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Dynamic Constructing 3D Electronic Technical Manual of Mechanical Products Based on Publishing Rules

Journal of Physics: Conference Series 2019年第2期1176卷

作者： Feng Zhao Aijian Wu Lijuan Yan Shen li State Key Laboratory of Intelligent Manufacturing of Advanced Construction Machinery Jiangsu XCMG Construction Machinery Research Institute Ltd. Xuzhou 221000 China Key Laboratory of Electronic Equipment Structure Design of Ministry of Education School of Mechano-electronic Engineering Xidian Univ. Xi'an 710071 China

In order to solve the different contents of 3D Electronic Technical Manual (3DETM) for classified users in the Process of Publishing Mechanical Products, a method of dynamic constructing 3DETM is presented based on publishing rules. Firstly, the object data of 3DETM was extracted automatically; then the publishing behavior of 3DETM was encapsulated by CAD API method. Finally, the dynamic mapping between different classified users and the publishing contents modes of 3DETM was realized by defining Publishing Rules. Validation in the prototype software developed shows that the 3DETM was constructed dynamically for classified users.

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Reversible Data Hiding Based on DNA computing

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Computational Intelligence and Neuroscience 2017年第20170101期2017卷 7276084-7276084页

作者： Wang, Bin Xie, Yingjie Zhou, Shihua Zhou, Changjun Zheng, Xuedong Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian116622 China Applied Technology College Dalian Ocean University Dalian116300 China

Biocomputing, especially DNA, computing has got great development. It is widely used in information security. In this paper, a novel algorithm of reversible data hiding based on DNA computing is proposed. Inspired by the algorithm of histogram modification, which is a classical algorithm for reversible data hiding, we combine it with DNA computing to realize this algorithm based on biological technology. Compared with previous results, our experimental results have significantly improved the ER (Embedding Rate). Furthermore, some PSNR (peak signal-to-noise ratios) of test images are also improved. Experimental results show that it is suitable for protecting the copyright of cover image in DNA-based information security. © 2017 Bin Wang et al.

关键词： Signal to noise ratio

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Theoretical prediction and experimental testing of mechanical properties for 3d printed silk fibroin-type II collagen scaffolds for cartilage regeneration

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MCB Molecular and Cellular Biomechanics 2018年第2期15卷 85-98页

作者： Gao, Lilan Yuan, Qingxian Li, Ruixin Chen, Lei Zhang, Chunqiu Zhang, Xizheng Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin30000 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300000 China Hospital of Stomatolgy NanKai University Tianjin300000 China

Silk fibroin-type II collagen scaffold was made by 3D printing technique and freeze-drying method, and its mechanical properties were studied by experiments and theoretical prediction. The results show that the three-dimensional silk fibroin-typeII collagen scaffold has good porosity and water absorption, which is (89.3%+3.26%) and (824.09%+93.05%), respectively. With the given strain value, the stress of scaffold decreases rapidly firstly and then tends to be stable during the stress relaxation. Both initial and instantaneous stresses increase with increase of applied strain value. The creep strains of scaffold with different stress levels show the two stages: the rapidly increasing stage and the second stable stage. It is noted that the scaffold with compressive stress of less than 35 kPa can recover when the compressive stress is removed. However when the compressive stress is higher than 50 kPa, the scaffold is damaged and its structure is destroyed. Not only the compressive property but tensile property of scaffold are dependent on the applied displacement rate or strain rate. Its compressive elastic modulus and tensile modulus increase with increase of strain rate or displacement rate. The nonlinear relaxation model and creep model were constructed respectively and applied to predict the stress relaxation behavior and creep behavior of scaffold. It is found that there are good agreements between the experimental data and predictions, which mean that the built theoretical model can predict the mechanical behavior of scaffold. Copyright © 2018 Tech Science Press.

关键词： Strain rate

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Relation Model of Burden Operation and State Variables of Blast Furnace Based on Low Frequency Feature Extraction*

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IFAC-PapersOnLine 2017年第1期50卷 13796-13801页

作者： Zhang, Kexin Wu, Min An, Jianqi Cao, Weihua Liu, Zhentao Ning, Fulong School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Faculty of Engineering China University of Geosciences wuhan430074 China Department of Computer Science School of Computing Tokyo Institute of Technology Yokohama226-8502 Japan

In the blast furnace ironmaking process, the running state of the blast furnace can be directly adjusted by the burden operation. Therefore, the explicit relation between the burden operation and the running state variables is vital for the blast furnace operators. However, the state variables of the blast furnace are affected by many factors and the burden matrix is complicated. In this paper, a support vector regression(SVR) predicting model based on low frequency feature extraction is proposed to solve these problems. First, the low frequency components of state variables time series which are mostly affected by the burden operation are extracted. Then, the dimensions of the burden matrix are reduced by a devised simple expression method. Finally, the relation model based on SVR is proposed to predict the values of the expected state variables according to the simplified burden matrix and the value of initial state variables. The simulation on real factory data indicates that the model reflects the accurate quantitative relation between the burden operation and the state variables. © 2017

关键词： Blast furnaces Blast furnace practice Extraction Feature extraction Support vector regression Blast furnace iron making Blast furnace operators burden operation Initial state variables Low frequency components Relation models State variables Support vector regression (SVR)

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Four digits BCD adder with DNA strand displacement

Four digits BCD adder with DNA strand displacement

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International Conference on Systems and Informatics (ICSAI)

作者： Lanlan Shi Changjun Zhou Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing Dalian University Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China

As a way of biological computing technology, DNA strand displacement has become more and more popular in recent years. With the principle of the DNA strand displacement, a four digits BCD adder is presented in this paper, in which single-stranded DNA express input signals and output signals, and double-stranded DNA represent gates. The progress of DNA strand displacement reaction can be easily achieved and operated. The proposed adder can autonomously correct its computing results, when the computing results overflows. Then, the reaction progress is simulated in the Visual DSD software. The experiment results of the four digits BCD adder show that the design of the four digits BCD adder is feasible and successful. The proposed BCD adder provides a new pattern to the development of DNA strand displacement computing.

关键词： DNA Adders Logic gates Visualization Logic circuits Software Integrated circuit modeling

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BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2023年第6期20卷 824-835页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

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Influence of Micro-texture Parameters on Bone Drilling Force and Torque: A Finite Element Model

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IOP Conference Series: Materials Science and Engineering 2019年第1期470卷

作者： Yahui Hu Xiangjun Li Chuncheng Chen Lili Su Qingchun Zheng Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin 300384 China Tianjin University of Technology 391 Binshui West Road Xiqing District Tianjin 300384 China.

The micro-texture on the tool surface is an effective way to improve the quality of the drilling. While high-performance micro-texture plays an important role in improving the quality of working surface and prolonging the life of tool. In this study, a three-dimensional finite element model was established to study the relationship between drilling thrust, torque and microstructure parameters (micro-pit depth, micro-pit diameter and micro-pit spacing) during drilling of cortical bone. The model was validated by cortical bone drilling using a micro-structured tool. On basis of this, the thrust and torque prediction models of the micro-texture parameters were obtained. The results indicate that the thrust and torque increased with the increase of micro-pit diameter; while the increase of the micro-pit spacing caused the thrust and torque to decrease. When the depth of the micro-pit increased, the thrust and torque decreased first and then increased, and we found that the effect of micro-pit spacing and micro-pit depth on force and torque is insignificant.

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Parameter-transferred wasserstein generative adversarial network (PT-WGAN) for low-dose PET image denoising

arXiv

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arXiv 2019年

作者： Gong, Yu Shan, Hongming Teng, Yueyang Tu, Ning Li, Ming Liang, Guodong Wang, Ge Wang, Shanshan College of Medicine and Biological Information Engineering Northeastern University Shenyang110169 China Paul C. Lauterbur Research Center for Biomedical Imaging Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Key Laboratory of Intelligent Computing in Medical Images Ministry of Education Shenyang110169 China Department of Biomedical Engineering Rensselaer Polytechnic Institute TroyNY12180 United States PET-CT/MRI Center Molecular Imaging Center Wuhan University Renmin Hospital Wuhan430060 China Neusoft Medical Systems Co. Ltd Shenyang110167 China

Due to the widespread use of positron emission tomography (PET) in clinical practice, the potential risk of PET-associated radiation dose to patients needs to be minimized. However, with the reduction in the radiation dose, the resultant images may suffer from noise and artifacts that compromise diagnostic performance. In this paper, we propose a parameter-transferred Wasserstein generative adversarial network (PT-WGAN) for lowdose PET image denoising. The contributions of this paper are twofold: i) a PT-WGAN framework is designed to denoise lowdose PET images without compromising structural details, and ii) a task-specific initialization based on transfer learning is developed to train PT-WGAN using trainable parameters transferred from a pretrained model, which significantly improves the training efficiency of PT-WGAN. The experimental results on clinical data show that the proposed network can suppress image noise more effectively while preserving better image fidelity than recently published state-of-the-art methods. We make our code available at https://***/90n9-yu/PT-WGAN. Copyright © 2019, The Authors. All rights reserved.

关键词： Positron emission tomography

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Author Correction: Effects of Precipitates Evolution on Low Stress Creep Properties in P92 Heat-resistant Steel

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Scientific reports 2019年第1期9卷 9567页

作者： Hongguang Han Junjie Shen Jiaxing Xie Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin 300384 China. National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin 300384 China. Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin 300384 China. 58920151@***. National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin 300384 China. 58920151@***.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

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DNA self-assembly model to solve compound logic operators problem 11th

DNA self-assembly model to solve compound logic operators pr...

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11th International Conference on Bio-inspired computing – Theories and Applications, BIC-TA 2016

作者： Zhou, Shihua Wang, Bin Zheng, Xuedong Zhou, Changjun Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian116622 China

ISBN: (纸本)9789811036101

Self-assembly is the process that the component form an ordered form or structure. Because of the biochemical characteristics of DNA molecules, they become a research emphasis in the field of selfassembly. DNA-based self-assembly technology has been widely used in the fields of nanometer machining, molecular circuit, polymer materials, and so on. DNA self-assembly is an effective mechanism that nanometer structure is built bottom-up. In order to overcome the problem that any kind of self-assembled model can only solve the single algorithm, in this paper, a new DNA self-assembly algorithmic model is designed to solve compound logic operators problem. Five types of DNA tiles are designed according to the characteristic of compound operation problem, namely Initial Tile, Process Tile, Operation Tile, End Tile and Boundary Tile. At last, the process of self-assembly are demonstrated by an instance. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Self assembly

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