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  • Open Access

    ARTICLE

    Wind Turbine Drivetrain Expert Fault Detection System: Multivariate Empirical Mode Decomposition based Multi-sensor Fusion with Bayesian Learning Classification

    R. Uma Maheswari1,*, R. Umamaheswari2

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 479-488, 2020, DOI:10.32604/iasc.2020.013924

    Abstract To enhance the predictive condition-based maintenance (CBMS), a reliable automatic Drivetrain fault detection technique based on vibration monitoring is proposed. Accelerometer sensors are mounted on a wind turbine drivetrain at different spatial locations to measure the vibration from multiple vibration sources. In this work, multi-channel signals are fused and monocomponent modes of oscillation are reconstructed by the Multivariate Empirical Mode Decomposition (MEMD) Technique. Noise assisted methodology is adapted to palliate the mixing of modes with common frequency scales. The instantaneous amplitude envelope and instantaneous frequency are estimated with the Hilbert transform. Low order and high More >

  • Open Access

    ARTICLE

    Personalized Nutrition Recommendation for Diabetic Patients Using Optimization Techniques

    Bhavithra Janakiraman1,*, Saradha Arumugam2

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 269-280, 2020, DOI:10.31209/2019.100000150

    Abstract Personalization in recommendation system has been emerging as the most predominant area in service computing. Collaborative filtering and content based approaches are two major techniques applied for recommendation. However, to improve the accuracy and enhance user satisfaction, optimization techniques such as Ant Colony and Particle Swarm Optimization were analyzed in this paper. For theoretical analysis, this paper investigates web page recommender system. For experimentation, Diabetic patient’s health records were investigated and recommendation algorithms are applied to suggest appropriate nutrition for improving their health. Experiment result shows that Particle Swarm Optimization outperforms other traditional methods with More >

  • Open Access

    ARTICLE

    Hybrid Soft Computing Technique Based Trust Evaluation Protocol for Wireless Sensor Networks

    Supreet Kaur*, Vijay Kumar Joshi

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 217-226, 2020, DOI:10.31209/2018.100000064

    Abstract Wireless sensor networks (WSNs) are susceptible to safety threats due to cumulative dependence upon transmission, computing, and control mechanisms. Therefore, securing the end-to-end communication becomes a major area of research in WSNs. A majority of existing protocols are based upon signature and recommended-based trust evaluation techniques only. However, these techniques are vulnerable to wormhole attacks that happen due to lesser synchronization between the sensor nodes. Therefore, to handle this problem, a novel hybrid crossover-based ant colony optimization-based routing protocol is proposed. An integrated modified signature and recommendationbased trust evaluation protocol for WSNs is presented. Extensive More >

  • Open Access

    ARTICLE

    Edge Detection Based on Generative Adversarial Networks

    Xiaoyan Chen, Jiahuan Chen*, Zhongcheng Sha

    Journal of New Media, Vol.2, No.2, pp. 61-77, 2020, DOI:10.32604/jnm.2020.010062 - 21 August 2020

    Abstract Aiming at the problem that the detection effect of traditional edge detection algorithm is not good, and the problem that the existing edge detection algorithm based on convolution network cannot solve the thick edge problem from the model itself, this paper proposes a new edge detection method based on the generative adversarial network. The confrontation network consists of generator network and discriminator network, generator network is composed of U-net network and discriminator network is composed of five-layer convolution network. In this paper, we use BSDS500 training data set to train the model. Finally, several images More >

  • Open Access

    ARTICLE

    A Reinforcement Learning System for Fault Detection and Diagnosis in Mechatronic Systems

    Wanxin Zhang1,*, Jihong Zhu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1119-1130, 2020, DOI:10.32604/cmes.2020.010986 - 21 August 2020

    Abstract With the increasing demand for the automation of operations and processes in mechatronic systems, fault detection and diagnosis has become a major topic to guarantee the process performance. There exist numerous studies on the topic of applying artificial intelligence methods for fault detection and diagnosis. However, much of the focus has been given on the detection of faults. In terms of the diagnosis of faults, on one hand, assumptions are required, which restricts the diagnosis range. On the other hand, different faults with similar symptoms cannot be distinguished, especially when the model is not trained… More >

  • Open Access

    ARTICLE

    Validating the Correct Wearing of Protection Mask by Taking a Selfie: Design of a Mobile Application “CheckYourMask” to Limit the Spread of COVID-19

    Karim Hammoudi1,2,*, Adnane Cabani3, Halim Benhabiles4, Mahmoud Melkemi1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1049-1059, 2020, DOI:10.32604/cmes.2020.011663 - 21 August 2020

    Abstract In a context of a virus that is transmissive by sputtering, wearing masks appear necessary to protect the wearer and to limit the propagation of the disease. Currently, we are facing the 2019–2020 coronavirus pandemic. Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. The symptom of COVID-19 was reported first in China and very quickly spreads to the rest of the world. The COVID-19 contagiousness is known to be high by comparison with the flu. In this paper, we propose a design of a mobile application for permitting… More >

  • Open Access

    ARTICLE

    A Hybrid Deep Learning Architecture for the Classification of Superhero Fashion Products: An Application for Medical-Tech Classification

    Inzamam Mashood Nasir1, Muhammad Attique Khan1,*, Majed Alhaisoni2, Tanzila Saba3, Amjad Rehman3, Tassawar Iqbal4

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1017-1033, 2020, DOI:10.32604/cmes.2020.010943 - 21 August 2020

    Abstract Comic character detection is becoming an exciting and growing research area in the domain of machine learning. In this regard, recently, many methods are proposed to provide adequate performance. However, most of these methods utilized the custom datasets, containing a few hundred images and fewer classes, to evaluate the performances of their models without comparing it, with some standard datasets. This article takes advantage of utilizing a standard publicly dataset taken from a competition, and proposes a generic data balancing technique for imbalanced dataset to enhance and enable the in-depth training of the CNN. In More >

  • Open Access

    ARTICLE

    A Novel Analytical Technique of the Fractional Bagley-Torvik Equations for Motion of a Rigid Plate in Newtonian Fluids

    Mahmoud H. Taha1, Mohamed A. Ramadan2,*, Dumitru Baleanu3,4,5, Galal M. Moatimid1

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 969-983, 2020, DOI:10.32604/cmes.2020.010942 - 21 August 2020

    Abstract The current paper is concerned with a modified Homotopy perturbation technique. This modification allows achieving an exact solution of an initial value problem of the fractional differential equation. The approach is powerful, effective, and promising in analyzing some classes of fractional differential equations for heat conduction problems and other dynamical systems. To crystallize the new approach, some illustrated examples are introduced. More >

  • Open Access

    ARTICLE

    Numerical Simulation on Oil Spilling of Submarine Pipeline and Its Evolution on Sea Surface

    Yi Wang*, Mohan Lin

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 885-914, 2020, DOI:10.32604/cmes.2020.09810 - 21 August 2020

    Abstract Due to the interaction and corrosion of the seawater, submarine pipelines are easy to be broken to spill oil. The special environment of subsea restricts the technical development of pipeline maintenance. Therefore, the study on the oil spilling model of submarine pipeline is very important for predicting the movement and diffusion of spilled oil, so that oil spilling traces and relating strategies can be determined. This paper aims to establish an oil spilling model of a submarine pipeline, study the movement characteristics of spilled oil in seawater by numerical simulation, and determine the traces, diffusion… More >

  • Open Access

    ARTICLE

    Isogeometric Analysis and Shape Optimization of Holed Structures via the Patch Removing Technique

    Daoyuan Yu, Shouyu Cai*, Wenya Fan, Lan Zhang*

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 787-806, 2020, DOI:10.32604/cmes.2020.09936 - 21 August 2020

    Abstract In this study, a patch removing based Isogeometric analysis (PR-IGA) method is proposed to conduct the holed structural analysis with only one parametric domain, in which there are also no trimmed elements. The theoretical foundation of this novel patch removing approach is that any holed structure can be obtained by removing sub-patches (i.e., the holes) from an intact base patch. Since the parametric domains of these patches are all meshed by rectangular grids, the elements in the resulted holed structural parametric domain could all be untrimmed rectangles under certain mapping conditions. To achieve the special… More >

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