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Open access Aug 2026

A hybrid random forest–ANFIS framework for accurate power estimation in CMOS VLSI circuits

Accurate estimation of power is a main requirement throughout the use of Complementary Metal–Oxide–Semiconductor Very Large-Scale Integration (CMOS VLSI) because it determines how efficiently energy is used; how hot a device will get from high temperatures; whether a device will work properly over long periods of time...

V. Govindaraj, M. Sheela, P. M. Krishnammal et al. · 0 citations
Open access Sep 2026

Computational modeling of catastrophic fault classification in Digital to Analog Converters using machine learning

This study compares the performance of Back Propagation Neural Network, Support Vector Machine, and Probabilistic Neural Network to classify catastrophic faults in both 16-bit Charge Scaling and Binary Weighted DACs that have experienced process variation such as variable threshold voltage, oxide thickness and temperat...

V. Govindaraj, M. Sheela, M. Muthuraja et al. · 0 citations
Open access Aug 2026

An NLP-Based Framework for Fake News Detection Using Contextual and Engineered Features in Communication Technologies

The model achieved remarkable results over various phases, accuracy, precision, recall, and F1-score increased, reaching 97.0%, 96.8%, and 96.9%, respectively, in the final classification phase, demonstrating robust and reliable detection capabilities.

S. Gopalakrishnan, J. Thangamalar, M. Sheela et al. · 0 citations

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