Dataset contains generated traffic from single requests towards DNS and DNS over Encryption servers as well as network traffic generated by browsers towards multiple DNS over HTTPS servers. The dataset contains also logs and csv files with queried domains. The IP addresses of the DoH servers are provided in the readme so that users can easily label the data extracted from pcap files. The dataset may be used for Machine Learning purposes (DNS over HTTPS identification).
COVIFN is a CoVID-19-specific dataset that consists of fact-checked fake news scraped from Poynter and true news from news publishers' verified portals. The dataset was pre-processed, the removal of special characters and non-vital information is performed.
The file contains columns such as:
Date: publish date of news article
country: country the article is about
text: the news article content
label: fake or real news label
URL: the fact-checked site
source: original news source site
Any work using this dataset should cite the following paper:
These simulated live cell microscopy sequences were generated by the CytoPacq web service https://cbia.fi.muni.cz/simulator [R1]. The dataset is composed of 51 2D sequences and 41 3D sequences. The 2D sequences are divided into distinct 44 training and 7 test sets. The 3D sequences are divided into distinct 34 training and 7 test sets. Each sequence contains up to 200 frames.
The dataset represents the negative interaction dataset of the Drugbank that has been generated from our proposed machine learning method based on drug similarity, which achieved an average accuracy of 95% compared to the randomly generated negative datasets in the literature. Drugbank was used as the drug target interaction dataset from https://go.drugbank.com/. It consists of 1,264 interactions among 504 drugs and 507 proteins. The dataset includes drugs names, their accession numbers, proteins names, their UniproteId on Uniprot at https://www.uniprot.org/.
This dataset contains measurements of TPC-C benchmark executions in MySQL server deployed in Google Cloud Platform.
The SiCWell Dataset contains data of battery electric vehicle lithium-ion batteries for modeling and diagnosis purposes. In this experiment, automotive-grade lithium-ion pouch bag cells are cycled with current profiles plausible for electric vehicles.
The analysis of current ripples in electric vehicles and the corresponding aging experiments of the battery cells result in a dataset, which is composed of the following parts:
