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Zahra Ameli, Shabnam Jafarpoor Nesheli and Eric N. Landis
The application of deep learning (DL) algorithms has become of great interest in recent years due to their superior performance in structural damage identification, including the detection of corrosion. There has been growing interest in the application ...
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Imran Shafi, Muhammad Fawad Mazhar, Anum Fatima, Roberto Marcelo Alvarez, Yini Miró, Julio César Martínez Espinosa and Imran Ashraf
Monitoring tool conditions and sub-assemblies before final integration is essential to reducing processing failures and improving production quality for manufacturing setups. This research study proposes a real-time deep learning-based framework for iden...
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Guang Yang, Kainan Guan, Li Zou, Yibo Sun and Xinhua Yang
The cold metal transfer (CMT) process is widely used in thin plate welding because of its characteristics of low heat input and stable arc. In actual production, a larger weld gap, misalignment, or other problems due to assembly error lead to serious wel...
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Lei Yang, Dexu Mu, Zhen Xu and Kaiyu Huang
Aiming at the problems of uneven light reflectivity on the spherical surface and high similarity between the stems/calyxes and scars that exist in the detection of surface defects in apples, this paper proposed a defect detection method based on image se...
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Thanapong Champahom, Panuwat Wisutwattanasak, Chamroeun Se, Chinnakrit Banyong, Sajjakaj Jomnonkwao and Vatanavongs Ratanavaraha
Among several approaches to analyzing crash research, the use of machine learning and econometric analysis has found potential in the analysis. This study aims to empirically examine factors influencing the single-vehicle crash for personal cars and truc...
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Yanjie Zhao, Huicheng Lai and Guxue Gao
The development of single-modality target tracking based on visible light has been limited in recent years because visual light images are highly susceptible to environmental and lighting influences. Thermal infrared images can well compensate for this d...
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Michael Lo, Suria Devi Vijaya Kumar, Saravanan Karuppanan and Mark Ovinis
Numerical methods such as finite element analysis (FEA) can accurately predict remaining strength, with strong correlation with actual burst tests. However, parametric studies with FEA are time and computationally intensive. Alternatively, an artificial ...
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Michael Lo, Saravanan Karuppanan and Mark Ovinis
Most of the standards available for the assessment of the failure pressure of corroded pipelines are limited in their ability to assess complex loadings, and their estimations are conservative. To overcome this research gap, this study employed an artifi...
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Elena Jasiuniene, Bengisu Yilmaz, Damira Smagulova, Gawher Ahmad Bhat, Vaidotas Cicenas, Egidijus ?ukauskas and Liudas Ma?eika
The aim of this work is to achieve reliable nondestructive evaluation (NDE) of adhesively bonded aerospace components by developing novel multidimensional data fusion techniques, which would combine the information obtained by ultrasonic and X-ray NDE me...
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Yao Lu, Zhibin Qiu, Caibo Liao, Zhibiao Zhou, Tonghongfei Li and Zijian Wu
The correct identification of partial discharge types is of great significance to the stable operation of GIS. In order to improve the recognition accuracy and result of partial discharge, and to meet the requirements of real-time monitoring of GIS equip...
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