Machine Learning

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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379 Views

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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A synthetic data for low power (P ≤10 mW) InGaAsP MQW-DFB lasers operating at a wavelength (λ) ranging from 1.53 to 1.57 µm at a case temperature  laying between -40 ℃ to 85 ℃ with side mode suppression ratio of more than 35 dB is generated and can be used for laser lifetime prediction using machine learning based approaches. 

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The dataset includes processed sequences of optical time domain reflectometry (OTDR) traces incorporating different types of fiber faults namely fiber cut, fiber eavesdropping (fiber tapping), dirty connector and bad splice. The dataset can be used for developping ML-based approaches for optical fiber fault detection, localization, idenification, and characterization. 

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