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  • Open Access

    ARTICLE

    Genetic Algorithm Combined with the K-Means Algorithm: A Hybrid Technique for Unsupervised Feature Selection

    Hachemi Bennaceur, Meznah Almutairy, Norah Alhussain*

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2687-2706, 2023, DOI:10.32604/iasc.2023.038723

    Abstract The dimensionality of data is increasing very rapidly, which creates challenges for most of the current mining and learning algorithms, such as large memory requirements and high computational costs. The literature includes much research on feature selection for supervised learning. However, feature selection for unsupervised learning has only recently been studied. Finding the subset of features in unsupervised learning that enhances the performance is challenging since the clusters are indeterminate. This work proposes a hybrid technique for unsupervised feature selection called GAk-MEANS, which combines the genetic algorithm (GA) approach with the classical k-Means algorithm. In the proposed algorithm, a new… More >

  • Open Access

    ARTICLE

    Research on Optimization of Dual-Resource Batch Scheduling in Flexible Job Shop

    Qinhui Liu, Zhijie Gao, Jiang Li*, Shuo Li, Laizheng Zhu

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2503-2530, 2023, DOI:10.32604/cmc.2023.040505

    Abstract With the rapid development of intelligent manufacturing and the changes in market demand, the current manufacturing industry presents the characteristics of multi-varieties, small batches, customization, and a short production cycle, with the whole production process having certain flexibility. In this paper, a mathematical model is established with the minimum production cycle as the optimization objective for the dual-resource batch scheduling of the flexible job shop, and an improved nested optimization algorithm is designed to solve the problem. The outer layer batch optimization problem is solved by the improved simulated annealing algorithm. The inner double resource scheduling problem is solved by… More >

  • Open Access

    ARTICLE

    A Hybrid Heuristic Service Caching and Task Offloading Method for Mobile Edge Computing

    Yongxuan Sang, Jiangpo Wei*, Zhifeng Zhang, Bo Wang

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2483-2502, 2023, DOI:10.32604/cmc.2023.040485

    Abstract Computing-intensive and latency-sensitive user requests pose significant challenges to traditional cloud computing. In response to these challenges, mobile edge computing (MEC) has emerged as a new paradigm that extends the computational, caching, and communication capabilities of cloud computing. By caching certain services on edge nodes, computational support can be provided for requests that are offloaded to the edges. However, previous studies on task offloading have generally not considered the impact of caching mechanisms and the cache space occupied by services. This oversight can lead to problems, such as high delays in task executions and invalidation of offloading decisions. To optimize… More >

  • Open Access

    ARTICLE

    The whole-genome survey of Acer griseum, its polymorphic simple sequence repeats development and application

    XIAO-JUN ZHOU1,*, YU-WEI TIAN1, RUI-HAN LI2

    BIOCELL, Vol.47, No.8, pp. 1907-1913, 2023, DOI:10.32604/biocell.2023.030191

    Abstract Background: Acer griseum Pax is an endangered species endemic to China with both ornamental and economic value. However, the lack of information on its genome size and characteristics hinders further work at the genome level. Methods: This paper applied bioinformatics methods to predict the characteristics and patterns of the A. griseum genome, providing an important basis for formulating its whole-genome sequencing scheme. This study also characterized the simple sequence repeats (SSRs) of A. griseum, laying the foundation for the development and application of genome-wide SSR markers. In this study, PE150 sequencing was performed by the BGI MGISEQ platform, and the… More >

  • Open Access

    ARTICLE

    An Improved Soft Subspace Clustering Algorithm for Brain MR Image Segmentation

    Lei Ling1, Lijun Huang2, Jie Wang2, Li Zhang2, Yue Wu2, Yizhang Jiang1, Kaijian Xia2,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2353-2379, 2023, DOI:10.32604/cmes.2023.028828

    Abstract In recent years, the soft subspace clustering algorithm has shown good results for high-dimensional data, which can assign different weights to each cluster class and use weights to measure the contribution of each dimension in various features. The enhanced soft subspace clustering algorithm combines interclass separation and intraclass tightness information, which has strong results for image segmentation, but the clustering algorithm is vulnerable to noisy data and dependence on the initialized clustering center. However, the clustering algorithm is susceptible to the influence of noisy data and reliance on initialized clustering centers and falls into a local optimum; the clustering effect… More >

  • Open Access

    ARTICLE

    Optimizing Region of Interest Selection for Effective Embedding in Video Steganography Based on Genetic Algorithms

    Nizheen A. Ali1, Ramadhan J. Mstafa2,3,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1451-1469, 2023, DOI:10.32604/csse.2023.039957

    Abstract With the widespread use of the internet, there is an increasing need to ensure the security and privacy of transmitted data. This has led to an intensified focus on the study of video steganography, which is a technique that hides data within a video cover to avoid detection. The effectiveness of any steganography method depends on its ability to embed data without altering the original video’s quality while maintaining high efficiency. This paper proposes a new method to video steganography, which involves utilizing a Genetic Algorithm (GA) for identifying the Region of Interest (ROI) in the cover video. The ROI… More >

  • Open Access

    ARTICLE

    Multi-Objective Optimization of Traffic Signal Timing at Typical Junctions Based on Genetic Algorithms

    Zeyu Zhang1, Han Zhu1, Wei Zhang1, Zhiming Cai2,*, Linkai Zhu2, Zefeng Li2

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1901-1917, 2023, DOI:10.32604/csse.2023.039395

    Abstract With the rapid development of urban road traffic and the increasing number of vehicles, how to alleviate traffic congestion is one of the hot issues that need to be urgently addressed in building smart cities. Therefore, in this paper, a nonlinear multi-objective optimization model of urban intersection signal timing based on a Genetic Algorithm was constructed. Specifically, a typical urban intersection was selected as the research object, and drivers’ acceleration habits were taken into account. What’s more, the shortest average delay time, the least average number of stops, and the maximum capacity of the intersection were regarded as the optimization… More >

  • Open Access

    ARTICLE

    Quantitative Trait Loci (QTL) Mapping and Marker Analysis of Fatty Acids in Peanut

    Xiao Han, Songnan Yang, Xueying Li, Qiulin Wu, Yongyi Xing, Jun Zhang*, Fenglou Ling*

    Phyton-International Journal of Experimental Botany, Vol.92, No.9, pp. 2577-2589, 2023, DOI:10.32604/phyton.2023.029440

    Abstract Peanut, with high oil content, has been a major oil and food crop globally. The compositions of the fatty acids are the common factors in determining the oil quality. In the present study, an F2 segregated population with 140 individuals derived from the cross of Weihua8 (a cultivar) and 12L49 (a line with high oleic acid concentration) was used to construct a genetic map and conduct QTL mapping analysis. A total of 103 polymorphic SSR primers were utilized for genotyping the RILs and finally generating the SSR loci. Within the 103 SSR loci, a genetic linkage map, covering a total… More >

  • Open Access

    ARTICLE

    An Effective Neighborhood Solution Clipping Method for Large-Scale Job Shop Scheduling Problem

    Sihan Wang, Xinyu Li, Qihao Liu*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1871-1890, 2023, DOI:10.32604/cmes.2023.028339

    Abstract The job shop scheduling problem (JSSP) is a classical combinatorial optimization problem that exists widely in diverse scenarios of manufacturing systems. It is a well-known NP-hard problem, when the number of jobs increases, the difficulty of solving the problem exponentially increases. Therefore, a major challenge is to increase the solving efficiency of current algorithms. Modifying the neighborhood structure of the solutions can effectively improve the local search ability and efficiency. In this paper, a genetic Tabu search algorithm with neighborhood clipping (GTS_NC) is proposed for solving JSSP. A neighborhood solution clipping method is developed and embedded into Tabu search to… More >

  • Open Access

    REVIEW

    Elicitation-Based Modulation of Shelf Life in Fruits: Physiological and Molecular Insights

    Ankita Kundu1, Abir Das1, Sayan Pal1, Arijit Ghosh1, Malay Kumar Adak1,*, Masayuki Fujita2, Mirza Hasanuzzaman3,*

    Phyton-International Journal of Experimental Botany, Vol.92, No.8, pp. 2283-2300, 2023, DOI:10.32604/phyton.2023.028178

    Abstract The process of ripening involves physiological and biochemical events that become a concern during postharvest storage. We have documented different approaches for the preservation and maintenance of fruit quality during the postharvest period that are biocompatible and fully safe for consumption. Chemical residues that sustain sensory characteristics, such as color, flavor, aroma, and texture, are considered. In fruit ripening, both physical and chemical elicitors are described that regulate ethylene biosynthesis or its signaling for gene expression. The key regulatory enzymes, such as ACC synthase and ACC oxidase, for ethylene biosynthesis, are important for both climacteric and non-climacteric fruits. Anti-oxidizing genes… More >

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