Please cite the following paper when using this dataset:
N. Thakur and C.Y. Han, “An Exploratory Study of Tweets about the SARS-CoV-2 Omicron Variant: Insights from Sentiment Analysis, Language Interpretation, Source Tracking, Type Classification, and Embedded URL Detection,” Journal of COVID, 2022, Volume 5, Issue 3, pp. 1026-1049
Abstract
Glacial lake outburst floods (GLOFs) are a major threat to the local communities and important infrastructures in the high mountain regions. Early detection of glacial lakes can prevent these disastrous events. Towards this end, we collected Sentinel 2 true color scenes of High-Mountain Asia (HMA) region using glacial lakes inventory of this region. It covers an area of 2080.12 km2 with nearly 30,121 glacial lakes. After data collection, we retained 1200 cloud free true color images and manually generated their ground truth masks.
This dataset contains pipe images straight, right and left curves to support AUV navigation based on image.
Please cite the following paper when using this dataset:
N. Thakur, “A Large-Scale Dataset of Twitter Chatter about Online Learning during the Current COVID-19 Omicron Wave,” Journal of Data, vol. 7, no. 8, p. 109, Aug. 2022, doi: 10.3390/data7080109
Abstract
In this study, a primary IMU-based gait dataset has been collected from 30 participants using a MOTI goniometer. This device collects movement data related to specific joints depending on the location of the device. The MOTI sensor contains an IMU consisting of an accelerometer, gyroscope, and magnetometer. Accelerometers measure acceleration the acceleration of the device, gyroscopes measure angular velocity of the device, and magnetometers measure the magnetic field of the Earth. In our study, the device was attached to arm and leg (thigh) positions.
# Datasets
The datasets were collected from a software based simulation environment simulating a small scale IEC 61850 compliant substation with both the primary plant and the process bus.
Please cite the following paper when using this dataset:
N. Thakur, “MonkeyPox2022Tweets: A large-scale Twitter dataset on the 2022 Monkeypox outbreak, findings from analysis of Tweets, and open research questions,” Infect. Dis. Rep., vol. 14, no. 6, pp. 855–883, 2022, DOI: https://doi.org/10.3390/idr14060087.
Abstract
In recent years, Bitcoin and other cryptocurrencies have been increasingly considered an investment option for an emerging market. However, its erratic behavior has discouraged some potential investors. To get insights into its behavior and price fluctuation, past studies have discovered the correlation between Twitter sentiments and Bitcoin behavior. Most of them have focused exclusively on their relationships, instead of the Twitter sentiment analysis itself. Finding the most suitable classification algorithms for sentiment analysis for this kind of data is challenging.
The dataset contains maps with the objective analysis (OA) fields of available water contents. OA is based on ground-base and remote sensing (ASCAT) observations in the upper 10 and 20 cm soil layers for the period from September 11 to November 16, 2022.
