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Image encryption based on dna splicing system and henon model

ICIC Express Letters 2010年第3期4卷 1011-1018页

作者： Zhou, Changjun Wei, Xiaopeng Zhang, Qiang Wang, Bin School of Management Dalian University of Technology Dalian 116024 China Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian 116622 China

In this paper, we introduce a mixed image encryption scheme which is corn-posed of the Henon model and the formal model of DNA computing-splicing *** this scheme, we transform the digital image into DNA sequence based on DNAcode theory, and then scramble the DNA sequence through employing splicingoperation with a permutation matrix which, is generated by Henon chaotic ***, security analysis and simulation results show that the proposed schemeis effective, and it has wide secret key space, strong sensibility, high,security and good ability of resisting statistic attack. ICIC International © 2010.

关键词： DNA sequences

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The memory degradation based online sequential extreme learning machine

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Neurocomputing 2018年 275卷 2864-2879页

作者： Quan-Yi Zou Xiao-Jun Wang Chang-Jun Zhou Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian 116622 China School of Computer Science & Technology Dalian University of Technology Dalian 116622 China

In online learning, the contribution of old samples to a model decreases as time passes, and old samples gradually become invalid. Although the Online Sequential Extreme Learning Machine (OS-ELM) can avoid the repetitive training of old samples, invalid samples are still used, which goes against improving the accuracy of an OS-ELM model. The Online Sequence Extreme Learning Machine with Forgetting Mechanism (FOS-ELM) timely discards invalid samples, but it does not consider the differences among valid samples and then has the limitation on boosting the accuracy and generalization. To solve this issue, the Memory Degradation Based OS-ELM (MDOS-ELM) is proposed in this paper. The MDOS-ELM adjusts the weights of the old and new samples in real time by a self-adaptive memory factor, and simultaneously discards invalid samples. The self-adaptive memory factor is determined by two elements. One is the similarity between the new and old samples, and the other is the prediction errors of the current training samples on the previous model. The performance of the proposed MDOS-ELM is validated on both regression and classification datasets which include an artificial dataset and twenty-two real-world dataset. The results demonstrate that the MDOS-ELM model outperforms the OS-ELM and the FOS-ELM models on the accuracy and generalization.

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An Approach for Predicting and Compensating the End Deformation of a Heavy Load Robot for Friction Stir Welding 16th

An Approach for Predicting and Compensating the End Deformat...

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16th International Federation of Theory of Machines and Mechanisms World Congress, IFToMM WC 2023

作者： Bai, Yujie Liu, Haitao Meng, Shaofei Ma, Yue Yue, Wei Li, Guangxi Xiao, Juliang Wang, Guofeng Ding, Yabin Key Laboratory of Mechanism Theory and Equipment Design of State Ministry of Education Tianjin University Tianjin300072 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Dongguan University of Technology Dongguan523808 China

ISBN: (纸本)9783031457043

Aiming at solving the problem of insufficient plunge depth by the deformation of friction stir welding robots, this paper presents a method for predicting and compensating for the end deformation of friction stir welding robots. Firstly, the numerical model of FSW is established using DEFORM-3D software, then the axial force on the welding tool is obtained. Subsequently, the robot stiffness model is established based on the screw theory to realize the prediction of robot deformation in the workspace. Finally, a deformation compensation method based on the mirror principle is proposed to realize the compensation of the welding trajectory. Taking the 10 mm AA6061 aluminium alloy FSW as an example, the compensation method proposed in this paper is verified by using computer simulation. The results show that the stiffness model established in this paper can accurately predict the end deformation of the robot. The maximum plunge depth deviation of the compensation method proposed in this paper is reduced by 95.17% compared with the uncompensated case, which proves the effectiveness of the proposed compensation method. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Friction stir welding

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Robust H Sliding Mode Controller design of a Class of Time-Delayed Discrete Conic-Type Nonlinear Systems

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2021年第2期51卷 885-892页

作者： He, Shuping Lyu, Weizhi Liu, Fei Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi China

This paper studies the {H}_{ {\infty }} sliding mode control (SMC) problem for a class of discrete-time conic-type nonlinear systems with time-delays and uncertainties. The nonlinear terms satisfy the conic-type constraint condition that lies in a know hyper-sphere with an uncertain center. By choosing a proper Lyapunov candidate, sufficient conditions are derived to ensure the asymptotic stability of the sliding mode dynamics while achieving a prescribed {H}_{ {\infty }} disturbance attenuation level and finally converted into a minimization problem. The controller is constructed to guarantee the discrete-time reach condition and maintain the states on the prespecified sliding surface. A simulation result and a practical example related to the Chua's circuit are given at last to show the validity of our SMC strategy. © 2013 IEEE.

关键词： Time delay

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Micro-and nano-scale spindle perpendicularity modulation method to enhance the quality of milled surfaces

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International Journal of Extreme Manufacturing 2024年第6期6卷 515-533页

作者： Bingrui Lv Bin Lin Jinshuo Zhang Chunyan Liu Longfei Wang Tianyi Sui Key Laboratory of Advanced Ceramics and Machining Technology Ministry of EducationTianjin UniversityTianjin 300072People's Republic of China Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education Tianjin UniversityTianjin 300072People's Republic of China International Institute for Innovative Design and Intelligent Manufacturing of Tianjin University Shaoxing 312000People's Republic of China

Significant advancements in ultra-precision machining technology have forced a re-examination of the spindle perpendicularity errors'impact on the milled surface quality at the micro-nano *** this paper,a method of spindle precision adjustment is proposed to enhance surface finish *** errors in the machining process are identified using multi-body kinematic theory,with the milling process serving as an example.A two-degree-of-freedom(2-DOF)rotation platform is designed,optimized,and *** platform's static model is established based on elastic beam theory and verified by finite element *** parameters are optimized via the response surface method in combination with the Pareto *** results reveal the effects of spindle speed,voltage amplitude,vibration frequency,cutting depth,and feed rate on the platform's modulation *** static modulation experiment shows that the perpendicularity error between the spindle and the guideway can be reduced from 92.5μrad to 0.25μ***,milling experiments show that the surface quality can be improved by 37.6%after spindle modulation.

关键词： compliant mechanism spindle adjustment surface roughness milling

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Disease Phenotype Classification Model Based on Multi-channel Deep Supervised Bi-LSTM

Disease Phenotype Classification Model Based on Multi-channe...

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International Conference on Computer Engineering and Applications (ICCEA)

作者： Decong Wang Changyuan Zou Ziqi Wei Zhaoqian Zhong Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China CAS Key Laboratory of Molecular Imaging Institute of Automation Beijing China

ISBN: (数字)9798350386776

ISBN: (纸本)9798350386783

Phenotypic classification of diseases refers to the process of categorizing diseases into different classes based on their manifestations or characteristics, aiding doctors in diagnosing diseases and developing treatment plans. Current classification methods are challenged by issues such as strong subjectivity, high instability, and low data utilization. To conduct phenotypic classification of diseases more effectively, this paper proposed a disease phenotypic classification model based on multi-channel deep supervised Bi-LSTM. The proposed model integrates structured and unstructured data for classification, uses the multi-channel module to integrate temporal information from multi-variable time sequence data, and utilizes Bi-LSTM module to capture long-term dependencies in single-channel sequence data. Additionally, a deep supervision module is used to accelerate model convergence and improve generalization capability. The experimental results on the MIMIC-III dataset indicate that the proposed model achieves higher classification accuracy compared to various baseline models, with a smaller parameter size and shorter training time, thereby demonstrating the effectiveness of the method presented in this paper.

关键词： Training Phenotypes Runtime Computational modeling MIMICs Data models Computational efficiency

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Research on PCB tiny displacement estimation method for ORB feature-guided FREAK descriptor enhancement 4

Research on PCB tiny displacement estimation method for ORB ...

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2024 4th International Conference on Artificial Intelligence and Industrial Technology Applications, AIITA 2024

作者： Yang, Duo Su, Yang Wu, Hongwei Yi, Pengfei Key Laboratory for Advanced Design and Intelligent Computing Ministry of Education School of Mechanical Engineering and Software Engineering Dalian University Dalian116622 China Olympic Circuit Technology Co. Ltd. Guangdong Jiangmen529700 China Co. Ltd. Dalian116622 China

Given the hurdles posed by existing techniques for identifying microscopic offsets in miniature printed circuit boards (PCBs), including their low accuracy and high iteration count, this study presents an innovative approach that measures micrometer offsets by utilizing the ORB feature-guided FREAK descriptor enhancement. It improves matching outcomes with a brute-force matcher and RANSAC via ORB feature extraction to guide FREAK descriptors for better feature uniqueness. A PCB small offset detection algorithm is developed with a homography matrix and a theoretical offset model. A novel distance threshold performance evaluation method for this suggested matching algorithm that objectively evaluates matching results is also proposed in this article. The proposed matching method outperforms alternative algorithms in precision and recall, according to its experiments. This research conducts simulation detection of PCB calibration bare boards and instance verification of real PCB boards by constructing a PCB tiny offset detection experimental system. The results show that micron-level detection precision can be achieved without iteration. © Published under licence by IOP Publishing Ltd.

关键词： Engineering education

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Blockchain-based multi-role healthcare data sharing system 22

Blockchain-based multi-role healthcare data sharing system

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22nd IEEE International Conference on E-Health Networking, Application and Services, HEALTHCOM 2020

作者： Yu, Yao Li, Qirui Zhang, Qieshi Hu, Wenjian Liu, Shumei Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang China School of Computer Science and Engineering Northeastern University Shenyang China Shenzhen Institutes of Advanced Technology Chinese Academy of Science Shenzhen China

ISBN: (纸本)9781728162676

Blockchain has unique advantages in data privacy protection and data integrity. We can solve many security problems, such as the single point of failure and data sharing in the current centralized system through blockchain approach. Existing studies have demonstrated that the application of blockchain in the medical system could improve the patient's medical experience. However, we found that the blockchain-based medical systems didn't consider the problems of long insurance claim cycle and complicated procedures. There are also very few healthcare systems that provide targeted sharing protocols for medical data and personal health data. In this paper, we propose a multi-role healthcare data sharing system framework based on blockchain. In this system, we reduce the storage cost through the collaborative storage of blockchain and IPFS. Then we design a smart contract on insurance to help patients achieve automatic insurance claim. In addition, we design two different sharing protocols to realize the fine management of personal data. The system analysis shows that our proposed blockchain-based multi-role healthcare data sharing system can effectively address the actual needs of users and has perfect performance in data storage, privacy protection, insurance claims and personal data management. © 2021 IEEE.

关键词： Blockchain

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Robotic Global Path-Planning Based Modified Genetic Algorithm and A* Algorithm

Robotic Global Path-Planning Based Modified Genetic Algorith...

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International Conference on Measuring Technology and Mechatronics Automation, ICMTMA

作者： Cen Zeng Qiang Zhang Xiaopeng Wei Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian Dalian University China Dalian University of Technology Dalian Liaoning China

ISBN: (纸本)9781424490103

Global path planning for mobile robot using genetic algorithm and A* algorithm is investigated in this paper. The proposed algorithm includes three steps: the MAKLINK graph theory is adopted to establish the free space model of mobile robots firstly, then Dijkstra algorithm is utilized for finding a feasible collision-free path, finally the global optimal path of mobile robots is obtained based on the hybrid algorithm of A* algorithm and genetic algorithm. Experimental results indicate that the proposed algorithm has better performance than Dijkstra algorithm in term of both solution quality and computational time, and thus it is a viable approach to mobile robot global path planning.

关键词： Mobile robots Path planning Gallium Genetic algorithms Encoding Algorithm design and analysis

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Impulsive Control of Heterogeneous Multi-agent Systems with Saturation Constraint and Time Delay

Impulsive Control of Heterogeneous Multi-agent Systems with ...

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2024 China Automation Congress, CAC 2024

作者： Jiao, Ranran Li, Bo Chen, Xiangyong Jiang, Xiaowei School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Finance Anhui University of Finance and Economics Bengbu China Key Laboratory of Complex systems and Intelligent Computing in Universities of Shandong Linyi University Linyi China

ISBN: (纸本)9798350368604

This paper addresses the problem of leader-following consensus in heterogeneous multi-agent systems (HMAS) with input saturation and communication delay. Given the practical differences between leader and follower dimensions, we design virtual leaders to address this problem by allowing actual leaders and followers to communicate with virtual leaders separately, thus enabling indirect communication between actual leaders and followers. Additionally, the control protocol proposed in this paper takes into account the effects of input saturation and time delay that exist in real communication. At last, a simulation example is presented to demonstrate the effectiveness of the designed control protocol. © 2024 IEEE.

关键词： Multi agent systems

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