Manuel J. C. S. Reis^*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3023-3039, 2025, DOI:10.32604/cmc.2025.066390 - 23 September 2025

Abstract The Vehicle Routing Problem with Time Windows (VRPTW) presents a significant challenge in combinatorial optimization, especially under real-world uncertainties such as variable travel times, service durations, and dynamic customer demands. These uncertainties make traditional deterministic models inadequate, often leading to suboptimal or infeasible solutions. To address these challenges, this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms (GA) with Local Search (LS), while incorporating stochastic uncertainty modeling through probabilistic travel times. The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance. This adaptivity enhances the algorithm’s… More >

Kejun Zhang¹, Meijiao Li^1,*, Jiahao Cheng¹, Jun Wang¹, Ying Yang²

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1019-1035, 2025, DOI:10.32604/cmc.2025.066532 - 29 August 2025

Abstract With the rapid growth of the Internet and social media, information is widely disseminated in multimodal forms, such as text and images, where discriminatory content can manifest in various ways. Discrimination detection techniques for multilingual and multimodal data can identify potential discriminatory behavior and help foster a more equitable and inclusive cyberspace. However, existing methods often struggle in complex contexts and multilingual environments. To address these challenges, this paper proposes an innovative detection method, using image and multilingual text encoders to separately extract features from different modalities. It continuously updates a historical feature memory bank, More >

Cheng Cheng^*, Xuan-Ping Gong, Xiao-Yu Cheng, Lu Xiao, Xing-Ying Ma

Frontiers in Heat and Mass Transfer, Vol.23, No.3, pp. 1037-1051, 2025, DOI:10.32604/fhmt.2025.065719 - 30 June 2025

Abstract To overcome the challenges associated with predicting gas extraction performance and mitigating the gradual decline in extraction volume, which adversely impacts gas utilization efficiency in mines, a gas extraction pure volume prediction model was developed using Support Vector Regression (SVR) and Random Forest (RF), with hyperparameters fine-tuned via the Genetic Algorithm (GA). Building upon this, an adaptive control model for gas extraction negative pressure was formulated to maximize the extracted gas volume within the pipeline network, followed by field validation experiments. Experimental results indicate that the GA-SVR model surpasses comparable models in terms of mean… More >

Wenjia Zhang^*, Sixuan Xu, Wanchun Qi, Zhuyi Peng, Wentao Sun

Energy Engineering, Vol.122, No.6, pp. 2371-2387, 2025, DOI:10.32604/ee.2025.064160 - 29 May 2025

Abstract Countries worldwide are advocating for energy transition initiatives to promote the construction of low-carbon energy systems. The low voltage ride through (LVRT) characteristics of renewable energy units and commutation failures in line commutated converter high voltage direct current (LCC-HVDC) systems at the receiving end leads to short-term power shortage (STPS), which differs from traditional frequency stability issues. STPS occurs during the generator’s power angle swing phase, before the governor responds, and is on a timescale that is not related to primary frequency regulation. This paper addresses these challenges by examining the impact of LVRT on… More >

Manjit Singh, Sunil Kumar Singla^*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 3003-3029, 2025, DOI:10.32604/cmes.2025.060863 - 03 March 2025

Abstract Deep Learning-based systems for Finger vein recognition have gained rising attention in recent years due to improved efficiency and enhanced security. The performance of existing CNN-based methods is limited by the puny generalization of learned features and deficiency of the finger vein image training data. Considering the concerns of existing methods, in this work, a simplified deep transfer learning-based framework for finger-vein recognition is developed using an EfficientNet model of deep learning with a self-attention mechanism. Data augmentation using various geometrical methods is employed to address the problem of training data shortage required for a… More > Graphic Abstract

Eric Bourreau¹, Gérard Fleury², Philippe Lacomme^2,*

Journal of Quantum Computing, Vol.6, pp. 25-51, 2024, DOI:10.32604/jqc.2024.048792 - 25 October 2024

Abstract The paper presents a novel quantum method for addressing two fundamental routing problems: the Traveling Salesman Problem (TSP) and the Vehicle Routing Problem (VRP), both central to routing challenges. The proposed method, named the Indirect Quantum Approximate Optimization Algorithm (IQAOA), leverages an indirect solution representation using ranking. Our contribution focuses on two main areas: 1) the indirect representation of solutions, and 2) the integration of this representation into an extended version of QAOA, called IQAOA. This approach offers an alternative to QAOA and includes the following components: 1) a quantum parameterized circuit designed to simulate… More >

Ji Zhou^1,2, Yijun Lu³, Qiong Tian^1,2, Haichuan Liu³, Mahdi Hasanipanah^4,5,*, Jiandong Huang^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1595-1617, 2024, DOI:10.32604/cmes.2024.048398 - 20 May 2024

Abstract Blasting in surface mines aims to fragment rock masses to a proper size. However, flyrock is an undesirable effect of blasting that can result in human injuries. In this study, support vector regression (SVR) is combined with four algorithms: gravitational search algorithm (GSA), biogeography-based optimization (BBO), ant colony optimization (ACO), and whale optimization algorithm (WOA) for predicting flyrock in two surface mines in Iran. Additionally, three other methods, including artificial neural network (ANN), kernel extreme learning machine (KELM), and general regression neural network (GRNN), are employed, and their performances are compared to those of four More >

SEUNG-HEE GWAK¹, JUHYUN LEE¹, EUNJI OH¹, DOHYUN LEE^1,2, WONSHIK HAN³, JONGMIN KIM^1,*, KYONG-TAI KIM^4,*

Oncology Research, Vol.32, No.2, pp. 421-432, 2024, DOI:10.32604/or.2023.031031 - 28 December 2023

Abstract Genetic information is transcribed from genomic DNA to mRNA, which is then translated into three-dimensional proteins. mRNAs can undergo various post-transcriptional modifications, including RNA editing that alters mRNA sequences, ultimately affecting protein function. In this study, RNA editing was identified at the 499th base (c.499) of human vaccinia-related kinase 2 (VRK2). This RNA editing changes the amino acid in the catalytic domain of VRK2 from isoleucine (with adenine base) to valine (with guanine base). Isoleucine-containing VRK2 has higher kinase activity than the valine-containing VRK2, which leads to an increase in tumor cell proliferation. Earlier we… More > Graphic Abstract

Devon M. Langston¹, Daniel Evans², Stanley Moore³, Jolie Shen³, Ziho Lee⁴, Jonathan Wingate⁴, Alexander J. Skokan⁴, Aron Liaw⁵, Judith C. Hagedorn³, Benjamin N. Breyer⁵, Nima Baradaran²

Canadian Journal of Urology, Vol.30, No.2, pp. 11487-11494, 2023

Abstract Introduction: Fournier’s gangrene (FG), is a progressive, necrotizing soft tissue infection of the external genitalia, perineum, and/or anorectal region. How treatment and recovery from FG impacts quality of life related to sexual and general health is poorly characterized. Our purpose is to evaluate the long term impact of FG on overall and sexual quality of life using standardized questionnaires through a multi-institutional observational study.
Materials and methods: Multi-institutional retrospective data were collected by standardized questionnaires on patient-reported outcome measures including the Changes in Sexual Functioning Questionnaire (CSFQ) and the Veterans RAND 36 (VR-36) survey of general health-related… More >

Kehuan Xie¹, Longhai Yu^2,3, Chuanchang Li^1,*

Energy Engineering, Vol.120, No.12, pp. 2903-2915, 2023, DOI:10.32604/ee.2023.027636 - 29 November 2023

Abstract Vanadium redox flow battery (VRFB) is considered one of the most potential large-scale energy storage technologies in the future, and its electrolyte flow rate is an important factor affecting the performance of VRFB. To study the effect of electrolyte flow rate on the performance of VRFB, the hydrodynamic model is established and a VRFB system is developed. The results show that under constant current density, with the increase of electrolyte flow rate, not only the coulombic efficiency, energy efficiency, and voltage efficiency will increase, but also the capacity and energy discharged by VRFB will also More >