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  • Open Access

    ARTICLE

    A Novel Anti-Collision Algorithm for Large Scale of UHF RFID Tags Access Systems

    Xu Zhang1, Yi He1, Haiwen Yi1, Yulu Zhang2, Yuan Li2, Shuai Ma2, Gui Li3, Zhiyuan Zhao4, Yue Liu1, Junyang Liu1, Guangjun Wen1, Jian Li1,*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 897-912, 2024, DOI:10.32604/cmc.2024.050000 - 18 July 2024

    Abstract When the radio frequency identification (RFID) system inventories multiple tags, the recognition rate will be seriously affected due to collisions. Based on the existing dynamic frame slotted Aloha (DFSA) algorithm, a sub-frame observation and cyclic redundancy check (CRC) grouping combined dynamic framed slotted Aloha (SUBF-CGDFSA) algorithm is proposed. The algorithm combines the precise estimation method of the quantity of large-scale tags, the large-scale tags grouping mechanism based on CRC pseudo-random characteristics, and the Aloha anti-collision optimization mechanism based on sub-frame observation. By grouping tags and sequentially identifying them within subframes, it accurately estimates the number More >

  • Open Access

    ARTICLE

    A Dual Domain Robust Reversible Watermarking Algorithm for Frame Grouping Videos Using Scene Smoothness

    Yucheng Liang1,2,*, Ke Niu1,2,*, Yingnan Zhang1,2, Yifei Meng1,2

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5143-5174, 2024, DOI:10.32604/cmc.2024.051364 - 20 June 2024

    Abstract The proposed robust reversible watermarking algorithm addresses the compatibility challenges between robustness and reversibility in existing video watermarking techniques by leveraging scene smoothness for frame grouping videos. Grounded in the H.264 video coding standard, the algorithm first employs traditional robust watermark stitching technology to embed watermark information in the low-frequency coefficient domain of the U channel. Subsequently, it utilizes histogram migration techniques in the high-frequency coefficient domain of the U channel to embed auxiliary information, enabling successful watermark extraction and lossless recovery of the original video content. Experimental results demonstrate the algorithm’s strong imperceptibility, with… More >

  • Open Access

    ARTICLE

    Multi-Objective Optimization Algorithm for Grouping Decision Variables Based on Extreme Point Pareto Frontier

    Jun Wang1,2, Linxi Zhang1,2, Hao Zhang1, Funan Peng1,*, Mohammed A. El-Meligy3, Mohamed Sharaf3, Qiang Fu1

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1281-1299, 2024, DOI:10.32604/cmc.2024.048495 - 25 April 2024

    Abstract The existing algorithms for solving multi-objective optimization problems fall into three main categories: Decomposition-based, dominance-based, and indicator-based. Traditional multi-objective optimization problems mainly focus on objectives, treating decision variables as a total variable to solve the problem without considering the critical role of decision variables in objective optimization. As seen, a variety of decision variable grouping algorithms have been proposed. However, these algorithms are relatively broad for the changes of most decision variables in the evolution process and are time-consuming in the process of finding the Pareto frontier. To solve these problems, a multi-objective optimization algorithm… More >

  • Open Access

    ARTICLE

    Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables

    Liang Chen1, Jingbo Zhang1, Linjie Wu1, Xingjuan Cai1,2,*, Yubin Xu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 363-383, 2024, DOI:10.32604/cmes.2024.049044 - 16 April 2024

    Abstract The large-scale multi-objective optimization algorithm (LSMOA), based on the grouping of decision variables, is an advanced method for handling high-dimensional decision variables. However, in practical problems, the interaction among decision variables is intricate, leading to large group sizes and suboptimal optimization effects; hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables (MOEAWOD) is proposed in this paper. Initially, the decision variables are perturbed and categorized into convergence and diversity variables; subsequently, the convergence variables are subdivided into groups based on the interactions among different decision variables. If the size of… More >

  • Open Access

    ARTICLE

    Dendritic Cell Algorithm with Grouping Genetic Algorithm for Input Signal Generation

    Dan Zhang1, Yiwen Liang1,*, Hongbin Dong2

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2025-2045, 2023, DOI:10.32604/cmes.2023.022864 - 23 November 2022

    Abstract The artificial immune system, an excellent prototype for developing Machine Learning, is inspired by the function of the powerful natural immune system. As one of the prevalent classifiers, the Dendritic Cell Algorithm (DCA) has been widely used to solve binary problems in the real world. The classification of DCA depends on a data pre-processing procedure to generate input signals, where feature selection and signal categorization are the main work. However, the results of these studies also show that the signal generation of DCA is relatively weak, and all of them utilized a filter strategy to… More > Graphic Abstract

    Dendritic Cell Algorithm with Grouping Genetic Algorithm for Input Signal Generation

  • Open Access

    ARTICLE

    Improvisation of Node Mobility Using Cluster Routing-based Group Adaptive in MANET

    J. Shanthini1, P. Punitha2,*, S. Karthik2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2619-2636, 2023, DOI:10.32604/csse.2023.027330 - 01 August 2022

    Abstract In today's Internet routing infrastructure, designers have addressed scaling concerns in routing constrained multiobjective optimization problems examining latency and mobility concerns as a secondary constrain. In tactical Mobile Ad-hoc Network (MANET), hubs can function based on the work plan in various social affairs and the internally connected hubs are almost having the related moving standards where the topology between one and the other are tightly coupled in steady support by considering the touchstone of hubs such as a self-sorted out, self-mending and self-administration. Clustering in the routing process is one of the key aspects to… More >

  • Open Access

    ARTICLE

    AI-Enabled Grouping Bridgehead to Secure Penetration Topics of Metaverse

    Woo Hyun Park1, Isma Farah Siddiqui3, Nawab Muhammad Faseeh Qureshi2,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5609-5624, 2022, DOI:10.32604/cmc.2022.030235 - 28 July 2022

    Abstract With the advent of the big data era, security issues in the context of artificial intelligence (AI) and data analysis are attracting research attention. In the metaverse, which will become a virtual asset in the future, users’ communication, movement with characters, text elements, etc., are required to integrate the real and virtual. However, they can be exposed to threats. Particularly, various hacker threats exist. For example, users’ assets are exposed through notices and mail alerts regularly sent to users by operators. In the future, hacker threats will increase mainly due to naturally anonymous texts. Therefore,… More >

  • Open Access

    ARTICLE

    Feature Selection Using Grey Wolf Optimization with Random Differential Grouping

    R. S. Latha1,*, B. Saravana Balaji2, Nebojsa Bacanin3, Ivana Strumberger3, Miodrag Zivkovic3, Milos Kabiljo3

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 317-332, 2022, DOI:10.32604/csse.2022.020487 - 23 March 2022

    Abstract Big data are regarded as a tremendous technology for processing a huge variety of data in a short time and with a large storage capacity. The user’s access over the internet creates massive data processing over the internet. Big data require an intelligent feature selection model by addressing huge varieties of data. Traditional feature selection techniques are only applicable to simple data mining. Intelligent techniques are needed in big data processing and machine learning for an efficient classification. Major feature selection algorithms read the input features as they are. Then, the features are preprocessed and… More >

  • Open Access

    ARTICLE

    High Performance Classification of Android Malware Using Ensemble Machine Learning

    Pagnchakneat C. Ouk1, Wooguil Pak2,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 381-398, 2022, DOI:10.32604/cmc.2022.024540 - 24 February 2022

    Abstract Although Android becomes a leading operating system in market, Android users suffer from security threats due to malwares. To protect users from the threats, the solutions to detect and identify the malware variant are essential. However, modern malware evades existing solutions by applying code obfuscation and native code. To resolve this problem, we introduce an ensemble-based malware classification algorithm using malware family grouping. The proposed family grouping algorithm finds the optimal combination of families belonging to the same group while the total number of families is fixed to the optimal total number. It also adopts… More >

  • Open Access

    ARTICLE

    Sustainable Waste Collection Vehicle Routing Problem for COVID-19

    G. Niranjani1,*, K. Umamaheswari2

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 457-472, 2022, DOI:10.32604/iasc.2022.024264 - 05 January 2022

    Abstract COVID-19 pandemic has imposed many threats. One among them is the accumulation of waste in hospitals. Waste should be disposed regularly and safely using sustainable methods. Sustainability is self development with preservation of society and its resources. The main objective of this research is to achieve sustainability in waste collection by minimizing the cost factor. Minimization of sustainable-cost involves minimization of three sub-components – total travel-cost representing economical component, total emission-cost representing environmental component and total driver-allowance-cost representing social component. Most papers under waste collection implement Tabu search algorithm and fail to consider the environmental More >

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