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Hybrid Translation And Language Model For Micro Learning Material Recommendation, Jiayin Lin
Hybrid Translation And Language Model For Micro Learning Material Recommendation, Jiayin Lin
Faculty of Engineering and Information Sciences - Papers: Part A
As an emerging pedagogy, micro learning aims to make use of people’s fragmented spare time and provide personalized online learning service, for example, by pushing fragmented knowledge to specific learners. In the context of big data, the recommender system is the key factor for realizing the online personalization service, which significantly determines what information will be fmally accessed by the target learners. In the education discipline, due to the pedagogical requirements and the domain characteristics, ranking recommended learning materials is essential for maintaining the outcome of the massive learning scenario. However, many widely used recommendation strategies in other domains showed …
From Ideal To Reality: Segmentation, Annotation, And Recommendation, The Vital Trajectory Of Intelligent Micro Learning, Jiayin Lin, Geng Sun, Tingru Cui, Jun Shen, Dongming Xu, Ghassan Beydoun, Ping Yu, David Pritchard, Li Li, Shiping Chen
From Ideal To Reality: Segmentation, Annotation, And Recommendation, The Vital Trajectory Of Intelligent Micro Learning, Jiayin Lin, Geng Sun, Tingru Cui, Jun Shen, Dongming Xu, Ghassan Beydoun, Ping Yu, David Pritchard, Li Li, Shiping Chen
Faculty of Engineering and Information Sciences - Papers: Part B
The soaring development of Web technologies and mobile devices has blurred time-space boundaries of people’s daily activities. Such development together with the life-long learning requirement give birth to a new learning style, micro learning. Micro learning aims to effectively utilize learners’ fragmented time to carry out personalized learning activities through online education resources. The whole workflow of a micro learning system can be separated into three processing stages: micro learning material generation, learning materials annotation and personalized learning materials delivery. Our micro learning framework is firstly introduced in this paper from a higher perspective. Then we will review representative segmentation …
Evolutionary Learner Profile Optimization Using Rare And Negative Association Rules For Micro Open Learning, Geng Sun, Jiayin Lin, Jun Shen, Tingru Cui, Dongming Xu, Huaming Chen
Evolutionary Learner Profile Optimization Using Rare And Negative Association Rules For Micro Open Learning, Geng Sun, Jiayin Lin, Jun Shen, Tingru Cui, Dongming Xu, Huaming Chen
Faculty of Engineering and Information Sciences - Papers: Part B
The actual data availability, readiness and publicity has slowed down the research of making use of computational intelligence to improve the knowledge delivery in an emerging learning mode, namely adaptive micro open learning, which naturally has high demand in quality and quantity of data to be fed. In this study, we contribute a novel approach to tackle the current scarcity of both data and rules in micro open learning, by adopting evolutionary algorithm to produce association rules with both rare and negative associations taken into account. These rules further drive the generation and optimization of learner profiles through refinement and …
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 …
Refinement And Augmentation For Data In Micro Learning Activity With An Evolutionary Rule Generators, Geng Sun, Jiayin Lin, Tingru Cui, Jun Shen, Dongming Xu, Mahesh Kayastha
Refinement And Augmentation For Data In Micro Learning Activity With An Evolutionary Rule Generators, Geng Sun, Jiayin Lin, Tingru Cui, Jun Shen, Dongming Xu, Mahesh Kayastha
Faculty of Engineering and Information Sciences - Papers: Part B
Improving both the quantity and quality of existing data are placed at the center of research for adaptive micro open learning. To cover this research gap, our work targets on the current scarcity of both data and rules that represent open learning activities. An evolutionary rule generator is constructed, which consists of an outer loop and an inner loop. The outer loop runs a genetic algorithm (GA) to produce association rules that can be effective in the micro open learning scenario from a small amount of available data sources; while the inner loop optimizes generated candidates by taking into account …
Mlaas: A Cloud-Based System For Delivering Adapative Micro Learning In Mobile Mooc Learning, Geng Sun, Tingru Cui, Jianming Yong, Jun Shen, Shiping Chen
Mlaas: A Cloud-Based System For Delivering Adapative Micro Learning In Mobile Mooc Learning, Geng Sun, Tingru Cui, Jianming Yong, Jun Shen, Shiping Chen
Faculty of Engineering and Information Sciences - Papers: Part B
No abstract provided.
Investigation Of Track Structure And Condensed History Physics Models For Applications In Radiation Dosimetry On A Micro And Nano Scale In Geant4, Peter Lazarakis, Sebastien Incerti, Vladimir N. Ivanchenko, Ioanna Kyriakou, Dimitris Emfietzoglou, Stephanie Corde, Anatoly B. Rosenfeld, Michael L. F Lerch, Moeava Tehei, Susanna Guatelli
Investigation Of Track Structure And Condensed History Physics Models For Applications In Radiation Dosimetry On A Micro And Nano Scale In Geant4, Peter Lazarakis, Sebastien Incerti, Vladimir N. Ivanchenko, Ioanna Kyriakou, Dimitris Emfietzoglou, Stephanie Corde, Anatoly B. Rosenfeld, Michael L. F Lerch, Moeava Tehei, Susanna Guatelli
Faculty of Engineering and Information Sciences - Papers: Part B
Monte Carlo methods apply various physical models, either condensed history (CH) or track structure (TS), to simulate the passage of radiation through matter. Both CH and TS models continue to be applied to radiation dosimetry investigations on a micro and nano scale. However, as there has been no systematic comparison of the use of these models for such applications there can be no quantification of the uncertainty that is being introduced by the choice of physics model. A comparison of CH and TS models available in Geant4, along with a quantification of the differences in calculated quantities on a micro …
Ontological Learner Profile Identification For Cold Start Problem In Micro Learning Resources Delivery, Geng Sun, Tingru Cui, Jun Shen, Dongming Xu, Ghassan Beydoun, Shiping Chen
Ontological Learner Profile Identification For Cold Start Problem In Micro Learning Resources Delivery, Geng Sun, Tingru Cui, Jun Shen, Dongming Xu, Ghassan Beydoun, Shiping Chen
Faculty of Engineering and Information Sciences - Papers: Part B
No abstract provided.
Towards Massive Data And Sparse Data In Adaptive Micro Open Educational Resource Recommendation: A Study On Semantic Knowledge Base Construction And Cold Start Problem, Geng Sun, Tingru Cui, Ghassan Beydoun, Shiping Chen, Fang Dong, Dongming Xu, Jun Shen
Towards Massive Data And Sparse Data In Adaptive Micro Open Educational Resource Recommendation: A Study On Semantic Knowledge Base Construction And Cold Start Problem, Geng Sun, Tingru Cui, Ghassan Beydoun, Shiping Chen, Fang Dong, Dongming Xu, Jun Shen
Faculty of Engineering and Information Sciences - Papers: Part B
Micro Learning through open educational resources (OERs) is becoming increasingly popular. However, adaptive micro learning support remains inadequate by current OER platforms. To address this, our smart system, Micro Learning as a Service (MLaaS), aims to deliver personalized OER with micro learning to satisfy their real-time needs.
Assisting Open Education Resource Providers And Instructors To Deal With Cold Start Problem In Adaptive Micro Learning: A Service Oriented Solution, Geng Sun, Tingru Cui, Dongming Xu, Huaming Chen, Shiping Chen, Jun Shen
Assisting Open Education Resource Providers And Instructors To Deal With Cold Start Problem In Adaptive Micro Learning: A Service Oriented Solution, Geng Sun, Tingru Cui, Dongming Xu, Huaming Chen, Shiping Chen, Jun Shen
Faculty of Engineering and Information Sciences - Papers: Part B
No abstract provided.
A Framework Of Mlaas For Facilitating Adaptive Micro Learning Through Open Education Resources In Mobile Environment, Geng Sun, Tingru Cui, Wanwu Guo, Shiping Chen, Jun Shen
A Framework Of Mlaas For Facilitating Adaptive Micro Learning Through Open Education Resources In Mobile Environment, Geng Sun, Tingru Cui, Wanwu Guo, Shiping Chen, Jun Shen
Faculty of Engineering and Information Sciences - Papers: Part B
No abstract provided.
Organizing Online Computation For Adaptive Micro Open Education Resource Recommendation, Geng Sun, Tingru Cui, Ghassan Beydoun, Shiping Chen, Dongming Xu, Jun Shen
Organizing Online Computation For Adaptive Micro Open Education Resource Recommendation, Geng Sun, Tingru Cui, Ghassan Beydoun, Shiping Chen, Dongming Xu, Jun Shen
Faculty of Engineering and Information Sciences - Papers: Part B
Our previous work, Micro Learning as a Service (MLaaS), aimed to deliver adaptive micro open education resources (OERs). However, relying solely on the offline computation, the recommendation lacks rationality and timeliness. It is also difficult to make the first recommendation to a new learner. In this paper we introduce the organization of the online computation of the MLaaS. It targets at solving the cold start problem due to the shortage of learner information and real-time updates of the learner-micro OER profile
Effect Of Grain Size On Springback And System Energy In Micro V-Bending With Phosphor Bronze Foil, Zhi Fang, Zhengyi Jiang, Xiaogang Wang, Cunlong Zhou, Xianming Zhao, Xiaoming Zhang, Di Wu
Effect Of Grain Size On Springback And System Energy In Micro V-Bending With Phosphor Bronze Foil, Zhi Fang, Zhengyi Jiang, Xiaogang Wang, Cunlong Zhou, Xianming Zhao, Xiaoming Zhang, Di Wu
Faculty of Engineering and Information Sciences - Papers: Part A
In this paper, the effect of grain size on springback in the micro V-bending process of phosphor bronze foil (face-centered cubic structure) is investigated. Grain size effect is expressed by the ratio of material thickness (T) to average grain size (D), and these T/D values are divided into three groups: larger than 1, less than 1, and approximately equal to 1. It has been found that springback angles were the lowest when T/D ≈ 1. Electron backscattering diffraction (EBSD) measurement results show that the twinning boundaries change with the ratios of T/D before and after bending. When T/D > 1, the …
Analysis Of Micro Flexible Rolling With Consideration Of Material Heterogeneity, Feijun Qu, Zhengyi Jiang, Haina Lu
Analysis Of Micro Flexible Rolling With Consideration Of Material Heterogeneity, Feijun Qu, Zhengyi Jiang, Haina Lu
Faculty of Engineering and Information Sciences - Papers: Part A
This paper establishes a finite element model to numerically study the springback in thickness direction during micro flexible rolling process, in which 3D Voronoi tessellation has been applied to describe grain boundary and generation process of grain in the workpiece. To reflect material heterogeneity, nine kinds of mechanical properties defined by nine types of heterogeneity coefficients are selected and assigned to Voronoi polyhedrons as per the statistical distribution of hardness of grains identified by micro hardness testing. Initial workpiece thicknesses of 100, 250 and 500 μm with reduction changing from 20% to 50% are respectively considered in the numerical simulation …
Microstructure And Micro-Texture Evolution During The Dynamic Recrystallisation Of A Ni-30fe-Nb-C Model Alloy, Parvez Mannan, Ahmed A. Saleh, Azdiar A. Gazder, Gilberto Casillas, Elena V. Pereloma
Microstructure And Micro-Texture Evolution During The Dynamic Recrystallisation Of A Ni-30fe-Nb-C Model Alloy, Parvez Mannan, Ahmed A. Saleh, Azdiar A. Gazder, Gilberto Casillas, Elena V. Pereloma
Faculty of Engineering and Information Sciences - Papers: Part A
The evolution of microstructure and micro-texture during discontinuous dynamic recrystallisation of an austenitic Ni-30Fe-Nb-C model alloy subjected to interrupted plane strain compression at strains (ε) of 0.23, 0.35, 0.68, 0.85 and 1.2 was investigated using electron backscattering diffraction and transmission electron microscopy. Throughout the strain range, the majority of dynamic recrystallisation events comprised nucleation in necklace-like arrangements located at and along grain boundaries via bulging. At ε ≥ 0.68, discrete nucleation events were also observed within grain interiors. Grain growth during dynamic recrystallisation is characteristic of strain induced boundary migration. The initial texture comprised Cube-RD ({013}〈100〉), Cube-ND ({001}〈310〉) and Cube …
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 …
A New Micro Scale Fe Model Of Crystalline Materials In Micro Forming Process, Liang Luo, Haibo Xie, Dongbin Wei, Xiaogang Wang, Cunlong Zhou, Zhengyi Jiang
A New Micro Scale Fe Model Of Crystalline Materials In Micro Forming Process, Liang Luo, Haibo Xie, Dongbin Wei, Xiaogang Wang, Cunlong Zhou, Zhengyi Jiang
Faculty of Engineering and Information Sciences - Papers: Part A
Micro forming of metals has drawn global attention due to the increasing requirement of micro metal products. However, the size effects become significant in micro forming processes and affect the application of finite element (FE) simulation of micro forming processes. Dividing samples into small areas according to their microstructures and assigning individual properties to each small area are a possible access to micro forming simulation considering material size effects. In this study, a new model that includes both grains and their boundaries was developed based on the observed microstructures of samples. The divided subareas in the model have exact shapes …
Finite Element Method Analysis Of Surface Roughness Transfer In Micro Flexible Rolling, Feijun Qu, Haibo Xie, Zhengyi Jiang
Finite Element Method Analysis Of Surface Roughness Transfer In Micro Flexible Rolling, Feijun Qu, Haibo Xie, Zhengyi Jiang
Faculty of Engineering and Information Sciences - Papers: Part A
Micro flexible rolling aims to fabricate submillimeter thick strips with varying thickness profile, where the surface quality of products is mainly determined by initial workpiece surface roughness and subsequent surface asperity flattening process, which is affected by process parameters during rolling. This paper shows a 3D finite element model for flexible rolling of a 250 μm thick workpiece with reduction of 20 to 50%, and rolling phase with thinner thickness indicates a better ability to decrease the surface roughness. Four types of initial workpiece surface roughness are studied in the simulation, and the influences of process parameters, such as friction …
An Experimental And Numerical Investigation On Micro Rolling For Ultra-Thin Strip, Haibo Xie, Kenichi Manabe, Tsuyoshi Furushima, Kazuo Tada, Zhengyi Jiang
An Experimental And Numerical Investigation On Micro Rolling For Ultra-Thin Strip, Haibo Xie, Kenichi Manabe, Tsuyoshi Furushima, Kazuo Tada, Zhengyi Jiang
Faculty of Engineering and Information Sciences - Papers: Part A
The demand for miniaturized parts and miniaturized semi-finished products is increasing nowadays, because microforming processes can improve production rate and minimize material waste due to less forming passes. However, traditional macro metal forming processes and modelling cannot be simply scaled down to produce miniaturized micro parts. In this study, a 2-Hi micro rolling mill has been successfully built. Experimental and numerical investigations on the micro rolling process for ultra-thin SUS 304 stainless steel strip have been conducted. The experimental results show that the micro rolling deformation of ultra-thin strip is influenced by size effect which results from the specimen size …
Lubrication Characterisation Analysis Of Stainless Steel Foil During Micro Rolling, Haibo Xie, Kenichi Manabe, Tsuyoshi Furushima, Kazuo Tada, Zhengyi Jiang
Lubrication Characterisation Analysis Of Stainless Steel Foil During Micro Rolling, Haibo Xie, Kenichi Manabe, Tsuyoshi Furushima, Kazuo Tada, Zhengyi Jiang
Faculty of Engineering and Information Sciences - Papers: Part A
Physical parameters, such as microscopic and roughness, play important roles in microforming process due to an increasing ratio of surface to volume of the deformed material. The study on lubrication characterisation in microforming is getting more attractive to researchers because traditional models are not reliable in this scaled down process. In this study, the micro rolling deformation characterisation has been investigated on SUS 304 stainless steel considering lubricant effect and feature size effect. The foil thickness plays an important role in the tribological features of micro rolling. The evolutions of both oil film thickness and foil surface are analysed accordingly. …
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.
Thin Silicon Strip Detectors For Beam Monitoring In Micro-Beam Radiation Therapy, Marco Povoli, Enver Alagoz, Alberto Bravin, Iwan Cornelius, E Bräuer-Krisch, Pauline Fournier, Thor E. Hansen, Angela Kok, Michael L. F Lerch, E Monakhov, J Morse, Marco Petasecca, Herwig Requardt, Anatoly B. Rosenfeld, D Röhrich, H Sandaker, M Salome, B Stugu
Thin Silicon Strip Detectors For Beam Monitoring In Micro-Beam Radiation Therapy, Marco Povoli, Enver Alagoz, Alberto Bravin, Iwan Cornelius, E Bräuer-Krisch, Pauline Fournier, Thor E. Hansen, Angela Kok, Michael L. F Lerch, E Monakhov, J Morse, Marco Petasecca, Herwig Requardt, Anatoly B. Rosenfeld, D Röhrich, H Sandaker, M Salome, B Stugu
Faculty of Engineering and Information Sciences - Papers: Part A
Microbeam Radiation Therapy (MRT) is an emerging cancer treatment that is currently being developed at the European Synchrotron Radiation Facility (ESRF) in Grenoble, France. This technique uses a highly collimated and fractionated X-ray beam array with extremely high dose rate and very small divergence, to benefit from the dose-volume effect, thus sparing healthy tissue. In case of any beam anomalies and system malfunctions, special safety measures must be installed, such as an emergency safety shutter that requires continuous monitoring of the beam intensity profile. Within the 3DMiMic project, a novel silicon strip detector that can tackle the special features of …
Micro Sheet Hydroforming Process Of Ultra-Thin Pure Titanium Foil, Hideki Sato, Kenichi Manabe, Dongbin Wei, Zhengyi Jiang, Daiki Kondo
Micro Sheet Hydroforming Process Of Ultra-Thin Pure Titanium Foil, Hideki Sato, Kenichi Manabe, Dongbin Wei, Zhengyi Jiang, Daiki Kondo
Faculty of Engineering and Information Sciences - Papers: Part A
A micro hydromechanical deep drawing is carried out using the pure titanium and the effect of fluid pressure on formability of pure titanium is investigated. The experiments are performed using the two kinds of pure titanium foils (TR270C-H and TR270C-O) and stainless steel foil (SUS304-H) with 50 thickness and the cylindrical and conical punches. As a result, it is found that the peeling off the oxide film of pure titanium can be reduced by applying the fluid pressure because the friction force and contact pressure between the blank and die decreases. However, the formability is lower for pure titanium than …
Towards Bringing Adaptive Micro Learning Into Mooc Courses, Geng Sun, Tingru Cui, Kuanching Li, Dongming Xu, Shiping Chen, Jun Shen, Wanwu Guo
Towards Bringing Adaptive Micro Learning Into Mooc Courses, Geng Sun, Tingru Cui, Kuanching Li, Dongming Xu, Shiping Chen, Jun Shen, Wanwu Guo
Faculty of Engineering and Information Sciences - Papers: Part A
In this paper we illustrate a proposal with regard to providing learners adaptive micro learning experiences, which can be fulfilled within fragmented time pieces. The framework of our system is demonstrated, while it aims to deliver customized micro learning contents taking into account learners’ specific demands, learning styles, preference and context.
Mlaas: A Cloud System For Mobile Micro Learning In Mooc, Geng Sun, Tingru Cui, Shiping Chen, Wanwu Guo, Jun Shen
Mlaas: A Cloud System For Mobile Micro Learning In Mooc, Geng Sun, Tingru Cui, Shiping Chen, Wanwu Guo, Jun Shen
Faculty of Engineering and Information Sciences - Papers: Part A
No abstract provided.
Drawing Micro Learning Into Mooc: Using Fragmented Pieces Of Time To Enable Effective Entire Course Learning Experiences, Geng Sun, Tingru Cui, Jianming Yong, Jun Shen, Shiping Chen
Drawing Micro Learning Into Mooc: Using Fragmented Pieces Of Time To Enable Effective Entire Course Learning Experiences, Geng Sun, Tingru Cui, Jianming Yong, Jun Shen, Shiping Chen
Faculty of Engineering and Information Sciences - Papers: Part A
Recently the massive open online course (MOOC) is an emerging trend that attracts many educators’ and researchers’ attentions. Based on our pilot study focusing on the development and operation of MOOC in Australia, we found MOOC is featured with mastery learning and blended learning, but it suffers from low completion rates. Brining micro learning into MOOC can be a feasible solution to improve current MOOC delivery and learning experience. We design a system which aims to provide adaptive micro learning contents as well as learning path identifications customized for each individual learner. To investigate how micro learning can impact learning …
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 …
Classification Of Micro-Doppler Signatures Of Human Motions Using Log-Gabor Filters, Fok Hing Chi Tivive, Son Lam Phung, Abdesselam Bouzerdoum
Classification Of Micro-Doppler Signatures Of Human Motions Using Log-Gabor Filters, Fok Hing Chi Tivive, Son Lam Phung, Abdesselam Bouzerdoum
Faculty of Engineering and Information Sciences - Papers: Part A
In recent years, Doppler radar has been used as a sensing modality for human gait recognition, due to its ability to operate in adverse weather and penetrate opaque obstacles. Doppler radar captures not only the speed of the target, but also the micro-motions of its moving parts. These micro-motions induce frequency modulations that can be used to characterise the target movements. However, a major challenge in Doppler signal processing is to extract discriminative features from the radar returns for target classification. This study presents a feature extraction method for classification of human motions from the micro-Doppler radar signal. The proposed …
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 …