Home / Journals / CMES / Vol.133, No.2, 2022
Table of Content
  • Open Access

    REVIEW

    Advances in Hyperspectral Image Classification Based on Convolutional Neural Networks: A Review

    Somenath Bera1, Vimal K. Shrivastava2, Suresh Chandra Satapathy3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 219-250, 2022, DOI:10.32604/cmes.2022.020601
    Abstract Hyperspectral image (HSI) classification has been one of the most important tasks in the remote sensing community over the last few decades. Due to the presence of highly correlated bands and limited training samples in HSI, discriminative feature extraction was challenging for traditional machine learning methods. Recently, deep learning based methods have been recognized as powerful feature extraction tool and have drawn a significant amount of attention in HSI classification. Among various deep learning models, convolutional neural networks (CNNs) have shown huge success and offered great potential to yield high performance in HSI classification. Motivated by this successful performance, this… More >

  • Open Access

    ARTICLE

    A CFD-DEM-Wear Coupling Method for Stone Chip Resistance of Automotive Coatings with a Rigid Connection Particle Method for Non-Spherical Particles

    Jiacheng Qian1, Chenqi Zou1, Mengyan Zang1,*, Shunhua Chen2,3,*, Makoto Tsubokura4
    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 251-280, 2022, DOI:10.32604/cmes.2022.020738
    Abstract The stone chip resistance performance of automotive coatings has attracted increasing attention in academic and industrial communities. Even though traditional gravelometer tests can be used to evaluate stone chip resistance of automotive coatings, such experiment-based methods suffer from poor repeatability and high cost. The main purpose of this work is to develop a CFD-DEM-wear coupling method to accurately and efficiently simulate stone chip behavior of automotive coatings in a gravelometer test. To achieve this end, an approach coupling an unresolved computational fluid dynamics (CFD) method and a discrete element method (DEM) are employed to account for interactions between fluids and… More >

  • Open Access

    ARTICLE

    A Multi-Scale Grasp Detector Based on Fully Matching Model

    Xinheng Yuan, Hao Yu, Houlin Zhang, Li Zheng, Erbao Dong*, Heng’an Wu*
    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 281-301, 2022, DOI:10.32604/cmes.2022.021383
    Abstract Robotic grasping is an essential problem at both the household and industrial levels, and unstructured objects have always been difficult for grippers. Parallel-plate grippers and algorithms, focusing on partial information of objects, are one of the widely used approaches. However, most works predict single-size grasp rectangles for fixed cameras and gripper sizes. In this paper, a multi-scale grasp detector is proposed to predict grasp rectangles with different sizes on RGB-D or RGB images in real-time for hand-eye cameras and various parallel-plate grippers. The detector extracts feature maps of multiple scales and conducts predictions on each scale independently. To guarantee independence… More >

  • Open Access

    ARTICLE

    Numerical Study for Magnetohydrodynamic (MHD) Unsteady Maxwell Nanofluid Flow Impinging on Heated Stretching Sheet

    Muhammad Shoaib Arif1,2,*, Muhammad Jhangir2, Yasir Nawaz2, Imran Abbas2, Kamaleldin Abodayeh1, Asad Ejaz2
    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 303-325, 2022, DOI:10.32604/cmes.2022.020979
    Abstract The numerous applications of Maxwell Nanofluid Stagnation Point Flow, such as those in production industries, the processing of polymers, compression, power generation, lubrication systems, food manufacturing and air conditioning, among other applications, require further research into the effects of various parameters on flow phenomena. In this paper, a study has been carried out for the heat and mass transfer of Maxwell nanofluid flow over the heated stretching sheet. A mathematical model with constitutive expressions is constructed in partial differential equations (PDEs) through obligatory basic conservation laws. A series of transformations are then used to take the system into an ordinary… More >

  • Open Access

    ARTICLE

    An Intelligent Cluster Verification Model Using WSN to Avoid Close Proximity and Control Outbreak of Pandemic in a Massive Crowd

    Naeem Ahmed Nawaz1, Norah Saleh Alghamdi2,*, Hanen Karamti2, Mohammad Ayoub Khan3
    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 327-350, 2022, DOI:10.32604/cmes.2022.020791
    Abstract Assemblage at public places for religious or sports events has become an integral part of our lives. These gatherings pose a challenge at places where fast crowd verification with social distancing (SD) is required, especially during a pandemic. Presently, verification of crowds is carried out in the form of a queue that increases waiting time resulting in congestion, stampede, and the spread of diseases. This article proposes a cluster verification model (CVM) using a wireless sensor network (WSN), single cluster approach (SCA), and split cluster approach (SpCA) to solve the aforementioned problem for pandemic cases. We show that SD, cluster… More >

  • Open Access

    ARTICLE

    Hysteresis of Dam Slope Safety Factor under Water Level Fluctuations Based on the LEM Coupled with FEM Method

    Guodong Liu1,2,*, Zhijun Zhou1, Shiqiang Xu1, Wenjing Mi2
    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 351-375, 2022, DOI:10.32604/cmes.2022.020335
    (This article belongs to this Special Issue: Computer Modelling in Disaster Prevention and Mitigation for Engineering Structures)
    Abstract Water level variations have caused numerous dam slope collapse disasters around the world, illustrating the large influence of water level fluctuations on dam slopes. The required indoor tests were conducted and a numerical model of an actual earth-filled dam was constructed to investigate the influences of the water level fluctuation rate and the hysteresis of the soil–water characteristic curve (SWCC) on the stability of the upstream dam slope. The results revealed that the free surface in the dam body for the desorption SWCC during water level fluctuations was higher than that for the adsorption SWCC, which would be more evident… More >

  • Open Access

    ARTICLE

    Cotangent Similarity Measure of Consistent Neutrosophic Sets and Application to Multiple Attribute Decision-Making Problems in Neutrosophic Multi-Valued Setting

    Angyan Tu1,2, Jiancheng Chen3, Bing Wang1,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 377-387, 2022, DOI:10.32604/cmes.2022.021299
    (This article belongs to this Special Issue: Extension, Modeling and Applications of Fuzzy Set Theory in Engineering and Science)
    Abstract A neutrosophic multi-valued set (NMVS) is a crucial representation for true, false, and indeterminate multi-valued information. Then, a consistent single-valued neutrosophic set (CSVNS) can effectively reflect the mean and consistency degree of true, false, and indeterminate multi-valued sequences and solve the operational issues between different multi-valued sequence lengths in NMVS. However, there has been no research on consistent single-valued neutrosophic similarity measures in the existing literature. This paper proposes cotangent similarity measures and weighted cotangent similarity measures between CSVNSs based on cotangent function in the neutrosophic multi-valued setting. The cosine similarity measures show the cosine of the angle between two… More >

  • Open Access

    ARTICLE

    A Hybrid Local/Nonlocal Continuum Mechanics Modeling of Damage and Fracture in Concrete Structure at High Temperatures

    Runze Song1, Fei Han1,*, Yong Mei2,*, Yunhou Sun2, Ao Zhang2
    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 389-412, 2022, DOI:10.32604/cmes.2022.021127
    (This article belongs to this Special Issue: Peridynamics and its Current Progress)
    Abstract This paper proposes a hybrid peridynamic and classical continuum mechanical model for the high-temperature damage and fracture analysis of concrete structures. In this model, we introduce the thermal expansion into peridynamics and then couple it with the thermoelasticity based on the Morphing method. In addition, a thermomechanical constitutive model of peridynamic bond is presented inspired by the classic Mazars model for the quasi-brittle damage evolution of concrete structures under high-temperature conditions. The validity and effectiveness of the proposed model are verified through two-dimensional numerical examples, in which the influence of temperature on the damage behavior of concrete structures is investigated.… More >

  • Open Access

    ARTICLE

    Efficient UAV-Based MEC Using GPU-Based PSO and Voronoi Diagrams

    Mohamed H. Mousa1,2,*, Mohamed K. Hussein2
    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 413-434, 2022, DOI:10.32604/cmes.2022.020639
    (This article belongs to this Special Issue: Artificial Intelligence for Mobile Edge Computing in IoT)
    Abstract Mobile-Edge Computing (MEC) displaces cloud services as closely as possible to the end user. This enables the edge servers to execute the offloaded tasks that are requested by the users, which in turn decreases the energy consumption and the turnaround time delay. However, as a result of a hostile environment or in catastrophic zones with no network, it could be difficult to deploy such edge servers. Unmanned Aerial Vehicles (UAVs) can be employed in such scenarios. The edge servers mounted on these UAVs assist with task offloading. For the majority of IoT applications, the execution times of tasks are often… More >

  • Open Access

    ARTICLE

    Fault Detection and Identification Using Deep Learning Algorithms in Induction Motors

    Majid Hussain1,2,*, Tayab Din Memon3,4, Imtiaz Hussain5, Zubair Ahmed Memon3, Dileep Kumar2
    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 435-470, 2022, DOI:10.32604/cmes.2022.020583
    (This article belongs to this Special Issue: Failure Detection Algorithms, Methods and Models for Industrial Environments)
    Abstract Owing to the 4.0 industrial revolution condition monitoring maintenance is widely accepted as a useful approach to avoiding plant disturbances and shutdown. Recently, Motor Current Signature Analysis (MCSA) is widely reported as a condition monitoring technique in the detection and identification of individual and multiple Induction Motor (IM) faults. However, checking the fault detection and classification with deep learning models and its comparison among themselves or conventional approaches is rarely reported in the literature. Therefore, in this work, we present the detection and identification of induction motor faults with MCSA and three Deep Learning (DL) models namely MLP, LSTM, and… More >

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