cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/wy4cw82jpz.1
title: Dataset Purchase Intention and Purchase Behavior Online: A cross-cultural approach

description: The aim of this research is to assess the main theories about consumer behavior/making decision from the social psychology perspective, to understand the intention to adopt electronic channel and, in this way, to determine the precursors of online purchase intention in an emerging economy, and to compare these precursors with the precursors in a developed economy through a cross-cultural study: H1. Consumer online purchase intention has a positive effect on online purchase behavior H1a. The effect of online purchase intention on online purchase behavior is moderated by culture H2. Attitude toward e-commerce has a positive effect on online purchase intention H2a. The effect of attitude toward e-commerce on online purchase intention is moderated by culture H3. Subjective norms have a positive effect on online purchase intention H3a. The effect of subjective norms on online purchase intention is moderated by culture H4. PBC has a positive effect on online purchase intention H4a. The effect of PBC on online purchase intention is moderated by culture H5. Self-efficacy in online stores has a positive effect on online purchase intention H5a. The effect of self-efficacy in online stores on online purchase intention is moderated by culture H6. EOU of e-stores has a positive effect on attitudes toward e-commerce H6a. The effect of EOU of e-stores on attitudes toward e-commerce is moderated by culture H7. The perceived usefulness of online stores has a positive effect on consumers’ attitudes towards online shopping H7a. National culture moderates the effect of perceived usefulness on attitudes toward online shopping H8. Buying impulse has a positive effect on online purchase intention H9. The perceived EOU of e-stores has a positive effect on buying impulse. H8a. The effect of buying impulse on online purchase intention is moderated by culture H9a. The effect of EOU on buying impulse is moderated by culture H10. Compatibility with e-commerce has a positive effect on online purchase intention H10a. The effect of compatibility on online purchase intention is moderated by culture H11. PIIT has a positive effect on online purchase intention H11a. The effect of PIIT on online purchase intention is moderated by culture
DOI: 10.17632/9vjc4ggnrp.1
title: CE skills - SOTA sample

description: The file includes the paper selected for the final stage of the systematic literature review conducted in the paper "Unleashing the role of skills and job profiles in circular manufacturing" by Beducci E., Acerbi F., Pinzone M., Taisch M.
DOI: 10.17632/kvm3pygs6w.1
title: Data for: Examine the effects of neighbourhood equity on disaster situational awareness: Harness machine learning and geotagged Twitter data

description: This data set is used for the manuscript "Examine the effects of neighbourhood equity on disaster situational awareness: Harness machine learning and geotagged Twitter data". The Twitter data has been filtered and processed.
DOI: 10.17632/g3k425zjsb.1
title: HybridHP-Retrofit-GermanGrid

description: This dataset contains simulation results for the publication "Impact of hybrid heat pump shares and building retrofit rates on load penetration in German low-voltage grids" submitted to Applied Energy. Along with the open-source git-repository https://github.com/RWTH-EBC/heat-pumps-grid-interaction, readers can recreate, analyze, or visualize the variety of scenarios considered in the contribution.
DOI: 10.17632/p6dbmjxgrb.1
title: Data for Entrepreneurial Risk Shocks and Financial Acceleration Asymmetry in a Two-Country DSGE Model

description: Data for Entrepreneurial Risk Shocks and Financial Acceleration Asymmetry in a Two-Country DSGE Model
DOI: 10.17632/3pkp8kg6g3.2
title: Multi-Isotope Variation Reveals Social Complexity in Viking Age Norway

description: Vikings_isotopes_publication_script. R to the data and code availability section
DOI: 10.17632/c66r92wt7t.1
title: Analysis of laboratory incident database

description: Incident database
DOI: 10.17632/sv7ns5xv7f.1
title: FASSEG: a FAce Semantic SEGmentation repository for face image analysis (v2019)

description: The FASSEG (v2019) repository is composed by four subsets containing face images useful for training and testing automatic methods for the task of face segmentation. Three subsets, namely frontal01, frontal02, and frontal 03 are specifically built for performing frontal face segmentation. Frontal01 contains 70 original RGB images and the corresponding roughly labelled ground-truth masks. Frontal02 contains the same image data, with high-precision labelled ground-truth masks. Frontal03 consists in 150 annotated face masks of twins captured in various orientations, illumination conditions and facial expressions. The last subset, namely multipose01, contains more than 200 faces in multiple poses and the corresponding ground- truth masks. For all face images, ground-truth masks are labelled on six classes (mouth, nose, eyes, hair, skin, and background).
DOI: 10.17632/p7ypnxbfr9.1
title: NEW DYNAMIC SCORING METHOD FOR DEEP EVALUATION OF NALOXEGOL AS Β-TUBULIN BINDING INHIBITOR

description: Dataset of Computer Aided Drug Design (CADD) and Molecular Dynamics (MD) operations for article, titled "NEW DYNAMIC SCORING METHOD FOR DEEP EVALUATION OF NALOXEGOL AS Β-TUBULIN BINDING INHIBITOR"
DOI: 10.17632/brwptm8wjb.1
title: In-Vehicle alcohol detection

description: The goal of this experiment is to detect the presense of alcohol inside  of a  vehicle, for this  6 MQ3 sensors were placed inside the vehicle. 
The raw data for four different  experiments (two without alcohol and two with a sample of 90° ethanol alcohol).
DOI: 10.17632/7pyhbzb2n9.1
title: Lumpy Skin disease dataset

description: Assessing machine learning techniques in forecasting Lumpy Skin Disease occurrence based on meteorological and geospatial features - dataset
DOI: 10.17632/bkz6jvfwsr.1
title: Simulation of piezoelectric fan bidirectional flow-solid coupling in confined space

description: Based on ANSYS Workbench numerical simulation platform, numerical simulation work has been carried out around the intrinsic correlation mechanisms and laws of non-constant flow field, nonlinear aerodynamic force, amplitude response and heat transfer characteristics of piezoelectric fan flow-solid coupling under different confined environments.
DOI: 10.17632/mn6wr4k3s2.2
title: Data for: A Flamboyant Mandarin in a Declining Liberal Order: China's Revisionist Agenda in Global Human Rights Institutions

description: The files show the results of text analytics on official Chinese human rights statements by the Xi Jinping government.
DOI: 10.17632/9bpcypmh2j.1
title: High-resolution Digital Outcrop Models of Late Jurassic outcrop, Wadi Birk, Saudi Arabia

description: The catalog represents supplementary materials for:
Panara, Y., Menegoni, N., Finkbeiner, T., Zühlke, R., Vahrenkamp, V., 2024. High-resolution analysis of 3D fracture networks from Digital Outcrop Models, correlation to plate-tectonic events and calibration of subsurface models (Jurassic, Arabian Plate). Mar. Pet. Geol. https://doi.org/10.1016/j.marpetgeo.2024.106998
DOI: 10.17632/vgmytzpty5.1
title: Social Sustainability within the digital design process of buildings

description: Literature review database for Social Sustainability in the design of neighbourhoods. RQ1. What are the reasons for a fragmented discourse on Social Sustainability in the built environment? RQ2. What are the prevailing definitions of social sustainability in the built environment? RQ3. What are the core themes of Social Sustainability to be included in a digital design support tool?
DOI: 10.17632/yhdtkszvgp.2
title: Euvsdisinfo dataset

description: EUvsDisinfo is the flagship project of the European External Action Service’s East StratCom Task Force. It was established in 2015 to better forecast, address, and respond to the Russian Federation’s ongoing disinformation campaigns affecting the European Union, its Member States, and countries in the shared neighbourhood.
Using data analysis and media monitoring services in 15 languages, EUvsDisinfo identifies, compiles, and exposes disinformation cases originating in pro-Kremlin media that are propagated across the EU and Eastern Partnership countries. 

EUvsDisinfo is the only searchable, open-source repository of its kind, and has two core objectives:

(1) To increase public awareness and understanding of the Kremlin’s disinformation operations;
(2) To help citizens to develop resistance to digital information and media manipulation.

As the data is not directly accessible for analysis, we scraped it using the Selenium and Beautiful soup Python’s packages. We retrieved 14 497 cases of Disinformation and their disproofs (information) from the 6th of January 2015 to the 22nd of November 2022.

Each case has seven attributes:

Date: Date of publication;
Links: Link to the article in the EUvsDisinfo database;
Title: Title of the disinformation article;
Outlets: Outlets of propagation;
Country: Target countries;
Disinformation: Text of Disinformation;
Information: Factual Information.
DOI: 10.17632/3f4hb2gt5w.1
title: Mobile-Assisted Language Learning Dataset (2008-2020)

description: Mobile-Assisted Language Learning research and publication dataset, which was indexed by Scopus from 2008 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/mvd5c3mc3v
title: Influence of The Inclusion of Off-Nadir Images on UAV-Photogrammetry Projects from Nadir Images and AGL (Above Ground Level) or AMSL (Above Mean Sea Level) Flights

description: The data provided are those used for the development of the work 'Influence of The Inclusion of Off-Nadir Images on UAV-Photogrammetry Projects from Nadir Images and AGL (Above Ground Level) or AMSL (Above Mean Sea Level) Flights', published in the journal DRONES (mdpi). They are separated into four files:
- The file ‘STUDY AREA CONTOUR.dxf’. is the contour of the study area in vector dxf format. It can be used to cut out the point cloud generated in each of the photogrammetric projects carried out.
- The file ‘TLS REFERENCE CLOUD.las’. Contains the X,Y,Z coordinates of the 3D point cloud used as reference, obtained with a terrestrial laser scanner (TLS), in las format.
- The file 'photogrammetry projects GCPs.txt' contains the X,Y,Z coordinatas of the eight ground control points (GCPs), used for the georeferencing of the photogrammetric projects. The first column is the label of each point.
- The compressed file ‘IMAGES.zip’ contains the images used to carry out each of the projects carried out in this work. When unzipped, a folder with 10 subfolders will appear:
1. '0_AGL_90_70'. Contains 135 images taken with the UAV in Avobe Ground Level flight mode. Frotal overlap: 90%. Side overlap: 70%.Camera orientation: nadir.
2. '0_AMSL_90_70'. Contains 118 images taken with the UAV in Avobe Mean Sea Level flight mode. Frotal overlap: 90%. Side overlap: 70%.Camera orientation: nadir.
3. 'A-CROSS', oblique images formed a cross centered in the study area with one flight path in the NS direction and the other in the EW direction. Four subfolders:
 3.1. 'A-CROSS-11'
 3.2. 'A-CROSS-22'
 3.3. 'A-CROSS-33'
 3.4. 'A-CROSS-45'
4. 'B-BOX EX', oblique images were arranged in a rectangular box around the study area and pointing towards the interior. Four subfolders:
 4.1. 'B-BOX EX-11'
 4.2. 'B-BOX EX-22'
 4.3. 'B-BOX EX-33'
 4.4. 'B-BOX EX-45'
5. 'B-BOX IN', oblique images were arranged in a rectangular box inside the study area and pointing to-wards the interior.Four subfolders:
 5.1. 'C-BOX IN-11'
 5.2. 'C-BOX IN-22'
 5.3. 'C-BOX IN-33'
 5.4. 'C-BOX IN-45'
6. 'D-B PLUS C'', combination of both interior and exterior rectangular boxes. Four subfolders:
 6.1. 'D-11'
 6.2. 'D-22'
 6.3. 'D-33'
 6.4. 'D-45'
 7. 'E-CUR NS', oblique images were arranged in arcs on the E and W sides of the study area, so these curves ran from N to S. Four subfolders:
 7.1. 'E-CUR NS-11'
 7.2. 'E-CUR NS-22'
 7.3. 'E-CUR NS-33'
 7.4. 'E-CUR NS-45'
 8. 'F-CUR EW', oblique images were arranged in arcs on the N and S sides of the study area, so these curves ran from E to W . Four subfolders:
 8.1. 'F-CUR EW-11'
 8.2. 'F-CUR EW-22'
 8.3. 'F-CUR EW-33'
 8.4. 'F-CUR EW-45'
 9. 'G-E PLUS F', combination of both NS and EW curves. Four subfolders:
 9.1. 'G-11'
 9.2. 'G-22'
 9.3. 'G-33'
 9.4. 'G-45'
In the names of the folders, 11, 22, 33 and 45 mean the angle of de camera.
DOI: 10.17632/r9bfpnvyxr.6
title: Monkeypox Skin Images Dataset (MSID)

description: The latest outbreak of monkeypox has now become a source of concern for healthcare professionals throughout the world. It is essential to have an early diagnosis in order to slow down its rapid progression. For this purpose, we have created a new skin image-based dataset for the detection of monkeypox disease. This dataset consists of four classes: Monkeypox, Chickenpox, Measles, and Normal. All the image classes are collected from internet-based health website sources. The entire dataset has been developed by two students named Diponkor Bala and Md. Shamim Hossain of the Department of Computer Science and Engineering, Islamic University, Kushtia-7003, Bangladesh, and School of Computer Science and Technology, University of Science and Technology of China (USTC), Hefei, Anhui, 230026, China respectively.
DOI: 10.17632/v493dkxk8r.1
title: DynaPhoPy: A code for extracting phonon quasiparticles from molecular dynamics simulations

description: We have developed a computational code, DynaPhoPy, that allow us to extract the microscopic anharmonic phonon properties from molecular dynamics (MD) simulations using the normal-mode-decomposition technique as presented by Sun et al. (2014). Using this code we calculated the quasiparticle phonon frequencies and linewidths of crystalline silicon at different temperatures using both of first-principles and the Tersoff empirical potential approaches. In this work we show the dependence of these properties on the temperature using both approaches and compare them with reported experimental data obtained by Raman spectroscopy (Balkanski et al., 1983; Tsu and Hernandez, 1982).
DOI: 10.17632/tsy6rbc5d4.1
title: Data for: MACHINE LEARNING IN MEDICINE: CLASSIFICATION AND PREDICTION OF DEMENTIA BY SUPPORT VECTOR MACHINES (SVM)

description: This set consists of a longitudinal collection of 150 subjects aged 60 to 96. Each subject was scanned on two or more visits, separated by at least one year for a total of 373 imaging sessions. For each subject, 3 or 4 individual T1-weighted MRI scans obtained in single scan sessions are included. The subjects are all right-handed and include both men and women. 72 of the subjects were characterized as nondemented throughout the study. 64 of the included subjects were characterized as demented at the time of their initial visits and remained so for subsequent scans, including 51 individuals with mild to moderate Alzheimer’s disease. Another 14 subjects were characterized as nondemented at the time of their initial visit and were subsequently characterized as demented at a later visit.
DOI: 10.17632/chv5t9fynt.1
title: Local government debt and corporate R&D investment: Evidence from China

description: We collect the data to examine the crowding-out effect of local government debt on R&D investment of Chinese corporations. We find that there is a significant negative correlation between local government debt and corporate R&D investment, which indicate that corporations based in provinces with higher government debt are more reluctant to carry out innovation activities. Furthermore, our empirical results show that the crowding-out effect is more pronounced for firms with fewer financing constraints. We initially collect the data of Chinese A-share listed companies in Shanghai and Shenzhen Stock Exchanges and provincial government debt for the years 2012-2017. We match firm data with provincial government debt based on location. Then, we exclude special treatment firms, financial enterprises and firms with missing data. Due to missing data of provincial government debt, we also exclude firms headquartered in Tibet autonomous region. Finally, we have a sample consists of 11417 firm-year observations representing 2483 listed companies in 30 provincial districts in mainland China including 22 provinces, 4 autonomous regions and 4 municipalities directly under the central government. Data analysis was performed with STATA software package.
DOI: 10.17632/v5j6m8dzhv.1
title: Multi-pose dog dataset

description: This dataset is proposed for the Re-ID study, which contains a total of 1657 images of 192 dogs. On average, there are 9 images per dog. When we took the data, we collected as many images as possible with different postures and different perspectives.
DOI: 10.17632/yzhcvn7sj5.2
title: Ransomware Combined Structural Feature Dataset

description: This dataset contains several strutuctural features extracted of 2675 binary executable samples. The training and validation set consisted of 2157 samples (80%): 1023 ransomware belonging to 25 relevant families and 1134 goodware. Meanwhile, a testing set consisted of 518 samples (20%): 385 ransomware belonging to the 15 recent families and 133 goodware.

The CSV file columns are sample ID, filename, target class (GR), family ID, and numerical columns (features), as follows:
 | ID | filename | GR | family | Features |
Training Goodware | 10000 to 11133 | Their name.exe | 0 | 0 | Numerical features |
Testing Goodware | 12000 to 12132 | Their name.exe | 0 | 0 | Numerical features |
Training Ransomware | 20000 to 21022 | Their SHA-256 hash | 1 | 1-25 family IDs | Numerical features |
Testing Ransomware | 22000 to 22384 | Their SHA-256 hash | 1 | 26-40 family IDs | Numerical features |

Options:
1) The dataset is split into individual types of features without preprocessing, including headers, imported DLLs, function calls, entropy of sections, and 3, 4, and 5-grams opcode frequencies.

2) The combined datasets include headers, imported DLLs, function calls, and entropy of sections feature sets, with and without the 3-gram feature set, after the preprocessing step, according to our research paper entitled "A Comprehensive Analysis Combining Structural Features for Detection of New Ransomware Families," from the Journal of Information Security and Applications.
Note: The preprocessing step primarily involved merging similar APIs, feature selection, and normalizing the features based on their maximum and minimum values, considering only the training data. Some features exclusively exist in the test data, with zero occurrences in the training samples. For accurate testing, it's advisable to exclude these features from the training set.

Family IDs:
Avaddon 1
Babuk 2
Blackmatter 3
Conti 4
Darkside 5
Dharma 6
Doppelpaymer 7
Exorcist 8
Gandcrab 9
Lockbit 10
Makop 11
Maze 12
Mountlocker 13
Nefilim 14
Netwalker 15
Phobos 16
Pysa 17
Ragnarok 18
RansomeXX 19
Revil 20
Ryuk 21
Stop 22
Thanos 23
Wastedlocker 24
Zeppelin 25

AvosLocker 26
BianLian 27
BlackBasta 28
BlackByte 29
BlackCat 30
BlueSky 31
Clop 32
Hive 33
HolyGhost 34
Karma 35
Lorenz 36
Maui 37
Night Sky 38
PlayCrypt 39
Quantum 40
DOI: 10.17632/68yt34zs22.2
title: Effective economic information

description: This data set computes a measure of effective economic information (EEI) and TFP for 25 EU countries for the period 2000 to 2018. EEI is computed with a simple model that takes ICT investment and includes a propagation factor composed of variables that underlie a TFP-information absorption ecosystem such as educational, socioeconomic, institutional, and political factors. Primary data for the measure is from indices extracted from UNCTAD's productive capacity index and UNECE Statistical database . TFP data is from the Penn World Tables 10.0 (ctfp US = 1) converted to country TFP using the FRED data on US TFP (2017 =1). Measures of EEI for each EU country and their TFP are used to determine the relationship between EEI and TFP.
DOI: 10.17632/64xkbj2ry5.2
title: The American Customer Satisfaction Index (ACSI): A Sample Dataset and Description

description: This dataset provides a sample of survey data collected by the American Customer Satisfaction Index (ACSI). Using online sampling and stratified interviewing techniques of actual customers of predominantly large market-share (“large cap”) companies, the ACSI annually collects data from some 400,000 consumers residing across the United States for more than 400 companies within about 50 consumer industries. For this data depository, consumers’ perceptions of their experiences with individual companies included within four consumer industries as defined and measured by ACSI – processed food, commercial airlines, Internet service providers, and commercial banks – are included in the dataset. The overall sample size is n=8239 consumer responses for this sample ACSI dataset. These industries were chosen to represent and illustrate a cross-section of data from differentiated sectors, not because they are representative of the larger economy or larger ACSI dataset per se.
DOI: 10.17632/b6br4yk6r3.1
title: Aluminium alloy dataset for supervised learning

description: The dataset contains information on the composition and processing conditions of aluminium alloys. The mechanical properties included are yield strength, tensile strength, and elongation. Additionally, the dataset provides information about the class to which each alloy belongs.
DOI: 10.17632/p3v94dft2y.1
title: Ransomware PE Header Feature Dataset

description: This dataset contains headers of 2157 binary executable samples comprising 1134 legitimate software (goodware) and 1023 ransomware, grouped into 25 ransomware families. The dataset was retrieved by extracting raw information of the PE header (first 1024 bytes).

The CSV file columns are sample ID, filename, target class (GR), family ID, and numerical columns from 0 to 1023, as follows:
			| 	ID			| 	filename			| GR	| 	family	| 			0 - 1023					|
Goodware	| 10000 to 11133	| Their name.exe		| 0	| 0			| Numerical features ranging from 0 to 255	|
Ransomware	| 20000 to 21022	| Their SHA-256 hash	| 1	| 25 family IDs	| Numerical features ranging from 0 to 255	|

Family IDs:
Avaddon			1
Babuk			2
Blackmatter		3
Conti			4
Darkside			5
Dharma			6
Doppelpaymer	7
Exorcist			8
Gandcrab		9
Lockbit			10
Makop			11
Maze			12
Mountlocker		13
Nefilim			14
Netwalker		15
Phobos			16
Pysa				17
Ragnarok		18
RansomeXX		19
Revil			20
Ryuk			21
Stop				22
Thanos			23
Wastedlocker		24
Zeppelin			25

A complete description of this dataset can be found in the paper "Moreira, C.C., Moreira, D.C., Sales Jr., C. de S. de:
Improving Ransomware Detection based on Portable Executable Header using Xception Convolutional Neural Network. Computers & Security, 2023, DOI: https://doi.org/10.1016/j.cose.2023.103265, URL: https://www.sciencedirect.com/science/article/pii/S016740482300175X "

Please, reference our work when using this dataset.