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Fabric Defect Detection Using Activation Layer Embedded Convolutional Neural Network
This article develops a deep-learning algorithm for an on-loom fabric defect inspection system by combining the techniques of image pre-processing, fabric motif determination, candidate defect map generation, and convolutional neural networks (CNNs).
Date:
April 29, 2019
Creator:
Ouyang, Wenbin; Xu, Bugao; Hou, Jue & Yuan, Xiaohui
System:
The UNT Digital Library
Nanoindentation behavior of high entropy alloys with transformation-induced plasticity
Article describes an experiment where nanoindentation of three metastable dual-phase high entropy alloys (HEAs) was performed to obtain their inherent elastoplastic deformation responses.
Date:
April 29, 2019
Creator:
Sinha, S.; Mirshams, Reza; Wang, Tianhao; Nene, S. S.; Frank, M.; Liu, K et al.
System:
The UNT Digital Library
Sculpted grain boundaries in soft crystals
Article describes study in which "soft heteroepitaxy” is used to exert precise control over the lattice orientation of three-dimensional liquid crystalline soft crystals, thereby granting the ability to sculpt the grain boundaries between them.
Date:
November 29, 2019
Creator:
Li, Xaio; Martínez-González, José A.; Guzmán, Orlando; Ma, Xuedan; Park, Kangho; Zhou, Chun et al.
System:
The UNT Digital Library
Preparation and Characterization of 3D Printed PLA-Based Conductive Composites Using Carbonaceous Fillers by Masterbatch Melting Method
This article highlights a study aimed at improving the conductivity of polylactic acid (PLA)-based composites by incorporating carbonaceous fillers. The composites with the addition of graphene nanoplatelets (rGO) or multi-walled carbon nanotubes (MWCNTs) were fabricated by the masterbatch melting method in order to improve the dispersion of the two kinds of nano-fillers. The results showed that, with the addition of 9 wt % rGO, the volume electrical resistivity of the composite reached the minimum electrical resistance of 10³ Ω·m, at which point the conductive network in the composites was completely formed.
Date:
September 29, 2019
Creator:
Guo, Rui; Ren, Zechun; Jia, Xin; Bi, Hongjie; Yang, Haiying; Ji, Tong et al.
System:
The UNT Digital Library