Chaozhi Cai, Yuqi Ren, Yingfang Xue^*, Jianhua Ren

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 665-682, 2025, DOI:10.32604/sdhm.2025.059044 - 03 April 2025

Abstract Rolling bearings are important parts of industrial equipment, and their fault diagnosis is crucial to maintaining these equipment’s regular operations. With the goal of improving the fault diagnosis accuracy of rolling bearings under complex working conditions and noise, this study proposes a multiscale information fusion method for fault diagnosis of rolling bearings based on fast Fourier transform (FFT) and variational mode decomposition (VMD), as well as the Senet (SE)-TCNnet (TCN) model. FFT is used to transform the original one-dimensional time domain vibration signal into a frequency domain signal, while VMD is used to decompose the… More >

Chuanyun Xu^1,#, Die Hu^1,#, Yang Zhang^1,*, Shuaiye Huang¹, Yisha Sun¹, Gang Li²

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 559-574, 2025, DOI:10.32604/cmc.2025.061579 - 26 March 2025

Abstract Detecting abnormal cervical cells is crucial for early identification and timely treatment of cervical cancer. However, this task is challenging due to the morphological similarities between abnormal and normal cells and the significant variations in cell size. Pathologists often refer to surrounding cells to identify abnormalities. To emulate this slide examination behavior, this study proposes a Multi-Scale Feature Fusion Network (MSFF-Net) for detecting cervical abnormal cells. MSFF-Net employs a Cross-Scale Pooling Model (CSPM) to effectively capture diverse features and contextual information, ranging from local details to the overall structure. Additionally, a Multi-Scale Fusion Attention (MSFA)… More >

Xiang Zhang^1,2,*, Shenyan Han^1,2, Wenbin Huang^1,2, Daoyong Fu^1,2

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1149-1171, 2025, DOI:10.32604/cmc.2025.060876 - 26 March 2025

Abstract Generative image steganography is a technique that directly generates stego images from secret information. Unlike traditional methods, it theoretically resists steganalysis because there is no cover image. Currently, the existing generative image steganography methods generally have good steganography performance, but there is still potential room for enhancing both the quality of stego images and the accuracy of secret information extraction. Therefore, this paper proposes a generative image steganography algorithm based on attribute feature transformation and invertible mapping rule. Firstly, the reference image is disentangled by a content and an attribute encoder to obtain content features… More >

Sai Venkata Akhil Ammu¹, Sukhjit Singh Sehra^1,*, Sumeet Kaur Sehra², Jaiteg Singh³

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 435-453, 2025, DOI:10.32604/cmc.2025.057792 - 26 March 2025

Abstract Duplicate bug reporting is a critical problem in the software repositories’ mining area. Duplicate bug reports can lead to redundant efforts, wasted resources, and delayed software releases. Thus, their accurate identification is essential for streamlining the bug triage process mining area. Several researchers have explored classical information retrieval, natural language processing, text and data mining, and machine learning approaches. The emergence of large language models (LLMs) (ChatGPT and Huggingface) has presented a new line of models for semantic textual similarity (STS). Although LLMs have shown remarkable advancements, there remains a need for longitudinal studies to… More >

Dongdong Zhang, Chunping Wang, Huiying Wang, Qiang Fu^*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4319-4338, 2025, DOI:10.32604/cmc.2025.060653 - 06 March 2025

Abstract Video camouflaged object detection (VCOD) has become a fundamental task in computer vision that has attracted significant attention in recent years. Unlike image camouflaged object detection (ICOD), VCOD not only requires spatial cues but also needs motion cues. Thus, effectively utilizing spatiotemporal information is crucial for generating accurate segmentation results. Current VCOD methods, which typically focus on exploring motion representation, often ineffectively integrate spatial and motion features, leading to poor performance in diverse scenarios. To address these issues, we design a novel spatiotemporal network with an encoder-decoder structure. During the encoding stage, an adjacent space-time More >

Shaoqi Hou^1,2,3,*, Zebang Qin², Chenyu Wu², Guangqiang Yin², Xinzhong Wang¹, Zhiguo Wang^2,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5019-5033, 2025, DOI:10.32604/cmc.2025.058233 - 06 March 2025

Abstract Visual Place Recognition (VPR) technology aims to use visual information to judge the location of agents, which plays an irreplaceable role in tasks such as loop closure detection and relocation. It is well known that previous VPR algorithms emphasize the extraction and integration of general image features, while ignoring the mining of salient features that play a key role in the discrimination of VPR tasks. To this end, this paper proposes a Domain-invariant Information Extraction and Optimization Network (DIEONet) for VPR. The core of the algorithm is a newly designed Domain-invariant Information Mining Module (DIMM)… More >

Yuan Ping^1,2,*, Huina Li¹, Chun Guo³, Bin Hao⁴

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4949-4976, 2025, DOI:10.32604/cmc.2025.057693 - 06 March 2025

Abstract Towards optimal k-prototype discovery, k-means-like algorithms give us inspirations of central samples collection, yet the unstable seed samples selection, the hypothesis of a circle-like pattern, and the unknown K are still challenges, particularly for non-predetermined data patterns. We propose an adaptive k-prototype clustering method (kProtoClust) which launches cluster exploration with a sketchy division of K clusters and finds evidence for splitting and merging. On behalf of a group of data samples, support vectors and outliers from the perspective of support vector data description are not the appropriate candidates for prototypes, while inner samples become the first candidates for… More >

Bernard Bayangbe^1,*, Ababacar Thiam^1,2, El hadji I. Cissé², Kory Faye¹

Energy Engineering, Vol.122, No.3, pp. 943-969, 2025, DOI:10.32604/ee.2025.060273 - 07 March 2025

Abstract Concentrating Solar Power (CSP) is one of the most promising solar technologies for sustainable power generation in countries with high solar potential, like Chad. Identifying suitable sites is of great importance for deploying solar power plants. This work focuses on the identification of potential sites for the installation of solar power plants in Chad as well as a comparative analysis using the Analytical Hierarchy Process (AHP), Fuzzy Analytical Hierarchy Process (FAHP), and Full Consistency Method (FUCOM). The results show that 35% of the Chadian territory, i.e., an area of 449,400 km², is compatible with the implementation… More >

Donghyeok Park¹, Sumin Yeon², Hyeon Seo², Seok-Jun Buu², Suwon Lee^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2725-2737, 2025, DOI:10.32604/cmes.2025.061732 - 03 March 2025

Abstract Recent research on adversarial attacks has primarily focused on white-box attack techniques, with limited exploration of black-box attack methods. Furthermore, in many black-box research scenarios, it is assumed that the output label and probability distribution can be observed without imposing any constraints on the number of attack attempts. Unfortunately, this disregard for the real-world practicality of attacks, particularly their potential for human detectability, has left a gap in the research landscape. Considering these limitations, our study focuses on using a similar color attack method, assuming access only to the output label, limiting the number of More >

Baoping Zou^1,2, Chenhao Pei^1,*, Qizhi Chen^1,2, Yansheng Deng^1,2, Yongguo Chen^1,2, Xu Long^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2457-2485, 2025, DOI:10.32604/cmes.2025.061429 - 03 March 2025

Abstract The utilization of multi-field coupling simulation methods has become a pivotal approach for the investigation of intricate fracture behavior and interaction mechanisms of rock masses in deep strata. The high temperatures, pressures and complex geological environments of deep strata frequently result in the coupling of multiple physical fields, including mechanical, thermal and hydraulic fields, during the fracturing of rocks. This review initially presents an overview of the coupling mechanisms of these physical fields, thereby elucidating the interaction processes of mechanical, thermal, and hydraulic fields within rock masses. Secondly, an in-depth analysis of multi-field coupling is… More >