cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/9kpt7k5dd3.1
title: Datasets of Chemical Compounds in Three Different Species of Aquilaria using GC-MS coupled with GC-FID Analysis

description: The datasets presented in this article consist of detailed chemical analyses of three different species of Aquilaria using GC-MS and GC-FID techniques. The datasets consist of two samples from each of the three species of Aquilaria, specifically A. crassna (designated as ACS1 and ACS2), A. malaccensis (designated as AMS1 and AMS2), and A. subintegra (designated as ASS1 and ASS2). The datasets include information on the retention times, Tr (min), peak area (%), identified compounds, molecular formulas, molecular weights, identification modes, and similar chemical compounds found in every species of Aquilaria. in each sample, were meticulously tabulated in MS Excel. Concurrently, the chemical analyses collectively unveil that agarwood oil is predominantly composed of a mixture of compounds. These compounds can be categorized into four distinct groups: carboxylic acid, other compounds, sesquiterpene, and sesquiterpenoid. This comprehensive dataset facilitates a thorough understanding of the chemical profiles and analytical nuances across the different Aquilaria species, enhancing the robustness and interpretability of the datasets.
DOI: 10.17632/r7bthvstxw.2
title: Vehicle Type Image Dataset (Version 1): VTID1

description: The main objective for the use of an image dataset was to examine the five vehicle types of motor vehicles that were the most commonly used ones in Thailand (sedan, hatchback, pick-up, SUV, and van). The recording devices to collect the images were part of a video surveillance system located at Loei Rajabhat University in Loei province, Thailand. The collection process took place during the daytime for four weeks between July and December 2018. Two cameras were installed at the front gate of the university. However, a small number of van images was produced in the dataset compared to the number of images of the other four vehicle types. Because of this, the researchers decided to add other vehicle-type images such as those of motorcycles into the van group and changed the name of the group to "other vehicles" to increase diversity. Finally, the first dataset called "Vehicle Type Image Dataset (VTID)" had a total of 1,410 images that could be separated into vehicle types as follows; 400 sedans, 478 pick-ups, 129 SUVs, 181 hatchbacks, and 122 other vehicle images. Each image was collected using the 224x224 pixel resolution.
DOI: 10.15468/dl.xe6e8u
title: Occurrence Download

description: A dataset containing 2825 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Platycladus orientalis (L.) Franco",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 2825 records from 214 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009278-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/5bztky29hr.1
title: Digital Education Dataset (1983-2020)

description: The Digital Education research & publication dataset, which was indexed by Scopus from 1983 to 2020. The dataset contains data authors, authors ID Scopus, title, year, source title, volume, issue, article number in Scopus, DOI, link, affiliation, abstract, index keywords, references, Correspondence Address, editors, publisher, conference name, conference date, conference code, ISSN, language, document type, access type, and EID.
DOI: 10.17632/dzscktddsg.1
title: Inverse Laplace Transform Algorithms for IgorPro

description: Two files are included: an Wavemetrics IgorPro file (*.pxp) for analyzing magnetization recovery data for a T1 measurement to extract the distribution of relaxation rates, and a procedure file (*.ipf) which contains the actual functions and procedures for performing the inverse Laplace transform analysis.
DOI: 10.17632/n7h8kb4dfh.2
title: SI-Database AOP

description: Supplementary Information for Evaluation of advanced oxidation processes for water and wastewater treatment – A critical review
DOI: 10.17632/8bhhk7c5n9.1
title: Whole-cortex in situ sequencing reveals peripheral input-dependent cellular and area identity - pilot brain

description: BARseq was used as a standalone spatial transcriptomic method to interrogate the expression of 104 cell type maker genes in one hemisphere of the mouse cortex. Data consist of 40 hemi-coronal sections covering the whole cortex and subcortical areas. Include intermediate processed data and cell type spatial analysis. Associated clustering and gene expression-level analyses are provided at https://github.com/gillislab/barseq_analysis. Accompanying manuscript: https://doi.org/10.1101/2022.11.06.515380
DOI: 10.17632/w3r29kbgcf.1
title: Dataset of the article - Deep Reinforcement Learning-Based Secondary Control for Microgrids in Islanded Mode

description: This article proposes an intelligent secondary controller for islanded microgrids using the Deep Deterministic Policy Gradient (DDPG). The proposed controller could maintain the microgrid voltage and frequency stability for three different scenarios. Moreover, the proposed control performance was compared to another one based in the droop method.
DOI: 10.17632/w5sjw4cbsh.1
title: New SEIR Epidemic Model in Excel- Example 3: Determining Time-Dependent Transmission Rate Coefficient and Calculating the Number of Total Infections by COVID-19 in the United States

description: The process of determining time-dependent transmission rate coefficient and calculating the number of total infections by COVID-19 in the United States and related results have been described in the attached word and excel files.
DOI: 10.17632/ch5jxrnpxm.1
title: Sandwich feedback: The empirical evidence of its effectiveness

description: This is a dataset from between-subject experiment that tested the effectiveness of “sandwich feedback. 91 university students solved 12 mathematical problems from the secondary-school curriculum. After the time limit, we assigned them randomly to one of three possible treatments. One group received negative computer-administrated feedback, describing the mistakes with their methods and solutions. The second group received sandwich feedback, which contained the same constructive critique, though sandwiched between two general, positive statements that were not related to the real respondents’ effort or performance. The third group did not receive any feedback. Afterwards, the respondents had 10 minutes to prepare for the second set of similar problems.
DOI: 10.17632/9tm59d3nsn.1
title: Dataset for Pedestrian Traffic Lights detection

description: The dataset contains a total of 809 raw images , where 441 images are of red pedestrian light and 368 images belong to green pedestrian light class. The dataset is created by scanning through various search engines by using different keywords that include pedestrian crosswalk light, pedestrian green light, pedestrian lights, pedestrian red light, pedestrian traffic light and so on. We tried to consider versatile images in both classes for creating a certain degree of inter-class confusion in order to better train the model. The dataset is designed for binary problem of red or green pedestrian traffic lights detection in the city landscape. The dataset is divided into 80:20 for training and testing purposes in our study. The dataset can be used by the prospective researchers to propose machine learning algorithms for automated detection and screening of jaywalkers towards ensuring the efficient traffic monitoring system and performing surveillance in smart cities.
DOI: 10.17632/d73rs38yk6.1
title: Benchmark Diagnostic MRI and Medical Imaging Dataset

description: This medical image dataset provides a well-off collection of images to enhance the training of computer vision and artificial intelligence models for accurate diagnosis. By supporting the early detection of diseases, it accelerates research into common and rare conditions, fostering advancements in medical imaging technologies.

We collected 34,192 medical images with 40 classes of diseases focused on MRI scans of the brain, neuro, and spine, sourced from multiple hospitals. The dataset includes 40 classes, with 26 MRI brain classes and additional classes covering neuro, spinal cord, and systemic disorders. The dataset includes several rare diseases, such as Walker-Warburg Syndrome (808), Pachygyria with Cerebellar Hypoplasia (592), Moyamoya Disease with Intraventricular Hemorrhage (864), Hallervorden-Spatz Disease (Pantothenate Kinase-Associated Neurodegeneration) (1064), and Fukuyama Muscular Dystrophy (920). It also includes more common diseases, including Retinoblastoma with Intracranial Spread Along Cranial Nerve (1200), Sjögren's Syndrome (1056), Bilateral Osgood-Schlatter Disease with Chronic Inflammatory Arthritis (665), Neurofibromatosis Type 1 (NF1) with Optic Glioma (944), Tuberous Sclerosis (664), and Brain Tumors (1048).

This dataset can be applied to a wide range of computer vision as well as image processing, image recognition and classification, segmentation, deep segmentation, and deep learning in vision. Its diverse conditions make it a valuable resource for advancing medical research and developing innovative diagnostic tools in healthcare.
DOI: 10.17632/j7sfr8w6ts.2
title: Persistent and Transitory Components of Firm Characteristics 4

description: Part 4 of Dataset for replicating Persistent and Transitory Components of Firm Characteristics
DOI: 10.17632/vp977psjcb.2
title: MicroRNA profiling data of fresh lung adenocarcinoma and adjacent normal tissues obtained from ten Korean patients using miRNA-seq

description: MicroRNA transcriptomes from fresh tumor and adjacent normal tissues of ten Korean patients who were diagnosed with lung adenocarcinoma were profiled using a next-generation sequencing (NGS) technique called miRNA-seq. The quality of sequencing was measured using FastQC, and low-quality and/or adapter-contaminated portions of reads were removed with Trim Galore. Quality-assured reads were analyzed using miRDeep2 with Bowtie. The abundance of known miRNAs was estimated by the read per million (RPM) normalization method. Then, differentially expressed miRNAs and potential miRNA biomarkers for lung adenocarcinoma tissues compared to adjacent normal tissues were identified using DESeq2 and Wx, respectively. Finally, reliable miRNA biomarkers for lung adenocarcinoma were defined as those detected by both methods. The miRNA-seq data are available in the gene expression omnibus (GEO) database with accession number GSE196633.
DOI: 10.17632/d6bn4py7xw.1
title: The Impact and Mechanisms of Artificial Intelligence on Green Economic Efficiency：Empirical Evidence from China's GTFP Improvement

description: This dataset encompasses empirical data on the impact of artificial intelligence (AI) on green total factor productivity (GTFP) across 30 provinces in China from 2011 to 2021, including province-level AI adoption metrics, environmental indicators, and productivity measures, collected to analyze the intersection of technological innovation and sustainable economic growth.
DOI: 10.17632/hn4v58fkkz.1
title: Vietnamese General School Teachers and Administrators': Job Satisfaction and Happiness

description: This data was collected through a questionnaire for Vietnamese teachers. Description of their level of happiness and job satisfaction based on the differences between the factors and the level of support for teachers by stakeholders
DOI: 10.17632/sc8whx4pvm.2
title: Old_ADA_Bridge-damage_vibration_data

description: This data presents the vibration data of a steel truss bridge situated in Japan: Old ADA bridge. Five different damage scenarios were designed to represent different real-world cases by introducing artificial damage in the truss.
DOI: 10.17632/f6vfr96m2p.1
title: Dataset - Performance Comparison Oracle, PostgreSQL, and MySQL Database Using JMeter Tools

description: In order to compare the performance of various Database Management Systems (DBMS), five primary tables—customer, salesman, category, qty_product, and product—were used to create an extensive test dataset. This data was then stored in two principal tables, transaction_hdr and transaction_dtl, each containing over 100,000 records. The utilization of this large dataset allows for a thorough evaluation of DBMS performance using tools such as JMeter.

Tables Used:
1. Customer: Stores information about customers, including customer ID, name, contact details, and address.
2. Salesman: Contains data about sales personnel, including salesman ID, name, contact details, and address.
3. Category_Product: Classifies products into specific categories, including category ID and category type.
4.Qty_Product: Maintains information regarding the quantity of products available, including quantity ID, quantity name, and quantity value.
5. Product: Details information about products, including product ID, product name, category ID, size, quantity ID, stock, and price.

By utilizing the above tables, a substantial dataset was generated by populating the transaction_hdr and transaction_dtl tables with over 100,000 records each. The transaction_hdr table includes transaction headers with information such as transaction ID, date, customer ID, salesman ID, and total price. The transaction_dtl table records the details of each transaction, including transaction ID, product ID, product name, category ID, quantity ID, quantity value, quantity, and product price. JMeter was employed to conduct performance testing on the DBMS using this dataset to assess throughput and response time across MySQL, Oracle, and PostgreSQL databases.
DOI: 10.17632/nzcrfhgfh4.2
title: COVID-19 Pandemic: A Dataset from Khyber Pakhtunkhwa, Pakistan

description: This dataset demonstrates the fear of Coronavirus (COVID-19) among the people of Khyber Pakhtunkhwa (Pakistan), their preventive behaviour, mental health condition, and level of anxiety during the pandemic. To gauge these constructs, a questionnaire was developed with the help of various scales – Fear of COVID-19 Scale (FCV-19S), Positive Mental Health Scale (PMHS), and General Anxiety Disorder Scale (GAD). At the time of data collection, the COVID-19 cases were emerging rapidly in the country due to which the KPK province was also facing lock-down and other mobility restrictions to limit the spread of viral infection. Keeping in view the prevalent emergency conditions, the research tool was developed in Google form and disseminated online for the collection of data. The informed consent of the respondents was obtained electronically, and they participated voluntarily in this survey research. Social media apps like Facebook, WhatsApp, LinkedIn, and personal contacts were also used for speedy collection of data. All the questions in the questionnaire were mandatory and the respondents could not send their responses by skipping any of them, so there is no missing value in the dataset. A total of 501 responses were received out of which 208 were females. For the convenience of the participants, every question in the questionnaire was translated into the Urdu language. All the responses were automatically saved online into a .xlsx spreadsheet and later that data was converted to digitized form by developing a coding frame. There are two main sections in this dataset, first is about the socio-demographic information (gender, age, marital status, employment status, area of residence and education) of the participants and the second demonstrates the fear, mental health, preventive behaviour, and anxiety while in the second section, the responses were rated on Likert scale. This dataset could be beneficial to the researchers and policymakers as they can get further insight to develop better skills and practices from a rapidly evolving situation.
DOI: 10.17632/nf8bvtfhk4.1
title: Amazon Air Flights, 01 September 2018 to 31 August 2019
DOI: 10.17632/zvfyrhy8mh.1
title: Trends in the Mobile banking research

description: All 1367 Publications on the topic of the Mobile banking research on Scopus for bibliometric analysis!
DOI: 10.17632/sktz4xv4vh.2
title: Media Use Pattern with Respect to Mental Health in COVID-19: A Dataset from India

description: The purpose of the study is to fill a void how media as a whole (including social and electronic media) has been impacted the mental health of Indian people in terms of growing anxiety and mental well-being.Thus the research questions addressed in the study are- 1. Is there any relationship between media use pattern with mental Well-being and Anxiety? 2. How the demographic attributes do associated with mental Well-being and Anxiety? Data collection: The researchers here conducted a web based cross sectional survey to assess the psychological impact of COVID-19 on the Indian public. The Data was gathered after three weeks of commencement of lock down in India from 426 respondents through snowball sampling. Media use pattern: There were ten structured validated items regarding the information and news about COVID-19 perspective. Depending upon the hour of exposer to the media, the respondents were categorised in to three group subsequently High (≥9 hrs.), Medium (7-8 hrs.) and Low (≤6 hrs.)Media user. Mental Well-Being Scale: Warwick-Edinburgh Mental Well-Being Scale (NHS Health Scotland, University of Warwick and University of Edinburgh, 2006) was used to collect data about the status of mental well-being. It was a 5 point Likert type scale having 14 items. The summated score of the respondent is used as mental well-being score. It is also classified as high (Score&gt;56), medium (Score 47-56) and low (score&lt;47) mental well-being. Mental Anxiety Scale Beck Anxiety Inventory (BAI) Scale (Beck et al., 1988) was applied to collect the information regarding anxiety level. It was a 4 point Likert scale having 21 items. The summated score of the respondent is also used as mental anxiety score. It is also classified as high (Score&gt;35), medium (Score 22-35 ) and low (score&lt;22) mental anxiety. Data Analysis: The demographic characteristics here include age (young, middle & old); gender (male & female); habitat (rural, urban municipality & metropolitan city); and educational qualification (undergraduate or below, postgraduate & above postgraduate). The data showed that there is significant negative relationship exists between of respondent’s media use and mental wellbeing status, and significant positive relationship exists between media use of respondents’ mental anxiety. Any researcher may use the data to test the association between demographic variables with media user pattern, mental well-being and mental anxiety. The data might be helpful for the psychologist and policy makers to make decision about mental health condition during COVID-19 crisis both in and outside of India.
DOI: 10.17632/rgrg58szs6.2
title: UNCOVER-3 5 Year Efficacy and Safety Manuscript Supplemental Materials

description: Supplemental materials for "Long-term efficacy and safety of ixekizumab: 5-year analysis of the UNCOVER-3 randomized controlled trial" (JAAD-D-20-01565)
DOI: 10.17632/xdnjy9p5zn.1
title: RNN data

description: The data for the manuscript "Self-supervised Learning and Prediction of Microstructure Evolution with Recurrent Neural Networks". Detailed data description is included in file "data_description.pdf".
DOI: 10.17632/xz4xhrc4yr.8
title: Images of resolved phase patterns of partial discharges in electric generators

description: This dataset contains images of resolved phase patterns of partial discharges tipe corona, superficial and in electric generators
DOI: 10.17632/wdz462zbby.1
title: Geomatics Comprehensive Evaluation Index Model for Pipeline Route Optimisation

description: Oil and gas pipeline routing criteria, sub-criteria, parameters and the routine alternatives were reviewed from literature and later structured using the concept of Multi-Criteria Decision Analysis (MCDA) based on Analytical Network Process (ANP) that offer a feedback mechanism model of these factors to obtain their various weights for prioritization, through questionnaire administration. Moreover, the land use land cover for the study areas were sourced through the acquisition of LANDSAT 8 imageries, thereafter processed, and classified. Other spatial data were sourced and bathymetry information were further modelled in ArcMap 10.2 environment in order to obtain an optimum route for the study areas. The spatial analysis thereafter was carried out to validate the model for the optimal route that out-performed the original design route and three other alternative routes.
DOI: 10.17632/cprx2kx2ws.2
title: A 3D solid beam benchmark for parametric model order reduction

description: A 3D solid beam benchmark is provided for benchmarking parametric model order reduction methods, for example. 
The example consists of solid brick FE elements and kinematic couplings, thus industry relevant modeling. 
Using sampled system matrices from Simulia ABAQUS, an affine matrix decomposition is recalculated, which preserves ten variable input parameters.
DOI: 10.17632/c85d3wczbs.1
title: Dataset for
DOI: 10.17632/kvpmv75hvg.1
title: Data for: Branch Detection for Apple Trees Trained in Fruiting Wall Architecture using Depth Features and Regions-Convolutional Neural Network (R-CNN)

description: This data mainly includes the testing images of apple tree branches in our paper, and the corresponding R-CNN detection results.
DOI: 10.17632/75yt9j86r2.1
title: landslide data

description: Landslide related factors.
DOI: 10.17632/7z67nyc57w.2
title: FlowerNet: An extensive rose leaves dataset for disease recognition applying machine learning and deep learning models

description: (1) Plant diseases are the leading cause of decreased agricultural output, which leads to economic losses. Rose is known as both the "Queen of Flowers" and the "King of Flowers." This implies that it possesses both kingliness (magnificence, status, and power) and queenliness (beauty, grace, and cultural refinement). Rose illnesses, on the other hand, have a detrimental effect on rose production.
(2) Computer vision and image processing have a big influence on detecting numerous illnesses in flowering plants.
(3) The collection comprises images of diseased Rose leaves as well as disease-free Rose leaves, which may be used to construct an automated method for researchers to forecast illnesses in Rose Flowers. The dataset includes two Rose diseases: black spot and downy mildew. Aside from the disease-free leaves, the dataset also includes them.
(4) This section includes two types of datasets: the original dataset (a total of 917 photos) and the augmented dataset (a total of 4342 images). Each picture has a generalized dimension of 512*512 pixels.
(5) The photos were personally taken from the Village of Roses (Golap Gram), Sadullapur Road Birulia Bridge, Dhaka 1216, Bangladesh, with the assistance of domain specialists and a plant study institute.
DOI: 10.17632/nr4vt4h8gt.3
title: Numerical modeling of MH370 flaperon drift based on barnacle geochemical data

description: Numerical modeling simulation data for Lepas project
DOI: 10.17632/z9d3hw9szy.1
title: Dataset: Tensile experimental data from monotonic loading on connections to concrete filled steel tubes using Extended Hollo-bolt blind bolts

description: This dataset includes text files for 28 tensile experimental results, and images recorded during testing for each specimen.