The development of compact and controllable generative models under resource constraints remains a critical challenge for the practical deployment of conditional generative adversarial networks (cGANs). In this work, QuCon-GAN, a hybrid quantum-classical conditional GAN, is proposed to enhance generation&#...

This paper addresses the problem of distributed recursive state estimation over sensor networks utilizing the gossip protocol, where communication resources are conserved by allowing each node to randomly select neighboring nodes for data exchange. An easily implementable and scalable mathematical...

Waterproofing is crucial for maintaining the structural integrity and extending the longevity of buildings. However, traditional waterproofing materials possess limitations, including restricted durability, complex installation procedures, and environmental pollution, making them insufficient to meet the advanced wa...

In cloud manufacturing, Manufacturing Execution Systems (MES) must dynamically optimize MES-level process parameters under multi-objective and constraint-intensive conditions, including quality conformity, production-takt feasibility, energy consumption, and equipment-stability risk. Conventional rule-based approaches suffer from ...

Carbon dioxide is a promising refrigerant for refrigeration and heat pump applications because of its environmental sustainability. However, unlike supercritical gas coolers, the thermohydraulic behaviour of subcritical CO₂ finned-tube condensers remains inadequately investigated and understood because of compl...

Linear Fresnel Reflectors (LFR) are a type of concentrated solar collector that uses direct solar radiation (DSR) to provide useful heat for a range of applications, including power generation, heating and cooling. This study introduces a simplified analytical method for predicting the ...

Flood risks are escalating under climate change, necessitating advanced methods to improve runoff prediction and multivariate flood-risk assessment. In this study, a physics–XGBoost-based Bayesian model averaging with bivariate copulas (PXB-BVC) framework was developed by integrating the Soil and Water...

Understanding how different drought indicators characterise future drought conditions is essential for climate monitoring and adaptation planning. This study quantified annual severe- and extreme-drought occurrence rates at the 1- and 3-month timescales using the Standardised Precipitation Index (SPI), the...

The continued growth in computational demand, driven in large part by machine learning workloads, has coincided with the slowing of performance gains from semiconductor scaling alone. Therefore, additional computing power can no longer be simply obtained by using increased transistor density ...