Chao Zhang¹, Shang-Xi Lai¹, Hua-Ping Wang^1,2,*

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 25-54, 2025, DOI:10.32604/sdhm.2024.053662 - 15 November 2024

Abstract Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure. Therefore, it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring (SHM) system, so as to provide a scientific basis for structural damage identification and dynamic model modification. In view of this, this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters. The paper primarily introduces data-driven modal parameter recognition methods… More >

Xiong Zhang^1,2, Minqing Zhang^1,2,3,*, Xu’an Wang^1,2,3,*, Siyuan Huang^1,2, Fuqiang Di^1,2

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1433-1448, 2024, DOI:10.32604/cmc.2024.056742 - 15 October 2024

Abstract Traditional information hiding techniques achieve information hiding by modifying carrier data, which can easily leave detectable traces that may be detected by steganalysis tools. Especially in image transmission, both geometric and non-geometric attacks can cause subtle changes in the pixels of the image during transmission. To overcome these challenges, we propose a constructive robust image steganography technique based on style transformation. Unlike traditional steganography, our algorithm does not involve any direct modifications to the carrier data. In this study, we constructed a mapping dictionary by setting the correspondence between binary codes and image categories and… More >

Menghan Zhang^1,2, Fangfang Shan^1,2,*, Mengyao Liu^1,2, Zhenyu Wang^1,2

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1565-1580, 2024, DOI:10.32604/cmc.2024.056008 - 15 October 2024

Abstract With the emergence and development of social networks, people can stay in touch with friends, family, and colleagues more quickly and conveniently, regardless of their location. This ubiquitous digital internet environment has also led to large-scale disclosure of personal privacy. Due to the complexity and subtlety of sensitive information, traditional sensitive information identification technologies cannot thoroughly address the characteristics of each piece of data, thus weakening the deep connections between text and images. In this context, this paper adopts the CLIP model as a modality discriminator. By using comparative learning between sensitive image descriptions and… More >

Qianqian Zhang^1,2,3, Yi Zhang^1,2, Yuanyuan Ma³, Yanmei Liu^1,2, Xiangyang Luo^1,2,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 105-131, 2024, DOI:10.32604/cmc.2024.055735 - 15 October 2024

Abstract The rapid development of the internet and digital media has provided convenience while also posing a potential risk of steganography abuse. Identifying steganographer is essential in tracing secret information origins and preventing illicit covert communication online. Accurately discerning a steganographer from many normal users is challenging due to various factors, such as the complexity in obtaining the steganography algorithm, extracting highly separability features, and modeling the cover data. After extensive exploration, several methods have been proposed for steganographer identification. This paper presents a survey of existing studies. Firstly, we provide a concise introduction to the More >

Abbas Ali Hassan, Fardin Abdali-Mohammadi^*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 971-983, 2024, DOI:10.32604/cmc.2024.053817 - 15 October 2024

Abstract From a medical perspective, the 12 leads of the heart in an electrocardiogram (ECG) signal have functional dependencies with each other. Therefore, all these leads report different aspects of an arrhythmia. Their differences lie in the level of highlighting and displaying information about that arrhythmia. For example, although all leads show traces of atrial excitation, this function is more evident in lead II than in any other lead. In this article, a new model was proposed using ECG functional and structural dependencies between heart leads. In the prescreening stage, the ECG signals are segmented from… More >

Yanxue Ma¹, Xiaoling Liu^1,*, Bing Wang², Ying Liu¹

Structural Durability & Health Monitoring, Vol.18, No.6, pp. 871-889, 2024, DOI:10.32604/sdhm.2024.052683 - 20 September 2024

Abstract In the bridge technical condition assessment standards, the evaluation of bridge conditions primarily relies on the defects identified through manual inspections, which are determined using the comprehensive hierarchical analysis method. However, the relationship between the defects and the technical condition of the bridges warrants further exploration. To address this situation, this paper proposes a machine learning-based intelligent diagnosis model for the technical condition of highway bridges. Firstly, collect the inspection records of highway bridges in a certain region of China, then standardize the severity of diverse defects in accordance with relevant specifications. Secondly, in order… More >

Sheng Xu¹, Shixiong Xiang², Feiyu Meng¹, Qiang Wu^1,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4197-4218, 2024, DOI:10.32604/cmc.2024.055157 - 12 September 2024

Abstract In Unsupervised Domain Adaptation (UDA) for person re-identification (re-ID), the primary challenge is reducing the distribution discrepancy between the source and target domains. This can be achieved by implicitly or explicitly constructing an appropriate intermediate domain to enhance recognition capability on the target domain. Implicit construction is difficult due to the absence of intermediate state supervision, making smooth knowledge transfer from the source to the target domain a challenge. To explicitly construct the most suitable intermediate domain for the model to gradually adapt to the feature distribution changes from the source to the target domain,… More >

Xu Sun, Yinhui Yu^*, Qing Cheng

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4149-4171, 2024, DOI:10.32604/cmc.2024.052725 - 12 September 2024

Abstract Object detection in unmanned aerial vehicle (UAV) aerial images has become increasingly important in military and civil applications. General object detection models are not robust enough against interclass similarity and intraclass variability of small objects, and UAV-specific nuisances such as uncontrolled weather conditions. Unlike previous approaches focusing on high-level semantic information, we report the importance of underlying features to improve detection accuracy and robustness from the information-theoretic perspective. Specifically, we propose a robust and discriminative feature learning approach through mutual information maximization (RD-MIM), which can be integrated into numerous object detection methods for aerial images.… More >

R. Mahaveerakannan¹, Thanarajan Tamilvizhi^2,*, Sonia Jenifer Rayen³, Osamah Ibrahim Khalaf⁴, Habib Hamam^5,6,7,8

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3945-3966, 2024, DOI:10.32604/cmc.2024.051611 - 12 September 2024

Abstract The demands on conventional communication networks are increasing rapidly because of the exponential expansion of connected multimedia content. In light of the data-centric aspect of contemporary communication, the information-centric network (ICN) paradigm offers hope for a solution by emphasizing content retrieval by name instead of location. If 5G networks are to meet the expected data demand surge from expanded connectivity and Internet of Things (IoT) devices, then effective caching solutions will be required to maximize network throughput and minimize the use of resources. Hence, an ICN-based Cooperative Caching (ICN-CoC) technique has been used to select… More >

Benxin Li^*, Xuanming Chang

Energy Engineering, Vol.121, No.10, pp. 3001-3018, 2024, DOI:10.32604/ee.2024.051332 - 11 September 2024

Abstract The increasingly large number of electric vehicles (EVs) has resulted in a growing concern for EV charging station load prediction for the purpose of comprehensively evaluating the influence of the charging load on distribution networks. To address this issue, an EV charging station load prediction method is proposed in coupled urban transportation and distribution networks. Firstly, a finer dynamic urban transportation network model is formulated considering both nodal and path resistance. Then, a finer EV power consumption model is proposed by considering the influence of traffic congestion and ambient temperature. Thirdly, the Monte Carlo method… More > Graphic Abstract