*.csv (zip)
This is the dataset used in our journal paper, submitted to: IEEE Transactions on Dependable and Secure Computing, Special Issue on Explainable Artificial Intelligence for Cyber Threat Intelligence (XAI-CTI) Applications.
Submitted = 12-Jan-2021 (under review)
ID = TDSCSI-2021-01-0045
Source codes are available at IEEE Code Ocean:
Hatma Suryotrisongko (2020) Botnet DGA [Source Code]. https://doi.org/10.24433/CO.4005597.v2
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The aircraft fuel distribution system has two primary functions: storing fuel and distributing fuel to the engines. These functions are provided in refuelling and consumption phases, respectively. During refuelling, the fuel is first loaded in the Central Reservation Tank and then distributed to the Front and Rear Tanks. In the consumption phase, the two engines receive an adequate level of fuel from the appropriate tanks. For instance, the Port Engine (PE) will receive fuel from Front Tank and the Starboard Engine (SE) will receive fuel from Rear Tank.
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The Costas condition on a permutation matrix, expressed as row indices as elements of a vector c, can be expressed as A*c=b, where b is a vector of integers in which no element is zero. A particular formulation of the matrix A allows a singular value decomposition in which the eigenvalues are squared integers and the eigenvalues may be scaled to vectors with all integer elements. This is a database of the Costas constraint matrices A, the scaled eigenvectors, and the squared eigenvalues for orders 3 through 100.
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Dataset of the signals monitored in a typical overfeed refrigeration system. The system is composed of two compressors in parallel, four evaporative condensers and various evaporators distributed in the different spaces to refrigerate. The dataset contains variables from all the main components of the refrigeration system such as the compressors, the condensers and the evaporators, with additional information about the outdoor temperature, the temperature of the refrigerated spaces and all the set points.
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This dataset is offered as .csv and is part of 3 files which are:
- File 1: has all 1699 arabic news headlines colllected with the corresponding emotion classification that 3 annotators agreed on with no bias
- File 2: has the dataset with BOW features extracted
- File 3: has the dataset with n-gram features extracted
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E-nose can be used for food authentication and adulteration assessment. Recently, halal authentication has gained attention because of cases of pork adulteration in beef. In this study, The electronic nose was built using nine MQ series gas sensors from Zhengzhou Winsen Electronics Technology Co., Ltd for detection pork adulteration in beef. The list of gas sensors are MQ2, MQ4, MQ6, MQ9, MQ135, MQ136, MQ137, and MQ138. These gas sensors were assembled with an Arduino microcontroller.
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This data set includes Covid-19 related Tweet messages written in Turkish that contain at least one of four keywords (Covid, Kovid, Corona, Korona). These keywords are used to express Covid-19 virus in Turkey. Tweets collection was started from 11th March 2020, the first Covid-19 case seen in Turkey.
Currently dataset contain 4,8 million tweets with 6 different attribute of each tweets that were sent from 9 March 2020 until 6 May 2020.
The data file contains comma separated values (CSV). It contains the following information (6 Column) for each tweet in the data file:
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