KSU-ArSL was developed by the Center of Smart Robotics Research at King Saud University (KSU) in conjunction with the Higher Education Program for the Deaf and Hard of Hearing. The dataset consists of 80 classes (belonging to 80 signs) recorded by 40 healthy subjects using three cameras (one RGB and two Microsoft Kinect cameras). Each subject repeated each sign 5 times in five separate sessions at the same day. As a result, there are 200 video samples per class, 16000 samples in total per camera.


The dialogue corpus is  described in the paper "Anticipating User Intentions in Customer Care Dialogue Systems" and contains a selection of human-chatbot Italian dialogues concerning customer-care requests.

In order to preserve the privacy and company data property, we removed the actual sentences and we present only the annotation described in the paper.


Data contains results of WCAG 2.0 Web Accessibility tests of 41 government websites


The dataset contains an example of energy consumption, Functioning hours and Production KPI of different stages of the experimental open pit mine, mainly the destoning, the screening, and the train loading station. The Code is an example of the prediction algorithm, and the API can be used to apply the same algorithm used in this article.

In the proposed Dataset the energy consumption data for each station are collected from power meters and stored into a database that contains functioning hours and production.


The train set and test set of NSL-KDD


These data is used to test the performance of the proposed in-motion inital alignment method.


These data includes the raw data of inertial measurement units, the raw data of GPS and the reference attitude angles.

All these data is simulated.

The frequency of inertial measurement units and GPS are 100Hz and 1Hz, respectively.

The data are explained below:

imu=[gryo;acc;time]       Unit is rad; m/s; s

GPS=[lat;lon;height;ve;vn;vu]; Unit is rad; rad; m; m/s; m/s; m/s

Ref_angle=[pitch;roll;yaw];      Unit is rad; rad; rad



The dielectric spectroscopy data was obtained to characterize the dielectric responses and calculate the dielectric loss in the FEM model. The complex dielectric permittivity was measured with the Novocontrol Concept 80 broadband dielectric spectrometer. Silver electrode with a diameter of 30 mm was prepared on both sides of the sample by sputtering. The temperature range in this experiment was from -30 to 150 °C with an interval of 10 °C. The frequency range was from 1 Hz to 1 MHz.



Opportunity++ is a precisely annotated dataset designed to support AI and machine learning research focused on the multimodal perception and learning of human activities (e.g. short actions, gestures, modes of locomotion, higher-level behavior).


Complete documentation is provided in the readme.




This dataset contains about 140,000 Tweets related to exoskeletons. that were mined for a period of 5-years from May 21, 2017, to May 21, 2022. The tweets contain diverse forms of communications and conversations which communicate user interests, user perspectives, public opinion, reviews, feedback, suggestions, etc., related to exoskeletons.


The dataset contains only tweet identifiers (Tweet IDs) due to the terms and conditions of Twitter to re-distribute Twitter data ONLY for research purposes. They need to be hydrated to be used. The process of retrieving a tweet's complete information (such as the text of the tweet, username, user ID, date and time, etc.) using its ID is known as the hydration of a tweet ID. For hydrating this dataset the Hydrator application (link to download and a step-by-step tutorial on how to use Hydrator) may be used.


Data Description

This dataset consists of 7 .txt files. The following shows the number of Tweet IDs and the date range (of the associated tweets) in each of these files. 

Filename: Exoskeleton_TweetIDs_Set1.txt

Number of Tweet IDs – 22945, Date Range of Tweets - July 20, 2021 – May 21, 2022

Filename: Exoskeleton_TweetIDs_Set2.txt

Number of Tweet IDs – 19416, Date Range of Tweets - Dec 1, 2020 – July 19, 2021

Filename: Exoskeleton_TweetIDs_Set3.txt

Number of Tweet IDs – 16673, Date Range of Tweets - April 29, 2020 - Nov 30, 2020

Filename: Exoskeleton_TweetIDs_Set4.txt

Number of Tweet IDs – 16208, Date Range of Tweets - Oct 5, 2019 - Apr 28, 2020

Filename: Exoskeleton_TweetIDs_Set5.txt

Number of Tweet IDs – 17983, Date Range of Tweets - Feb 13, 2019 - Oct 4, 2019

Filename: Exoskeleton_TweetIDs_Set6.txt

Number of Tweet IDs – 34009, Date Range of Tweets - Nov 9, 2017 - Feb 12, 2019

Filename: Exoskeleton_TweetIDs_Set7.txt

Number of Tweet IDs – 11351, Date Range of Tweets - May 21, 2017 - Nov 8, 2017


For any questions related to the dataset, please contact Nirmalya Thakur at thakurna@mail.uc.edu


This dataset contains actual field/experimental data for the following environmental engineering applications, namely:

  • Concentration data generated from filtration systems which treat influents, having contaminant materials, via adsorption process.
  • Streamflow height data collated for 50 states/cities in America for the historical period between 1900-2018.