With the current footprint of the embedded IoT industries, there is a huge requirement to understand and analyze the existing IoT boards to provide the future IoT board manufacturers with a direction of research and development.

This datasheet contains the comparative architectural survey of 60 computing boards from the rapid prototyping industries. This dataset was collected directly from the manufacturers’ datasheet. The motivation to build this dataset is to analyze the current advancements in the IoT industries to reflect the future architectural designs of various boards.

This publication contains three new datasets for scene-level sketch semantic segmentation task, namely SKY-Scene, TUB-Scene, and Freehand-Scene. SKY-Scene and TUB-Scene are synthetic datasets, where the scene layout templates were extracted from dataset SketchyScene, and the object components were adopted from dataset Sketchy. They are composed to include more sketch-specific characteristics, e.g., sparsity, abstractness, and diversity, to truly evaluate segmentation performance. Freehand-Scene are fifty real human-drawn scene sketches for practical test.

This dataset contains usability evaluation raw data of the "Child-Home Interaction: Design and Usability Evaluation of Game-based End-user Development for Children" paper.

This dataset contains a collection of videos consisting of satellite imagery augmented with 3D ship models, accompanied by the ships' corresponding AIS data. The intention of this dataset is for detecting dark ships, which are sea vessels acting maliciously, often while spoofing their AIS data. Multiple datasets exist that consist of satellite imagery of ships, however this dataset has the advantage of including each ships' corresponding AIS data. The simulated ships include both normal and anomalous behavior, whether the anomalous behavior is benign or malicious.

 These medical texts data are derived from the patients' real disease cases, including the patients' diseases, symptoms and other information

Tweets related to 10 different types of disasters were monitored from 28 September 2021 till 6 October 2021. 67528 rows containing 16 fields were extracted using Artificial Intelligence and Natural Language Processing Services of Microsoft.

Sed vitae dui libero. Ut turpis nisl, bibendum a cursus congue, iaculis ac ante. In hac habitasse platea dictumst. Sed nec feugiat lacus. Quisque efficitur mattis blandit. Fusce feugiat condimentum facilisis. Mauris a consectetur magna. Pellentesque eleifend lacus nec malesuada facilisis. In et convallis massa. Ut tempor, lectus vel tincidunt lobortis, augue justo commodo velit, at congue mi augue vel nisi. Donec sit amet lorem ut felis mattis vehicula ut at felis. Curabitur non nisl ex. Nam venenatis augue ut dui mollis, eu volutpat leo varius.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed eget elit sollicitudin, molestie sem non, sodales purus. Pellentesque sagittis hendrerit fermentum. Nam at metus vel mi molestie luctus sit amet at diam. Morbi vitae diam tristique, tincidunt orci eu, feugiat odio. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Donec auctor enim lacinia vulputate pellentesque. Morbi ac arcu ut nisi aliquam venenatis nec ut diam. Donec viverra est lacus, in volutpat neque tempor vitae. Vestibulum sollicitudin malesuada convallis. Donec ultricies mi eu lacus finibus dignissim.

this is it