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2022 International Conference on Blockchain Technology and Information Security, ICBCTIS 2022

作者： Liang, Xiao An, Ningyu Li, Da Zhang, Qiang Wang, Ruimiao Global Energy Interconnection Research Institute Co. Ltd Artificial Intelligence on Electric Power System State Grid Corporation Joint Laboratory Beijing102209 China State Grid E-Commerce Co. Ltd. State Grid Co. Ltd. Blockchain Technology Laboratory Beijing100053 China State Grid Jiangsu Electric Power Co. Ltd Nanjing210029 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (数字)9781665496919

ISBN: (纸本)9781665496919

In the smart grid, the sharing of power data among various energy entities can make the data play a higher value. However, there may be unauthorized access while sharing data, which makes many entities unwilling to share their data to prevent data leakage. Based on blockchain and ABAC (Attribute-based Access control) technology, this paper proposes an access control scheme, so that users can achieve fine-grained access control of their data when sharing them. The solution uses smart contract to achieve automated and reliable policy evaluation. IPFS (Interplanetary File system) is used for off-chain distributed storage to share the storage pressure of blockchain and guarantee the reliable storage of data. At the same time, all processes in the system are stored in the blockchain, ensuring the accountability of the system. Finally, the experiment proves the feasibility of the proposed scheme. © 2022 IEEE.

关键词： Smart contract

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Use Knowledge to Augment Data from Scratch: An Explainable Deep Immunohistochemical Diagnosis Model

SSRN

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SSRN 2024年

作者： Zhao, Jing Liu, Yuhan Zhang, Xinzhu Sun, Shiliang Yin, Minzhi School of Computer Science and Technology East China Normal University Shanghai200062 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China Department of Pathology Shanghai Children’s Medical Center Shanghai Jiao Tong University School of Medicine Shanghai200127 China

Pathological diagnosis has an important role as the last step in cancer diagnosis. When the naked eye is not enough to identify cancer, we usually use further immunohistochemical diagnosis, which is the detection of specific proteins to obtain protein sequences and their negative/positive expression, and make the final diagnosis based on the sequences. This process is a classification task for protein detection sequences. However, when deep learning goes into this field, it often has the problem of lack of data and poor explainability. Based on the above description, to solve the problem of small sample classification, we propose to extract knowledge from scratch, build protein knowledge graphs, and reuse protein embeddings from the knowledge graph to improve classification performance. In addition, we give explanation for the diagnostic model by visualizing importance and coupling degree of proteins. In our experiments, we find that our proposed classification model has good classification performance and explainability. © 2024, The Authors. All rights reserved.

关键词： Knowledge graph

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A Pricing Rule for Third-Party Platoon Coordination Service Provider

A Pricing Rule for Third-Party Platoon Coordination Service ...

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Asian control Conference

作者： Ting Bai Alexander Johansson Shaoyuan Li Karl Henrik Johansson Jonas Må rtensson Integrated Transport Research Lab Digital Futures and Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai China

We model a platooning system including trucks and a third-party service provider that performs platoon coordination, distributes the platooning profit within platoons, and charges the trucks in exchange for its services. This paper studies one class of pricing rules, where the third-party service provider keeps part of the platooning profit each time a platoon is formed. Furthermore, we propose a platoon coordination solution based on distributed model predictive control in which the pricing rule is integrated. To evaluate the effect of the pricing on the platooning system, we perform a simulation over the Swedish road network. The simulation shows that the platooning rate and profit highly depend on the pricing. This suggests that pricing needs to be set carefully to obtain a satisfactory platooning system in the future.

关键词： Roads Pricing Predictive control

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A Recommendation system Based on Adaptive Genetic Algorithm for Enclosed Spaces

A Recommendation System Based on Adaptive Genetic Algorithm ...

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International Symposium on Autonomous systems (ISAS)

作者： Meng Guo Songhang Chen Yaozong Wang Fujian Normal University College of Computer and Cyber Security Fuzhou China Department of Quanzhou Institute of Equipment Manufacturing Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences Quanzhou China Department of Quanzhou Institute of Equipment Manufacturing Fujian Provincial Key Laboratory of Intelligent Identification and Control of Complex Dynamic System Quanzhou China

Most of the management systems used in common enclosed spaces only have basic functions such as booking and payment, and do not have epidemic prevention and traceability functions. In the COVID-19 pandemic, enclosed scenes, without an epidemic prevention system, clearly increase the risk of cross-contamination of the population, making it a black box that will amplify the severity of the outbreak. In this paper, we develop an intelligent recommendation system designed to coordinate the operation of enclosed spaces and decentralize the new customers to a low-infection risk box. An adaptive genetic algorithm is proposed to achieve optimal allocation of personnel and boxes, which can avoid contact between customers during low peak hours and minimize cross-contact during peak hours. On the one hand, it guarantees the user experience, and on the other hand, it guarantees these enclosed spaces have a high decentralization of crowd density when an epidemic occurs. This greatly reduces the risk of exposure to infection and is of great significance in preventing the spread of the epidemic.

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Fault diagnosis for PV arrays considering dust impact based on transformed graphical feature of characteristic curves and convolutional neural network with CBAM modules

arXiv

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arXiv 2023年

作者： Qu, Jiaqi Wei, Lu Sun, Qiang Zareipour, Hamidreza Qian, Zheng School of Instrumentation and Optoelectronic Engineering Beihang University Beijing China School of Electronics and Information Engineering Beihang University Beijing China State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing China The Department of Electrical and Computer Engineering University of Calgary Calgary Canada

Various faults can occur during the operation of PV arrays, and both the dust-affected operating conditions and various diode configurations make the faults more complicated. However, current methods for fault diagnosis based on I-V characteristic curves only utilize partial feature information and often rely on calibrating the field characteristic curves to standard test conditions (STC). It is difficult to apply it in practice and to accurately identify multiple complex faults with similarities in different blocking diodes configurations of PV arrays under the influence of dust. Therefore, a novel fault diagnosis method for PV arrays considering dust impact is proposed. In the preprocessing stage, the Isc-Voc normalized Gramian angular difference field (GADF) method is presented, which normalizes and transforms the resampled PV array characteristic curves from the field including I-V and P-V to obtain the transformed graphical feature matrices. Then, in the fault diagnosis stage, the model of convolutional neural network (CNN) with convolutional block attention modules (CBAM) is designed to extract fault differentiation information from the transformed graphical matrices containing full feature information and to classify faults. And different graphical feature transformation methods are compared through simulation cases, and different CNN-based classification methods are also analyzed. The results indicate that the developed method for PV arrays with different blocking diodes configurations under various operating conditions has high fault diagnosis accuracy and reliability. Copyright © 2023, The Authors. All rights reserved.

关键词： Failure analysis

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Energy management of solid oxide fuel cell/lithium battery hybrid system

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CSEE Journal of Power and Energy systems 2022年 1-14页

作者： Li, Dong Zhong, Xiao Bo Xu, Yuan Wu Wei, Chong Yang Zhao, Song Jiang, Jianhua Deng, Zhonghua Fu, Xiaowei Li, Xi School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Hubei Wuhan430074 China College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan430081 China

The research of fuel cell and lithium battery hybrid system has attracted more and more researchers because of its advantages of low emission. However, the lower efficiency of energy management has been a critical factor that obstruct the commercialization of hybrid system. In this work, based on finite element ideas, a solid oxide full cell node model is developed to accurately estimate the operating status of the fuel cell. As for lithium battery, previous energy management studies generally only focused on state of charge, however, state of health is also a key parameter for lithium battery. In this paper, considering the strong coupling between variables we use particle filter algorithm to jointly estimate the state of charge and state of health. To reasonably distribute and manage the energy in the hybrid system, a T-S fuzzy controller for the hybrid system is designed by controlling the state variables in the SOFC model and the state of lithium battery. Finally, our algorithm is verified by DSPACE simulation platform. The result shows that the hybrid system with the energy management strategy not only meets the real-time sharply changing demand but also ensures the hybrid system working efficiently and safely. © 2022 China Electric Power Research Institute. All rights reserved.

关键词： Hybrid systems

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Plasmonic and photonic enhancement of chiral near fields

arXiv

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arXiv 2022年

作者： Hu, Li Sun, Zhiguang Nie, Yingdong Huang, Yingzhou Fang, Yurui Chongqing Engineering Laboratory for Detection Control and Integrated System School of Computer Science and Information Engineering Chongqing Technology and Business University Chongqing400067 China School of Physics Dalian University of Technology Dalian116024 China State Key Laboratory of Coal Mine Disaster Dynamics and Control Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials College of Physics Chongqing University Chongqing400044 China

A chiral near field with a highly contorted electromagnetic field builds a bridge to match the chiral molecules and light wavelengths with large size differences. It significantly enhances the circular dichroism of chiral molecules and has great prospects in chirality sensing, detection, trapping, and other chirality-related applications. Surface plasmons feature outstanding light-trapping and electromagnetic-field-concentrating abilities. Plasmonic chiral nanostructures facilitate light manipulation to generate superchiral near fields. Meanwhile, the nanophotonic structures have attracted significant interest to obtain strong chiral fields due to their unique electromagnetic resonant properties. During the interaction of light and chiral materials, the chiral near field not only bridges the light and chiral molecules but is also responsible for the optical activities. This paper reviews state-of-the-art studies on chiral near field enhancement using plasmonic and photonic nanostructures. We review the principle of chiral electromagnetic fields and the development of plasmonic and photonic nanostructures for near field enhancement. The properties and applications of enhanced chiral near fields for chiral molecule detection, spin-orbit angular interaction, and the generation of the chiral optical force are examined. Finally, we discuss current challenges and provide a brief outlook of this field. Copyright © 2022, The Authors. All rights reserved.

关键词： Dichroism

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A Graphical Pressure Sensor Array With Multilayered Structure: Written Through Graphene Ink on Cellulose Paper Substrate

Research Square

引用

Research Square 2021年

作者： Ji, Chao Zhang, Qiang Li, Qiang Pei, Zhen Zhao, Dong Yuan, Zhongyun Wang, Jie Zhang, Wendong Sang, Shengbo MicroNano System Research Center Key Laboratory of Advanced Transducers and Intelligent Control System of the Ministry of Education and Shanxi Province College of Information and Computer Taiyuan University of Technology Shanxi Taiyuan030024 China

Paper based flexible pressure sensors have received extensive attention due to their recoverability and accessibility. In this paper, we proposed graphical pressure sensors array with multilayered structure. A simple writing method was adopted to achieve the adsorption of sensitive materials on the fiber structure of cellulose paper. Pressure sensors with 1, 3, 5 and 7 stacked layers were fabricated and compared, respectively. The results show that the 7-layers sensor combined high sensitivity (44 kPa-1) and fast time response (150 ms). The highly sensitive stacked paper-based sensor array realizes the pressure detection of objects and special-shaped surfaces. A pressure sensor base on commercial corrugated box was also fabricated to compare. The corrugated carton array was made to switch reminder devices for its convenience and accessibility. Since there are many scenarios that require a safe distance, especially under the influence of the COVID-19, the writable paper-based sensor array was used to realize graphical distance perception and warning. © 2021, CC BY.

关键词： Pressure sensors

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Privacy Preservation for Cloud-Edge-Collaborative Energy Management system Using Post-Quantum Homomorphic Encryption

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IEEE Transactions on Smart Grid 2025年

作者： Jiang, Cheng Li, Xue Du, Dajun Qian, Hong Wen, Mi Wu, Lei Findeisen, Rolf Shanghai University of Electric Power Shanghai Key Laboratory of Power Station Automation Technology College of Automation Engineering Shanghai200090 China Shanghai University Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronical Engineering and Automation Shanghai200072 China Shanghai University of Electric Power College of Computer Science and Technology Shanghai201306 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610225 China Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ07030 United States TU Darmstadt Control and Cyber-Physical Systems Laboratory Darmstadt64227 Germany

Cloud-based energy management systems (EMS) in smart grids face privacy challenges, as existing methods based on traditional homomorphic encryption support limited operations and are vulnerable to quantum attacks. We propose a privacy preservation method for smart grid energy management system, leveraging edge-assisted computing and ring learning with errors (RLWE) homomorphic encryption. Our approach enables both addition and multiplication operations on encrypted smart grid data while defending against quantum threats. We demonstrate the methods security under the RLWE hardness assumption and validate its effectiveness through an experimental platform simulating smart grid environments. This work addresses computational limitations in current privacy-preserving techniques, enhancing data security for evolving smart grid technologies © 2010-2012 IEEE.

关键词： Power management (telecommunication)

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PDEGAN: A Panoramic Style Transfer Based on Generative Adversarial Networks

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第4期9卷 2112-2121页

作者： Wang, Qinghua Long, Xinling Huang, Jingwei Chen, Yang Yang, Lirong Zhang, Fuquan College of Computer and Big Data Minjiang University Fuzhou350108 China Fuzhou Technology Innovation Center of intelligent Manufacturing information System Minjiang University Fuzhou350108 China Fujian Province University Fuzhou350300 China College of Computer and Control Engineering Minjiang University Fuzhou350108 China College of Computer and Big Data Fuzhou University Fuzhou China School of Mechanical and Automotive Engineering Fujian University of Technology Fuzhou China College of foreign languages Dalian Jiaotong University Dalian116028 China Digital Media Art Key Laboratory of Sichuan Province Sichuan Conservatory of Music Chengdu610021 China

Panoramic image plays an extremely important role in the application of 3D, but in some special scenarios, the depth information is also needed as an auxiliary, but to obtain the panoramic depth information needs a high cost, it is extremely difficult to obtain. Therefore, this paper proposes a panoramic depth estimation method called PDEGAN (Panoramic Depth Estimation Generative Adversarial Network). This method first enhances the style migration, transfers the input panoramic image to a style closer to the panoramic depth image domain, and then combines the conversion results with the original panoramic image as the input data for further depth estimation training. By using the style closer to the depth estimation, the texture, color and other characteristics of the image can be adjusted, so as to better highlight the depth information of the object in the image, so that the generator network is more focused on performing the image translation task, reduce the impact of style differences on the image translation task, and improve the generalization ability of the model. At the same time, the model will also use multi-scale feature fusion, combined with the attention mechanism, to better capture the depth information of different scales, viewing angles and channels. Not only that, but also by introducing depth gradient loss, surface normal loss to improve the accuracy and stability of depth estimation. To this end, we also made a set of related datasets for the related experiments of PDEGAN, and named it PDE Images. Finally, it is shown that the method proposed in this paper has more accurate estimation results than the traditional Pix2Pix image conversion model. © 2024, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Generative adversarial networks

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