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  • Open Access

    ARTICLE

    Enhancing Energy Efficiency with a Dynamic Trust Measurement Scheme in Power Distribution Network

    Yilei Wang1, Xin Sun1, Guiping Zheng2,3, Ahmar Rashid4, Sami Ullah5, Hisham Alasmary6, Muhammad Waqas7,8,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3909-3927, 2024, DOI:10.32604/cmc.2024.047767

    Abstract The application of Intelligent Internet of Things (IIoT) in constructing distribution station areas strongly supports platform transformation, upgrade, and intelligent integration. The sensing layer of IIoT comprises the edge convergence layer and the end sensing layer, with the former using intelligent fusion terminals for real-time data collection and processing. However, the influx of multiple low-voltage in the smart grid raises higher demands for the performance, energy efficiency, and response speed of the substation fusion terminals. Simultaneously, it brings significant security risks to the entire distribution substation, posing a major challenge to the smart grid. In response to these challenges, a… More >

  • Open Access

    ARTICLE

    Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks

    Youseef Alotaibi1, B. Rajasekar2, R. Jayalakshmi3, Surendran Rajendran4,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4243-4262, 2024, DOI:10.32604/cmc.2024.047608

    Abstract Rapid development in Information Technology (IT) has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle (V2V) transmission. Vehicular networks give a safe and more effective driving experience by presenting time-sensitive and location-aware data. The communication occurs directly between V2V and Base Station (BS) units such as the Road Side Unit (RSU), named as a Vehicle to Infrastructure (V2I). However, the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with time. Therefore, the scheme of an effectual routing protocol for reliable and stable communications is significant. Current research demonstrates… More >

  • Open Access

    ARTICLE

    Adaptation of Federated Explainable Artificial Intelligence for Efficient and Secure E-Healthcare Systems

    Rabia Abid1, Muhammad Rizwan2, Abdulatif Alabdulatif3,*, Abdullah Alnajim4, Meznah Alamro5, Mourade Azrour6

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3413-3429, 2024, DOI:10.32604/cmc.2024.046880

    Abstract Explainable Artificial Intelligence (XAI) has an advanced feature to enhance the decision-making feature and improve the rule-based technique by using more advanced Machine Learning (ML) and Deep Learning (DL) based algorithms. In this paper, we chose e-healthcare systems for efficient decision-making and data classification, especially in data security, data handling, diagnostics, laboratories, and decision-making. Federated Machine Learning (FML) is a new and advanced technology that helps to maintain privacy for Personal Health Records (PHR) and handle a large amount of medical data effectively. In this context, XAI, along with FML, increases efficiency and improves the security of e-healthcare systems. The… More >

  • Open Access

    ARTICLE

    Improving Heat Transfer in Parabolic Trough Solar Collectors by Magnetic Nanofluids

    Ritesh Singh1, Abhishek Gupta1, Akshoy Ranjan Paul1, Bireswar Paul1, Suvash C. Saha2,*

    Energy Engineering, Vol.121, No.4, pp. 835-848, 2024, DOI:10.32604/ee.2024.046849

    Abstract A parabolic trough solar collector (PTSC) converts solar radiation into thermal energy. However, low thermal efficiency of PTSC poses a hindrance to the deployment of solar thermal power plants. Thermal performance of PTSC is enhanced in this study by incorporating magnetic nanoparticles into the working fluid. The circular receiver pipe, with dimensions of 66 mm diameter, 2 mm thickness, and 24 m length, is exposed to uniform temperature and velocity conditions. The working fluid, Therminol-66, is supplemented with Fe3O4 magnetic nanoparticles at concentrations ranging from 1% to 4%. The findings demonstrate that the inclusion of nanoparticles increases the convective heat… More >

  • Open Access

    ARTICLE

    Investigation of FRP and SFRC Technologies for Efficient Tunnel Reinforcement Using the Cohesive Zone Model

    Gang Niu1,2, Zhaoyang Jin2, Wei Zhang3,*, Yiqun Huang3

    Structural Durability & Health Monitoring, Vol.18, No.2, pp. 161-179, 2024, DOI:10.32604/sdhm.2023.044580

    Abstract Amid urbanization and the continuous expansion of transportation networks, the necessity for tunnel construction and maintenance has become paramount. Addressing this need requires the investigation of efficient, economical, and robust tunnel reinforcement techniques. This paper explores fiber reinforced polymer (FRP) and steel fiber reinforced concrete (SFRC) technologies, which have emerged as viable solutions for enhancing tunnel structures. FRP is celebrated for its lightweight and high-strength attributes, effectively augmenting load-bearing capacity and seismic resistance, while SFRC’s notable crack resistance and longevity potentially enhance the performance of tunnel segments. Nonetheless, current research predominantly focuses on experimental analysis, lacking comprehensive theoretical models. To… More > Graphic Abstract

    Investigation of FRP and SFRC Technologies for Efficient Tunnel Reinforcement Using the Cohesive Zone Model

  • Open Access

    ARTICLE

    Numerical Studies on Thermal and Hydrodynamic Characteristics of LNG in Helically Coiled Tube-in-Tube Heat Exchangers

    Fayi Yan*, Xuejian Pei, He Lu, Shuzhen Zong

    Frontiers in Heat and Mass Transfer, Vol.22, No.1, pp. 287-304, 2024, DOI:10.32604/fhmt.2023.045038

    Abstract As compact and efficient heat exchange equipment, helically coiled tube-in-tube heat exchangers (HCTT heat exchangers) are widely used in many industrial processes. However, the thermal-hydraulic research of liquefied natural gas (LNG) as the working fluid in HCTT heat exchangers is rarely reported. In this paper, the characteristics of HCTT heat exchangers, in which LNG flows in the inner tube and ethylene glycol-water solution flows in the outer tube, are studied by numerical simulations. The influences of heat transfer characteristics and pressure drops of the HCTT heat transfers are studied by changing the initial flow velocity, the helical middle diameter, and… More >

  • Open Access

    ARTICLE

    HOT WATER COOLED HEAT SINKS FOR EFFICIENT DATA CENTER COOLING: TOWARDS ELECTRONIC COOLING WITH HIGH EXERGETIC UTILITY

    Peter Kastena, Severin Zimmermanna, Manish K. Tiwaria, Bruno Michelb, Dimos Poulikakosa,*

    Frontiers in Heat and Mass Transfer, Vol.1, No.2, pp. 1-10, 2010, DOI:10.5098/hmt.v1.2.3006

    Abstract Electronic data center cooling using hot water is proposed for high system exergetic utility. The proof-of-principle is provided by numerically modeling a manifold micro-channel heat sink for cooling microprocessors of a data center. An easily achievable 0.5l/min per chip water flow, with 60°C inlet water temperature, is found sufficient to address the typical data center thermal loads. A maximum temperature difference of ~8°C was found between the solid and liquid, confirming small exergetic destruction due to heat transport across a temperature differential. The high water outlet temperature from the heat sink opens the possibility of waste heat recovery applications. More >

  • Open Access

    ARTICLE

    Priority Based Energy Efficient MAC Protocol by Varying Data Rate for Wireless Body Area Network

    R. Sangeetha, Usha Devi Gandhi*

    Computer Systems Science and Engineering, Vol.48, No.2, pp. 395-411, 2024, DOI:10.32604/csse.2023.041217

    Abstract Wireless Body Area Network (WBAN) is a cutting-edge technology that is being used in healthcare applications to monitor critical events in the human body. WBAN is a collection of in-body and on-body sensors that monitor human physical parameters such as temperature, blood pressure, pulse rate, oxygen level, body motion, and so on. They sense the data and communicate it to the Body Area Network (BAN) Coordinator. The main challenge for the WBAN is energy consumption. These issues can be addressed by implementing an effective Medium Access Control (MAC) protocol that reduces energy consumption and increases network lifetime. The purpose of… More >

  • Open Access

    ARTICLE

    DETERMINATION OF RADIATION HEAT TRANSFER COEFFICIENT OF STANDING HUMAN BODY MODEL BY NUMERICAL APPROACH

    Ahmad Najjaran1, Ali R. Tahavvor, Abdolkarim Najjaran, Mohammad A. Ahmadfard

    Frontiers in Heat and Mass Transfer, Vol.3, No.3, pp. 1-6, 2012, DOI:10.5098/hmt.v3.3.3007

    Abstract In this paper, external radiation heat transfer coefficient and flux of a standing human body model are calculated for different emissivity coefficients and various temperature differences. To do this, a standing human body sample is designed in such a way that hands and feet are totally open and stretched. Soles are in contact with the ground and so do not have heat transfer. The results are extracted by weighted average method. Despite the existence of the air around the body in reality, the convection heat transfer of human body with the surrounding air is neglected in order to prevent errors… More >

  • Open Access

    ARTICLE

    Efficient and Secure IoT Based Smart Home Automation Using Multi-Model Learning and Blockchain Technology

    Nazik Alturki1, Raed Alharthi2, Muhammad Umer3,*, Oumaima Saidani1, Amal Alshardan1, Reemah M. Alhebshi4, Shtwai Alsubai5, Ali Kashif Bashir6,7,8,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3387-3415, 2024, DOI:10.32604/cmes.2023.044700

    Abstract The concept of smart houses has grown in prominence in recent years. Major challenges linked to smart homes are identification theft, data safety, automated decision-making for IoT-based devices, and the security of the device itself. Current home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical features. This paper proposes a smart home system based on ensemble learning of random forest (RF) and convolutional neural networks (CNN) for programmed decision-making tasks, such as categorizing gadgets as “OFF” or “ON” based… More >

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