Xiaohui Ye^1,*, Fucheng Tan¹, Xinli Song², Hanyang Dai², Xia Li², Shixia Mu², Shaohang Hao²

Energy Engineering, Vol.121, No.12, pp. 3689-3710, 2024, DOI:10.32604/ee.2024.055200 - 22 November 2024

Abstract Energy storage batteries can smooth the volatility of renewable energy sources. The operating conditions during power grid integration of renewable energy can affect the performance and failure risk of battery energy storage system (BESS). However, the current modeling of grid-connected BESS is overly simplistic, typically only considering state of charge (SOC) and power constraints. Detailed lithium (Li)-ion battery cell models are computationally intensive and impractical for real-time applications and may not be suitable for power grid operating conditions. Additionally, there is a lack of real-time batteries risk assessment frameworks. To address these issues, in this… More >

Hui Huang^1,*, Yongbing Li¹, Shuhui Li¹, Ninshu Ma²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.011348

Abstract The sequentially coupled thermo-mechanical finite element analysis (FEA) with implicit iteration scheme is widely adopted for welding process simulation because the one-way coupling scheme is believed to be more efficient. However, such computational framework faces the bottleneck of scalability in large-scale analysis due to the exponential growth of computational burden with respect to the number of unknowns in a FEA model. In the present study, a fully coupled approach with explicit integration was developed to simulate fusion welding induced temperature, distortion, and residual stresses. A mass scaling and heat capacity inverse scaling technique was proposed More >

Hamad Naeem¹, Amjad Alsirhani^2,*, Faeiz M. Alserhani³, Farhan Ullah⁴, Ondrej Krejcar¹

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2185-2223, 2024, DOI:10.32604/cmes.2024.056308 - 31 October 2024

Abstract When it comes to smart healthcare business systems, network-based intrusion detection systems are crucial for protecting the system and its networks from malicious network assaults. To protect IoMT devices and networks in healthcare and medical settings, our proposed model serves as a powerful tool for monitoring IoMT networks. This study presents a robust methodology for intrusion detection in Internet of Medical Things (IoMT) environments, integrating data augmentation, feature selection, and ensemble learning to effectively handle IoMT data complexity. Following rigorous preprocessing, including feature extraction, correlation removal, and Recursive Feature Elimination (RFE), selected features are standardized… More >

Hamed Taherdoost^1,2,3,4,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 79-104, 2024, DOI:10.32604/cmc.2024.054378 - 15 October 2024

Abstract Technical and accessibility issues in hospitals often prevent patients from receiving optimal mental and physical health care, which is essential for independent living, especially as societies age and chronic diseases like diabetes and cardiovascular disease become more common. Recent advances in the Internet of Things (IoT)-enabled wearable devices offer potential solutions for remote health monitoring and everyday activity recognition, gaining significant attention in personalized healthcare. This paper comprehensively reviews wearable healthcare technology integrated with the IoT for continuous vital sign monitoring. Relevant papers were extracted and analyzed using a systematic numerical review method, covering various More >

Changtao Wang¹, Honghua Dai^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.010943

Abstract Orbital uncertainty propagation is fundamental in space situational awareness-related missions such as orbit prediction and tracking. Linear models and full nonlinear Monte Carlo simulations were primarily used to propagate uncertainties [1]. However, these methods hampered the application due to low precision and intensive computation. Over the past two decades, numerous nonlinear uncertainty propagators have been proposed. Among these methods, the state transition tensor (STT) method has been widely used due to its controllable accuracy and high efficiency [2]. However, this method has two drawbacks. First, its semi-analytical formulation is too intricate to implement, which hinders… More >

Abdelkader Mendas^*, Abdellah Mebrek, Zohra Mekranfar

Revue Internationale de Géomatique, Vol.33, pp. 383-398, 2024, DOI:10.32604/rig.2024.055321 - 25 September 2024

Abstract The main purpose of this work is to propose a methodology that considers the multicriteria and multi-actor aspects for assessing land suitability for agriculture. This involves offering a group spatial decision-making approach. The members of a multidisciplinary team can decide on the relative importance of the criteria and the ranking of alternatives. Each member provides his judgment and contributes in a distinct and identifiable manner to find a compromise solution. Twelve criteria (easily available water reserve, cation exchange capacity, electric conductivity, potential of hydrogen (pH), drainage, permeability, active limestone, soil texture, soil useful depth, slopes,… More >

Christina Khokhryakova^1,*, Konstantin Kostarev², Irina Mizeva³

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.10, pp. 2205-2218, 2024, DOI:10.32604/fdmp.2024.051053 - 23 September 2024

Abstract Magnetic fluids, also known as ferrofluids, are versatile functional materials with a wide range of applications. These applications span from industrial uses such as vacuum seals, actuators, and acoustic devices to medical uses, including serving as contrast agents for magnetic resonance imaging (MRI), delivering medications to specific locations within the body, and magnetic hyperthermia for cancer treatment. The use of a non-wettable immiscible liquid substrate to support a layer of magnetic fluid opens up new possibilities for studying various fluid flows and related instabilities in multi-phase systems with both a free surface and an interface.… More > Graphic Abstract

Weiqiang Jin^1,#, Xingwu Tian^1,#, Bohang Shi¹, Biao Zhao^1,*, Haibin Duan², Hao Wu³

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3523-3553, 2024, DOI:10.32604/cmc.2024.055125 - 12 September 2024

Abstract The UAV pursuit-evasion problem focuses on the efficient tracking and capture of evading targets using unmanned aerial vehicles (UAVs), which is pivotal in public safety applications, particularly in scenarios involving intrusion monitoring and interception. To address the challenges of data acquisition, real-world deployment, and the limited intelligence of existing algorithms in UAV pursuit-evasion tasks, we propose an innovative swarm intelligence-based UAV pursuit-evasion control framework, namely “Boids Model-based DRL Approach for Pursuit and Escape” (Boids-PE), which synergizes the strengths of swarm intelligence from bio-inspired algorithms and deep reinforcement learning (DRL). The Boids model, which simulates collective… 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 - 15 August 2024

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 >

Yolotzin Apatzingán Palomino-Hermosillo¹, Ángel Elpidio Díaz-Jasso², Rosendo Balois-Morales¹, Verónica Alhelí Ochoa-Jiménez^1,3, Pedro Ulises Bautista-Rosales¹, Guillermo Berumen-Varela^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1717-1732, 2024, DOI:10.32604/phyton.2024.052216 - 30 July 2024

Abstract Soursop (Annona muricata L.) is a tropical fruit highly valued for its unique flavor, nutritional value, and health-promoting properties. The ripening process of soursop involves complex changes in gene expression and metabolite accumulation, which have been studied using various omics technologies. Transcriptome analysis has provided insights into the regulation of key genes involved in ripening, while metabolic compound analysis has revealed the presence of numerous bioactive compounds with potential health benefits. However, the integration of transcriptome and metabolite compound data has not been extensively explored in soursop. Therefore, in this paper, we present a comprehensive analysis… More >