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Service Encapsulation Method Based on Industrial Internet

Service Encapsulation Method Based on Industrial Internet

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作者： Li, Kai Pan, Hao Tong, Xing Li, Dong Wang, Ting Shenyang University of Chemical Technology Liaoning Shenyang110142 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Liaoning Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Liaoning Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang110016 China

Based on the analysis of software and hardware integration and highly heterogeneous infrastructure in the traditional industrial field, this paper puts forward the concept of service packaging engine, puts forward a unified service packaging model for Industry by using the Internet thinking design mode, and can complete the control of complex industrial field equipment by editing only simple logic in the programming interface. This article focuses on basic service encapsulation. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computer programming

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Optimization method of Data interaction in power IoT based on particle swarm algorithm 2

Optimization method of Data interaction in power IoT based o...

引用

2nd International Conference on Consumer Electronics and Computer Engineering, ICCECE 2022

作者： Wang, Tianyu Miao, Weiwei Zeng, Zeng Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China State Grid Jiangsu Electric Power Co. Ltd. Information Telecommunication Branch Nanjing China

ISBN: (纸本)9781665408868

The ubiquitous power Internet of things (IoT) constructs an intelligent service system with comprehensive perception, efficient response and flexible processing around all departments of the power system and with the support of communication technologies such as mobile Internet and artificial intelligence. With the rapid development of smart IoT perceptual devices and edge computing, it has become possible for perceptual devices and edge IoT agents to cooperate in processing tasks. The task completion time can be greatly reduced through the cooperative processing among multiple entities in the IoT. However, as the scale of the Internet of things and number of to-be-processed tasks expanding year by year, the simple task data interaction between devices can not meet the needs of the completion time. Therefore, it is an urgent problem to optimize data transmission and data interaction in the process of collaborative task processing among IoT devices. Motivated by this point, we propose an optimization method of data interaction in power IoT based on particle swarm algorithm. Evaluation on example IoT networks shows the effectiveness of our method to reduce overall task completion time. © 2022 IEEE.

关键词： Internet of things

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Research on prefabricated component production line mold platform combination method

Research on prefabricated component production line mold pla...

引用

2021 International Conference on Advanced Manufacturing Technology and Electronic Information, AMTEI 2021

作者： Han, Zhonghua Yu, Lingfeng Li, Bo Qi, Yuanwei School of Information and Control Engineering Shenyang Jianzhu University Shenyang110168 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

In traditional prefabricated component manufacturing enterprises, there are often problems such as low utilization rate of the platform surface due to poor production plans of the enterprise, resulting in waste of production resources and low production capacity of the enterprise. In order to solve the problem of mold platform combination allocation in the production process of prefabricated component manufacturers, a mold platform combination allocation method based on the combination of machine learning and backtracking is proposed. The backtracking method is used to search for the theoretical best fit combination result, and the improved BL is used. The positioning algorithm simulates the placement process of the mold on the platform, and uses the Apriori algorithm to train the obtained data set to obtain the association rules contained in the frequent item set. When the enterprise re-produces, the prefabricated components are combined according to the association rules for production, and the utilization rate of the platform is improved. The simulation test is carried out with the example data of the prefabricated component manufacturing enterprise, which verifies the effectiveness of the combination allocation method of mold and platform combined with the backtracking method and the Apriori algorithm to solve the problem. © Published under licence by IOP Publishing Ltd.

关键词： Production control

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A non-interactive verifiable computation model of perceptual layer data based on CP-ABE 2

A non-interactive verifiable computation model of perceptual...

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2nd International Conference on Consumer Electronics and Computer Engineering, ICCECE 2022

作者： Zhao, Jianming Miao, Weiwei Zeng, Zeng Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China State Grid Jiangsu Electric Power Co. Ltd. Information Telecommunication Branch Nanjing China

ISBN: (纸本)9781665408868

The computing of smart devices at the perception layer of the power Internet of Things is often insufficient, and complex computing can be outsourced to server resources such as the cloud computing, but the allocation process is not safe and controllable. Under special constraints of the power Internet of Things such as multi-users and heterogeneous terminals, we propose a CP-ABE-based non-interactive verifiable computation model of perceptual layer data. This model is based on CP-ABE, NPOT, FHE and other relevant safety and verifiable theories, and designs a new multi-user non-interactive secure verifiable computing scheme to ensure that only users with the decryption key can participate in the execution of NPOT Scheme. In terms of the calculation process design of the model, we gave a detailed description of the system model, security model, plan. Based on the definition given, the correctness and safety of the non-interactive safety verifiable model design in the power Internet of Things environment are proved, and the interaction cost of the model is analyzed. Finally, it proves that the CP-ABE-based non-interactive verifiable computation model for the perceptual layer proposed in this paper has greatly improved security, applicability, and verifiability, and is able to meet the security outsourcing of computing in the power Internet of Things environment. © 2022 IEEE.

关键词： Internet of things

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Trajectory Tracking Error Optimization based on Iterative Learning 4

Trajectory Tracking Error Optimization based on Iterative Le...

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4th IEEE International Conference on Power, intelligent Computing and systems, ICPICS 2022

作者： Huang, Haoran Zhang, Tao Jia, Danping Zhang, Hualiang Yan, Hongyu Pei, Quanshen Ding, Fan Shenyang University of Technology School of Information Science and Engineering Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Artificial Intelligence Shenyang University of Technology Shenyang China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

The X-Y precision plane motion platform is widely used in various precision motion control fields. In this paper, to improve the tracking accuracy of the X-Y precision plane motion table, a high-level iterative learning control with forgetting factor is proposed, and it is combined with a kind of PD-type iterative learning control with low-pass filter, and the method is applied to the Simulink model of the linear motor of the X-Y precision plane platform, thereby improving the trajectory accuracy of the X-Y precision plane motion platform. The traditional ILC has the disadvantage that the more number of iterations, the more divergent tracking error is. The new ILC proposed in this paper can not only effectively reduce the noise, reduce the tracking error, but also eliminate the problem of error divergence caused by too many iterations. At last, the experimental results of high-order PD iterative learning with forgetting factor and low-pass filter, PD iterative learning with low-pass filter, ordinary PD iterative learning are compared. The results show that the high-order PD iterative learning with forgetting factor and low-pass filter has better tracking effect than the first-order iterative learning and other several algorithms. It can make the movement trajectory of the X-Y precision plane motion platform more stable and improve the accuracy. © 2022 IEEE.

关键词： Low pass filters

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DropPos: pre-training vision transformers by reconstructing dropped positions 23

DropPos: pre-training vision transformers by reconstructing ...

引用

Proceedings of the 37th International Conference on Neural Information Processing systems

作者： Haochen Wang Junsong Fan Yuxi Wang Kaiyou Song Tong Wang Zhaoxiang Zhang Center for Research on Intelligent Perception and Computing (CRIPAC) State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS) Institute of Automation Chinese Academy of Sciences (CASIA) and University of Chinese Academy of Sciences (UCAS) Center for Research on Intelligent Perception and Computing (CRIPAC) State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS) Institute of Automation Chinese Academy of Sciences (CASIA) and Centre for Artificial Intelligence and Robotics HKISI_CAS Megvii Technology Center for Research on Intelligent Perception and Computing (CRIPAC) State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS) Institute of Automation Chinese Academy of Sciences (CASIA) and University of Chinese Academy of Sciences (UCAS) and Centre for Artificial Intelligence and Robotics HKISI_CAS

As it is empirically observed that Vision Transformers (ViTs) are quite insensitive to the order of input tokens, the need for an appropriate self-supervised pretext task that enhances the location awareness of ViTs is becoming evident. To address this, we present DropPos, a novel pretext task designed to reconstruct Dropped Positions. The formulation of DropPos is simple: we first drop a large random subset of positional embeddings and then the model classifies the actual position for each non-overlapping patch among all possible positions solely based on their visual appearance. To avoid trivial solutions, we increase the difficulty of this task by keeping only a subset of patches visible. Additionally, considering there may be different patches with similar visual appearances, we propose position smoothing and attentive reconstruction strategies to relax this classification problem, since it is not necessary to reconstruct their exact positions in these cases. Empirical evaluations of DropPos show strong capabilities. DropPos outperforms supervised pre-training and achieves competitive results compared with state-of-the-art self-supervised alternatives on a wide range of downstream benchmarks. This suggests that explicitly encouraging spatial reasoning abilities, as DropPos does, indeed contributes to the improved location awareness of ViTs. The code is publicly available at https://***/Haochen-Wang409/DropPos.

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Research on cloud-side collaborative task migration strategy based on simulated annealing-Bee Colony Algorithm in Power IoT 2

Research on cloud-side collaborative task migration strategy...

引用

2nd International Conference on Consumer Electronics and Computer Engineering, ICCECE 2022

作者： Zhang, Bowen Zeng, Zeng Miao, Weiwei Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China State Grid Jiangsu Electric Power Co. Ltd. Information Telecommunication Branch Nanjing China

ISBN: (纸本)9781665408868

In the power IoT, in order to make up for the shortcomings of insufficient computing capabilities of edge-side devices, cloud-side collaboration technology has attracted more and more attention. The cloud-side collaboration technology relies on the selection of task migration strategies. However, when the existing migration strategies face the complex edge-side terminal devices in the power IoT, the energy consumption and delay performance are not good enough, which greatly affects the user's power experience. Therefore, it is very valuable to study a cloud-side collaborative task migration strategy under the power IoT environment. This paper proposes a task migration strategy based on simulated annealing-Bee Colony Algorithm in the environment of power IoT, which can solve the problem of task migration. Experimental results show that compared with the existing popular methods, this method has advantages in terms of energy consumption and time delay. This research can meet the real-time requirements of the power IoT, while reducing energy consumption and improving the user's power experience, thereby promoting the further development of the power IoT. © 2022 IEEE.

关键词： Simulated annealing

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Research on optimization method of routing buffer linkage based on Q-learning

Research on optimization method of routing buffer linkage ba...

引用

2021 International Conference on Advanced Manufacturing Technology and Electronic Information, AMTEI 2021

作者： Han, Zhonghua Qi, Hongfeng Chang, Daliang Gong, Wei Dai, Shilong School of Information and Control Engineering Shenyang Jianzhu University Shenyang110168 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

According to the characteristics of the painting process of passenger car manufacturing enterprises, by formulating the routing buffer linkage rules based on the total renewal cost, the linkage process of the bus in the routing buffer is controlled, and an improved Q-learning (Q- The routing buffer of learning) algorithm quickly finds the optimal path method. According to the actual production situation, this method improves the dynamic parameters of the algorithm on the basis of the traditional Q-learning algorithm, and improves the optimization speed and accuracy of the algorithm by establishing the correlation between the work-in-process and its neighboring work-in-process in the current state. Through multiple sets of example simulation tests, the effectiveness of the Q-learning algorithm in solving the optimization problem of routing buffer linkage is verified. © Published under licence by IOP Publishing Ltd.

关键词： Learning algorithms

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Magnetically Driven Capsule Robot for Multi-Targeted Biopsy and Drug Delivery in Stomach

Magnetically Driven Capsule Robot for Multi-Targeted Biopsy ...

引用

IEEE International Conference on robotics and Biomimetics

作者： Zhihui Xu Tanyong Wei Zongze Li Ding Huang Shoubin Liu Chengzhi Hu Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China

Capsule robots have emerged as a promising solution for non-invasive and painless screening of gastrointestinal diseases, offering significant advantages in patient comfort and reduced risk of cross-infection. Despite these advantages, existing capsule robots fall short in their ability to conduct targeted biopsies and deliver drugs to specific gastric lesions. To address this limitation, this paper presents the design and development of a magnetically driven capsule robot that leverages visual feedback to achieve accurate targeting for biopsy and drug administration in gastric lesions. Internal magnets, responsive to an external gradient magnetic field, enable the controlled propulsion of the capsule robot. A kinetic model of the capsule robot is analyzed, allowing it to recognize lesion contours through the endoscopic camera. This recognition determines the rotation angle or small adjustments required for the capsule robot's attitude and positioning. Experimental results in a simplified in vitro stomach model showcase the capability of the capsule robot to achieve targeted biopsy and drug delivery. These results highlight the potential feasibility of the proposed capsule robot in enhancing diagnostic accuracy and treatment efficacy with broader applications within the realm of gastric healthcare.

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A Charge Density Model of Silicon-nanowire GAA MOSFET Incoroperating the Source-drian Tunneling Effect for IC Design

A Charge Density Model of Silicon-nanowire GAA MOSFET Incoro...

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2021 International Symposium on Computer Technology and Information Science, ISCTIS 2021

作者： Cheng, He Zhang, Chao Liu, Tiefeng Xie, Chuang Yang, Zhjia Zhang, Zhipeng Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781665414418

One numerical compact model for one-dimensional electron charge density of n-Type silicon ballistic nanowire gate-All-Around metal-oxide-semiconductor field-effect transistors with ultra-short channel incorporating the source-drain tunneling is proposed. When establishing the AC model in practical device applications, compact models describing transient analysis of the carrier behaviors in the device channel are needed. When focusing on the charge density of carriers within GAA MOSFET devices, carriers transporting along the channel direction induced by the source-drain tunneling effect should also be taken into account in the subthreshold region. In this study, transmission coefficients of the source-drain tunneling effect are evaluated through expressing energy level of the lowest subband with bringing in the exact boundary conditions and using the Wentzel-Kramers-Brillouin approximation. Then, the carrier density can be derived from the charge profile in the channel using quantum statistics theory. Finally, comparisons of the calculations of the carrier densities between the source-drain tunneling and the thermionic modes in ballistic transport are demonstrated. © 2021 IEEE.

关键词： MOSFET devices

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