.csv; .zip

Unified Multimodal Network Intrusion Detection Systems Dataset

The Unified Multimodal Network Intrusion Detection System (UM-NIDS) dataset is a comprehensive, standardized dataset that integrates network flow data, packet payload information, and contextual features, making it highly suitable for machine learning-based intrusion detection models. This dataset addresses key limitations in existing NIDS datasets, such as inconsistent feature sets and the lack of payload or time-window-based contextual features.

Categories:: Artificial Intelligence
Wireless Networking
IoT
Machine Learning
Standards Research Data
Communications
Security

775 Views

SART

SART contains 3000 tweets labelled with respect to the polarity of the sentiment expressed: positive, negative or neutral. Each class contains 1300 tweets and the dataset is split into train/validation/test csv files.

Categories:: Machine Learning
Social Sciences
Computational Intelligence

21 Views

CRAWDAD columbia/kinetic

200 hours of accelerometer information recorded over 25 days from 5 participants.

To help us better understand the properties of various energy sources and their impact on energy harvesting adaptive algorithms, we collected acceleration traces from different participants.

release date: 2014-05-13

Categories:: Wireless Networking

151 Views

Dataset for Iron Losses of IPMSMs

This dataset includes the rotor geometrical parameters (*.csv) and motor parameters (*.csv) of interior permanent magnet synchronous motors. The rotor geometry covers three structures: 2D-, V-, and Nabla-structures. The motor parameters are generated by machine learning based on the finite element analysis results. The software JMAG Designer 19.1 was used for the finite element analysis.

Categories:: Artificial Intelligence

557 Views

RETED

Although several databases of handwriting movements have been created so, none of them has been specifically designed for studying the effect of age during ellipse drawing. Ninety subjects voluntarily participated in the database construction. Their age ranged from 19 to 85 years: 30 participants in the range [19, 39] years, 30 in the range [40, 59] and 30 subjects in the range [60, 85]. Twenty-six women (range 19-72 years) and sixty-four men (range 25-85 years) participated.