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Full-Text Articles in Engineering
Deep Gabor Neural Network For Automatic Detection Of Mine-Like Objects In Sonar Imagery, Hoang Thanh Le, Son Lam Phung, Philip B. Chapple, Abdesselam Bouzerdoum, Christian H. Ritz, Le Chung Tran
Deep Gabor Neural Network For Automatic Detection Of Mine-Like Objects In Sonar Imagery, Hoang Thanh Le, Son Lam Phung, Philip B. Chapple, Abdesselam Bouzerdoum, Christian H. Ritz, Le Chung Tran
Faculty of Engineering and Information Sciences - Papers: Part B
With the advances in sonar imaging technology, sonar imagery has increasingly been used for oceanographic studies in civilian and military applications. High-resolution imaging sonars can be mounted on various survey platforms, typically autonomous underwater vehicles, which provide enhanced speed and improved data quality with long-range support. This paper addresses the automatic detection of mine-like objects using sonar images. The proposed Gabor-based detector is designed as a feature pyramid network with a small number of trainable weights. Our approach combines both semantically weak and strong features to handle mine-like objects at multiple scales effectively. For feature extraction, we introduce a parameterized …
Deep Sequence Labelling Model For Information Extraction In Micro Learning Service, Jiayin Lin, Zhexuan Zhou, Geng Sun, Jun Shen, David Pritchard, Tingru Cui, Dongming Xu, Li Li, Ghassan Beydoun
Deep Sequence Labelling Model For Information Extraction In Micro Learning Service, Jiayin Lin, Zhexuan Zhou, Geng Sun, Jun Shen, David Pritchard, Tingru Cui, Dongming Xu, Li Li, Ghassan Beydoun
Faculty of Engineering and Information Sciences - Papers: Part B
Micro learning aims to assist users in making good use of smaller chunks of spare time and provides an effective online learning service. However, to provide such personalized online services on the Web, a number of information overload challenges persist. Effectively and precisely mining and extracting valuable information from massive and redundant information is a significant preprocessing procedure for personalizing online services. In this study, we propose a deep sequence labelling model for locating, extracting, and classifying key information for micro learning services. The proposed model is general and combines the advantages of different types of classical neural network. Early …
Automatic Ventricular Nuclear Magnetic Resonance Image Processing With Deep Learning, Binbin Yong, Chen Wang, Jun Shen, Fucun Li, Hang Yin
Automatic Ventricular Nuclear Magnetic Resonance Image Processing With Deep Learning, Binbin Yong, Chen Wang, Jun Shen, Fucun Li, Hang Yin
Faculty of Engineering and Information Sciences - Papers: Part A
Cardiovascular diseases (CVD) seriously threaten the health of human beings, and they have caused widespread concern in recent years. At present, the diagnosis of CVD is mainly conducted by computed tomography (CT), echocardiography and nuclear magnetic resonance (NMR) technologies. NMR imaging technology is widely used in medical applications owing to its characteristics of high resolution and very low radiation. However, manual NMR image segmentation is time-consuming and error-prone, which has led to the research on automatic NMR image segmentation technologies. Researchers tend to explore the ventricular NRM image segmentation to improve the accuracy of CVD diagnosis. In this study, based …
Effects Of Hydraulic Pressure On Wrinkling And Earing In Micro Hydro Deep Drawing Of Sus304 Circular Cups, Liang Luo, Dongbin Wei, Xiaogang Wang, Cunlong Zhou, Qingxue Huang, Jianzhong Xu, Di Wu, Zhengyi Jiang
Effects Of Hydraulic Pressure On Wrinkling And Earing In Micro Hydro Deep Drawing Of Sus304 Circular Cups, Liang Luo, Dongbin Wei, Xiaogang Wang, Cunlong Zhou, Qingxue Huang, Jianzhong Xu, Di Wu, Zhengyi Jiang
Faculty of Engineering and Information Sciences - Papers: Part A
Influences of hydraulic pressure on forming features in micro hydro deep drawing are different from those in normal drawing due to the small size of specimens. In this study, micro hydro deep drawing of SUS304 sheets was carried out in order to study the impacts of the hydraulic pressure on the quality of the drawn cup. Experimental results indicate that there is a critical hydraulic pressure range from 3 to 6 % of the blank's initial yield stress, where wrinkling and earing development trends change twice. The wrinkling and the earing of the drawn cup also reach their local extremes …
Study On Micro Hydro-Mechanical Deep Drawing Using Finite Element Method, Xiaoguang Ma, Jingwei Zhao, Wei Du, Xin Zhang, Laizhu Jiang, Zhengyi Jiang
Study On Micro Hydro-Mechanical Deep Drawing Using Finite Element Method, Xiaoguang Ma, Jingwei Zhao, Wei Du, Xin Zhang, Laizhu Jiang, Zhengyi Jiang
Faculty of Engineering and Information Sciences - Papers: Part B
A numerical model was established to investigate the micro hydro-mechanical deep drawing process of austenitic stainless steel 304 foil (0.05 mm thickness). Due to the miniaturisation of the specimen size, the effect of grain size, gap distance and radial pressure during drawing process could be prominent. The results indicate that the appropriate radial pressure and gap distance could improve the limit drawing ratio (LDR) of manufactured cylindrical cups by reducing the friction resistance. The maximum LDR obtained in the present work reaches 3.2, which is much higher than that obtained by conventional deep drawing process.
Vivambc: Estimating Viral Sequence Variation In Complex Populations From Illumina Deep-Sequencing Data Using Model-Based Clustering, Bie M. P Verbist, Lieven Clement, Joke Reumers, Kim Thys, Alexander Vapirev, Willem Talloen, Yves Wetzels, Joris Meys, Jeroen Aerssens, Luc Bijnens, Olivier Thas
Vivambc: Estimating Viral Sequence Variation In Complex Populations From Illumina Deep-Sequencing Data Using Model-Based Clustering, Bie M. P Verbist, Lieven Clement, Joke Reumers, Kim Thys, Alexander Vapirev, Willem Talloen, Yves Wetzels, Joris Meys, Jeroen Aerssens, Luc Bijnens, Olivier Thas
Faculty of Engineering and Information Sciences - Papers: Part A
Background: Deep-sequencing allows for an in-depth characterization of sequence variation in complex populations. However, technology associated errors may impede a powerful assessment of low-frequency mutations. Fortunately, base calls are complemented with quality scores which are derived from a quadruplet of intensities, one channel for each nucleotide type for Illumina sequencing. The highest intensity of the four channels determines the base that is called. Mismatch bases can often be corrected by the second best base, i.e. the base with the second highest intensity in the quadruplet. A virus variant model-based clustering method, ViVaMBC, is presented that explores quality scores and second …
Development Of Servo-Type Micro-Hydromechanical Deep-Drawing Apparatus And Micro Deep-Drawing Experiments Of Circular Cups, Hideki Sato, Kenichi Manabe, Kikukatsu Ito, Dongbin Wei, Zhengyi Jiang
Development Of Servo-Type Micro-Hydromechanical Deep-Drawing Apparatus And Micro Deep-Drawing Experiments Of Circular Cups, Hideki Sato, Kenichi Manabe, Kikukatsu Ito, Dongbin Wei, Zhengyi Jiang
Faculty of Engineering and Information Sciences - Papers: Part A
A micro-hydromechanical deep-drawing (MHDD) apparatus for manufacturing a micro-complex-shape components and increasing of drawn cup accuracy has been developed in this study. This apparatus with simple tooling structure and forming process can achieve high dimensional accuracy using servo press mechanics with a double-action type, one-stroke forming process without transferring and positioning, force control, and fine flow rate control of the pressure medium. The developed MHDD apparatus can prevent wrinkling by applying an appropriate constant gap and Stably generate the counterpressure. Micro drawn cups of 0.8 mm diameter are successfully fabricated. Also, the effects of counterpressure on drawability and dimensional accuracy …
Experimental And Numerical Study Of Micro Deep Drawing, Liang Luo, Zhengyi Jiang, Dongbin Wei, Kenichi Manabe, Hideki Sato
Experimental And Numerical Study Of Micro Deep Drawing, Liang Luo, Zhengyi Jiang, Dongbin Wei, Kenichi Manabe, Hideki Sato
Faculty of Engineering and Information Sciences - Papers: Part A
Micro forming is a key technology for an industrial miniaturisation trend, and micro deep drawing (MDD) is a typical micro forming method. It has great advantages comparing to other micro manufacturing methods, such as net forming ability, mass production potential, high product quality and complex 3D metal products fabrication capacity. Meanwhile, it is facing difficulties, for example the so-called size effects, once scaled down to micro scale. To investigate and to solve the problems in MDD, a combined micro blanking-drawing machine is employed and an explicit-implicit micro deep drawing model with a voronoi blank model is developed. Through heat treatment …
An Experimental And Numerical Study Of Micro Deep Drawing Of Sus304 Circular Cups, Liang Luo, Zhengyi Jiang, Dongbin Wei, Kenichi Manabe, Hideki Sato, Xiaofeng He, Pengfei Li
An Experimental And Numerical Study Of Micro Deep Drawing Of Sus304 Circular Cups, Liang Luo, Zhengyi Jiang, Dongbin Wei, Kenichi Manabe, Hideki Sato, Xiaofeng He, Pengfei Li
Faculty of Engineering and Information Sciences - Papers: Part B
Micro deep drawing is a promising technology for mass production of complex 3D micro metal products. Significant size effects at a micro scale, however, obstruct application of this technology and block utilisation of traditional finite element method (FEM). Therefore, a micro tensile test system was developed to obtain accurate material properties considering size effects. Subsequently, a Voronoi blank model was developed for the micro scale simulation. Moreover, micro deep drawing experiments were conducted and their results were compared with the simulation results. The simulation results have a good agreement with the experimental data. Furthermore, the wrinkling at the cup mouth …
Numerical Modeling Of Size Effect In Micro Hydromechanical Deep Drawing, Hideki Sato, Ken-Ichi Manabe, Dongbin Wei, Zhengyi Jiang
Numerical Modeling Of Size Effect In Micro Hydromechanical Deep Drawing, Hideki Sato, Ken-Ichi Manabe, Dongbin Wei, Zhengyi Jiang
Faculty of Engineering and Information Sciences - Papers: Part A
A modeling of tribological size effects in micro deep drawing (MDD) and micro hydromechanical deep drawing (MHDD) is a main focus in this study. The inner and outer pockets in which the different friction coefficients can be applied at different lubrication conditions are considered on the blank surface. The ratio of the area of outer pockets to inner pockets is changed with the decrease in the size. The low friction coefficient at the outer pockets is assumed in MHDD by considering the lubrication effect of fluid medium. The numerical analysis is performed under six lubrication conditions. The analytical results of …
A Micro Deep Drawing Of Arb Processed Aluminium Foil Aa1235, Syamsul Hadi, A Kiet Tieu, Cheng Lu, Hongtao Zhu
A Micro Deep Drawing Of Arb Processed Aluminium Foil Aa1235, Syamsul Hadi, A Kiet Tieu, Cheng Lu, Hongtao Zhu
Faculty of Engineering and Information Sciences - Papers: Part A
The flow stress of AA1235 aluminium series-H14 material of 16 to 300 μm thickness has been determined here for the first time which showed the stress reduced significantly with thickness. A stress-strain relationship has been determined as a function of the thickness and grain size. A limiting drawing ratio (LDR) of 2.003 was achieved by a subsequent heat treatment of accumulative roll bonded (ARB) materials before the micro-cup drawing. The cup was successfully formed as the combined process has reduced the planar anisotropy, increased the normal anisotropy and improved the formability of a cup.
Simulation Of Defects In Micro-Deep Drawing Of An Aluminium Alloy Foil, Syamsul Hadi, Hai-Liang Yu, Kiet Tieu, Cheng Lu
Simulation Of Defects In Micro-Deep Drawing Of An Aluminium Alloy Foil, Syamsul Hadi, Hai-Liang Yu, Kiet Tieu, Cheng Lu
Faculty of Engineering and Information Sciences - Papers: Part A
Micro-forming refers to the application of conventional forming processes to manufacture products from ultra-thin sheet materials. While attempting to meet the increasing demand for cost-effective manufacturing of micro-formed components, it is very important to reduce the defects in the products. In this paper, we report a number of Finite Element (FE) simulations of the micro-deep drawing process with various sample thicknesses and eccentric distances. The simulations indicated that when the sample thickness is nearly equal to the gap between the plunger and the die, the sample is likely to develop fractures at the bottom corner. When the sample thickness is …