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  • Open Access

    ARTICLE

    Research on Tracking and Registration Algorithm Based on Natural Feature Point

    Tingting Yang1,*, Shuwen Jia1, Boxiong Yang1, Chenxi Kan2

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 683-692, 2021, DOI:10.32604/iasc.2021.017235

    Abstract In the augmented reality system, the position and direction of the user’s point of view and line of sight in the real scene is acquired in real-time. The position and direction information will determine the exact position of the virtual object of the real scene. At the same time, various coordinate systems are established according to the user’s line of sight. So registration tracking technology is very important. The paper proposes an accurate, stable, and effective augmented reality registration algorithm. The method adopts the method of ORB (oriented FAST and rotated BRIEF) features matching combined with RANSAC (random sample consensus)… More >

  • Open Access

    ARTICLE

    Identification of Abnormal Patterns in AR (1) Process Using CS-SVM

    Hongshuo Zhang1, Bo Zhu1,*, Kaimin Pang1, Chunmei Chen1, Yuwei Wan2

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 797-810, 2021, DOI:10.32604/iasc.2021.017232

    Abstract Using machine learning method to recognize abnormal patterns covers the shortage of traditional control charts for autocorrelation processes, which violate the applicable conditions of the control chart, i.e., the independent identically distributed (IID) assumption. In this study, we propose a recognition model based on support vector machine (SVM) for the AR (1) type of autocorrelation process. For achieving a higher recognition performance, the cuckoo search algorithm (CS) is used to optimize the two hyper-parameters of SVM, namely the penalty parameter c and the radial basis kernel parameter g. By using Monte Carlo simulation methods, the data sets containing samples of… More >

  • Open Access

    ARTICLE

    Case Optimization Using Improved Genetic Algorithm for Industrial Fuzzing Test

    Ming Wan1, Shiyan Zhang1, Yan Song2, Jiangyuan Yao3,*, Hao Luo1, Xingcan Cao4

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 857-871, 2021, DOI:10.32604/iasc.2021.017214

    Abstract Due to the lack of security consideration in the original design of industrial communication protocols, industrial fuzzing test which can successfully exploit various potential security vulnerabilities has become one new research hotspot. However, one critical issue is how to improve its testing efficiency. From this point of view, this paper proposes a novel fuzzing test case optimization approach based on improved genetic algorithm for industrial communication protocols. Moreover, a new individual selection strategy is designed as the selection operator in this genetic algorithm, which can be actively engaged in the fuzzing test case optimization process. In this individual selection strategy,… More >

  • Open Access

    ARTICLE

    A New Estimation of Nonlinear Contact Forces of Railway Vehicle

    Khakoo Mal1,2, Imtiaz Hussain Kalwar3, Khurram Shaikh2, Tayab Din Memon2,4, Bhawani Shankar Chowdhry1, Kashif Nisar5,*, Manoj Gupta6

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 823-841, 2021, DOI:10.32604/iasc.2021.016990

    Abstract

    The core part of any study of rolling stock behavior is the wheel-track interaction patch because the forces produced at the wheel-track interface govern the dynamic behavior of the whole railway vehicle. It is significant to know the nature of the contact force to design more effective vehicle dynamics control systems and condition monitoring systems. However, it is hard to find the status of this adhesion force due to its complexity, highly non-linear nature, and also affected with an unpredictable operation environment. The purpose of this paper is to develop a model-based estimation technique using the Extended Kalman Filter (EKF)… More >

  • Open Access

    ARTICLE

    Improving Network Longevity in Wireless Sensor Networks Using an Evolutionary Optimization Approach

    V. Nivedhitha1,*, A. Gopi Saminathan2, P. Thirumurugan3

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 603-616, 2021, DOI:10.32604/iasc.2021.016780

    Abstract Several protocols strive to improve network longevity but fail to ameliorate the uneven overhead imparted upon the sensor nodes that lead to temporal deaths. The proposed work uses a metaheuristic approach that promotes load balancing and energy-efficient data transmission using the fruit fly optimization algorithm (FFOA). The approach combines the LEACH protocol with differential evolution (DE) to select an optimum cluster head in every cluster. The algorithm is designed to provide energy-efficient data transmissions based on the smell and vision foraging behavior of fruit flies. The approach considers the compactness of nodes, energy capacity, and the distance of sensor nodes… More >

  • Open Access

    ARTICLE

    Effect of Load on Transient Performance of Unearthed and Compensated Distribution Networks

    Nehmdoh A. Sabiha*, Hend I. Alkhammash

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 769-784, 2021, DOI:10.32604/iasc.2021.016752

    Abstract The maximum temperature that cable insulation can withstand determines the maximum load that the cable conductor can carry, which is called cable ampacity. However, a temperature far from this value under normal load conditions affects the transients due to earth faults in the distribution network. Accordingly, error estimation in the fault location occurs, and the smart grids do not accept such errors. Considering heterogenous unearthed and compensated distribution networks, the temperature rise in different underground cables is estimated under different load conditions. These loads are full load, three quarters (3/4) load, one half (1/2) load, and one quarter (1/4) load.… More >

  • Open Access

    ARTICLE

    Computational Technique for Effectiveness of Treatments Used in Curing SARS-CoV-2

    Wael Alosaimi1, Rajeev Kumar2,*, Abdullah Alharbi1, Hashem Alyami3, Alka Agrawal4, Gaurav Kaithwas5, Sanjay Singh6, Raees Ahmad Khan4

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 617-628, 2021, DOI:10.32604/iasc.2021.016703

    Abstract COVID-19 pandemic has unleashed an unprecedented humanitarian crisis in the world at present. With each passing day, the number of patients afflicted with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is rising at an alarming pace, so much so that some countries are now combating the second wave of the contagion. As the death ratio due to the Virus increases, the medical fraternity and pharmacologists are working relentlessly to identify and prescribe a standardized and effective course of treatment for treating COVID-19 patients. However, medical specialists are confused about opting for the most efficacious course of treatment because the patients… More >

  • Open Access

    ARTICLE

    Data Mining of Scientometrics for Classifying Science Journals

    Muhammad Shaheen1,*, Ali Ahsan2, Saeed Iqbal3

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 873-885, 2021, DOI:10.32604/iasc.2021.016622

    Abstract While there are several Scientometrics that can be used to assess the quality of the scientific work published in journals and conferences, yet; their validity and suitability is a great concern for stakeholders from both academia and industry. Different organizations have a different set of criteria for assessing the journals publishing scientific content. This is mostly based on the information generated from Scientometrics. A unified journal ranking system is therefore required that is acceptable to all concerned. This paper, collects data concerning Scientometrics for unified assessment of journals and proposes a mechanism of assessment using data mining methods. In order… More >

  • Open Access

    ARTICLE

    Improved Model of Eye Disease Recognition Based on VGG Model

    Ye Mu1,2,3,4, Yuheng Sun1, Tianli Hu1,2,3,4, He Gong1,2,3,4, Shijun Li1,2,3,4,*, Thobela Louis Tyasi5

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 729-737, 2021, DOI:10.32604/iasc.2021.016569

    Abstract The rapid development of computer vision technology and digital images has increased the potential for using image recognition for eye disease diagnosis. Many early screening and diagnosis methods for ocular diseases based on retinal images of the fundus have been proposed recently, but their accuracy is low. Therefore, it is important to develop and evaluate an improved VGG model for the recognition and classification of retinal fundus images. In response to these challenges, to solve the problem of accuracy and reliability of clinical algorithms in medical imaging this paper proposes an improved model for early recognition of ophthalmopathy in retinal… More >

  • Open Access

    ARTICLE

    Non-contact Real-time Monitoring of Driver’s Physiological Parameters under Ambient Light Condition

    Zhengzheng Li1, Jiancheng Zou2,*, Peizhou Yan1, Don Hong3

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 811-822, 2021, DOI:10.32604/iasc.2021.016516

    Abstract Real-time and effective monitoring of a driver’s physiological parameters and psychological states can provide early warnings and help avoid traffic accidents. In this paper, we propose a non-contact real-time monitoring algorithm for physiological parameters of drivers under ambient light conditions. First, video sequences of the driver’s head are obtained by an ordinary USB camera and the AdaBoost algorithm is used to locate the driver’s facial region. Second, a face expression recognition algorithm based on an improved convolutional neural network (CNN) is proposed to recognize the driver’s facial expression. The forehead region is divided into three RGB channels as the region… More >

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