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  • Open Access

    ARTICLE

    TransSSA: Invariant Cue Perceptual Feature Focused Learning for Dynamic Fruit Target Detection

    Jianyin Tang, Zhenglin Yu*, Changshun Shao

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2829-2850, 2025, DOI:10.32604/cmc.2025.063287 - 16 April 2025

    Abstract In the field of automated fruit harvesting, precise and efficient fruit target recognition and localization play a pivotal role in enhancing the efficiency of harvesting robots. However, this domain faces two core challenges: firstly, the dynamic nature of the automatic picking process requires fruit target detection algorithms to adapt to multi-view characteristics, ensuring effective recognition of the same fruit from different perspectives. Secondly, fruits in natural environments often suffer from interference factors such as overlapping, occlusion, and illumination fluctuations, which increase the difficulty of image capture and recognition. To address these challenges, this study conducted… More >

  • Open Access

    ARTICLE

    Entropy-Bottleneck-Based Privacy Protection Mechanism for Semantic Communication

    Kaiyang Han1, Xiaoqiang Jia1, Yangfei Lin2, Tsutomu Yoshinaga2, Yalong Li2, Jiale Wu2,*

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2971-2988, 2025, DOI:10.32604/cmc.2025.061563 - 16 April 2025

    Abstract With the rapid development of artificial intelligence and the Internet of Things, along with the growing demand for privacy-preserving transmission, the need for efficient and secure communication systems has become increasingly urgent. Traditional communication methods transmit data at the bit level without considering its semantic significance, leading to redundant transmission overhead and reduced efficiency. Semantic communication addresses this issue by extracting and transmitting only the most meaningful semantic information, thereby improving bandwidth efficiency. However, despite reducing the volume of data, it remains vulnerable to privacy risks, as semantic features may still expose sensitive information. To… More >

  • Open Access

    ARTICLE

    SA-ResNet: An Intrusion Detection Method Based on Spatial Attention Mechanism and Residual Neural Network Fusion

    Zengyu Cai1,*, Yuming Dai1, Jianwei Zhang2,3,*, Yuan Feng4

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3335-3350, 2025, DOI:10.32604/cmc.2025.061206 - 16 April 2025

    Abstract The rapid development and widespread adoption of Internet technology have significantly increased Internet traffic, highlighting the growing importance of network security. Intrusion Detection Systems (IDS) are essential for safeguarding network integrity. To address the low accuracy of existing intrusion detection models in identifying network attacks, this paper proposes an intrusion detection method based on the fusion of Spatial Attention mechanism and Residual Neural Network (SA-ResNet). Utilizing residual connections can effectively capture local features in the data; by introducing a spatial attention mechanism, the global dependency relationships of intrusion features can be extracted, enhancing the intrusion More >

  • Open Access

    ARTICLE

    Event-Driven Attention Network: A Cross-Modal Framework for Efficient Image-Text Retrieval in Mass Gathering Events

    Kamil Yasen1,#, Heyan Jin2,#, Sijie Yang2, Li Zhan2, Xuyang Zhang2, Ke Qin1,3, Ye Li2,3,*

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3277-3301, 2025, DOI:10.32604/cmc.2025.061037 - 16 April 2025

    Abstract Research on mass gathering events is critical for ensuring public security and maintaining social order. However, most of the existing works focus on crowd behavior analysis areas such as anomaly detection and crowd counting, and there is a relative lack of research on mass gathering behaviors. We believe real-time detection and monitoring of mass gathering behaviors are essential for migrating potential security risks and emergencies. Therefore, it is imperative to develop a method capable of accurately identifying and localizing mass gatherings before disasters occur, enabling prompt and effective responses. To address this problem, we propose… More >

  • Open Access

    ARTICLE

    Collaborative Decomposition Multi-Objective Improved Elephant Clan Optimization Based on Penalty-Based and Normal Boundary Intersection

    Mengjiao Wei1,*, Wenyu Liu2

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2505-2523, 2025, DOI:10.32604/cmc.2025.060887 - 16 April 2025

    Abstract In recent years, decomposition-based evolutionary algorithms have become popular algorithms for solving multi-objective problems in real-life scenarios. In these algorithms, the reference vectors of the Penalty-Based boundary intersection (PBI) are distributed parallelly while those based on the normal boundary intersection (NBI) are distributed radially in a conical shape in the objective space. To improve the problem-solving effectiveness of multi-objective optimization algorithms in engineering applications, this paper addresses the improvement of the Collaborative Decomposition (CoD) method, a multi-objective decomposition technique that integrates PBI and NBI, and combines it with the Elephant Clan Optimization Algorithm, introducing the… More >

  • Open Access

    ARTICLE

    A Transformer Based on Feedback Attention Mechanism for Diagnosis of Coronary Heart Disease Using Echocardiographic Images

    Chunlai Du1,#, Xin Gu1,#, Yanhui Guo2,*, Siqi Guo3, Ziwei Pang3, Yi Du3, Guoqing Du3,*

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3435-3450, 2025, DOI:10.32604/cmc.2025.060212 - 16 April 2025

    Abstract Coronary artery disease is a highly lethal cardiovascular condition, making early diagnosis crucial for patients. Echocardiograph is employed to identify coronary heart disease (CHD). However, due to issues such as fuzzy object boundaries, complex tissue structures, and motion artifacts in ultrasound images, it is challenging to detect CHD accurately. This paper proposes an improved Transformer model based on the Feedback Self-Attention Mechanism (FSAM) for classification of ultrasound images. The model enhances attention weights, making it easier to capture complex features. Experimental results show that the proposed method achieves high levels of accuracy, recall, precision, F1 More >

  • Open Access

    ARTICLE

    A Privacy-Preserving Graph Neural Network Framework with Attention Mechanism for Computational Offloading in the Internet of Vehicles

    Aishwarya Rajasekar*, Vetriselvi Vetrian

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 225-254, 2025, DOI:10.32604/cmes.2025.062642 - 11 April 2025

    Abstract The integration of technologies like artificial intelligence, 6G, and vehicular ad-hoc networks holds great potential to meet the communication demands of the Internet of Vehicles and drive the advancement of vehicle applications. However, these advancements also generate a surge in data processing requirements, necessitating the offloading of vehicular tasks to edge servers due to the limited computational capacity of vehicles. Despite recent advancements, the robustness and scalability of the existing approaches with respect to the number of vehicles and edge servers and their resources, as well as privacy, remain a concern. In this paper, a lightweight… More >

  • Open Access

    ARTICLE

    Numerical Simulation of Residual Strength for Corroded Pipelines

    Yaojin Fan, Huaqing Dong*, Zixuan Zong, Tingting Long, Qianglin Huang, Guoqiang Huang

    Structural Durability & Health Monitoring, Vol.19, No.3, pp. 731-769, 2025, DOI:10.32604/sdhm.2025.061056 - 03 April 2025

    Abstract This study presents a comprehensive investigation of residual strength in corroded pipelines within the Yichang-Qianjiang section of the Sichuan-East Gas Pipeline, integrating advanced numerical simulation with experimental validation. The research methodology incorporates three distinct parameter grouping approaches: a random group based on statistical analysis of 389 actual corrosion defects detected during 2023 MFL inspection, a deviation group representing historically documented failure scenarios, and a structural group examining systematic parameter variations. Using ABAQUS finite element software, we developed a dynamic implicit analysis model incorporating geometric nonlinearity and validated it through 1:12.7 scaled model testing, achieving prediction… More >

  • Open Access

    REVIEW

    From Cell Division to Stress Tolerance: The Versatile Roles of Cytokinins in Plants

    Antonio Rodrigues da Cunha Neto1, Alexandra dos Santos Ambrósio1, Arlinda de Jesus Rodrigues Resende1, Breno Régis Santos1, Michele Carla Nadal2,*

    Phyton-International Journal of Experimental Botany, Vol.94, No.3, pp. 539-560, 2025, DOI:10.32604/phyton.2025.061776 - 31 March 2025

    Abstract Cytokinins are plant hormones that are essential for plant growth and development and are involved in a variety of processes. They are synthesized by the modification of adenine with an isoprenoid chain, resulting in cytokinins such as isopentenyladenine and zeatin. The levels of these hormones are regulated by conjugation, degradation and oxidation processes that modulate their activity. Cytokinins are perceived by cells through specific receptors that, when activated, trigger signaling cascades responsible for regulating the expression of genes critical for development. In addition, cytokinins interact with other hormones, such as auxins, to coordinate plant growth… More >

  • Open Access

    ARTICLE

    Low-Carbon Economic Dispatch Strategy for Integrated Energy Systems under Uncertainty Counting CCS-P2G and Concentrating Solar Power Stations

    Zhihui Feng1, Jun Zhang1, Jun Lu1, Zhongdan Zhang1, Wangwang Bai1, Long Ma1, Haonan Lu2, Jie Lin2,*

    Energy Engineering, Vol.122, No.4, pp. 1531-1560, 2025, DOI:10.32604/ee.2025.060795 - 31 March 2025

    Abstract In the background of the low-carbon transformation of the energy structure, the problem of operational uncertainty caused by the high proportion of renewable energy sources and diverse loads in the integrated energy systems (IES) is becoming increasingly obvious. In this case, to promote the low-carbon operation of IES and renewable energy consumption, and to improve the IES anti-interference ability, this paper proposes an IES scheduling strategy that considers CCS-P2G and concentrating solar power (CSP) station. Firstly, CSP station, gas hydrogen doping mode and variable hydrogen doping ratio mode are applied to IES, and combined with… More >

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