Vehicular networks have various characteristics that can be helpful in their inter-relations identifications. Considering that two vehicles are moving at a certain speed and distance, it is important to know about their communication capability. The vehicles can communicate within their communication range. However, given previous data of a road segment, our dataset can identify the compatibility time between two selected vehicles. The compatibility time is defined as the time two vehicles will be within the communication range of each other.


One-way delay (OWD) is the transmission time of the network packet from the first to the last bit from the sender node to the receiver node. The data set presented here was obtained as a result of measurements performed for the paper “Improving the Accuracy of One-Way Delay Measurements”.

One-way delay measurements were performed using three different utilities:

* the utility from the OWAMP protocol;

* first version of our utility, owping1; and

* the new version of our utility, owping2.


This dataset contains the results of the simulation runs of the experiments performed to evaluate and compare the proposed spatial model for situated multi-agent systems. The model was introduced in a paper entitled "BioMASS, a spatial model for situated multiagent systems that optimizes neighborhood search". In this paper we presented a new model to implement a spatially explicit environment that supports constant-time sensory (neighborhood search) and locomotion functions for situated multiagent systems.


This is a dataset of Finite Difference Time Domain (FDTD) simulation results of 13 defective crystals and one non-defective crystal.  There are 4 fields in the dataset, namely: Real, Img, Int, and Attribute. The header real shows a real part of the simulated result, img shows the imaginary part, int gives the intensity all in superimposed form. Attribute denotes the label of a crystal simulated. The label 0 is for the simulated crystal, which is non-defective.  Other 13 labels, from crystal 1 to crystal 13 are assigned to the 13 different crystals whose simulations are studied.


Modern science is build on systematic experimentation and observation.  The reproducibility and replicability of  the experiments and observations are central to science. However, reproducibility and replicability are not always guaranteed, sometimes referred to as 'crisis of reproducibility'. To analyze the extent of the crisis, we conducted a survey on the state of reproducibility in remote sensing. This survey was conducted as an online survey. The answers of the respondents are saved in this dataset in full-text CSV format.


The dataset consists of the following columns:

Data description

ColumnDescriptiongift_idUnique ID of giftgift_typeType of gift (clothes/perfumes/etc.)gift_categoryCategory to which the gift belongs under that gift typegift_clusterType of industry the gift belongsinstock_dateDate of arrival of stockstock_update_dateDate on which the stock was updatedlsg_1 - lsg_6Anonymized variables related to giftuk_date1, uk_date2Buyer related datesis_discountedShows whether the discounted is applicable on the giftvolumesNumber of packages boughtpriceThe total price


This dataset (GeoCOV19Tweets) contains IDs and sentiment scores of geo-tagged tweets related to the COVID-19 pandemic. The real-time Twitter feed is monitored for coronavirus-related tweets using 90+ different keywords and hashtags that are commonly used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. The tweet IDs in this dataset belong to the tweets created providing an exact location.


While social media has been proved as an exceptionally useful tool to interact with other people and massively and quickly spread helpful information, its great potential has been ill-intentionally leveraged as well to distort political elections and manipulate constituents. In the paper at hand, we analyzed the presence and behavior of social bots on Twitter in the context of the November 2019 Spanish general election.


This dataset is the result of test case and developer metrics extraction from Honfi's experiment in https://zenodo.org/record/2596044#.Xnm4sS2B1QJ

The detail of test case extraction is attached.

It contained 20 metrics from the generated test case and six metrics from the profile of developers. 26 metrics act as independent variable. There are two dependent variables : ABU (Actual Binary Understandability) and TAU (Timed Actual Understandability).


The dataset is system activities captured by Procmon on Windows, including running malware WannaPeace and Infostealer.Dexter.