Junyu Ge¹, Yifan Wang¹, Hong Li^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.4, pp. 1-3, 2025, DOI:10.32604/icces.2025.011446

Abstract The advancement of untethered and adaptive robotic systems necessitates the development of compact, efficient, and silent pneumatic power sources [1,2]. Traditional pneumatic actuation relies on bulky compressors or external gas reservoirs, limiting their practical applications in mobile and autonomous systems [3,4]. This work presents a novel electrochemical pneumatic battery (EPB) that exploits electrochemical driven gas generation to achieve controlled and energy-efficient pneumatic actuation, offering a viable alternative to conventional air supply methods. The EPB operates through an electrochemical redox mechanism based on a zinc-oxygen battery [5–7], enabling reversible gas storage and controlled pressure modulation. This… More >

Abubakar Elsafi^1,*, Arafat Abdulgader Mohammed Elhag², Lubna A. Gabralla³, Ali Ahmed⁴, Ashraf Osman Ibrahim⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 621-647, 2025, DOI:10.32604/cmes.2025.072726 - 30 October 2025

Abstract Energy efficiency stands as an essential factor when implementing deep reinforcement learning (DRL) policies for robotic control systems. Standard algorithms, including Deep Deterministic Policy Gradient (DDPG), primarily optimize task rewards but at the cost of excessively high energy consumption, making them impractical for real-world robotic systems. To address this limitation, we propose Physics-Informed DDPG (PI-DDPG), which integrates physics-based energy penalties to develop energy-efficient yet high-performing control policies. The proposed method introduces adaptive physics-informed constraints through a dynamic weighting factor (), enabling policies that balance reward maximization with energy savings. Our motivation is to overcome the… More >

Ramadan Abdul-Rashid¹, Mohd Amiruddin Abd Rahman^1,*, Abdulaziz Yagoub Barnawi²

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3213-3250, 2025, DOI:10.32604/cmes.2025.066589 - 30 September 2025

Abstract Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks (WSNs), especially in security-critical, time-sensitive applications. However, most existing protocols degrade substantially under malicious interference. We introduce iSTSP, an Intelligent and Secure Time Synchronization Protocol that implements a four-stage defense pipeline to ensure robust, precise synchronization even in hostile environments: (1) trust preprocessing that filters node participation using behavioral trust scoring; (2) anomaly isolation employing a lightweight autoencoder to detect and excise malicious nodes in real time; (3) reliability-weighted consensus that prioritizes high-trust nodes during time aggregation; and (4) convergence-optimized synchronization… More >

Deyu Lin^1,2, Yujie Zhang ², Zhiwei Hua², Jianfeng Xu^2,3,*, Yufei Zhao¹, Yong Liang Guan¹

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1859-1882, 2025, DOI:10.32604/cmc.2025.066283 - 29 August 2025

Abstract Energy efficiency is critical in Wireless Sensor Networks (WSNs) due to the limited power supply. While clustering algorithms are commonly used to extend network lifetime, most of them focus on single-layer optimization. To this end, an Energy-efficient Cross-layer Clustering approach based on the Gini (ECCG) index theory was proposed in this paper. Specifically, a novel mechanism of Gini Index theory-based energy-efficient Cluster Head Election (GICHE) is presented based on the Gini Index and the expected energy distribution to achieve balanced energy consumption among different clusters. In addition, to improve inter-cluster energy efficiency, a Queue synchronous More >

P. William^1,2, Ved Prakash Mishra¹, Osamah Ibrahim Khalaf^3,*, Arvind Mukundan⁴, Yogeesh N⁵, Riya Karmakar⁶

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5133-5156, 2025, DOI:10.32604/cmc.2025.065840 - 30 July 2025

Abstract Cloud computing has become an essential technology for the management and processing of large datasets, offering scalability, high availability, and fault tolerance. However, optimizing data replication across multiple data centers poses a significant challenge, especially when balancing opposing goals such as latency, storage costs, energy consumption, and network efficiency. This study introduces a novel Dynamic Optimization Algorithm called Dynamic Multi-Objective Gannet Optimization (DMGO), designed to enhance data replication efficiency in cloud environments. Unlike traditional static replication systems, DMGO adapts dynamically to variations in network conditions, system demand, and resource availability. The approach utilizes multi-objective optimization More >

Linlan Chang¹, Win-Jet Luo^1,2, Indra Permana², Bowo Yuli Prasetyo³, Alya Penta Agharid¹, Fujen Wang^2,*

Energy Engineering, Vol.122, No.5, pp. 1771-1787, 2025, DOI:10.32604/ee.2025.062209 - 25 April 2025

Abstract Heating, Ventilation, and Air Conditioning (HVAC) systems are critical for maintaining thermal comfort in office environments which also crucial for occupant well-being and productivity. This study investigates the impact of integrating ceiling fans with higher air conditioning setpoints on thermal comfort and energy efficiency in office environments. Field measurements and questionnaire surveys were conducted to evaluate thermal comfort and energy-saving potential under varying conditions. Results show that increasing the AC setpoint from 25°C to 27°C, combined with ceiling fan operation, reduced power consumption by 10%, achieving significant energy savings. Survey data confirmed that 85% of… More >

Tabassum Kanwal¹, Saif Ur Rehman^1,*, Azhar Imran², Haitham A. Mahmoud³

Computer Systems Science and Engineering, Vol.49, pp. 185-212, 2025, DOI:10.32604/csse.2024.056535 - 10 January 2025

Abstract This study presents an energy-efficient Internet of Things (IoT)-based wireless sensor network (WSN) framework for autonomous data validation in remote environmental monitoring. We address two critical challenges in WSNs: ensuring data reliability and optimizing energy consumption. Our novel approach integrates an artificial neural network (ANN)-based multi-fault detection algorithm with an energy-efficient IoT-WSN architecture. The proposed ANN model is designed to simultaneously detect multiple fault types, including spike faults, stuck-at faults, outliers, and out-of-range faults. We collected sensor data at 5-minute intervals over three months, using temperature and humidity sensors. The ANN was trained on 70%… More >

Rahma Gantassi, Zaki Masood, Yonghoon Choi^*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 327-343, 2025, DOI:10.32604/cmc.2024.058143 - 03 January 2025

Abstract Wireless sensor network (WSN) technologies have advanced significantly in recent years. Within WSNs, machine learning algorithms are crucial in selecting cluster heads (CHs) based on various quality of service (QoS) metrics. This paper proposes a new clustering routing protocol employing the Traveling Salesman Problem (TSP) to locate the optimal path traversed by the Mobile Data Collector (MDC), in terms of energy and QoS efficiency. To be more specific, to minimize energy consumption in the CH election stage, we have developed the M-T protocol using the K-Means and the grid clustering algorithms. In addition, to improve More >

Surbhi Bhatia Khan^1,2,*, Mohammad Alojail³, Mahesh Thyluru Ramakrishna⁴, Hemant Sharma⁵

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4895-4914, 2024, DOI:10.32604/cmc.2024.057585 - 19 December 2024

Abstract In Intelligent Manufacturing, Big Data and industrial information enable enterprises to closely monitor and respond to precise changes in both internal processes and external environmental factors, ensuring more informed decision-making and adaptive system management. It also promotes decision making and provides scientific analysis to enhance the efficiency of the operation, cost reduction, maximizing the process of production and so on. Various methods are employed to enhance productivity, yet achieving sustainable manufacturing remains a complex challenge that requires careful consideration. This study aims to develop a methodology for effective manufacturing sustainability by proposing a novel Hybrid… More >

Alya Penta Agharid¹, Indra Permana², Nitesh Singh¹, Fujen Wang^2,*, Susan Gustiyana²

Energy Engineering, Vol.121, No.12, pp. 3549-3571, 2024, DOI:10.32604/ee.2024.056398 - 22 November 2024

Abstract Hotel buildings are currently among the largest energy consumers in the world. Heating, ventilation, and air conditioning are the most energy-intensive building systems, accounting for more than half of total energy consumption. An energy audit is used to predict the weak points of a building’s energy use system. Various factors influence building energy consumption, which can be modified to achieve more energy-efficient strategies. In this study, an existing hotel building in Central Taiwan is evaluated by simulating several scenarios using energy modeling over a year. Energy modeling is conducted by using Autodesk Revit 2025. It… More >