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  • Open Access

    ARTICLE

    Rail Surface Defect Detection Based on Improved UPerNet and Connected Component Analysis

    Yongzhi Min1,2,*, Jiafeng Li3, Yaxing Li1

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 941-962, 2023, DOI:10.32604/cmc.2023.041182

    Abstract To guarantee the safety of railway operations, the swift detection of rail surface defects becomes imperative. Traditional methods of manual inspection and conventional nondestructive testing prove inefficient, especially when scaling to extensive railway networks. Moreover, the unpredictable and intricate nature of defect edge shapes further complicates detection efforts. Addressing these challenges, this paper introduces an enhanced Unified Perceptual Parsing for Scene Understanding Network (UPerNet) tailored for rail surface defect detection. Notably, the Swin Transformer Tiny version (Swin-T) network, underpinned by the Transformer architecture, is employed for adept feature extraction. This approach capitalizes on the global information present in the image… More >

  • Open Access

    PROCEEDINGS

    Comprehensive Simulation of Hot Shape Rolling by Considering the Casting Defects

    Umut Hanoglu1,2,*, Božidar Šarler1,2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09610

    Abstract In this research, a rolling simulation system based on a novel meshless solution procedure is upgraded considering casting defects in the material model. The improved model can predict the final stage of the defects after multi-pass rolling. The casted steel billet that enters the rolling mill arrives with casting defects. Those defects may be porosity due to the shrinkage and cavity or micro-cracks near the surface due to hot tearing. In this work, porosity is considered the main defect source since it can easily be determined experimentally. The damage theory develops a damaged stiffness matrix with a scalar damage value.… More >

  • Open Access

    PROCEEDINGS

    Nanomechanics of Incipient Kink Defects Formed in Nanocellulose

    Rongzhuang Song1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09608

    Abstract Kink defects in nanocellulose are ubiquitous yet associated questions remain open regarding the unclear microstructure-mechanical property relationship. Various kink patterns without molecular-scale resolution result in bemusements of how nanocellulose forms different kinks and what the fundamental mechanisms of reversible and irreversible kinks are. In our atomic force microscopy images of mechanically treated cellulose nanofibrils, bent nanofibrils usually exhibit small curvatures while kinked nanofibrils feature sharp bends, in which kinks are conspicuous due to their promiscuous configurations. To identify the nanomechanics of incipient kink defects formed in nanocellulose, molecular dynamics simulations of cellulose nanocrystals (CNCs) under curvature-dependent bending are subsequently carried… More >

  • Open Access

    PROCEEDINGS

    Design and Deformation Behavior of Multi-phase Mechanical Metamaterials

    Huitian Wang1, Junjie You1, Sha Yin1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.010417

    Abstract Strong and tough mechanical metamaterials are highly demanded in engineering application. Nature inspired dual-phase metamaterial composites was developed and examined, by employing architectured lattice materials with different mechanical properties respectively as the constituent matrix and reinforcement phases. Then, the reinforcement phase was incorporated into the matrix phase with specific patterning. The composite metamaterials were simply fabricated using additive manufacturing. From quasistatic compression tests, the strength and toughness could be simultaneously enhanced after the addition of reinforcement phase grains. Through simulation modeling, effects of dual-phase distribution, elementary architecture, parent material and defects on mechanical properties of dual-phase mechanical metamaterials were investigated.… More >

  • Open Access

    ARTICLE

    Study on Intermittent Discharge Characteristics of Typical Solid Insulation Defects in Gas Insulated Switchgear

    Xu Yang1,2, Jing Zhang1,2, Chuanxian Luo1,2, Qinqing Huang1,2, Hui Xu1,2, Guozhi Zhang1,2,*

    Energy Engineering, Vol.120, No.9, pp. 2115-2132, 2023, DOI:10.32604/ee.2023.027198

    Abstract In response to the problem of frequent leakage and false alarm of partial discharge insulation defects in GIS, this paper conducts experimental research on intermittent discharge characteristics of common solid insulation defects in GIS. Using true GIS to build a multi-source testing platform for intermittent discharge of solid insulation defects, and using pulse current method, ultra-high frequency method, ultrasonic method, and gas characteristic component detection method to study the variation law of intermittent discharge characteristics of solid insulation defects. The results show that: the intermittent discharge state of metal fouling defects on the solid insulation surface decreases with the extension… More >

  • Open Access

    ARTICLE

    Development of Features for Early Detection of Defects and Assessment of Bridge Decks

    Ahmed Silik1,2,7, Xiaodong Wang3, Chenyue Mei3, Xiaolei Jin3, Xudong Zhou4, Wei Zhou4, Congning Chen4, Weixing Hong1,2, Jiawei Li1,2, Mingjie Mao1,2, Yuhan Liu1,2, Mohammad Noori5,6,*, Wael A. Altabey8,*

    Structural Durability & Health Monitoring, Vol.17, No.4, pp. 257-281, 2023, DOI:10.32604/sdhm.2023.023617

    Abstract Damage detection is an important area with growing interest in mechanical and structural engineering. One of the critical issues in damage detection is how to determine indices sensitive to the structural damage and insensitive to the surrounding environmental variations. Current damage identification indices commonly focus on structural dynamic characteristics such as natural frequencies, mode shapes, and frequency responses. This study aimed at developing a technique based on energy Curvature Difference, power spectrum density, correlation-based index, load distribution factor, and neutral axis shift to assess the bridge deck condition. In addition to tracking energy and frequency over time using wavelet packet… More > Graphic Abstract

    Development of Features for Early Detection of Defects and Assessment of Bridge Decks

  • Open Access

    ARTICLE

    Quantitative Parameters Analysis for Prenatally Echocardiographic Diagnosis of Atrioventricular Septal Defects

    Xiaoxue Zhou1, Tingyang Yang2, Ye Zhang1, Yanping Ruan1, Jiancheng Han1, Xiaowei Liu1, Ying Zhao1, Xiaoyan Gu1, Tingting Liu1, Hairui Wang1, Yihua He1,*

    Congenital Heart Disease, Vol.18, No.3, pp. 387-397, 2023, DOI:10.32604/chd.2023.029060

    Abstract Background: Atrioventricular septal defects (AVSDs) are screened and diagnosed usually rely on the imaging characteristics of fetal echocardiography (FE). However, diagnosis on images is heavily depended on sonographers’ experience and the quantitative data are rarely studied. Objective: This study aimed to realize the prenatal diagnosis of AVSDs by analyzing the quantitative data on FE. Methods: One hundred and thirteen cardiac quantitative data was analyzed in 370 normal and 49 AVSDs fetuses retrospectively. The top six with the highest diagnostic accuracy rate were acquired according to the area under the curve (AUC), and the diagnostic value of six variables was analyzed.… More >

  • Open Access

    ARTICLE

    Modeling & Evaluating the Performance of Convolutional Neural Networks for Classifying Steel Surface Defects

    Nadeem Jabbar Chaudhry1,*, M. Bilal Khan2, M. Javaid Iqbal1, Siddiqui Muhammad Yasir3

    Journal on Artificial Intelligence, Vol.4, No.4, pp. 245-259, 2022, DOI:10.32604/jai.2022.038875

    Abstract Recently, outstanding identification rates in image classification tasks were achieved by convolutional neural networks (CNNs). to use such skills, selective CNNs trained on a dataset of well-known images of metal surface defects captured with an RGB camera. Defects must be detected early to take timely corrective action due to production concerns. For image classification up till now, a model-based method has been utilized, which indicated the predicted reflection characteristics of surface defects in comparison to flaw-free surfaces. The problem of detecting steel surface defects has grown in importance as a result of the vast range of steel applications in end-product… More >

  • Open Access

    ARTICLE

    Automated X-ray Defect Inspection on Occluded BGA Balls Using Hybrid Algorithm

    Ki-Yeol Eom1, Byungseok Min2,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6337-6350, 2023, DOI:10.32604/cmc.2023.035336

    Abstract Automated X-ray defect inspection of occluded objects has been an essential topic in semiconductors, autonomous vehicles, and artificial intelligence devices. However, there are few solutions to segment occluded objects in the X-ray inspection efficiently. In particular, in the Ball Grid Array inspection of X-ray images, it is difficult to accurately segment the regions of occluded solder balls and detect defects inside solder balls. In this paper, we present a novel automatic inspection algorithm that segments solder balls, and detects defects fast and efficiently when solder balls are occluded. The proposed algorithm consists of two stages. In the first stage, the… More >

  • Open Access

    CASE REPORT

    Compound Heterozygous PLD1 Variants in Right-Sided Heart Malformations

    Cherith Somerville1,2, Kelsey Kalbfleisch1,2, Roozbeh Manshaei1,2, Qiliang Ding1,2, John B.A. Okello1,2,3, Rachel Silver4, David Chitayat2,4, Varsha Thakur5, Olivier Villemain5,6,7, Rebekah Jobling1,2,8,*

    Congenital Heart Disease, Vol.18, No.2, pp. 213-218, 2023, DOI:10.32604/chd.2023.023042

    Abstract We report a three-year-old male child who presented with congenital valvular defects, right ventricular malformation, and initial developmental delay. Genome sequencing showed rare deleterious biallelic missense variants in PLD1. In his parents’ second pregnancy, echocardiogram at 13 weeks gestation revealed right-sided cardiac malformations resembling the clinical presentation of the family’s first child. Targeted DNA analysis showed that the fetus carried the same biallelic PLD1 variants as their older sibling. This case helps to further delineate the clinical spectrum of PLD1-related defects and highlights the value of both genome sequencing in congenital heart disease and early fetal echocardiography to establish phenotype. More >

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