This dataset webpage contains datasets of exisiting and proposed models:

• 12cell.zip
• 16cell.zip
• 36cell.zip
• Proposed_

Presented in my 2nd (may be last) keynote Speaker Presentation in Conference -  2025*.   

Novel Perspective of Contemplating Existing Principles of Scientific Truth : Novel B-Unified Theory, Postulates, Propositions And Models With Applications in Impedance, Transformers, Inverters, Generators, Pumps, Solar, Machinery, Turbines, SMPS and Short Circuit Analysis

This dataset webpage contains datasets of exisiting and proposed models:

• tubular.zip
• tubular2.zip
• tubular3.zip

 B Model of Fault And Short-Circuit Analysis of Synchronous Generator 

 presented in my 3rd Probably last Speaker Presentation in Conference -  2025*.  

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.

We collected programming problems and their solutions from previous studies. After applying some pre-processing steps, we queried advanced LLMs, such as GPT4, with the collected problems to produce machine-generated codes, while the original solutions were labeled as human-written codes. Finally, the entire collected dataset was divided into training, validation, and test sets, ensuring that there is no overlap among these sets, meaning no solutions in two different sets that solve the same programming problem.