Jingcheng Zhang¹, Xingjian Zhou¹, Dong Shen¹, Qimeng Yu¹, Lin Yuan^2,*, Yingying Dong³

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 745-762, 2024, DOI:10.32604/phyton.2024.049734

Abstract As an important rice disease, rice bacterial leaf blight (RBLB, caused by the bacterium Xanthomonas oryzae pv. oryzae), has become widespread in east China in recent years. Significant losses in rice yield occurred as a result of the disease’s epidemic, making it imperative to monitor RBLB at a large scale. With the development of remote sensing technology, the broad-band sensors equipped with red-edge channels over multiple spatial resolutions offer numerous available data for large-scale monitoring of rice diseases. However, RBLB is characterized by rapid dispersal under suitable conditions, making it difficult to track the disease at a regional scale with… More >

Radwan Abu-Gdairi¹, R. Mareay^2,*, M. Badr³

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1025-1038, 2024, DOI:10.32604/cmc.2024.048647

Abstract Recently, much interest has been given to multi-granulation rough sets (MGRS), and various types of MGRS models have been developed from different viewpoints. In this paper, we introduce two techniques for the classification of MGRS. Firstly, we generate multi-topologies from multi-relations defined in the universe. Hence, a novel approximation space is established by leveraging the underlying topological structure. The characteristics of the newly proposed approximation space are discussed. We introduce an algorithm for the reduction of multi-relations. Secondly, a new approach for the classification of MGRS based on neighborhood concepts is introduced. Finally, a real-life application from medical records is… More >

Weiwu Jiang¹, Xiaowei Gao^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 41-76, 2024, DOI:10.32604/cmes.2024.048313

Abstract The collocation method is a widely used numerical method for science and engineering problems governed by partial differential equations. This paper provides a comprehensive review of collocation methods and their applications, focused on elasticity, heat conduction, electromagnetic field analysis, and fluid dynamics. The merits of the collocation method can be attributed to the need for element mesh, simple implementation, high computational efficiency, and ease in handling irregular domain problems since the collocation method is a type of node-based numerical method. Beginning with the fundamental principles of the collocation method, the discretization process in the continuous domain is elucidated, and how… More >

Mai Alzamel^1,*, Hamza Ali Rizvi², Najwa Altwaijry¹, Isra Al-Turaiki¹

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4177-4204, 2024, DOI:10.32604/cmc.2024.048370

Abstract Scalability and information personal privacy are vital for training and deploying large-scale deep learning models. Federated learning trains models on exclusive information by aggregating weights from various devices and taking advantage of the device-agnostic environment of web browsers. Nevertheless, relying on a main central server for internet browser-based federated systems can prohibit scalability and interfere with the training process as a result of growing client numbers. Additionally, information relating to the training dataset can possibly be extracted from the distributed weights, potentially reducing the privacy of the local data used for training. In this research paper, we aim to investigate… More >

Xia Li¹, Zhanyou Ma^1,*, Zhibao Mian², Ziyuan Liu¹, Ruiqi Huang¹, Nana He¹

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4129-4152, 2024, DOI:10.32604/cmc.2024.047168

Abstract Model checking is an automated formal verification method to verify whether epistemic multi-agent systems adhere to property specifications. Although there is an extensive literature on qualitative properties such as safety and liveness, there is still a lack of quantitative and uncertain property verifications for these systems. In uncertain environments, agents must make judicious decisions based on subjective epistemic. To verify epistemic and measurable properties in multi-agent systems, this paper extends fuzzy computation tree logic by introducing epistemic modalities and proposing a new Fuzzy Computation Tree Logic of Knowledge (FCTLK). We represent fuzzy multi-agent systems as distributed knowledge bases with fuzzy… More >

Yumin Jo¹, Jongho Paik^2,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4153-4176, 2024, DOI:10.32604/cmc.2024.047046

Abstract Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream. However, when the transmission environment is unstable, problems such as reduction in the lifespan of equipment due to frequent switching and interruption, delay, and stoppage of services may occur. Therefore, applying a machine learning (ML) method, which is possible to automatically judge and classify network-related service anomaly, and switch multi-input signals without dropping or changing signals by predicting or quickly determining the time of error occurrence for smooth stream switching when there are problems such as… More >

Rabia Abid¹, Muhammad Rizwan², Abdulatif Alabdulatif^3,*, Abdullah Alnajim⁴, Meznah Alamro⁵, Mourade Azrour⁶

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3413-3429, 2024, DOI:10.32604/cmc.2024.046880

Abstract Explainable Artificial Intelligence (XAI) has an advanced feature to enhance the decision-making feature and improve the rule-based technique by using more advanced Machine Learning (ML) and Deep Learning (DL) based algorithms. In this paper, we chose e-healthcare systems for efficient decision-making and data classification, especially in data security, data handling, diagnostics, laboratories, and decision-making. Federated Machine Learning (FML) is a new and advanced technology that helps to maintain privacy for Personal Health Records (PHR) and handle a large amount of medical data effectively. In this context, XAI, along with FML, increases efficiency and improves the security of e-healthcare systems. The… More >

Rashmi Sharma¹, Ashok Pal¹, Nitin Mittal², Lalit Kumar², Sreypov Van³, Yunyoung Nam^3,*, Mohamed Abouhawwash^4,5

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3489-3510, 2024, DOI:10.32604/cmc.2024.046606

Abstract This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm (MOALO) which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm (ALO) and the Genetic Algorithm (GA). MOALO version has been employed to address those problems containing many objectives and an archive has been employed for retaining the non-dominated solutions. The uniqueness of the hybrid is that the operators like mutation and crossover of GA are employed in the archive to update the solutions and later those solutions go through the process of MOALO. A first-time hybrid of these algorithms is employed to solve… More >

Talal Albalawi, P. Ganeshkumar^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3511-3528, 2024, DOI:10.32604/cmc.2024.046396

Abstract The Internet of Things (IoT) is a growing technology that allows the sharing of data with other devices across wireless networks. Specifically, IoT systems are vulnerable to cyberattacks due to its opennes The proposed work intends to implement a new security framework for detecting the most specific and harmful intrusions in IoT networks. In this framework, a Covariance Linear Learning Embedding Selection (CL2ES) methodology is used at first to extract the features highly associated with the IoT intrusions. Then, the Kernel Distributed Bayes Classifier (KDBC) is created to forecast attacks based on the probability distribution value precisely. In addition, a… More >

Yu Zhao, Zhijie Zhou^*, Hongdong Fan, Xiaoxia Han, Jie Wang, Manlin Chen

Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 73-91, 2024, DOI:10.32604/iasc.2024.042285

Abstract In industrial production and engineering operations, the health state of complex systems is critical, and predicting it can ensure normal operation. Complex systems have many monitoring indicators, complex coupling structures, non-linear and time-varying characteristics, so it is a challenge to establish a reliable prediction model. The belief rule base (BRB) can fuse observed data and expert knowledge to establish a nonlinear relationship between input and output and has well modeling capabilities. Since each indicator of the complex system can reflect the health state to some extent, the BRB is built based on the causal relationship between system indicators and the… More >