Run Yang^1,2,3, Yanping Chen^1,2,3,*, Jiaxin Yan^1,2,3, Yongbin Qin^1,2,3

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4129-4147, 2024, DOI:10.32604/cmc.2024.051675 - 12 September 2024

Abstract The relation is a semantic expression relevant to two named entities in a sentence. Since a sentence usually contains several named entities, it is essential to learn a structured sentence representation that encodes dependency information specific to the two named entities. In related work, graph convolutional neural networks are widely adopted to learn semantic dependencies, where a dependency tree initializes the adjacency matrix. However, this approach has two main issues. First, parsing a sentence heavily relies on external toolkits, which can be error-prone. Second, the dependency tree only encodes the syntactical structure of a sentence,… More >

Yuwei Xu, Baokang Zhao^*, Huan Zhou, Jinshu Su

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 609-629, 2024, DOI:10.32604/cmes.2024.053462 - 20 August 2024

Abstract The rapid expansion of artificial intelligence (AI) applications has raised significant concerns about user privacy, prompting the development of privacy-preserving machine learning (ML) paradigms such as federated learning (FL). FL enables the distributed training of ML models, keeping data on local devices and thus addressing the privacy concerns of users. However, challenges arise from the heterogeneous nature of mobile client devices, partial engagement of training, and non-independent identically distributed (non-IID) data distribution, leading to performance degradation and optimization objective bias in FL training. With the development of 5G/6G networks and the integration of cloud computing… More >

Nannan Chong^1,2,*, Fan Yang¹

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2761-2783, 2024, DOI:10.32604/cmc.2024.052217 - 15 August 2024

Abstract In minimally invasive surgery, endoscopes or laparoscopes equipped with miniature cameras and tools are used to enter the human body for therapeutic purposes through small incisions or natural cavities. However, in clinical operating environments, endoscopic images often suffer from challenges such as low texture, uneven illumination, and non-rigid structures, which affect feature observation and extraction. This can severely impact surgical navigation or clinical diagnosis due to missing feature points in endoscopic images, leading to treatment and postoperative recovery issues for patients. To address these challenges, this paper introduces, for the first time, a Cross-Channel Multi-Modal… More >

Huanhuan Li^1,2,*, Hongchang Wei², Zheliang Chen², Yue Xu³

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2199-2219, 2024, DOI:10.32604/cmc.2024.052155 - 15 August 2024

Abstract The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges, such as low user utilization, unbalanced resource allocation, and extended adaptive allocation time. We propose an adaptive allocation algorithm for mobile cloud communication resources in 5G vehicular networks to address these issues. This study analyzes the components of the 5G vehicular network architecture to determine the performance of different components. It is ascertained that the communication modes in 5G vehicular networks for mobile cloud communication include in-band and out-of-band modes. Furthermore, this study analyzes the single-hop and multi-hop modes in… More >

Jing Zhang^*, Guangli Wu, Shanshan Song

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1947-1965, 2024, DOI:10.32604/cmc.2024.051781 - 15 August 2024

Abstract Video summarization aims to select key frames or key shots to create summaries for fast retrieval, compression, and efficient browsing of videos. Graph neural networks efficiently capture information about graph nodes and their neighbors, but ignore the dynamic dependencies between nodes. To address this challenge, we propose an innovative Adaptive Graph Convolutional Adjacency Matrix Network (TAMGCN), leveraging the attention mechanism to dynamically adjust dependencies between graph nodes. Specifically, we first segment shots and extract features of each frame, then compute the representative features of each shot. Subsequently, we utilize the attention mechanism to dynamically adjust More >

Abdulraqeb Alhammadi^1,*, Zaid Ahmed Shamsan², Arijit De³

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1889-1905, 2024, DOI:10.32604/cmc.2024.051487 - 15 August 2024

Abstract Indoor localization systems are crucial in addressing the limitations of traditional global positioning system (GPS) in indoor environments due to signal attenuation issues. As complex indoor spaces become more sophisticated, indoor localization systems become essential for improving user experience, safety, and operational efficiency. Indoor localization methods based on Wi-Fi fingerprints require a high-density location fingerprint database, but this can increase the computational burden in the online phase. Bayesian networks, which integrate prior knowledge or domain expertise, are an effective solution for accurately determining indoor user locations. These networks use probabilistic reasoning to model relationships among… More >

Jiarui Zhang¹, Dan Liu^2,*, Kan Cao², Ping Xiong², Xiaotong Ji³, Yanze Xu¹, Yunfei Mu¹

Energy Engineering, Vol.121, No.8, pp. 2065-2083, 2024, DOI:10.32604/ee.2024.050342 - 19 July 2024

Abstract The system performance of grid-connected photovoltaic (PV) has a serious impact on the grid stability. To improve the control performance and shorten the convergence time, a predefined-time controller based on backstepping technology and dynamic surface control is formulated for the inverter in the grid-connected photovoltaic. The time-varying tuning functions are introduced into state-tracking errors to realize the predefined-time control effect. To address the “computational explosion problem” in the design process of backstepping control, dynamic surface control is adopted to avoid the analytical calculations of virtual control. The disturbances of the PV system are estimated and More >

Lirong Yin¹, Lei Wang¹, Siyu Lu^2,*, Ruiyang Wang², Haitao Ren², Ahmed AlSanad³, Salman A. AlQahtani³, Zhengtong Yin⁴, Xiaolu Li⁵, Wenfeng Zheng^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2315-2347, 2024, DOI:10.32604/cmes.2024.050853 - 08 July 2024

Abstract At present, super-resolution algorithms are employed to tackle the challenge of low image resolution, but it is difficult to extract differentiated feature details based on various inputs, resulting in poor generalization ability. Given this situation, this study first analyzes the features of some feature extraction modules of the current super-resolution algorithm and then proposes an adaptive feature fusion block (AFB) for feature extraction. This module mainly comprises dynamic convolution, attention mechanism, and pixel-based gating mechanism. Combined with dynamic convolution with scale information, the network can extract more differentiated feature information. The introduction of a channel More >

Song Deng^1,*, Yiming Yuan²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3679-3697, 2024, DOI:10.32604/cmc.2024.052008 - 20 June 2024

Abstract Malicious attacks against data are unavoidable in the interconnected, open and shared Energy Internet (EI), Intrusion tolerant techniques are critical to the data security of EI. Existing intrusion tolerant techniques suffered from problems such as low adaptability, policy lag, and difficulty in determining the degree of tolerance. To address these issues, we propose a novel adaptive intrusion tolerance model based on game theory that enjoys two-fold ideas: 1) it constructs an improved replica of the intrusion tolerance model of the dynamic equation evolution game to induce incentive weights; and 2) it combines a tournament competition More >

Djeldjli Halima^1,*, Benatiallah Djelloul¹, Ghasri Mehdi², Tanougast Camel³, Benatiallah Ali⁴, Benabdelkrim Bouchra¹

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4725-4740, 2024, DOI:10.32604/cmc.2024.051002 - 20 June 2024

Abstract When designing solar systems and assessing the effectiveness of their many uses, estimating sun irradiance is a crucial first step. This study examined three approaches (ANN, GA-ANN, and ANFIS) for estimating daily global solar radiation (GSR) in the south of Algeria: Adrar, Ouargla, and Bechar. The proposed hybrid GA-ANN model, based on genetic algorithm-based optimization, was developed to improve the ANN model. The GA-ANN and ANFIS models performed better than the standalone ANN-based model, with GA-ANN being better suited for forecasting in all sites, and it performed the best with the best values in the… More > Graphic Abstract