Mehrdad Shoeibi¹, Mohammad Mehdi Sharifi Nevisi², Sarvenaz Sadat Khatami³, Diego Martín^2,*, Sepehr Soltani⁴, Sina Aghakhani⁵

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2819-2843, 2024, DOI:10.32604/cmc.2024.056823 - 18 November 2024

Abstract In the evolving landscape of the smart grid (SG), the integration of non-organic multiple access (NOMA) technology has emerged as a pivotal strategy for enhancing spectral efficiency and energy management. However, the open nature of wireless channels in SG raises significant concerns regarding the confidentiality of critical control messages, especially when broadcasted from a neighborhood gateway (NG) to smart meters (SMs). This paper introduces a novel approach based on reinforcement learning (RL) to fortify the performance of secrecy. Motivated by the need for efficient and effective training of the fully connected layers in the RL… More >

R. Meena^1,*, V. Thulasi Bai²

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1643-1658, 2022, DOI:10.32604/iasc.2022.025305 - 25 May 2022

Abstract The Covid-19 outbreak has an unprecedented effects on people's daily lives throughout the world, causing immense stress amongst individuals owing to enhanced psychological disorders like depression, stress, and anxiety. Researchers have used social media data to detect behaviour changes in individuals with depression, postpartum changes and stress detection since it reveals critical aspects of mental and emotional diseases. Considerable efforts have been made to examine the psychological health of people which have limited performance in accuracy and demand increased training time. To conquer such issues, this paper proposes an efficient depression detection framework named Improved… More >