Fan Chen^*, Tianhui Zhang, Man Wang, Zhiheng Zhuang, Qiang Zhang, Zihan Ma

Energy Engineering, Vol.122, No.10, pp. 4099-4120, 2025, DOI:10.32604/ee.2025.069346 - 30 September 2025

Abstract The configuration of a hybrid energy storage system (HESS) plays a pivotal role in mitigating wind power fluctuations and enabling primary frequency regulation, thereby enhancing the active power support capability of wind power integration systems. However, most existing studies on HESS capacity configuration overlook the self-recovery control of the state of charge (SOC), creating challenges in sustaining capacity during long-term operation. This omission can impair frequency regulation performance, increase capacity requirements, and shorten battery lifespan. To address these challenges, this study proposes a bi-level planning–operation capacity configuration model that explicitly incorporates SOC self-recovery control. In… More >

Florentin Smarandache¹, Saleh I. Alzahrani², Sulaiman Al Amro³, Ijaz Ahmad⁴, Mubashir Ali^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3715-3735, 2025, DOI:10.32604/cmes.2025.068736 - 30 September 2025

Abstract Hemoglobin is a vital protein in red blood cells responsible for transporting oxygen throughout the body. Its accurate measurement is crucial for diagnosing and managing conditions such as anemia and diabetes, where abnormal hemoglobin levels can indicate significant health issues. Traditional methods for hemoglobin measurement are invasive, causing pain, risk of infection, and are less convenient for frequent monitoring. PPG is a transformative technology in wearable healthcare for noninvasive monitoring and widely explored for blood pressure, sleep, blood glucose, and stress analysis. In this work, we propose a hemoglobin estimation method using an adaptive lightweight… More >

Rodrigo Rafael da Silva^1,*, Gabriela Carvalho Maia de Queiroz¹, Amanda Cibele da Paz Sousa¹, Antônio Gustavo de Luna Souto¹, Francisco Hélio Alves de Andrade ², Francimar Maik da Silva Morais¹, Rita Magally Oliveira da Silva Marcelino¹, Fagner Nogueira Ferreira¹, Alex Alvares da Silva³, Maria Isabela Batista Clemente¹, Baltazar Cirino Junior¹, Wedson Aleff Oliveira da Silva¹, Mateus de Freitas Almeida dos Santos¹, José Francismar de Medeiros^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.9, pp. 2797-2814, 2025, DOI:10.32604/phyton.2025.068089 - 30 September 2025

Abstract Due to its tolerance to water deficit and salinity, sorghum is considered a suitable crop for cultivation in regions affected by these stress conditions, enabling the efficient use of limited water resources. This study evaluated the resilience of the sweet sorghum cultivar BRS 506 under water deficit and salinity stress, focusing on water relations and yield performance in semiarid conditions. A randomized complete block design was employed in a 3 × 3 factorial arrangement with four replicates. Treatments consisted of three levels of irrigation water salinity (1.50, 3.75, and 6.00 dS m⁻¹) and three irrigation levels… More >

Abdulaziz Alshahrani^*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 4067-4090, 2025, DOI:10.32604/cmc.2025.065211 - 23 September 2025

Abstract High dropout rates in short-term job skills training programs hinder workforce development. This study applies machine learning to predict program completion while addressing class imbalance challenges. A dataset of 6548 records with 24 demographic, educational, program-specific, and employment-related features was analyzed. Data preprocessing involved cleaning, encoding categorical variables, and balancing the dataset using the Synthetic Minority Oversampling Technique (SMOTE), as only 15.9% of participants were dropouts. six machine learning models—Logistic Regression, Random Forest, Support Vector Machine, K-Nearest Neighbors, Naïve Bayes, and XGBoost—were evaluated on both balanced and unbalanced datasets using an 80-20 train-test split. Performance More >

Mohamed Gamal^1,#, Hamdy Ashour^1,#, Omar Huzayyin², Maran Marimuthu³, Ghulam E Mustafa Abro^4,*, Lina Mohamed¹

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.8, pp. 2027-2046, 2025, DOI:10.32604/fdmp.2025.067678 - 12 September 2025

Abstract Atrium spaces, common in modern construction, provide significant fire safety challenges due to their large vertical openings, which facilitate rapid smoke spread and reduce sprinkler effectiveness. Traditional smoke management systems primarily rely on make-up air to replace the air expelled through vents. Inadequate calibration, particularly with air velocity, can worsen fire conditions by enhancing oxygen supply, increasing soot production, and reducing visibility, so endangering safe evacuation. This study investigates the impact of make-up air velocity on smoke behaviour in atrium environments through 24 simulations performed using the Fire Dynamics Simulator (FDS). Scenarios include various fire… More >

Gang He¹, Zhuoyan Chen¹, Mufeng Wang², Xingcheng Yang³, Zhenyong Zhang^1,*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 729-750, 2025, DOI:10.32604/cmc.2025.066748 - 29 August 2025

Abstract In rapid urban development, outdoor parking lots have become essential components of urban transportation systems. However, the increasing number of parking lots is accompanied by a rising risk of vehicle fires, posing a serious challenge to public safety. As a result, there is a critical need for fire warning systems tailored to outdoor parking lots. Traditional smoke detection methods, however, struggle with the complex outdoor environment, where smoke characteristics often blend into the background, resulting in low detection efficiency and accuracy. To address these issues, this paper introduces a novel model named Dynamic Contextual Transformer… More >

Umer Farooq¹, Nabil Kerdid^2,*, Yasir Nawaz³, Muhammad Shoaib Arif ⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 873-898, 2025, DOI:10.32604/cmes.2025.066800 - 31 July 2025

Abstract In this study, we proposed a numerical technique for solving time-dependent partial differential equations that arise in the electro-osmotic flow of Carreau fluid across a stationary plate based on a modified exponential integrator. The scheme is comprised of two explicit stages. One is the exponential integrator type stage, and the second is the Runge-Kutta type stage. The spatial-dependent terms are discretized using the compact technique. The compact scheme can achieve fourth or sixth-order spatial accuracy, while the proposed scheme attains second-order temporal accuracy. Also, a mathematical model for the electro-osmotic flow of Carreau fluid over… More >

Jiazheng Du¹, Ju Chen^1,2, Hongling Ye^1,*, Bing Lin¹, Zhichao Guo¹

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 791-809, 2025, DOI:10.32604/cmes.2025.066676 - 31 July 2025

Abstract The traditional topology optimization method of continuum structure generally uses quadrilateral elements as the basic mesh. This approach often leads to jagged boundary issues, which are traditionally addressed through post-processing, potentially altering the mechanical properties of the optimized structure. A topology optimization method of Movable Morphable Smooth Boundary (MMSB) is proposed based on the idea of mesh adaptation to solve the problem of jagged boundaries and the influence of post-processing. Based on the ICM method, the rational fraction function is introduced as the filtering function, and a topology optimization model with the minimum weight as More > Graphic Abstract

Christine Dewi^1,2, Melati Viaeritas Vitrieco Santoso¹, Hanna Prillysca Chernovita³, Evangs Mailoa¹, Stephen Abednego Philemon¹, Abbott Po Shun Chen^4,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5361-5379, 2025, DOI:10.32604/cmc.2025.067381 - 30 July 2025

Abstract Early detection of Forest and Land Fires (FLF) is essential to prevent the rapid spread of fire as well as minimize environmental damage. However, accurate detection under real-world conditions, such as low light, haze, and complex backgrounds, remains a challenge for computer vision systems. This study evaluates the impact of three image enhancement techniques—Histogram Equalization (HE), Contrast Limited Adaptive Histogram Equalization (CLAHE), and a hybrid method called DBST-LCM CLAHE—on the performance of the YOLOv11 object detection model in identifying fires and smoke. The D-Fire dataset, consisting of 21,527 annotated images captured under diverse environmental scenarios… More >

Chongyang Wang¹, Qiongyan Li¹, Shu Liu², Pengle Cheng^1,*, Ying Huang³

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5157-5176, 2025, DOI:10.32604/cmc.2025.067367 - 30 July 2025

Abstract With rapid urbanization, fires pose significant challenges in urban governance. Traditional fire detection methods often struggle to detect smoke in complex urban scenes due to environmental interferences and variations in viewing angles. This study proposes a novel multimodal smoke detection method that fuses infrared and visible imagery using a transformer-based deep learning model. By capturing both thermal and visual cues, our approach significantly enhances the accuracy and robustness of smoke detection in business parks scenes. We first established a dual-view dataset comprising infrared and visible light videos, implemented an innovative image feature fusion strategy, and More >