Acácio M. R. Amaral^1,2,*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3825-3859, 2025, DOI:10.32604/cmc.2025.067179 - 23 September 2025

Abstract Power converters are essential components in modern life, being widely used in industry, automation, transportation, and household appliances. In many critical applications, their failure can lead not only to financial losses due to operational downtime but also to serious risks to human safety. The capacitors forming the output filter, typically aluminum electrolytic capacitors (AECs), are among the most critical and susceptible components in power converters. The electrolyte in AECs often evaporates over time, causing the internal resistance to rise and the capacitance to drop, ultimately leading to component failure. Detecting this fault requires measuring the… More >

Hadeel AlQadi¹, Fatimah M. Alghamdi², Hamada H. Hassan³, Mohamed E. Mead⁴, Ahmed Z. Afify^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2029-2061, 2025, DOI:10.32604/cmes.2025.069801 - 31 August 2025

Abstract Parametric survival models are essential for analyzing time-to-event data in fields such as engineering and biomedicine. While the log-logistic distribution is popular for its simplicity and closed-form expressions, it often lacks the flexibility needed to capture complex hazard patterns. In this article, we propose a novel extension of the classical log-logistic distribution, termed the new exponential log-logistic (NExLL) distribution, designed to provide enhanced flexibility in modeling time-to-event data with complex failure behaviors. The NExLL model incorporates a new exponential generator to expand the shape adaptability of the baseline log-logistic distribution, allowing it to capture a… More >

Hang Zhou^*, Xiaojun Ding, Song Chen, Qijun Zhang

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1907-1933, 2025, DOI:10.32604/cmes.2025.069198 - 31 August 2025

Abstract Structural Reliability-Based Topology Optimization (RBTO), as an efficient design methodology, serves as a crucial means to ensure the development of modern engineering structures towards high performance, long service life, and high reliability. However, in practical design processes, topology optimization must not only account for the static performance of structures but also consider the impacts of various responses and uncertainties under complex dynamic conditions, which traditional methods often struggle accommodate. Therefore, this study proposes an RBTO framework based on a Kriging-assisted level set function and a novel Dynamic Hybrid Particle Swarm Optimization (DHPSO) algorithm. By leveraging… More >

Zohra A. Esaadi¹, Rabab S. Gomaa¹, Beih S. El-Desouky¹, Ehab M. Almetwally², Alia M. Magar^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2063-2097, 2025, DOI:10.32604/cmes.2025.065604 - 31 August 2025

Abstract A new extended distribution called the Odd Exponential Generalized Exponential-Exponential distribution is proposed based on generalization of the odd generalized exponential family (OEGE-E). The statistical properties of the proposed distribution are derived. The study evaluates the accuracy of six estimation methods under complete samples. Estimation techniques include maximum likelihood, ordinary least squares, weighted least squares, maximum product of spacing, Cramer von Mises, and Anderson-Darling methods. Two methods of estimation for the involved parameters are considered based on progressively type II censored data (PTIIC). These methods are maximum likelihood and maximum product of spacing. The proposed More >

Imene Tatar Caliskan^1,2, George Dzorgbenya Ametefe³, Aziz Caliskan⁴, Su-Ee Lau^1,5, Yvonne Jing Mei Liew⁶, Nur Kusaira Khairul Ikram⁵, Boon Chin Tan^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.8, pp. 2229-2254, 2025, DOI:10.32604/phyton.2025.067225 - 29 August 2025

Abstract Myeloblastosis (MYB) transcription factors (TFs) are evolutionarily conserved regulatory proteins that are crucial for plant growth, development, secondary metabolism, and stress adaptation. Recent studies have highlighted their crucial role in coordinating growth–defense trade-offs through transcriptional regulation of key biosynthetic and stress-response genes. Despite extensive functional characterization in model plants such as Arabidopsis thaliana, systematically evaluating the broader functional landscape of MYB TFs across diverse species and contexts remains necessary. This systematic review integrates results from 24 peer-reviewed studies sourced from Scopus and Web of Science, focusing on the functional diversity of MYB TFs, particularly in relation… More >

James A. Brown

Canadian Journal of Urology, Vol.32, No.4, pp. 237-237, 2025, DOI:10.32604/cju.2025.072192 - 29 August 2025

Abstract This article has no abstract. More >

Diego Vergara^*, Antonio del Bosque, Pablo Fernández-Arias

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 41-64, 2025, DOI:10.32604/cmc.2025.067881 - 29 August 2025

Abstract Digital twins (DTs) are rapidly emerging as transformative tools in materials science and engineering, enabling real-time data integration, predictive modeling, and virtual testing. This study presents a systematic bibliometric review of 1106 peer-reviewed articles published in the last decade in Scopus and Web of Science. Using a five-stage methodology, the review examines publication trends, thematic areas, citation metrics, and keyword patterns. The results reveal exponential growth in scientific output, with Materials Theory, Computation, and Data Science as the most represented area. A thematic analysis of the most cited documents identifies four major research streams: foundational More >

Md Monir Ahammod Bin Atique^1,#, Md Ilias Bappi^1,#, Kwanghoon Choi^1,*, Kyungbaek Kim^1,*, Md Abul Ala Walid², Pranta Kumar Sarkar³

Computer Systems Science and Engineering, Vol.49, pp. 455-479, 2025, DOI:10.32604/csse.2025.069213 - 19 August 2025

Abstract Employee turnover presents considerable challenges for organizations, leading to increased recruitment costs and disruptions in ongoing operations. High voluntary attrition rates can result in substantial financial losses, making it essential for Human Resource (HR) departments to prioritize turnover reduction. In this context, Artificial Intelligence (AI) has emerged as a vital tool in strengthening business strategies and people management. This paper incorporates two new representative features, introducing three types of feature engineering to enhance the analysis of employee turnover in the IBM HR Analytics dataset. Key Machine Learning (ML) techniques were subsequently employed in this work,… More >

Sumika Chauhan¹, Govind Vashishtha^1,*, Riya Singh², Divesh Bharti³

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 309-343, 2025, DOI:10.32604/cmes.2025.068628 - 31 July 2025

Abstract This paper introduces a novel optimization approach called Recuperated Seed Search Optimization (RSSO), designed to address challenges in solving mechanical engineering design problems. Many optimization techniques struggle with slow convergence and suboptimal solutions due to complex, nonlinear natures. The Sperm Swarm Optimization (SSO) algorithm, which mimics the sperm’s movement to reach an egg, is one such technique. To improve SSO, researchers combined it with three strategies: opposition-based learning (OBL), Cauchy mutation (CM), and position clamping. OBL introduces diversity to SSO by exploring opposite solutions, speeding up convergence. CM enhances both exploration and exploitation capabilities throughout More >

Ibrahim T. Teke^1,2, Ahmet H. Ertas^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 201-237, 2025, DOI:10.32604/cmes.2025.066644 - 31 July 2025

Abstract Fatigue failure continues to be a significant challenge in designing structural and mechanical components subjected to repeated and complex loading. While earlier studies mainly examined material properties and how stress affects lifespan, this review offers the first comprehensive, multiscale comparison of strategies that optimize geometry to improve fatigue performance. This includes everything from microscopic features like the shape of graphite nodules to large-scale design elements such as fillets, notches, and overall structural layouts. We analyze and combine various methods, including topology and shape optimization, the ability of additive manufacturing to fine-tune internal geometries, and reliability-based More >