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  • Open Access

    ARTICLE

    Power Data Preprocessing Method of Mountain Wind Farm Based on POT-DBSCAN

    Anfeng Zhu, Zhao Xiao, Qiancheng Zhao*

    Energy Engineering, Vol.118, No.3, pp. 549-563, 2021, DOI:10.32604/EE.2021.014177

    Abstract Due to the frequent changes of wind speed and wind direction, the accuracy of wind turbine (WT) power prediction using traditional data preprocessing method is low. This paper proposes a data preprocessing method which combines POT with DBSCAN (POT-DBSCAN) to improve the prediction efficiency of wind power prediction model. Firstly, according to the data of WT in the normal operation condition, the power prediction model of WT is established based on the Particle Swarm Optimization (PSO) Arithmetic which is combined with the BP Neural Network (PSO-BP). Secondly, the wind-power data obtained from the supervisory control and data acquisition (SCADA) system… More >

  • Open Access

    ARTICLE

    Diabetes Type 2: Poincaré Data Preprocessing for Quantum Machine Learning

    Daniel Sierra-Sosa1,*, Juan D. Arcila-Moreno2, Begonya Garcia-Zapirain3, Adel Elmaghraby1

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1849-1861, 2021, DOI:10.32604/cmc.2021.013196

    Abstract Quantum Machine Learning (QML) techniques have been recently attracting massive interest. However reported applications usually employ synthetic or well-known datasets. One of these techniques based on using a hybrid approach combining quantum and classic devices is the Variational Quantum Classifier (VQC), which development seems promising. Albeit being largely studied, VQC implementations for “real-world” datasets are still challenging on Noisy Intermediate Scale Quantum devices (NISQ). In this paper we propose a preprocessing pipeline based on Stokes parameters for data mapping. This pipeline enhances the prediction rates when applying VQC techniques, improving the feasibility of solving classification problems using NISQ devices. By… More >

  • Open Access

    ARTICLE

    Recognition of Offline Handwritten Arabic Words Using a Few Structural Features

    Abderrahmane Saidi*, Abdelmouneim Moulay Lakhdar, Mohammed Beladgham

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2875-2889, 2021, DOI:10.32604/cmc.2021.013744

    Abstract Handwriting recognition is one of the most significant problems in pattern recognition, many studies have been proposed to improve this recognition of handwritten text for different languages. Yet, Fewer studies have been done for the Arabic language and the processing of its texts remains a particularly distinctive problem due to the variability of writing styles and the nature of Arabic scripts compared to other scripts. The present paper suggests a feature extraction technique for offline Arabic handwriting recognition. A handwriting recognition system for Arabic words using a few important structural features and based on a Radial Basis Function (RBF) neural… More >

  • Open Access

    ARTICLE

    Scalable Electromagnetic Simulation Environment

    Raju R. Namburu1, Eric R. Mark, Jerry A. Clarke

    CMES-Computer Modeling in Engineering & Sciences, Vol.5, No.5, pp. 443-454, 2004, DOI:10.3970/cmes.2004.005.443

    Abstract Computational electromagnetic (CEM) simulations of full-range military vehicles play a critical role in enhancing the survivability and target recognition of combat systems. Modeling of full-range military systems subjected to high frequencies may involve generating large-scale meshes, solving equations, visualization, and analysis of results in the range of billions of unknowns or grid points. Hence, the overall objective of this research is to develop and demonstrate a scalable CEM software environment to address accurate prediction of radar cross sections (RCS) for full- range armored vehicles with realistic material treatments and complex geometric configurations. A software environment consisting of scalable preprocessing, postprocessing,… More >

  • Open Access

    RETRACTION

    RETRACTED: Implementation System of Human Eye Tracking Algorithm Based on FPGA

    Zhong Liu1,2, Xin’an Wang1, Chengjun Sun1, Ken Lu3

    CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 653-664, 2019, DOI:10.32604/cmc.2019.04597

    Abstract With the high-speed development of transportation industry, highway traffic safety has become a considerable problem. Meanwhile, with the development of embedded system and hardware chip, in recent years, human eye detection eye tracking and positioning technology have been more and more widely used in man-machine interaction, security access control and visual detection.
    In this paper, the high parallelism of FPGA was utilized to realize an elliptical approximate real-time human eye tracking system, which was achieved by the series register structure and random sample consensus (RANSAC), thus improving the speed of image processing without using external memory. Because eye images acquired by… More >

  • Open Access

    ARTICLE

    Adaptive Median Filtering Algorithm Based on Divide and Conquer and Its Application in CAPTCHA Recognition

    Wentao Ma1, Jiaohua Qin1,*, Xuyu Xiang1, Yun Tan1, Yuanjing Luo1, Neal N. Xiong2

    CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 665-677, 2019, DOI:10.32604/cmc.2019.05683

    Abstract As the first barrier to protect cyberspace, the CAPTCHA has made significant contributions to maintaining Internet security and preventing malicious attacks. By researching the CAPTCHA, we can find its vulnerability and improve the security of CAPTCHA. Recently, many studies have shown that improving the image preprocessing effect of the CAPTCHA, which can achieve a better recognition rate by the state-of-the-art machine learning algorithms. There are many kinds of noise and distortion in the CAPTCHA images of this experiment. We propose an adaptive median filtering algorithm based on divide and conquer in this paper. Firstly, the filtering window data quickly sorted… More >

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