Junseo Lee¹, Bongsoo Jang¹, Umer Saeed^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2165-2189, 2025, DOI:10.32604/cmes.2025.069023 - 31 August 2025

Abstract In recent years, variable-order fractional partial differential equations have attracted growing interest due to their enhanced ability to model complex physical phenomena with memory and spatial heterogeneity. However, existing numerical methods often struggle with the computational challenges posed by such equations, especially in nonlinear, multi-term formulations. This study introduces two hybrid numerical methods—the Linear-Sine and Cosine (L1-CAS) and fast-CAS schemes—for solving linear and nonlinear multi-term Caputo variable-order (CVO) fractional partial differential equations. These methods combine CAS wavelet-based spatial discretization with L1 and fast algorithms in the time domain. A key feature of the approach is More >

Xubo Liu¹, Yunxiang Liu², Peng Luo^2,*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1073-1094, 2025, DOI:10.32604/cmc.2025.066078 - 29 August 2025

Abstract Roads inevitably have defects during use, which not only seriously affect their service life but also pose a hidden danger to traffic safety. Existing algorithms for detecting road defects are unsatisfactory in terms of accuracy and generalization, so this paper proposes an algorithm based on YOLOv11. The method embeds wavelet transform convolution (WTConv) into the backbone’s C3k2 module to enhance low-frequency feature extraction while avoiding parameter bloat. Secondly, a novel multi-scale fusion diffusion network (MFDN) architecture is designed for the neck to strengthen cross-scale feature interactions, boosting detection precision. In terms of model optimization, the… More >

Pan Duan^*, Enze Peng

Energy Engineering, Vol.122, No.9, pp. 3817-3838, 2025, DOI:10.32604/ee.2025.066491 - 26 August 2025

Abstract To address the challenges of fault line identification and low detection accuracy of wave head in Fault Location (FL) research of distribution networks with complex topologies, this paper proposes an FL method of Multi-Branch distribution line based on Maximal Overlap Discrete Wavelet Transform (MODWT) combined with the improved Teager Energy Operator (TEO). Firstly, the current and voltage Traveling Wave (TW) signals at the head of each line are extracted, and the fault-induced components are obtained to determine the fault line by analyzing the polarity of the mutation amount of fault voltage and current TWs. Subsequently,… More >

Judy P. Yang^*, Yuan-Jun Zhang

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 669-691, 2025, DOI:10.32604/cmes.2025.068945 - 31 July 2025

Abstract Much of the research has focused on identifying bridge frequencies for health monitoring, while the bridge damping ratio also serves as an important factor in damage detection. This study presents an enhanced method for identifying bridge damping ratios using a two-axle, three-mass test vehicle, relying on wheel responses captured by only two mounted sensors. Damping ratio estimation formulas are derived using both the Hilbert Transform (HT) and Wavelet Transform (WT), with a consistent formulation that confirms accurate estimation is achievable with minimal instrumentation, particularly when addressing the support effect. A comparative analysis of the two More >

Kaihao Shi^1,2, Lin Yuan^1,2,*, Qimeng Yu³, Zhongting Shen², Yingtan Yu², Chenwei Nie¹, Xingjian Zhou³, Jingcheng Zhang³

Phyton-International Journal of Experimental Botany, Vol.94, No.7, pp. 2033-2054, 2025, DOI:10.32604/phyton.2025.066286 - 31 July 2025

Abstract Plant diseases are a major threat that can severely impact the production of agriculture and forestry. This can lead to the disruption of ecosystem functions and health. With its ability to capture continuous narrow-band spectra, hyperspectral technology has become a crucial tool to monitor crop diseases using remote sensing. However, existing continuous wavelet analysis (CWA) methods suffer from feature redundancy issues, while the continuous wavelet projection algorithm (CWPA), an optimization approach for feature selection, has not been fully validated to monitor plant diseases. This study utilized rice bacterial leaf blight (BLB) as an example by… More >

Selime Tuba Pesen, Mehmet Ali Altuncu^*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5597-5611, 2025, DOI:10.32604/cmc.2025.066702 - 30 July 2025

Abstract EEG signals are widely used in emotion recognition due to their ability to reflect involuntary physiological responses. However, the high dimensionality of EEG signals and their continuous variability in the time-frequency plane make their analysis challenging. Therefore, advanced deep learning methods are needed to extract meaningful features and improve classification performance. This study proposes a hybrid model that integrates the Swin Transformer and Temporal Convolutional Network (TCN) mechanisms for EEG-based emotion recognition. EEG signals are first converted into scalogram images using Continuous Wavelet Transform (CWT), and classification is performed on these images. Swin Transformer is… More >

Muhammad Farooq Siddique¹, Saif Ullah¹, Jong-Myon Kim^1,2,*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3577-3603, 2025, DOI:10.32604/cmc.2025.065326 - 03 July 2025

Abstract Centrifugal Pumps (CPs) are critical machine components in many industries, and their efficient operation and reliable Fault Diagnosis (FD) are essential for minimizing downtime and maintenance costs. This paper introduces a novel FD method to improve both the accuracy and reliability of detecting potential faults in such pumps. The proposed method combines Wavelet Coherent Analysis (WCA) and Stockwell Transform (S-transform) scalograms with Sobel and non-local means filters, effectively capturing complex fault signatures from vibration signals. Using Convolutional Neural Network (CNN) for feature extraction, the method transforms these scalograms into image inputs, enabling the recognition of More >

Guangfei Jia^*, Jinqiu Yang, Hanwen Liang

Structural Durability & Health Monitoring, Vol.19, No.4, pp. 1057-1072, 2025, DOI:10.32604/sdhm.2025.061805 - 30 June 2025

Abstract Considering the noise problem of the acquisition signals from mechanical transmission systems, a novel denoising method is proposed that combines Variational Mode Decomposition (VMD) with wavelet thresholding. The key innovation of this method lies in the optimization of VMD parameters K and using the improved Horned Lizard Optimization Algorithm (IHLOA). An inertia weight parameter is introduced into the random walk strategy of HLOA, and the related formula is improved. The acquisition signal can be adaptively decomposed into some Intrinsic Mode Functions (IMFs), and the high-noise IMFs are identified based on a correlation coefficient-variance method. Further noise… More > Graphic Abstract

Maazen Alsabaan¹, Zaid Bin Faheem², Yuanyuan Zhu², Jehad Ali^3,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 491-512, 2025, DOI:10.32604/cmc.2025.064971 - 09 June 2025

Abstract Image watermarking is a powerful tool for media protection and can provide promising results when combined with other defense mechanisms. Image watermarking can be used to protect the copyright of digital media by embedding a unique identifier that identifies the owner of the content. Image watermarking can also be used to verify the authenticity of digital media, such as images or videos, by ascertaining the watermark information. In this paper, a mathematical chaos-based image watermarking technique is proposed using discrete wavelet transform (DWT), chaotic map, and Laplacian operator. The DWT can be used to decompose… More >

Atheer Alrammahi^1,2, Hedieh Sajedi^1,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 887-918, 2025, DOI:10.32604/cmc.2025.063866 - 09 June 2025

Abstract Ensuring digital media security through robust image watermarking is essential to prevent unauthorized distribution, tampering, and copyright infringement. This study introduces a novel hybrid watermarking framework that integrates Discrete Wavelet Transform (DWT), Redundant Discrete Wavelet Transform (RDWT), and Möbius Transformations (MT), with optimization of transformation parameters achieved via a Genetic Algorithm (GA). By combining frequency and spatial domain techniques, the proposed method significantly enhances both the imperceptibility and robustness of watermark embedding. The approach leverages DWT and RDWT for multi-resolution decomposition, enabling watermark insertion in frequency subbands that balance visibility and resistance to attacks. RDWT,… More >