Age and Power Minimization via Meta-Deep Reinforcement Learning in UAV Networks
Age-of-information (AoI) and transmission power are crucial performance metrics in low energy wireless networks, where information freshness is of paramount importance. This […]
The integration of machine learning into proteomics advances food authentication and adulteration control
6G Radio Channel Sounding: Challenges and Potential Solutions
ML-Aided 2D Indoor Positioning Using Energy Harvesters and Optical Detectors for Self Powered Light-based IoT Sensors
Advancements in 6G and IoT sensor networks prioritise sustainability and energy efficiency, with positioning services essential for improved functionality. Light-based IoT (LIoT) […]
A Comprehensive Survey of Machine Learning Applied to Resource Allocation in Wireless Communications
Telecommunications play a pivotal role in shaping today’s interconnected world by fostering global development, supporting seamless information exchange across vast distances, and […]
Advances in image-based estimation of snow variable: A systematic literature review on recent studies
Accurately estimating snow hydrology parameters, including snow coverage mapping and snow depth, plays a significant role in comprehending water resource dynamics, flood […]
Co-optimization of Demand Response Aggregators and distribution system operator for resilient operation using machine learning based wind generation forecasting: A bilevel approach
The increasing occurrence of extreme weather events has severely compromised the resilience of power distribution systems, resulting in widespread outages and substantial […]
Model-Based Machine Learning for Max-Min Fairness Beamforming Design in JCAS Systems
Joint communications and sensing (JCAS) is expected to be a crucial technology for future wireless systems. This paper investigates beamforming design for […]
Toward a Dynamic Future with Adaptable Computing and Network Convergence (ACNC)
In the context of advancing 6G, a substantial paradigm shift is anticipated, highlighting comprehensive everything-to-everything interactions characterized by numerous connections and stringent […]
HD-sEMG-CORE: An Open-Source Hybrid Network Algorithm for Efficient Compression and Accurate Restoration of High-Density Surface Electromyography Signals
High-density surface electromyography (HD-sEMG) provides distinct advantages over traditional bipolar sEMG, including improved spatial resolution and enhanced localization of muscle activity. However, […]