BS-HMS-Dataset is a dataset of the users' brainwave signals and the corresponding hand movement signals from a large number of volunteer participants. The dataset has two parts; (1) Neurosky based Dataset (collected over several months in 2016 from 32 volunteer participants), and (2) Emotiv based Dataset (collected from 27 volunteer participants over several months in 2019). 

  • Machine Learning
  • Last Updated On: 
    Thu, 12/12/2019 - 13:17

    Multi-type residual data (vibrations, sound, magnetic intensity) collected from 3D printers & CNC machines.

  • IoT
  • Last Updated On: 
    Thu, 11/28/2019 - 17:31

    The bearing dataset  is acquired by the electrical engineering laboratory of Case Western Reserve University and published on the Bearing Data Center Website. The gearbox dataset  is from IEEE PHM Challenge Competition in 2009

  • Standards Research Data
  • Last Updated On: 
    Wed, 11/20/2019 - 03:31

    This dataset contains the actual sensor and calculated process variables in a winder station in a paper mill. Several Process variables change in time with the change of the rewind diameter. I provided the process data for two sets, in future I will add more data. Advanced time series forcasting techniques can be used to estimate many process variables considering the rewind diameter as the time axis.

  • Machine Learning
  • Last Updated On: 
    Tue, 10/08/2019 - 06:23

    Urban flooding is a common problem across the world. In India, it leads to casualties every year, and financial loss to the tune of tens of billions of rupees. The damage done due to flooding can be mitigated if the locations deserving attention are known. This will enable an effective emergency response, and provide enough information for the construction of appropriate storm water drains to mitigate the effect of floods. In this work, a new technique to detect flooding level is introduced, which requires no additional equipment, and consequent installation and maintenance costs.

  • Machine Learning
  • Last Updated On: 
    Mon, 01/06/2020 - 23:27

    Typically, a paper mill comprises three main stations: Paper machine, Winder station, and Wrapping station. The Paper machine produces paper with particular grammage in gsm (gram per square meter). The typical grammage classes in our paper mill are 48 gsm, 50 gsm, 58 gsm, 60 gsm, 68 gsm, 70 gsm. The Winder station takes a paper spool that is about 6 m width as it’s input and transfers is to customized paper rolls with particular diameter and width.

  • Artificial Intelligence
  • Last Updated On: 
    Tue, 10/08/2019 - 06:26

    The dataset contains some tests which were performed over composite material samples, propagating Lamb waves using PZT transducers.

  • Sensors
  • Last Updated On: 
    Tue, 09/17/2019 - 04:41

    One of the materials that is commonly being used in electronics applications is paper. It is flexible, cheap, highly available, and allows for simple manufacturing when paired with methods such as screen printing or inkjet printing. Proposed below is an optogenetic device that uses paper as the sole substrate, with a screen­printed PCB with Ag/AgCl wires. This device was quick and easy to manufacture, unlike the state of the art optoelectronic devices that use polymers and rely on complex fabrication methods such as photolithography.

  • Energy
  • Last Updated On: 
    Mon, 09/16/2019 - 18:18

    Dataset for Wi-Pose, which captures Fine-grained Human Poses with Commodity Wi-Fi

  • Communications
  • Last Updated On: 
    Fri, 08/30/2019 - 07:32

    This contains data for ISFET based pH sensor drift compensation using machine learning techniques

  • Sensors
  • Last Updated On: 
    Wed, 08/21/2019 - 08:49