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  • Open Access


    Up-Sampled Cross-Correlation Based Object Tracking & Vibration Measurement in Agriculture Tractor System

    R. Ganesan1,*, G. Sankaranarayanan1, M. Pradeep Kumar2, V. K. Bupesh Raja1

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 667-681, 2023, DOI:10.32604/iasc.2023.031932

    Abstract This research introduces a challenge in integrating and cleaning the data, which is a crucial task in object matching. While the object is detected and then measured, the vibration at different light intensities may influence the durability and reliability of mechanical systems or structures and cause problems such as damage, abnormal stopping, and disaster. Recent research failed to improve the accuracy rate and the computation time in tracking an object and in the vibration measurement. To solve all these problems, this proposed research simplifies the scaling factor determination by assigning a known real-world dimension to a predetermined portion of the… More >

  • Open Access


    Research on Leak Location Method of Water Supply Pipeline Based on MVMD

    Qiansheng Fang, Haojie Wang, Chenlei Xie*, Jie Chen

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1237-1250, 2023, DOI:10.32604/cmes.2022.021131

    Abstract At present, the leakage rate of the water distribution network in China is still high, and the waste of water resources caused by water distribution network leakage is quite serious every year. Therefore, the location of pipeline leakage is of great significance for saving water resources and reducing economic losses. Acoustic emission technology is the most widely used pipeline leak location technology. The traditional non-stationary random signal de-noising method mainly relies on the estimation of noise parameters, ignoring periodic noise and components unrelated to pipeline leakage. Aiming at the above problems, this paper proposes a leak location method for water… More >

  • Open Access


    A Novel GLS Consensus Algorithm for Alliance Chain in Edge Computing Environment

    Huijuan Wang1, *, Jiang Yong1, Qingwei Liu2, Alan Yang3

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 963-976, 2020, DOI:10.32604/cmc.2020.09803

    Abstract Edge computing devices are widely deployed. An important issue that arises is in that these devices suffer from security attacks. To deal with it, we turn to the blockchain technologies. The note in the alliance chain need rules to limit write permissions. Alliance chain can provide security management functions, using these functions to meet the management between the members, certification, authorization, monitoring and auditing. This article mainly analyzes some requirements realization which applies to the alliance chain, and introduces a new consensus algorithm, generalized Legendre sequence (GLS) consensus algorithm, for alliance chain. GLS algorithms inherit the recognition and verification efficiency… More >

  • Open Access


    A Fast Two-Stage Black-Box Deep Learning Network Attacking Method Based on Cross-Correlation

    Deyin Li1, 2, Mingzhi Cheng3, Yu Yang1, 2, *, Min Lei1, 2, Linfeng Shen4

    CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 623-635, 2020, DOI:10.32604/cmc.2020.09800

    Abstract Deep learning networks are widely used in various systems that require classification. However, deep learning networks are vulnerable to adversarial attacks. The study on adversarial attacks plays an important role in defense. Black-box attacks require less knowledge about target models than white-box attacks do, which means black-box attacks are easier to launch and more valuable. However, the state-of-arts black-box attacks still suffer in low success rates and large visual distances between generative adversarial images and original images. This paper proposes a kind of fast black-box attack based on the cross-correlation (FBACC) method. The attack is carried out in two stages.… More >

  • Open Access


    A Correlation Coefficient Approach for Evaluation of Stiffness Degradation of Beams Under Moving Load

    Thanh Q. Nguyen1,2, Thao T. D. Nguyen3, H. Nguyen-Xuan4,5,*, Nhi K. Ngo1,2

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 27-53, 2019, DOI:10.32604/cmc.2019.07756

    Abstract This paper presents a new approach using correlation and cross-correlation coefficients to evaluate the stiffness degradation of beams under moving load. The theoretical study of identifying defects by vibration methods showed that the traditional methods derived from the vibration measurement data have not met the needs of the actual issues. We show that the correlation coefficients allow us to evaluate the degree and the effectiveness of the defects on beams. At the same time, the cross-correlation model is the basis for determining the relative position of defects. The results of this study are experimentally conducted to confirm the relationship between… More >

  • Open Access


    Satellite Cloud-Derived Wind Inversion Algorithm Using GPU

    Lili He1,2, Hongtao Bai1,2, Dantong Ouyang1,2, Changshuai Wang1,2, Chong Wang1,2,3, Yu Jiang1,2,*

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 599-613, 2019, DOI:10.32604/cmc.2019.05928

    Abstract Cloud-derived wind refers to the wind field data product reversely derived through satellite remote sensing cloud images. Satellite cloud-derived wind inversion has the characteristics of large scale, computationally intensive and long time. The most widely used cloud-derived serial--tracer cloud tracking method is the maximum cross-correlation coefficient (MCC) method. In order to overcome the efficiency bottleneck of the cloud-derived serial MCC algorithm, we proposed a parallel cloud-derived wind inversion algorithm based on GPU framework in this paper, according to the characteristics of independence between each wind vector calculation. In this algorithm, each iteration is considered as a thread of GPU cores,… More >

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