Wang Zhang^1,#, Haozhuo Cao^2,#, Qiangqiang Yao^1,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072948 - 12 January 2026

Abstract Recent advances in deep learning have significantly improved image deblurring; however, existing approaches still suffer from limited global context modeling, inadequate detail restoration, and poor texture or edge perception, especially under complex dynamic blur. To address these challenges, we propose the Multi-Resolution Fusion Network (MRFNet), a blind multi-scale deblurring framework that integrates progressive residual connectivity for hierarchical feature fusion. The network employs a three-stage design: (1) TransformerBlocks capture long-range dependencies and reconstruct coarse global structures; (2) Nonlinear Activation Free Blocks (NAFBlocks) enhance local detail representation and mid-level feature fusion; and (3) an optimized residual subnetwork… More >

Xia Yan¹, Wei Wang¹, Kai Shen^2,*, Yanqing Feng¹, Junyi Sun¹, Xiaogang Li¹, Wentao Zhu¹, Binbin Shi¹, Guanglong Sheng^2,3

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.070360 - 27 December 2025

Abstract In the development of coalbed methane (CBM) reservoirs using multistage fractured horizontal wells, there often exist areas that are either repeatedly stimulated or completely unstimulated between fracturing stages, leading to suboptimal reservoir performance. Currently, there is no well-established method for accurately evaluating the effectiveness of such stimulation. This study introduces, for the first time, the concept of the Fracture Network Bridging Coefficient (FNBC) as a novel metric to assess stimulation performance. By quantitatively coupling the proportions of unstimulated and overstimulated volumes, the FNBC effectively characterizes the connectivity and efficiency of the fracture network. A background… More >

Yunjun Lee¹, Sanggyu Cheon², Woo Chul Chung^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3381-3403, 2025, DOI:10.32604/cmes.2025.073729 - 23 December 2025

Abstract The application of carbon capture systems on ships is technically constrained by limited onboard space and the weight of the conventional absorption tower. The rotating packed bed (RPB) has emerged as a promising alternative due to its small footprint and high mass transfer performance. However, despite its advantages, the structural and vibration stability of RPBs at high rotational speed remains insufficiently studied, and no international design standards currently exist for RPBs. To address this gap, this study performed a comprehensive finite element analysis (FEA) using ANSYS to investigate the structural and dynamic characteristics of an… More >

Jianchang Hou¹, Zhanpeng Jiang¹, Fenghe Wu¹, Hui Lian¹, Zhaohua Wang², Zijian Liu³, Weicheng Li^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1545-1572, 2025, DOI:10.32604/cmes.2025.068482 - 31 August 2025

Abstract In this paper, a topology optimization method for coordinated stiffness and strength design is proposed under mass constraints, utilizing the Solid Isotropic Material with Penalization approach. Element densities are regulated through sensitivity filtering to mitigate numerical instabilities associated with stress concentrations. A p-norm aggregation function is employed to globalize local stress constraints, and a normalization technique linearly weights strain energy and stress, transforming the multi-objective problem into a single-objective formulation. The sensitivity of the objective function with respect to design variables is rigorously derived. Three numerical examples are presented, comparing the optimized structures in terms More >

Cristian Martínez-Fuentes¹, Pedro Pesante^2,*, Karin Saavedra³, Paul Oumaziz⁴

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 581-595, 2025, DOI:10.32604/cmc.2025.065746 - 29 August 2025

Abstract Rubberized concrete is one of the most studied applications of discarded tires and offers a promising approach to developing materials with enhanced properties. The rubberized concrete mixture results in a reduced modulus of elasticity and a reduced compressive and tensile strength compared to traditional concrete. This study employs finite element simulations to investigate the elastic properties of rubberized mortar (RuM), considering the influence of inclusion stiffness and interfacial debonding. Different homogenization schemes, including Voigt, Reuss, and mean-field approaches, are implemented using DIGIMAT and ANSYS. Furthermore, the influence of the interfacial transition zone (ITZ) between mortar… More >

Trung-Hieu Tran^*

Structural Durability & Health Monitoring, Vol.19, No.4, pp. 869-886, 2025, DOI:10.32604/sdhm.2025.064902 - 30 June 2025

Abstract The design principles for conventional reinforced concrete structures have gradually transitioned to seismic-resistant design since the 1970s. However, until recently, the implementation of strength capacity and ductility design has not been rigorously enforced in many developing countries that are prone to seismic risks. Numerous studies have evaluated the effectiveness of joint behavior based on both ductile and non-ductile designs under cyclic loading. Previous research has demonstrated that enhancing joint regions with Ultra-High Performance Steel Fiber Reinforced Concrete (UHPSFRC) significantly improves the seismic resistance of structural components. This paper presents a detailed analysis of the considerable… More >

Yu-Xiang Zhao^*, Yi Lee

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 791-810, 2025, DOI:10.32604/cmc.2025.065048 - 09 June 2025

Abstract Bird species classification is not only a challenging topic in artificial intelligence but also a domain closely related to environmental protection and ecological research. Additionally, performing edge computing on low-level devices using small neural networks can be an important research direction. In this paper, we use the EfficientNetV2B0 model for bird species classification, applying transfer learning on a dataset of 525 bird species. We also employ the BiRefNet model to remove backgrounds from images in the training set. The generated background-removed images are mixed with the original training set as a form of data augmentation.… More >

Kangkang Zhao¹, Yaojie Chen^1,*, Jianbo Li²

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 745-762, 2025, DOI:10.32604/cmc.2025.063906 - 09 June 2025

Abstract Traditional cameras inevitably suffer from motion blur when facing high-speed moving objects. Event cameras, as high temporal resolution bionic cameras, record intensity changes in an asynchronous manner, and their recorded high temporal resolution information can effectively solve the problem of time information loss in motion blur. Existing event-based deblurring methods still face challenges when facing high-speed moving objects. We conducted an in-depth study of the imaging principle of event cameras. We found that the event stream contains excessive noise. The valid information is sparse. Invalid event features hinder the expression of valid features due to… More >

Rajendran Thanikachalam¹, Anandhavalli Muniasamy², Ashwag Alasmari³, Rajendran Thavasimuthu^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1971-2000, 2025, DOI:10.32604/cmes.2025.063063 - 30 May 2025

Abstract Content-Based Image Retrieval (CBIR) and image mining are becoming more important study fields in computer vision due to their wide range of applications in healthcare, security, and various domains. The image retrieval system mainly relies on the efficiency and accuracy of the classification models. This research addresses the challenge of enhancing the image retrieval system by developing a novel approach, EfficientNet-Convolutional Neural Network (EffNet-CNN). The key objective of this research is to evaluate the proposed EffNet-CNN model’s performance in image classification, image mining, and CBIR. The novelty of the proposed EffNet-CNN model includes the integration… More >

Yuen Lo Yau¹, Matthew S. Purlee², Lindsey M. Brinkley², Dipankar Gupta¹, David M. Saulino³, Dalia Lopez-Colon¹, John-Anthony Coppola¹, Dhanashree Rajderkar⁴, Himesh Vyas^1,*

Congenital Heart Disease, Vol.20, No.2, pp. 265-272, 2025, DOI:10.32604/chd.2025.065661 - 30 April 2025

Abstract Background: Patients with Fontan physiology are predisposed to congestive hepatopathy, progressive liver fibrosis, and end-stage liver disease. Ultrasound-based shear wave elastography (SWE) is a non-invasive tool to diagnose and monitor liver fibrosis. We sought to determine whether the degree of hemodynamic derangement prior to and after the Fontan operation is associated with increased liver stiffness measured by SWE. Methods: A single-center retrospective study of patients with Fontan circulation who underwent ultrasound elastography between 2008 and 2024 was conducted. Liver stiffness was measured by SWE and reported as velocity in m/s. Hemodynamic assessment with cardiac catheterization and… More >