The extraction and construction of high-precision and long-distance vehicle trajectory data and microscopic traffic flow characteristics are critical for traffic safety studies. Current research typically relies on a limited number of datasets which suffer from vehicle detection inaccuracy and limitation of the coverage area. Therefore, we establish a high-precision and long-distance vehicle trajectory dataset of urban scenarios, which is also named as WUT-NGSIM.

The data of the AC report are collected from the website JUCHAO(http://www.cninfo.com) through the crawler process of Python.

The text feature data is obtained by computing AC reports with the machine learning and text analysis methods of Python.

The data includes 1349 firms from 2014-2019, with 6987 observations.

Switching vectors of an inverter with model predictive control were collected for different conditions of an induction machine. The induction machine had a rated speed of w=3000 rpm and a rated torque of T=1.20 N·m. The switching vectors were recorded as data series for the induction machine operating at different combinations of speed and torque at healthy and faulty states. Each data series consisted of 22000 switching vectors. Inter-turn short circuit fault was introduced over 2 turns (out of 104 turns) in one phase of the machine.

The Open Big Healthy Brains (OpenBHB) dataset is a large (N>5000) multi-site 3D brain MRI dataset gathering 10 public datasets (IXI, ABIDE 1, ABIDE 2, CoRR, GSP, Localizer, MPI-Leipzig, NAR, NPC, RBP) of T1 images acquired across 93 different centers, spread worldwide (North America, Europe and China). Only healthy controls have been included in OpenBHB with age ranging from 6 to 88 years old, balanced between males and females.