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  • Open Access


    Design of an Observer-Based Controller for T-S Fuzzy Time-Delay Systems under Imperfect Premise Matching

    Zejian Zhang1, Dawei Wang2,*, Peng Li1, Xiao-Zhi Gao3

    Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 905-915, 2020, DOI:10.32604/iasc.2020.010123

    Abstract In this paper, the stabilization problem of an observer-based T-S fuzzy time-delay system under imperfect premise matching is studied, in which the T-S fuzzy observer model with time-delay and the fuzzy controller do not share the same membership functions. The objective is to design a state observer and unmatching fuzzy controller such that the closed-loop system with time-delay is asymptotically stable. A sufficient condition for the stabilization via observerbased state feedback under imperfect premise matching is presented, and an observer-based state feedback controller under imperfect premise is also constructed. The proposed control scheme is well More >

  • Open Access


    Multi-Scale Boxes Loss for Object Detection in Smart Energy

    Zhiyong Dai1,*, Jianjun Yi1, Yajun Zhang1, Liang He2

    Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 887-903, 2020, DOI:10.32604/iasc.2020.010122

    Abstract The rapid development of Internet of Things (IoT) technologies has boosted smart energy networks in recent years. However, power line surveillance systems still suffer from the low accuracy and efficiency of the power line area recognition and risk objects detection. This paper proposes a new customized loss function to tackle the disequilibrium of the size of objects on multi-scale feature maps in the deep learning-based detectors. To validate the new concept and improve the efficiency, we also presented a new object detection model. Experimental results are provided to exhibit the advantage of our proposed method More >

  • Open Access


    Causality Learning from Time Series Data for the Industrial Finance Analysis via the Multi-Dimensional Point Process

    Liangliang Shi1,2, Peili Lu3, Junchi Yan4,5,*

    Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 873-885, 2020, DOI:10.32604/iasc.2020.010121

    Abstract Causality learning has been an important tool for decision making, especially for financial analytics. Given the time series data, most existing works construct the causality network with the traditional regression models and estimate the causality by pairs. To fulfil a holistic one-shot inference procedure over the whole network, we propose a new causal inference method for the multidimensional time series data, specifically related to some case studies for the industrial finance analytics. Specifically, the time series are first converted to the event sequences with timestamps by fluctuation the detection, and then a multidimensional point process More >

  • Open Access


    A Hybrid Approach for the Lung(s) Nodule Detection Using the Deformable Model and Distance Transform

    Ayyaz Hussain1, Mohammed Alawairdhi2, Fayez Alazemi3, Sajid Ali Khan4, Muhammad Ramzan2,*

    Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 857-871, 2020, DOI:10.32604/iasc.2020.010120

    Abstract The Computer Aided Diagnosis (CAD) systems are gaining more recognition and being used as an aid by clinicians for detection and interpretation of diseases every passing day due to their increasing accuracy and reliability. The lung(s) nodule detection is a very crucial and difficult step for CAD systems. In this paper, a hybrid approach for the lung nodule detection using a deformable model and distance transform has been proposed. The proposed method has the ability to detect all major kinds of nodules such as the juxta-plueral, isolated, and the juxta-vescular, along with the non-solid nodules More >

  • Open Access


    An Anonymous Authentication Scheme with Controllable Linkability for Vehicle Sensor Networks

    Yousheng Zhou1,2, Lvjun Chen1, Xiaofeng Zhao1,*, Zheng Yang3

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1101-1118, 2020, DOI:10.32604/cmes.2021.013289

    Abstract Vehicle sensor networks (VSN) play an increasingly important part in smart city, due to the interconnectivity of the infrastructure. However similar to other wireless communications, vehicle sensor networks are susceptible to a broad range of attacks. In addition to ensuring security for both data-at-rest and data-in-transit, it is essential to preserve the privacy of data and users in vehicle sensor networks. Many existing authentication schemes for vehicle sensor networks are generally not designed to also preserve the privacy between the user and service provider (e.g., mining user data to provide personalized services without infringing on More >

  • Open Access


    ALCencryption: A Secure and Efficient Algorithm for Medical Image Encryption

    Jiao Ge1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1083-1100, 2020, DOI:10.32604/cmes.2021.013039

    Abstract With the rapid development of medical informatization and the popularization of digital imaging equipment, DICOM images contain the personal privacy of patients, and there are security risks in the process of storage and transmission, so it needs to be encrypted. In order to solve the security problem of medical images on mobile devices, a safe and efficient medical image encryption algorithm called ALCencryption is designed. The algorithm first analyzes the medical image and distinguishes the color image from the gray image. For gray images, the improved Arnold map is used to scramble them according to More >

  • Open Access


    A Fast Product of Conditional Reduction Method for System Failure Probability Sensitivity Evaluation

    Jie Yang1,2, Changping Chen1,2,*, Ao Ma1

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1159-1171, 2020, DOI:10.32604/cmes.2020.09640

    Abstract System reliability sensitivity analysis becomes difficult due to involving the issues of the correlation between failure modes whether using analytic method or numerical simulation methods. A fast conditional reduction method based on conditional probability theory is proposed to solve the sensitivity analysis based on the approximate analytic method. The relevant concepts are introduced to characterize the correlation between failure modes by the reliability index and correlation coefficient, and conditional normal fractile the for the multi-dimensional conditional failure analysis is proposed based on the two-dimensional normal distribution function. Thus the calculation of system failure probability can… More >

  • Open Access


    Real-Time Analysis of COVID-19 Pandemic on Most Populated Countries Worldwide

    Meenu Gupta1, Rachna Jain2, Akash Gupta2,*, Kunal Jain2

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 943-965, 2020, DOI:10.32604/cmes.2020.012467

    Abstract The spread of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has already taken on pandemic extents, inuencing even more than 200 nations in a couple of months. Although, regulation measures in China have decreased new cases by over 98%, this decrease is not the situation everywhere, and most of the countries still have been affected by it. The objective of this research work is to make a comparative analysis of the top 5 most populated countries namely United States, India, China, Pakistan and Indonesia, from 1st January 2020 to 31st July 2020. This research… More >

  • Open Access


    Predictive Models for Cumulative Confirmed COVID-19 Cases by Day in Southeast Asia

    Yupaporn Areepong1, Rapin Sunthornwat2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 927-942, 2020, DOI:10.32604/cmes.2020.012323

    Abstract Coronavirus disease 2019 outbreak has spread as a pandemic since the end of year 2019. This situation has been causing a lot of problems of human beings such as economic problems, health problems. The forecasting of the number of infectious people is required by the authorities of all countries including Southeast Asian countries to make a decision and control the outbreak. This research is to investigate the suitable forecasting model for the number of infectious people in Southeast Asian countries. A comparison of forecasting models between logistic growth curve which is symmetric and Gompertz growth More >

  • Open Access


    Investigation of Coronavirus Deposition in Realistic Human Nasal Cavity and Impact of Social Distancing to Contain COVID-19: A Computational Fluid Dynamic Approach

    Mohammad Zuber1, John Valerian Corda1, Milad Ahmadi2, B. Satish Shenoy1, Irfan Anjum Badruddin3,*, Ali E. Anqi3, Kamarul Arifin Ahmad4, S. M. Abdul Khader5, Leslie Lewis6, Mohammad Anas Khan7, Sarfaraz Kamangar3

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1185-1199, 2020, DOI:10.32604/cmes.2020.015015

    Abstract The novel coronavirus responsible for COVID-19 has spread to several countries within a considerably short period. The virus gets deposited in the human nasal cavity and moves to the lungs that might be fatal. As per safety guidelines by the World Health Organization (WHO), social distancing has emerged as one of the major factors to avoid the spread of infection. However, different guidelines are being followed across the countries with regards to what should be the safe distance. Thus, the current work is an attempt to understand the virus deposition pattern in the realistic human… More >

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