Laith Abualigah^*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 1539-1592, 2025, DOI:10.32604/cmc.2025.060765 - 17 February 2025

Abstract Particle Swarm Optimization (PSO) has been utilized as a useful tool for solving intricate optimization problems for various applications in different fields. This paper attempts to carry out an update on PSO and gives a review of its recent developments and applications, but also provides arguments for its efficacy in resolving optimization problems in comparison with other algorithms. Covering six strategic areas, which include Data Mining, Machine Learning, Engineering Design, Energy Systems, Healthcare, and Robotics, the study demonstrates the versatility and effectiveness of the PSO. Experimental results are, however, used to show the strong and More >

Menghui Hao¹, Shanshan Zhou¹, Yongchao Han¹, Zhanwei Zhu¹, Qiang Yang², Panxu Sun^2,*, Jiajun Fan²

Structural Durability & Health Monitoring, Vol.19, No.2, pp. 399-415, 2025, DOI:10.32604/sdhm.2024.056250 - 15 January 2025

Abstract As an evaluation index, the natural frequency has the advantages of easy acquisition and quantitative evaluation. In this paper, the natural frequency is used to evaluate the performance of external cable reinforced bridges. Numerical examples show that compared with the natural frequencies of first-order modes, the natural frequencies of higher-order modes are more sensitive and can reflect the damage situation and external cable reinforcement effect of T-beam bridges. For damaged bridges, as the damage to the T-beam increases, the natural frequency value of the bridge gradually decreases. When the degree of local damage to the… More >

Aswinraj Anbazhagan¹, Piyali Roy Choudhury¹, Sahila Sambandam², Jayakumari Lakshmanan Saraswathi^1,*

Journal of Polymer Materials, Vol.41, No.4, pp. 299-313, 2024, DOI:10.32604/jpm.2024.056261 - 16 December 2024

Abstract Petroleum-based cured epoxy polymers, used widely in aerospace, marine, and automotive industries, pose environmental threats due to their toxicity. Therefore, developing alternative curing systems for epoxy resin is crucial. This study explores the use of bio-based phenalkamines as curing agents for epoxy resin to enhance the mechanical properties of polymer composites and fiber-reinforced laminates. The functional groups, morphology, and thermal properties of the composites were analyzed using Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). Mechanical properties of two epoxy systems—EP-TETA (triethylenetetramine-cured) and EP-PA (phenalkamine-cured)—were evaluated according to ASTM standards. More > Graphic Abstract

Tanyawan Suwandecha¹, Supachai Pisuchpen^2,*

Journal of Renewable Materials, Vol.12, No.11, pp. 1811-1836, 2024, DOI:10.32604/jrm.2024.056334 - 22 November 2024

Abstract This study investigated the development of mycelium-based biofoams as sustainable cushioning materials using Pleurotus ostreatus and Lentinus squarrosulus, combined with different sawdust substrates, and subjected to various pressing methods. The results indicated significant effects of mushroom species, sawdust type, and pressing method on the properties of biofoams. Growth rate, morphology, chemical composition, physical and mechanical properties, water resistance, and cushioning factor were evaluated. The results indicated that Lentinus squarrosulus (LS) exhibited faster growth rates (up to 14.37 mm/day) and produced biofoams with superior properties compared to Pleurotus ostreatus (PO). Core wood (CW) sawdust generally resulted in biofoams with lower… More > Graphic Abstract

Abdulrahman M. Abdulghani^*

Journal on Artificial Intelligence, Vol.6, pp. 241-259, 2024, DOI:10.32604/jai.2024.056259 - 16 October 2024

Abstract Cloud computing has rapidly evolved into a critical technology, seamlessly integrating into various aspects of daily life. As user demand for cloud services continues to surge, the need for efficient virtualization and resource management becomes paramount. At the core of this efficiency lies task scheduling, a complex process that determines how tasks are allocated and executed across cloud resources. While extensive research has been conducted in the area of task scheduling, optimizing multiple objectives simultaneously remains a significant challenge due to the NP (Non-deterministic Polynomial) Complete nature of the problem. This study aims to address… More >

Ibtissam El Aouni, Hicham Labrim, Elhoussaine Ouabida, Ahmed Ait Errouhi, Rachid El Bouayadi, Driss Zejli, Aouatif Saad^*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.10, pp. 2323-2335, 2024, DOI:10.32604/fdmp.2024.050611 - 23 September 2024

Abstract The perfect combination of renewable energy and desalination technologies is the key to meeting water demands in a cost-effective, efficient and environmentally friendly way. The desalination technique by humidification-dehumidification is non-conventional approach suitable for areas with low infrastructure (such as rural and decentralized regions) since it does not require permanent maintenance. In this study, this technology is implemented by using solar energy as a source of thermal power. A seawater desalination unit is considered, which consists of a chamber with two evaporators (humidifiers), a wetted porous material made of a corrugated cellulose cardboard and a… More >

Kaveh Heidary^1,*, Venkata Atluri¹, John Bland²

Journal of Cyber Security, Vol.6, pp. 69-87, 2024, DOI:10.32604/jcs.2024.051196 - 28 August 2024

Abstract This paper investigates the impact of reducing feature-vector dimensionality on the performance of machine learning (ML) models. Dimensionality reduction and feature selection techniques can improve computational efficiency, accuracy, robustness, transparency, and interpretability of ML models. In high-dimensional data, where features outnumber training instances, redundant or irrelevant features introduce noise, hindering model generalization and accuracy. This study explores the effects of dimensionality reduction methods on binary classifier performance using network traffic data for cybersecurity applications. The paper examines how dimensionality reduction techniques influence classifier operation and performance across diverse performance metrics for seven ML models. Four… More >

Yaqiong He, Jinlin Fan^*, Huaiguang Wu

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 995-1032, 2024, DOI:10.32604/cmc.2024.052887 - 18 July 2024

Abstract With the rise of blockchain technology, the security issues of smart contracts have become increasingly critical. Despite the availability of numerous smart contract vulnerability detection tools, many face challenges such as slow updates, usability issues, and limited installation methods. These challenges hinder the adoption and practicality of these tools. This paper examines smart contract vulnerability detection tools from 2016 to 2023, sourced from the Web of Science (WOS) and Google Scholar. By systematically collecting, screening, and synthesizing relevant research, 38 open-source tools that provide installation methods were selected for further investigation. From a developer’s perspective,… More >

Ali Shokor Golam^*

Frontiers in Heat and Mass Transfer, Vol.22, No.2, pp. 633-653, 2024, DOI:10.32604/fhmt.2024.050218 - 20 May 2024

Abstract The thermal-hydraulic performance of plain tubes with and without wire coils in turbulent regimes is investigated experimentally and numerically. The effects of wire coil distribution (circular cross section) within the tube were explored experimentally, and water was employed as the working fluid. The numerical simulation was carried out using software programmer ANSYS Fluent 2019 R3 using the finite-volume approach. In the turbulent regime, six cross-sectioned wire coils were analyzed, including: circular, rectangular, hexagonal, square, star shape, and triangle. The utilization of a tube with a wire coil has been shown to increase heat transfer rate More >

Abdulghani M. Abdulghani, Mokhles M. Abdulghani, Wilbur L. Walters, Khalid H. Abed^*

Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 337-352, 2024, DOI:10.32604/iasc.2024.047017 - 21 May 2024

Abstract Multi-Agent Reinforcement Learning (MARL) has proven to be successful in cooperative assignments. MARL is used to investigate how autonomous agents with the same interests can connect and act in one team. MARL cooperation scenarios are explored in recreational cooperative augmented reality environments, as well as real-world scenarios in robotics. In this paper, we explore the realm of MARL and its potential applications in cooperative assignments. Our focus is on developing a multi-agent system that can collaborate to attack or defend against enemies and achieve victory with minimal damage. To accomplish this, we utilize the StarCraft… More >