Xing Wang^1,*, Huazhen Liu¹, Abdelazim G. Hussien², Gang Hu¹, Li Zhang³

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2791-2839, 2025, DOI:10.32604/cmes.2025.058473 - 03 March 2025

Abstract Feature selection (FS) is essential in machine learning (ML) and data mapping by its ability to preprocess high-dimensional data. By selecting a subset of relevant features, feature selection cuts down on the dimension of the data. It excludes irrelevant or surplus features, thus boosting the performance and efficiency of the model. Particle Swarm Optimization (PSO) boasts a streamlined algorithmic framework and exhibits rapid convergence traits. Compared with other algorithms, it incurs reduced computational expenses when tackling high-dimensional datasets. However, PSO faces challenges like inadequate convergence precision. Therefore, regarding FS problems, this paper presents a binary… More >

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 >

Miloš Sedak^*, Maja Rosić, Božidar Rosić

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 2111-2145, 2025, DOI:10.32604/cmes.2025.059319 - 27 January 2025

Abstract This paper introduces a hybrid multi-objective optimization algorithm, designated HMODESFO, which amalgamates the exploratory prowess of Differential Evolution (DE) with the rapid convergence attributes of the Sailfish Optimization (SFO) algorithm. The primary objective is to address multi-objective optimization challenges within mechanical engineering, with a specific emphasis on planetary gearbox optimization. The algorithm is equipped with the ability to dynamically select the optimal mutation operator, contingent upon an adaptive normalized population spacing parameter. The efficacy of HMODESFO has been substantiated through rigorous validation against established industry benchmarks, including a suite of Zitzler-Deb-Thiele (ZDT) and Zeb-Thiele-Laumanns-Zitzler (DTLZ) More >

Ahmed Manguri^1,2,3,*, Hogr Hassan³, Najmadeen Saeed^3,4, Robert Jankowski¹

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 933-971, 2025, DOI:10.32604/cmes.2025.059249 - 27 January 2025

Abstract The optimization of civil engineering structures is critical for enhancing structural performance and material efficiency in engineering applications. Structural optimization approaches seek to determine the optimal design, by considering material performance, cost, and structural safety. The design approaches aim to reduce the built environment’s energy use and carbon emissions. This comprehensive review examines optimization techniques, including size, shape, topology, and multi-objective approaches, by integrating these methodologies. The trends and advancements that contribute to developing more efficient, cost-effective, and reliable structural designs were identified. The review also discusses emerging technologies, such as machine learning applications with More >

YIXIAN YOU^1,3,#, YIHUNG LEE^2,#, YUSHIN HU², YOUHUI XU³, JOUCHEN CHEN², WEI JIANG¹, CHANGHAI LIU¹, ENQIANG CHEN¹, HONG TANG¹, HUA ZHANG^4,*, DONGBO WU^1,*

BIOCELL, Vol.49, No.1, pp. 45-59, 2025, DOI:10.32604/biocell.2024.057259 - 24 January 2025

Abstract With organ transplantation facing many dilemmas, tissue and organ regeneration as an alternative has bright prospects. In regenerative medicine, Three-dimensional (3D) printing technology and stem cells has been widely applied to the treatment of diseases related to tissue or organ replacement in dentistry, respectively. However, there are very few studies on the combination of the two, and even fewer clinical studies have been reported in dentistry. In this review, the current oral tissue engineering in vivo and in vitro based on 3D printing and stem cell technology will be summarized, and the discussion on the development… More >

Chengquan Wang^1,2, Lei Xu³, Xinquan Wang¹, Yun Zou^3,*, Kangyu Wang⁴, Boyan Ping⁵, Xiao Li¹

Structural Durability & Health Monitoring, Vol.19, No.2, pp. 233-263, 2025, DOI:10.32604/sdhm.2024.055096 - 15 January 2025

Abstract Kinked rebar is a special type of steel material, which is installed in beam column nodes and frame beams. It effectively enhances the blast resilience, seismic collapse resistance, and progressive collapse resistance of reinforced concrete (RC) structures without imposing substantial cost burdens, thereby emerging as a focal point of recent research endeavors. On the basis of explaining the working principle of kinked rebars, this paper reviews the research status of kinked rebars at home and abroad from three core domains: the tensile mechanical properties of kinked rebars, beam column nodes with kinked rebars, and concrete… More >

Mahmood Alsaadi, Mohammed E. Seno^*, Mohammed I. Khalaf

Intelligent Automation & Soft Computing, Vol.40, pp. 29-52, 2025, DOI:10.32604/iasc.2024.060390 - 10 January 2025

Abstract The agility of Internet of Things (IoT) software engineering is benchmarked based on its systematic insights for wide application support infrastructure developments. Such developments are focused on reducing the interfacing complexity with heterogeneous devices through applications. To handle the interfacing complexity problem, this article introduces a Semantic Interfacing Obscuration Model (SIOM) for IoT software-engineered platforms. The interfacing obscuration between heterogeneous devices and application interfaces from the testing to real-time validations is accounted for in this model. Based on the level of obscuration between the infrastructure hardware to the end-user software, the modifications through device replacement, More >

Nahed Alsaleh^1,2, Reem Alnanih^1,*, Nahed Alowidi¹

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 949-976, 2025, DOI:10.32604/cmc.2024.059351 - 03 January 2025

Abstract App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products. Automating the analysis of these reviews is vital for efficient review management. While traditional machine learning (ML) models rely on basic word-based feature extraction, deep learning (DL) methods, enhanced with advanced word embeddings, have shown superior performance. This research introduces a novel aspect-based sentiment analysis (ABSA) framework to classify app reviews based on key non-functional requirements, focusing on usability factors: effectiveness, efficiency, and satisfaction. We propose a hybrid DL model, combining BERT (Bidirectional Encoder Representations from Transformers) More >

Hariharasakthisudhan Ponnarengan^1,*, Sivakumar Rajendran², Vikas Khalkar³, Gunapriya Devarajan⁴, Logesh Kamaraj⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 1-48, 2025, DOI:10.32604/cmes.2024.056605 - 17 December 2024

Abstract The purpose of this review is to explore the intersection of computational engineering and biomedical science, highlighting the transformative potential this convergence holds for innovation in healthcare and medical research. The review covers key topics such as computational modelling, bioinformatics, machine learning in medical diagnostics, and the integration of wearable technology for real-time health monitoring. Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems, while machine learning algorithms have improved the accuracy of disease prediction and diagnosis. The synergy between bioinformatics and computational techniques has led to breakthroughs in More >

Afam Okonkwo^*, Pius Onobhayedo, Charles Igah

Journal on Artificial Intelligence, Vol.6, pp. 379-401, 2024, DOI:10.32604/jai.2024.058649 - 31 December 2024

Abstract Artificial Intelligence, in general, and particularly Natural language Processing (NLP) has made unprecedented progress recently in many areas of life, automating and enabling a lot of activities such as speech recognition, language translations, search engines, and text-generations, among others. Software engineering and Software Development Life Cycle (SDLC) is also not left out. Indeed, one of the most critical starting points of SDLC is the requirement engineering stage which, traditionally, has been dominated by business analysts. Unfortunately, these analysts have always done the job not just in a monotonous way, but also in an error-prone, tedious,… More >