A new small aerial flame dataset, called the Aerial Fire and Smoke Essential (AFSE) dataset, is created which is comprised of screenshots from different YouTube wildfire videos as well as images from FLAME2. Two object categories are included in this dataset: smoke and fire. The collection of images is made to mostly contain pictures utilizing aerial viewpoints. It contains a total of 282 images with no augmentations and has a combination of images with only smoke, fire and smoke, and no fire nor smoke.

Meituan Bench (MTB) is an enterprise-level benchmarking tool designed for time-series forecasting in real-world business scenarios. Built upon an open-source dataset derived from 10,000 real-world services across various business units, MTB provides a standardized evaluation framework for time-series prediction models. The dataset includes 200 representative services, capturing diverse traffic patterns essential for assessing forecasting performance.

This data set contains all relevant data content required in the experiment, and all data are stored in.mat format. This format is a commonly used data file format in MATLAB software, which facilitates efficient data processing and analysis. Users can import these.mat files directly without additional data conversion or processing, saving time and improving productivity. In addition, the content in the dataset has been carefully curated to ensure the integrity and accuracy of the data, which is suitable for use in various experiments and research work.

Contains 80 questions of LeetCode weekly and bi-weekly contests released after March 2024.
Each question contains an average of 644 test cases, as well as programming solutions in Python language collected from the official LeetCode website. The input fields of the data set contain function headers and natural language descriptions, which are mainly used to evaluate the ability of large models to solve programming problems according to requirements.