Machine Learning

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. 

This dataset is created for neural network-based surrogate modeling of the power conversion losses. The dataset includes two sets of training and test data (for AC/DC and DC/DC converters respectively) for the neural network. The raw data is generated using PLECS Blockset Packages in MATLAB-Simulink environment. 

Accurate fire load (combustible objects) information is crucial for safety design and resilience assessment of buildings. Traditional fire load acquisition methods, such as fire load survey, which are time-consuming, tedious, and error-prone, failed to adapt to dynamic changed indoor scenes. As a starting point of automatic fire load estimation, fast recognition and detection of indoor fire load are important. Thus, A dataset containing images of indoor scenes and annotations of instance segmentation is developed in this research.

The EegDot data set  (EEG data evoked by Different Odor Types established by Tianjin University) collected using a Cerebus neural signal acquisition equipment involved thirteen odor stimulating materials, five of which (smelling like rose (A), caramel (B), rotten (C), canned peach (D), and excrement (E)) were selected from the T&T olfactometer (from the Daiichi Yakuhin Sangyo Co., Ltd., Japan) and the remaining eight from essential oils (i.e., mint (F), tea tree (G), coffee (H), rosemary (I), jasmine (J), lemon (K), vanilla (L) and lavender (M)).

The C3I Synthetic Face Depth Dataset consists of 3D virtual human models and 2D rendered RGB and GT depth images in zipped version into two folders for male and female.

Technical question-answering sites like Stack Overflow are gaining enormous attention from the practitioners of specialized fields to exchange their programming knowledge. They ask questions on different topics, having various levels of difficulty and complexity. To answer such questions, all practitioners do not have the same level of expertise on those topics. However, the existing approach of Stack Overflow does not consider the difficulty and primarily filters out the questions based on topics only.