*.csv (zip)
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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