Linghong Kuang^1,2, Wenlong Shi^1,2, Jing Zhang^1,2,*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3193-3219, 2024, DOI:10.32604/cmc.2024.054377

Abstract The Advanced Metering Infrastructure (AMI), as a crucial subsystem in the smart grid, is responsible for measuring user electricity consumption and plays a vital role in communication between providers and consumers. However, with the advancement of information and communication technology, new security and privacy challenges have emerged for AMI. To address these challenges and enhance the security and privacy of user data in the smart grid, a Hierarchical Privacy Protection Model in Advanced Metering Infrastructure based on Cloud and Fog Assistance (HPPM-AMICFA) is proposed in this paper. The proposed model integrates cloud and fog computing… More >

Uddagiri Sirisha^1,, Parvathaneni Naga Srinivasu^2,3,*, Panguluri Padmavathi⁴, Seongki Kim^5,, Aruna Pavate⁶, Jana Shafi⁷, Muhammad Fazal Ijaz^8,*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2301-2330, 2024, DOI:10.32604/cmc.2024.053132

Abstract Fetal health care is vital in ensuring the health of pregnant women and the fetus. Regular check-ups need to be taken by the mother to determine the status of the fetus’ growth and identify any potential problems. To know the status of the fetus, doctors monitor blood reports, Ultrasounds, cardiotocography (CTG) data, etc. Still, in this research, we have considered CTG data, which provides information on heart rate and uterine contractions during pregnancy. Several researchers have proposed various methods for classifying the status of fetus growth. Manual processing of CTG data is time-consuming and unreliable.… More >

Mesut Ulu^1,*, Yusuf Sait Türkan², Kenan Mengüç³, Ersin Namlı², Tarık Küçükdeniz²

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2259-2281, 2024, DOI:10.32604/cmc.2024.052323

Abstract Today, urban traffic, growing populations, and dense transportation networks are contributing to an increase in traffic incidents. These incidents include traffic accidents, vehicle breakdowns, fires, and traffic disputes, resulting in long waiting times, high carbon emissions, and other undesirable situations. It is vital to estimate incident response times quickly and accurately after traffic incidents occur for the success of incident-related planning and response activities. This study presents a model for forecasting the traffic incident duration of traffic events with high precision. The proposed model goes through a 4-stage process using various features to predict the… More >

Dayong Wang^1,*, Kamalrulnizam Bin Abu Bakar¹, Babangida Isyaku²

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2065-2080, 2024, DOI:10.32604/cmc.2024.051944

Abstract The rapid development of Internet of Things (IoT) technology has led to a significant increase in the computational task load of Terminal Devices (TDs). TDs reduce response latency and energy consumption with the support of task-offloading in Multi-access Edge Computing (MEC). However, existing task-offloading optimization methods typically assume that MEC’s computing resources are unlimited, and there is a lack of research on the optimization of task-offloading when MEC resources are exhausted. In addition, existing solutions only decide whether to accept the offloaded task request based on the single decision result of the current time slot,… More >

Prasanna Kumar Kannughatta Ranganna¹, Siddesh Gaddadevara Matt², Chin-Ling Chen^3,4,*, Ananda Babu Jayachandra⁵, Yong-Yuan Deng^4,*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2557-2578, 2024, DOI:10.32604/cmc.2024.051634

Abstract In recent decades, fog computing has played a vital role in executing parallel computational tasks, specifically, scientific workflow tasks. In cloud data centers, fog computing takes more time to run workflow applications. Therefore, it is essential to develop effective models for Virtual Machine (VM) allocation and task scheduling in fog computing environments. Effective task scheduling, VM migration, and allocation, altogether optimize the use of computational resources across different fog nodes. This process ensures that the tasks are executed with minimal energy consumption, which reduces the chances of resource bottlenecks. In this manuscript, the proposed framework… More >

Saket Sarin¹, Sunil K. Singh¹, Sudhakar Kumar¹, Shivam Goyal¹, Brij Bhooshan Gupta^2,3,4,8,*, Wadee Alhalabi⁵, Varsha Arya^6,7

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3123-3138, 2024, DOI:10.32604/cmc.2024.051599

Abstract In the rapidly evolving landscape of today’s digital economy, Financial Technology (Fintech) emerges as a transformative force, propelled by the dynamic synergy between Artificial Intelligence (AI) and Algorithmic Trading. Our in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning (MARL) and Explainable AI (XAI) within Fintech, aiming to refine Algorithmic Trading strategies. Through meticulous examination, we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm, employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading decisions. These AI-infused Fintech platforms harness collective intelligence More >

Yu Zhou¹, Yun Zhang¹, Guowei Li¹, Hang Yang¹, Wei Zhang¹, Ting Lyu², Yueqiang Xu^2,*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1809-1829, 2024, DOI:10.32604/cmc.2024.050975

Abstract In current research on task offloading and resource scheduling in vehicular networks, vehicles are commonly assumed to maintain constant speed or relatively stationary states, and the impact of speed variations on task offloading is often overlooked. It is frequently assumed that vehicles can be accurately modeled during actual motion processes. However, in vehicular dynamic environments, both the tasks generated by the vehicles and the vehicles’ surroundings are constantly changing, making it difficult to achieve real-time modeling for actual dynamic vehicular network scenarios. Taking into account the actual dynamic vehicular scenarios, this paper considers the real-time… More >

Guochen Xu^*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.8, pp. 1915-1924, 2024, DOI:10.32604/fdmp.2024.048337

Abstract Microscopic pore structure in continental shale oil reservoirs is characterized by small pore throats and complex micro-structures. The adsorption behavior of hydrocarbons on the pore walls exhibits unique physical and chemical properties. Therefore, studying the adsorption morphology of hydrocarbon components in nanometer-sized pores and clarifying the exploitation limits of shale oil at the microscopic level are of great practical significance for the efficient development of continental shale oil. In this study, molecular dynamics simulations were employed to investigate the adsorption characteristics of various single-component shale oils in inorganic quartz fissures, and the influence of pore… More >

Nan Liu^1,2, Chen Hong^3,4,5, Xinchao Su^3,4,5, Xing Jin^1,2, Chen Jiang^3,4,5,*, Yuqi Shi^1,2, Bingkun Wang^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.8, pp. 1867-1882, 2024, DOI:10.32604/fdmp.2024.047427

Abstract As the velocity of a train increases, the corresponding air pumping power consumption of the brake discs increases proportionally. In the present experimental study, a standard axle-mounted brake disc with circumferential pillars was analyzed using a 1:1 scale model and a test rig in a wind tunnel. In particular, three upstream velocities were selected on the basis of earlier investigations of trains operating at 160, 250, and 400 km/h, respectively. Moreover, 3D steady computational fluid dynamics (CFD) simulations of the flow field were conducted to compare with the wind tunnel test outcomes. The results for More >

Md Zahir Ahmed^1,*, Oli Ahmed², Lingfeng Gao¹, Mary C. Jobe³, Weijian Li¹

International Journal of Mental Health Promotion, Vol.26, No.7, pp. 517-529, 2024, DOI:10.32604/ijmhp.2024.051055

Abstract In recent years, speculation of an increase in Internet Gaming Disorder (IGD) has surfaced with the growing popularity of internet gaming among Chinese children and adolescents. The detrimental impact of IGD on mental health cannot be denied, even though only a small portion of the screen-dependent population exhibits psychopathological and behavioral symptoms. The present study aimed to explore a latent profile analysis (LPA) of Internet Gaming Disorder on the mental health of Chinese school students. The data were collected from a sample of 1005 Chinese school students (49.8% male; age M = 13.32, SD = 1.34… More >