an open source (GPLv3) Java software tool that can be used for a large number of different knowledge data discovery tasks. KEEL provides a simple GUI based on data flow to design experiments with different datasets and computational intelligence algorithms (paying special attention to evolutionary algorithms) in order to assess the behavior of the algorithms. It contains a wide variety of classical knowledge extraction algorithms, preprocessing techniques (training set selection, feature selection, discretization, imputation methods for missing values, among others), computational intelligence based learning algorithms, hybrid models, statistical methodologies for contrasting experiments and so forth. It allows to perform a complete analysis of new computational intelligence proposals in comparison to existing ones. Moreover, KEEL has been designed with a two-fold goal: research and educational.
DOI: 10.15468/dl.mt8v5w
title: Occurrence Download

description: A dataset containing 3414 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Potamotrygonidae",
 "HasCoordinate is true",
 "BasisOfRecord is Specimen",
 "Continent is South America"
 ]
}

 The dataset includes 3414 records from 59 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009201-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/nt7r8hv2pz.1
title: Application of Machine Learning in Detecting Iron Deficiency Anemia Using  Conjunctiva image Dataset from Ghana

description: Anemia is a global public health issue that mostly emerges as a result of a decrease in red blood cell count and is particularly prevalent in Africa. Invasive ways of detecting anemia are expensive and time-consuming. Anemia may, however, be diagnosed using non-invasive technologies such as machine learning algorithms. In our study, we compared machine learning models to detect anemia using the conjunctiva of the eyes. The main datasets consisting of the conjunctiva of the eyes were acquired using Ghana as a case study for dataset collecting.
Before the study began, the ethical committees at the hospitals involved approved the collection of datasets. Also, because the participants (patients) in the study were minors, the ethical agreement was obtained from their parent(s) or guardian(s), and the purpose and objectives of the study were explained to them, along with the advantages of the health services. Before the participants were enrolled in the data collection, their parent(s) or guardian(s) gave their consent. Furthermore, the ethics and consent committee of the University of Energy and Natural Resources, Ghana approved the start of this experiment. Furthermore, patients' or participants' names and faces were not shown or exposed during image capture, rendering their identification unknown
DOI: 10.17632/r7fyyf9fhc.1
title: Cross-Sectional Analysis of Quality of Life in Pediatric Patients with Inflammatory Bowel Disease in British Columbia, Canada.

description: Pediatric IBD Quality of Life data along with disease activity at the time of survey completion.
DOI: 10.17632/kbzskd37zy.1
title: The factors determining the preference for COVID-19 Vaccine

description: A large section of the community is still skeptical about accepting COVID-vaccine. To understand the ground reality, we conducted a nationwide online survey study in the USA. The working hypothesis was that the sociodemographic factors such as age, race, education level, family income, gender would influence the decision of vaccine acceptance, and a prediction model built on those factors would precisely predict the vaccine acceptance. It was an anonymous survey, and we did not ask for any identifier. The survey questionnaire was built in Redcap and was primarily divided into three sections. The survey period was between 5/2020-01/2021. The primary outcome of the study was COVID-vaccine acceptance vs. hesitance. The study participants were divided into categories based on several sociodemographic factors. Fifty US states were regrouped into nine regions based on the census bureau's recommendation. We further asked whether the participant was a healthcare worker (HCW) (yes vs. no) and if they were satisfied with healthcare access (1-5 Likert scale). We divided the participants into pre vs. post-vaccine launch, through November 1st, since right after Pfizer announced a successful vaccine trial and a new COVID wave hit the USA. We also included questions to evaluate COVID-related knowledge and the source of COVID-related information. A new variable was computed to estimate perceived threat based on old age, HCW, chances of having severe COVID infection, state of COVID in his area. Several metrics of knowledge and perceived threat were consolidated into two continuous variables using factor analyses. Prediction models were built using binary backward logistic regression and neural networks. Nine variables- age, race, education level, family income, gender, US region, HCW, healthcare access, and vaccine launch period, were considered as potential predictors of vaccine acceptance. The US-based participants who completed all three sections of the survey and answered the key question of vaccine acceptance were considered eligible participants. Among 2978 eligible respondents, 81.1% of the participants indicated their willingness to accept the vaccine. Based on chi-square tests, all the predictors demonstrated an association with vaccine acceptance except the vaccine-launch period. Both the models identified age, education, and race as the top predictors, while the vaccine-launch period and gender were the least significant. People of middle-age, lower education, and black race were the most skeptical. Fear of side effects was the predominant cause of vaccine refusal affecting 84.2% of vaccine-hesitant vs. 51.0% of vaccine-compliant participants. The vaccine-complaint than the vaccine-hesitant group had more COVID-related knowledge, higher perceived threat, and better followed the CDC or other official health websites. There was an association between influenza and COVID-vaccine acceptance (χ2=316.6(df=4,N=2976),p&lt;0.001).
DOI: 10.17632/zv5nrm7v4k.3
title: Population Aging and Business Cycles

description: This paper aims at verifying if population aging promotes or hinders macroeconomic stability. The dataset contains information of 146 economies between 1996 and 2016, grouped in five blocks of years as described in the article. The Stata do.file contains the commands used in the estimation of the econometric models.
DOI: 10.6084/m9.figshare.27933978
title: test-maize

description: grainspace-maize-test
DOI: 10.6084/m9.figshare.27933918
title: test_rice

description: grianspace_rice-test