Machine Learning

Wireless Intelligence Channel (WIC) is a realistic channel data set, which is designed for deep learning research work in MIMO as well as other applications. The WIC data set is obtained directly through commercial BSs and a device capable of data acquisition that is similar to a commercial terminal. The scene selection and parameter configuration involved in the experiment are based on the characteristics of realistic scenarios and the existing configurations in commercial BSs, without assumptions and restrictions on the ideal experimental conditions.

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Here we provide the dataset containing the power measurements obtained with our RIS prototype, which were carried out in the anechoic chamber of TU Darmstadt.

The use of data here contained is intended only for research purposes.

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Sign languages are the most common mode of communication with and between hearing-impaired individuals. In the Arab world, Arabic sign language is used with different dialects supporting a distinct set of rules for the gestures used. With research on natural language processing advancing, models have been developed to translate sign language to spoken language and vice versa. However, Arabic sign language has rarely been studied due to the lack of availability of datasets dealing with Arabic sign language.

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Nowadays road accident in Bangladesh is a buzzword due to its lack of carefulness of the driver of the vehicle where some parameter exists. The traffic safety of the roadway is an essential concern not only for transportation governing agencies but also for citizens of our country. For safe driving suggestions, the important thing is to find the variables that are tensed to relate to the fatal accidents that are occurring often. In this dataset, we provides a detailed account of the road accidents that covers the year of 2016 to 2019.

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Nowadays road accident in Bangladesh is a buzzword due to its lack of carefulness of the driver of the vehicle where some parameter exists. The traffic safety of the roadway is an essential concern not only for transportation governing agencies but also for citizens of our country. For safe driving suggestions, the important thing is to find the variables that are tensed to relate to the fatal accidents that are occurring often. In this dataset, we provides a detailed account of the road accidents that covers the year of 2016 to 2019.

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We describe all the steps needed to build an original real-world dataset used to perform the so-called "Multivariate time series prediction" through Machine Learning (ML) techniques. The dataset contains several features of cellular traffic organized into time series. The goal is to exploit Machine Learning to predict the future behavior of a given feature. Such a prediction takes into account the past values of the feature itself and the past values of other concurrent features.

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The dataset is intended to cover core issues pertaining to the area of a traffic optimization via RET motors inside the antenna on the mobile base station system (BSS). The principle of RET operation was already known to scientists; however, the use of a machine learning and big data provides the possibility of creation an autonomous system, which control RET system.

Last Updated On: 
Sun, 10/23/2022 - 08:50

The datasets were originally crawled from the Meetup.com by authors of this work[1]. It consists of two part:

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The dataset contains short video clips of four shoulder exercises.

  1. Arm flexion and extension
  2. Arm abduction and adduction
  3. Arm lateral and medial rotation
  4. Arm circumduction

 

The videos are labeled as either correct or incorrect.

 

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<p>This multilingual Twitter dataset spans over 2 years from October 2019 to the end of 2021,&nbsp;including 3 months before the outbreak of the COVID-19&nbsp;pandemic.</p>

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