cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/gt37rfwtb5.1
title: MQTT DoS DDoS IoT Attack

description: The data collected on a raspberry pi 3B+ as a mosquitto brocker, and as mosquittos clients, from 12 sessions with terminator on an ubuntu 20 (4 publishers and 8 subscribers). The data collection was done with wireshark. The normal traffic was done during 3 days and produced 142.000 data entries. The attack traffic lasted 2 to 3 minutes for hundreds of thousands of data with the most popular and useful tools like hping3 and LOIC. The complete dataset is 424.716 harvested entries. The choice of the dataset fields was made in relation to the parameters most affected by a DDos attack. The dataset can be used for research purposes and on the other hand with machine learning techniques and implementation in IDS or IPS.
DOI: 10.17632/rcyyf5j9zg.1
title: Lemon Leaf Classification Data Set

description: Lemon Leaf Classification Dataset: A carefully curated dataset consisting of five distinct classes of lemon leaves, designed for robust image classification tasks. Each class represents unique variations in leaf characteristics, including shape, texture, and disease conditions. This dataset is ideal for developing and testing machine learning and deep learning models, contributing to the advancement of agricultural research. The balanced class distribution ensures a reliable foundation for classification models, enhancing precision in identifying different types of lemon leaves and promoting disease detection.
DOI: 10.17632/cb887gkmxw.2
title: SoC Estimation on Li-ion Batteries: A New EIS-based Dataset for data-driven applications

description: On 11 brand new cylindrical rechargeable Lithium Iron Phosphate batteries, Electrochemical Impedance Spectroscopy (EIS) were measured at SoC 100%, 95%, 90%, 85%, 80%, 75%, 70%, 65%, 60%, 55%, 50%, 45%, 35%, 30%, 25%, 20%, 15%, 10%, 5%. All of these measures for each battery are repeated for two discharge cycles. 

Impedance frequencies[ 0.01, 0.02, 0.03, 0.05, 0.08, 0.1, 0.2, 0.3, 0.5, 0.8, 1, 2, 3, 5, 8, 10, 11, 21, 31, 61, 81, 100, 110, 210, 310, 510, 810, 1000 ] Hz used for the all EIS spectrum.

The files are organized in directories. There are eleven directories one for each battery, from “ B01” to “ B11”. Each of these directories further contains two directories, “ EIS Measurement” and “Capacity Measurement”. In the first one there are all the test directories, inside each test folder there are the corresponding test comma-separated values (csv) files with all the impedance spectroscopy measurements. In the second folder, on the same level as “ EIS Measurement” there is the battery capacity test also in a csv formatted file.
DOI: 10.17632/zhygf2vdsr.1
title: Data for: Additively manufactured three-dimensional lightweight cellular solids: experimental and numerical analysis

description: A dataset for the publication:
Additively manufactured three-dimensional lightweight cellular solids: experimental and numerical analysis
Albert Forés-Garriga, Giovanni Gómez-Gras, Marco A. Pérez*
Materials and Design, 2023

One of the research fields in which additive manufacturing has made relevant progress is the development and fabrication of cellular solids. These bio-inspired structures are formed by a complex interconnected network of solid struts or shells that cover the space while considerably reducing the weight of the components. Accordingly, this work presents comprehensive research on the mechanical performance of fused deposition modeling three-dimensional lightweight cellular solids, including open-cell and closed-cell patterns with different cell sizes and infill densities. Moreover, two validated strategies for simulating the elastic behavior of cellular solids are investigated, comparing their accuracy and computational requirements. Furthermore, the paper provides experimental evidence on the differences over two-dimensional designs in terms of stiffness and strength while attending to manufacturing aspects such as printing time, proving that the elastic modulus, the compression strength, and the energy absorption efficiency are significantly superior to that obtained by two-dimensional patterns for an equivalent relative density. Furthermore, results prove that controlling engineering parameters allows producing lightweight structures with a wide range of specific stiffness and strength. Finally, experimental evidence states that the Shell-TPMS designs proved to be the most efficient cellular pattern, followed by the Skeletal-TPMS and the lattice configurations.

This dataset contains:

STL Files:
Bending Tests: 200x20x20 mm 3D-CAD geometry of the two and three-dimensional designs, Hexachiral and Diamond respectively, employed in the validation test of the study, ready for manufacturing or simulating.
Compression Tests: 40x40x40 mm 3D-CAD geometry of each three-dimensional design considered in the study, ready for manufacturing or simulating.

Test Files:
Bending Tests: Stress vs Strain data of the experimental bending tests conducted with the two and three-dimensional designs, Hexachiral and Diamond respectively.
Compression Tests:
Solid Specimens: Load vs displacement data of the experimental compression tests conducted with Solid ±45º Infill specimens.
Sparse Specimens: Load vs displacement data of the experimental compression tests conducted with Sparse 0.25 mm Infill specimens.
DOI: 10.17632/8kt969dhx6.1
title: Labeled Retinal Optical Coherence Tomography Dataset for Classification of Normal, Drusen, and CNV Cases

description: This dataset consists of more than 16,000 retinal OCT B-scans from 441 cases (Normal: 120, Drusen: 160, CNV: 161) and is acquired at Noor Eye Hospital, Tehran, Iran. Images are labeled by a retinal specialist.

The structure of the folders are as below:
- CNV, DRUSEN, NORMAL folders
- Within each class, folders are separated patient-wise with numbers from 1 to <number_of_patients>.
- Within each patient folder, images (B-scans) are labeled with <0XX_LABEL> format where <XX> is the B-scan number, and <LABEL> is the specialist's selected label for that specific B-scan.

The excel spreadsheet (data_information.csv) includes information such as "Patient ID", "Class", "Eye", "B-scan", "Label", and "Directory" for all images (16823 rows, 6 columns).

The python code (read_data.py) includes code for loading images and labels as NumPy arrays. The written function outputs the input data as an array with shape (number_of_images, imageSize, imageSize, 3) and output data as a list of labels (Normal: 0, Drusen: 1, CNV: 2). There are two different options for reading the files:
- Option 1: Reading all images. This would result in 16822 images.
- Option 2: Reading the worst-case condition images for each volume (i.e., if a patient was detected as a CNV case, only CNV-appearing B-scans were included for training procedure and normal and drusen B-scans of that patient are excluded from the dataset). This would result in 12649 images.
DOI: 10.17632/dc3797vf3t.1
title: Students_Academic_ Performance_Evaluation_Dataset

description: 31 features and 1195 individuals make up the publicly accessible dataset in a data repository. The Excel file that is part of the "Students Performance data set" folder contains the dataset. The 1195 rows and 31 columns of the Excel file provide information about the academic and non-academic data of the students. A student's question and response, gathered via an online survey form, are displayed in each row of an Excel file. The intended audience consisted of computer science and engineering department students at a private institution in Bangladesh.37,045 main data points were gathered via this survey. There are two categories of features: integer and nominal. Gender, merit scholarship, using university transportation, learning mode, English Skills, probation, suspension, faculty consultancy, relationship status, participation in extracurricular activities, living status political engagement, health issue, physical disability, SGPA, and CGPA are the nominal features. The HSC passing year, university admission year, study hours per day, frequency of study hours per day, social media time, and class attendance are the integer features.
Based on the present CGPA, SGPA, class attendance, daily study hours, frequency of study, social media time, and English proficiency, the targeted column, "student status," has been chosen.
DOI: 10.17632/h489xpc53b.1
title: Leveraging Azure Automated Machine Learning and CatBoost Gradient Boosting Algorithm for Service Quality Prediction in Hospitality: Dataset from the Indian Hotel Industry

description: The present study endeavours to ascertain whether all the dimensions of SERVQUAL carry equal weight in terms of their impact on overall service quality. Questions were framed to measure each of the dimensions of SERVQUAL with different predictor variables: gender, age, marital status, highest level of education, and frequency of staying at the hotel. Machine learning models are used to find the importance of each feature against a dimension. Comparative modeling of feature importance was done using the CatBoost gradient boosting technique and Microsoft Azure Automated Machine Learning studio. The result confirmed an excellent similarity between CatBoost's drawn feature importance and those obtained from Azure auto ML studio. The results of the investigation enable decision-makers to determine which dimension is dependent on specific predictors, allowing them to focus on targeted improvements.
DOI: 10.17632/vfz5pz4n8k.1
title: Datasets of captured images of 3 different devices for photogrammetry calculation comparison and integration to a laser scan point cloud

description: The present data article aims to provide the whole dataset obtained during an experiment of updating laser scan point clouds with photogrammetry meshes. It was investigated whether photos from smartphones are also appropriate for updating point clouds by using photogrammetry in a factory environment. The photos (369) taken in 08:30 min with the smartphone were taken with the App 645 PRO Mk III with the settings ISO 250, F-Stop 1.8, Shutterspeed 1/125 sec. The result was that photos from current smartphones (here tested: iPhone XS) are suitable for photogrammetry applications. Main component are the comparison of the datasets of three devices: Nikon D810 with Sigma art 24mm, iPhone 6 and iPhone XS. In this repository one dataset (photos in .TIFF) of the iPhone XS is provided. The test environment was a technical room in a factory. The data sets are used for a photogrammetry comparison. Furthermore, all settings in the RealityCapture BETA 1.0 and Meshroom 2019 2.0 software are provided. A comparison of calculation time and quality of the 3D meshes was performed. The data set of the iPhone XS can be used to compare further photogrammetry software or single algorithms. Besides the images, the point clouds of the laser scanner are provided. This also includes the combination of laser scan point cloud and photogrammetry mesh. This data in brief article is published as an co-submission of the paper "Approach for an Update Method for Digital Factory Models" in the Procedia CIRP CMS 2020. Conclusions and further information can be found in this paper.
DOI: 10.17632/z7dj3yyzt8.3
title: A DATASET for GPS Spoofing Detection on Unmanned Aerial System

description: A dataset of Global Positioning System (GPS) spoofing attacks is presented in this article. This dataset includes data extracted from authentic GPS signals collected using an eight-channel GPS receiver installed on top of a vehicle with a speed ranging from 0 mph to 60 mph emulating the UAS flight, as well as three static positions on top of different buildings (different altitudes) to emulate the UAS hovering operation. During the data collection, 13 features are extracted from eight-parallel channels. In addition to the collected authentic GPS signals, three GPS spoofing attack types were simulated, simplistic, intermediate, and sophisticated attacks.
DOI: 10.17632/wkjdmrmrg4.4
title: Dataset on Online Impulsive buying behaviour of E-paylater user and non E-paylater user

description: The provided dataset sheds light on the online impulsive buying behavior triggered by the e-paylater payment alternative. It includes two files, one of which is a codebook in MS Excel, containing raw data that showcases respondent characteristics such as gender, age, educational background, job status, and more. This file also encompasses all research data, complete with question labels. The second file is a CSV file that contains filtered data suitable for testing purposes. Additionally, the dataset includes a third file that contains the survey questionnaire, attached as a complementary document for reference.

This dataset provided here is a valuable resource for conducting various analyses on e-paylater usage and consumer decision-making, especially in Indonesia. With its diverse data and demographic attributes, this dataset allows for comprehensive as well as segmented analyses and tests based on consumer groups categorized by age, gender, education level, and other relevant parameters. It offers a broad range of potential applications for researchers and analysts to explore and gain insights into consumer behavior and preferences.
DOI: 10.17632/6c2p7r6p6y.1
title: Faculty data for information schools, public policy schools and neuroscience departments in U.S.

description: This dataset includes names, doctorate-granting institution, and doctoral programs for faculty members from three types of multidisciplinary institutions in the U.S. - 26 information schools (a.k.a., iSchools, collected in 2014) - 64 public policy schools (collected in 2016) - 26 neuroscience departments (collected in 2016) Please refer to the README.txt file for details. When using the information school dataset, please cite the following papers: - Zuo, Z., Zhao, K., & Eichmann, D. (2017). The State and Evolution of U.S. iSchools – from Talent Acquisitions to Research Outcome. Journal of the Association for Information Science and Technology, 68(5), 1266–1277. https://doi.org/10.1002/asi.23751 - Zuo, Z., Zhao, K. (In press). The More Multidisciplinary the Better? - The Prevalence and Interdisciplinarity of Research Collaborations in Multidisciplinary Institutions. Journal of Informetrics. When using the other two, please cite: - Zuo, Z., Zhao, K. (In press). The More Multidisciplinary the Better? - The Prevalence and Interdisciplinarity of Research Collaborations in Multidisciplinary Institutions. Journal of Informetrics.
DOI: 10.17632/fgznfsj8m8.1
title: Bullous pemphigoid & heart failure

description: Increased risk of heart failure among patients with bullous pemphigoid
DOI: 10.17632/thzhz2cs54.1
title: SPSS dataset barriers to the prevention and reduction of involuntary treatment

description: SPSS file of the data used to generate results for the the study named: Professional caregivers' perceived barriers hindering the prevention and reduction of involuntary treatment among older persons receiving long-term care: a mixed methods study.
DOI: 10.17632/2thnp7mcxx.1
title: Longjing tea classification dataset

description: This dataset is prepared for Longjing tea quality identification and classification by using computer vision. The dataset contains Longjing tea from three different origins: West Lake Zone （Wllj）, Qiantang Zone (Qtlj) and Yuezhou Zone (Yzlj). Longjing tea from each origin contains four grades, which are named 1-4 according to Arabic numerals. The tea grade of each image is judged by at least two experts. Small numbers represent high tea grade and good quality. The images in the dataset were captured using industrial camera under the same controlled environment. The label of every image is the folder name.
DOI: 10.15468/dl.e4684s
title: Occurrence Download

description: A dataset containing 1824 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Populus grandidentata Michx.",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 1824 records from 98 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009288-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/m2tk4652bm.2
title: Data for: Sexual assault victimization and psychopathology: A review and meta-analysis

description: This dataset contains coded effect sizes from articles comparing psychopathology in sexually assaulted to unassaulted groups.
DOI: 10.17632/9vr83n7z5j.2
title: Driver Behavior Detection Using Smartphone - Dataset

description: Dataset for driver behavior classification (normal, aggressive, risky) based on accelerometer (X,Y,Z axis in meters per second squared (m/s2)) and gyroscope (X,Y, Z axis in degrees per second (°/s) ) data. 
Sampling Rate: 50 Hz default
Cars: Ford Figo 1.2,  Maruti Suzuki Swift VXI, Tata Nexon XMS
Drivers: 3 different drivers with the ages between 35-40 yrs.
Driver Behaviors: Normal, Aggressive, and Risky
Smartphone Sensor: Accelerometer, Gyroscope
Smartphone Device: Redmi 4, MI A3
DOI: 10.17632/26kndg8xsw.2
title: DatasetCode

description: Sign Language Convert to Urdu Language
DOI: 10.17632/83bvxzx3bj.3
title: u-Blox F9P and Google Pixel 5 (repeated 20 minutes static measurements under variable conditions)

description: Raw GNSS data recorded using u-Blox ZED F9P receiver and Google Pixel 5 smartphone simultaneously. 20 minutes of measurement on open area point (first point according to time in a particular day), point with partial trees' canopy (second) and point under full canopy (third). 10 repetitions (particular days) under leaf-on conditions and 10 under leaf-off conditions.
The dataset is related to the paper "Static Positioning under Tree Canopy Using Low-Cost GNSS Receivers and Adapted RTKLIB Software " in the Sensors jornal (https://doi.org/10.3390/s23063136). Please, refer to this source when using the dataset.
DOI: 10.17632/35wbdcy3bc.1
title: Replication Files for "International joint ventures and internal technology transfer versus external technology spillovers: Evidence from China"

description: Data and scripts necessary for replication of the results discussed in Jiang et al., "International joint ventures and internal technology transfer versus external technology spillovers: Evidence from China," Journal of International Economics.
DOI: 10.17632/jrmm82m4mv.2
title: Wind Turbine Blade Surfaces Dataset

description: The proposed dataset aims to provide a number of wind turbine blade images for testing and training purposes. The featured datasets can be used for testing and evaluation of Structure from Motion algorithms for 3D reconstruction, as data for machine learning algorithms for detecting damaged areas on blades or for quantifying blade surface roughness. Images are taken using Canon 5Ds DSLR camera with resolution of 8688 x 5792. The images come with EXIF data, containing additional information about the used capturing settings. The dataset is separated into two parts: - A dataset containing 5 wind turbine blade patches of areas of different surface structure. Two of the patches are of damaged areas, two of the patches are of rough areas, without pronounced surface deformations and one of the patches is a reference area, that does not contain any roughness or damages. The final patch contains the whole of the blade's edge area and is comprised of a mix of severely damaged areas, areas of small roughness and clear areas. The dataset also contains ground truth microscopy data for two of the damaged patches. The ground truth is scaled to absolute scale. - A dataset containing images of a small blade segment. The blade has been sand blasted, to imitate prolonged real world use. The images are taken both outdoor and indoor. The indoor images contain patches specifying areas of interest - one containing a rough patch and one containing damages. The outdoor images are focused on the whole blade and do not contain patches. The dataset also contains ground truth microscopy data for the two patches, which is scaled to absolute scale.
DOI: 10.17632/f357zfzxfy.1
title: SPDL specifications:Security Enhancement and Technique to Overcome Software Weakness for Android-Based Local Storage

description: This dataset is for publishing our SPDL specifications for proposed protocol described in "(Submitted to journal)Security Enhancement and Technique to Overcome Software Weakness for Android-Based Local Storage". One can check any detail information by reading above paper. [Tools for Security Protocol Verification] A poorly designed security protocol can attract malicious attacks because of its potential vulnerability. To prevent such attacks, security protocol verification before implementation is important. As a flaw in the security protocol design is among the security weaknesses, prevention is important. Thus, the security properties of the security protocol should be verified in advance using a formal technique. Various tools have been used for security protocol verification, such as Failures-Divergences Refinement (FDR)/Casper, Automated Validation of Internet Security Protocols and Applications (AVISPA), Proverif, and Scyther. In this study, the proposed preventive technique is verified using Scyther, based on a protocol description written in Security Protocol Description Language (SPDL); this provides verification, counterevidence, and analysis of the protocol in graphical user interface (GUI) form. [Modeling Proposed Protocol in SPDL for Scyther] Scyther receives the protocol description specified in SPDL and provides verification results. All entities, such as the client or server, are represented by roles. In this study, roles D and S are defined as the client and server, respectively. We publish our SPDL specifications for each global variable definition, initialization phase, and authentication phase on Mendeley Data and provide it publicly available to the research community.
DOI: 10.17632/j543hyxkk4
title: Metabolic Shifts in the Tricarboxylic Acid Cycle and Glycolysis Reveal Respiratory Adaptations of Streltzoviella insularis (Staudinger) (Lepidoptera: Cossidae) Larvae to Cold Stress

description: These data are the raw data used for the figures and tables in the article titled 'Metabolic Shifts in the Tricarboxylic Acid Cycle and Glycolysis Reveal Respiratory Adaptations of Streltzoviella insularis (Staudinger) (Lepidoptera: Cossidae) Larvae to Cold Stress'.
DOI: 10.17632/gdx3pkwp47.2
title: Dataset of Malicious and Benign Webpages

description: The dataset contains extracted attributes from websites that can be used for Classification of webpages as malicious or benign. The dataset also includes raw page content including JavaScript code that can be used as unstructured data in Deep Learning or for extracting further attributes. The data has been collected by crawling the Internet using MalCrawler [1]. The labels have been verified using the Google Safe Browsing API [2]. Attributes have been selected based on their relevance [3]. The details of dataset attributes is as given below: 'url' - The URL of the webpage. 'ip_add' - IP Address of the webpage. 'geo_loc' - The geographic location where the webpage is hosted. 'url_len' - The length of URL. 'js_len' - Length of JavaScript code on the webpage. 'js_obf_len - Length of obfuscated JavaScript code. 'tld' - The Top Level Domain of the webpage. 'who_is' - Whether the WHO IS domain information is compete or not. 'https' - Whether the site uses https or http. 'content' - The raw webpage content including JavaScript code. 'label' - The class label for benign or malicious webpage. Python code for extraction of the above listed dataset attributes is attached. The Visualisation of this dataset and it python code is also attached. This visualisation can be seen online on Kaggle [5].