AI-driven Quantum Dot Transistors for Ultra-Low Power Computing | Mishra | International Journal of Engineering, Science and Information Technology

About The Authors

Archana Mishra
Kalinga University
India

Department of CS & IT

Anjali Krushna Kadao
Kalinga University
India

Department of CS & IT

Shruti Rohilla
New Delhi Institute of Management
India

User

ARTICLE TEMPLATE

TOOLS

CURRENT INDEXING

VISITOR STATISTICS

SUPPORT BY

ISSN BARCODE

Keywords 6G Communication, Network Optimisation, Machine Learning, Deep Learning, Edge Intelligence 6G Networks, Massive IoT, Energy-Efficient Protocols, Non-Orthogonal Multiple Access, Energy Harvesting Activity, City, Transportation, Analytical Hierarchy Process Biomaterial Supercapacitors, Artificial Intelligence, 3D Printing, Energy Storage, Sustainability Cloud Storage, STEM, Education, Project-Based Learning Ethical AI, Energy Management Systems, Reinforcement Learning, Federated Learning, Smart Grid Hospital, Waste, Management, Engineering, Patients Internet of Medical Things, Body Sensor Network, Remote Monitoring System, Neurological Disorder, Health Issues Multi-Hop Transmission, Oracle APEX, IoT Feedback Loops, Signal Propagation Simulation Nanophotonic Crystals, AI-Driven Self-Assembly, Optical Computing, Refractive Index Tuning, Photonic Neural Networks Occupational Health, Physical Recovery, Stress, Therapy, Well-being PCOS, PPD, LR, Naïve Bayes, SVM PRISMA, Health Outcomes, Relevant Articles, Clinical Power Electronics Propagation Faults, Streaming Resilience, Low-Bandwidth Infrastructure, Simulation-Based Analysis, Educational Technology. Quantum AI, Nano Magnetic Sensors, Biomedical Imaging, Noise Suppression, Quantum Classical Computing Quantum Dot Transistors, Reinforcement Learning, Neuromorphic AI, Ultra-Low Power Computing, Hybrid Quantum-Classical AI. Quantum Machine Learning, Significant Potential, Quantum Layers Social Media, Digital Marketing, Consumer Behavior, Bibliometric Analysis, Marketing Strategy Soft Intronis, Biocompatible Energy Storage, Artificial Intelligence, Biofuel Cells, Piezoelectric Nanogenerators Weeds, Arabica Coffee Plantation, Organic, Conventional

Information

Journal Content
Browse

Download this PDF file

Refbacks

There are currently no refbacks.

Copyright (c) 2025 Archana Mishra, Anjali Krushna Kadao, Shruti Rohilla

International Journal of Engineering, Science, and Information Technology (IJESTY) eISSN 2775-2674

Published by Malikussaleh University, Indonesia

Editor E-mail: journalijesty@gmail.com

The works in the IJESTY Journal are licensed under a Creative Commons Attribution 4.0 International Public License (CC BY 4.0).