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2020 3rd International Conference on Advanced Algorithms and Control Engineering, ICAACE 2020

作者： Tian, Fanghao Wei, Hongkui Li, Xu Lv, Meibo Wang, Pei School of Astronautics Northwestern Polytechnical University Xi'an Shaanxi710072 China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing100854 China

Salp Swarm Algorithm (SSA) is a novel optimization algorithm which is widely used in engineering problems. An improved SSA inspired by quantum computing is proposed in this paper. The principles of quantum computing, such as qubits and quantum states, are introduced into the original SSA in order to overcome the defect of trapping into local optimum easily. Instead of updating the salp position directly, the quantum angle related to the quantum state is updated to increase the diversity of states. Two multidimensional benchmark functions are used to verify the proposed improved SSA, the result shows that the introduction of quantum computing can successfully prevent the SSA from falling into the local optimum and increase the accuracy. © Published under licence by IOP Publishing Ltd.

关键词： Optimization

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3D Scene Flow Estimation on Pseudo-LiDAR: Bridging the Gap on Estimating Point Motion

arXiv

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arXiv 2022年

作者： Jiang, Chaokang Wang, Guangming Miao, Yanzi Wang, Hesheng Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China

3D scene flow characterizes how the points at the current time flow to the next time in the 3D Euclidean space, which possesses the capacity to infer autonomously the non-rigid motion of all objects in the scene. The previous methods for estimating scene flow from images have limitations, which split the holistic nature of 3D scene flow by estimating optical flow and disparity separately. Learning 3D scene flow from point clouds also faces the difficulties of the gap between synthesized and real data and the sparsity of LiDAR point clouds. In this paper, the generated dense depth map is utilized to obtain explicit 3D coordinates, which achieves direct learning of 3D scene flow from 2D images. The stability of the predicted scene flow is improved by introducing the dense nature of 2D pixels into the 3D space. Outliers in the generated 3D point cloud are removed by statistical methods to weaken the impact of noisy points on the 3D scene flow estimation task. Disparity consistency loss is proposed to achieve more effective unsupervised learning of 3D scene flow. The proposed method of self-supervised learning of 3D scene flow on real-world images is compared with a variety of methods for learning on the synthesized dataset and learning on LiDAR point clouds. The comparisons of multiple scene flow metrics are shown to demonstrate the effectiveness and superiority of introducing pseudo-LiDAR point cloud to scene flow estimation. © 2022, CC BY.

关键词： Three dimensional computer graphics

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Adipocyte Targeted Delivery of Rosiglitazone with Localized Photothermal Therapy for Treatment of Diet-Induced Obesity in Mice

SSRN

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SSRN 2024年

作者： Zhang, Yunxiao Luo, Maoqi Jia, Yaxin Deng, Li Gong, Tao Zhang, Zhirong Cao, Xi Fu, Yao Key Laboratory of Drug Targeting and Drug Delivery System The Education Ministry and Sichuan Province Sichuan Engineering Laboratory for Plant-Sourced Drug Sichuan Research Center for Drug Precision Industrial Technology West China School of Pharmacy Sichuan University Chengdu610041 China School of Pharmacy The First Affiliated Hospital of Anhui Medical University Anhui Medical University The Grade 3 Pharmaceutical Chemistry Laboratory of State Administrate of Traditional Chinese Medicine Hefei230032 China

Obesity represents a growing public health concern and is closely associated with metabolic complications such as diabetes and fatty liver disease. Anti-obesity medications currently available have limited efficacy in weight loss and are often accompanied by adverse effects. This study proposes a localized photothermal therapy (PTT) combined with adipocyte-targeted delivery of rosiglitazone (RSG) to address obesity. Specifically, cationic albumin nanoparticles (cNPs) were synthesized to deliver RSG precisely to white adipocytes, stimulating the browning process. An IR780-loaded thermosensitive hydrogel was injected and allowed to gel in situ to afford a subcutaneous reservoir that enables localized PTT and controlled release of RSG cNPs. Notably, cNPs significantly enhanced the internalization efficiency in adipocytes in vitro and prolonged the therapeutic retention in the adipose tissue in vivo. Co-administration of RSG cNPs and PTT substantially reduced fat content, induced browning in white adipose tissue in diet-induced obese mice, and mitigated complications such as insulin resistance, fatty liver, and hyperlipidemia. The increased expression of uncoupling protein 1 contributes to enhancing energy expenditure and facilitating adipose metabolism, thereby effectively combating obesity. This therapeutic approach integrates localized PTT with adipocyte-targeted delivery to combat the global obesity epidemic thus offering a promising solution with reduced systemic toxicity and heightened efficacy. © 2024, The Authors. All rights reserved.

关键词： Metabolism

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Energy management method of building microgrid considering energy consumption characteristics and virtual energy storage

Energy management method of building microgrid considering e...

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4th Energy Conversion and Economics Annual Forum (ECE Forum 2024)

作者： He Chen Shufeng Wang Yujing Huang Zhe Zheng Rui Liu Beijing SmartChip Microelectronics Technology Company Limited Beijing 102200 People's Republic of China IEEE PES Technical Committee Power System Operation Planning & Economics Committee - China Satellite Committee Beijing 102200 People's Republic of China State Key Laboratory of Alternate Electrical Power System Renewable Energy Sources North China Electric Power University Changping District Beijing 102206 People's Republic of China

ISBN: (数字)9781837242924

The proportion of building energy consumption in the total social energy consumption is increasing year by year, and the refined energy management method integrating building attributes and energy consumption characteristics has become the key to the economic and efficient operation of building microgrid. This paper proposes an energy management method of building microgrid considering energy consumption characteristics and virtual energy storage. Firstly, the system model is established for users and buildings, incorporating virtual energy storage with conventional energy storage system, electric vehicles and building virtual energy storage. Secondly, the building energy consumption model is established considering the human behavior characteristics and architectural attributes of buildings. Thirdly, the energy management model based on the Stackelberg game is then formulated, where users minimize costs and building operators maximize profits by adjusting energy prices based on user responses, and a distributed algorithm iteratively solves this to reach equilibrium. Finally, the numeri cal example validates the model and algorithm, analyzing the effects of human behavior on virtual energy storage and comparing generalized storage systems and strategies.

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An S-scheme NH2-MIL-101(Fe)@MCN/Bi2O3 heterojunction photocatalyst for the degradation of tetracycline and production of H2O2

引用

Chemosphere 2023年 343卷

作者： Li, Zhe Shen, Dongcai Hu, Xin Yang, Xiaolong Li, Yiming Bao, Mutai Frontiers Science Center for Deep Ocean Multispheres and Earth System Key Laboratory of Marine Chemistry Theory and Technology Ministry of Education Ocean University of China Qingdao266100 China College of Chemistry & Chemical Engineering Ocean University of China Qingdao266100 China Key Laboratory of Marine Chemistry Theory and Technology Ministry of Education College of Chemistry and Chemical Engineering Ocean University of China Qingdao266100 China School of Chemistry and Chemical Engineering State Key Laboratory of Bio-fibers and Eco-textiles Collaborative Innovation Center of Shandong Marine Bio-based Fibers and Ecological Textiles Qingdao University 308 Ning Xia Road Qingdao266071 China

Effective and durable photocatalysts are essential for the decomposition of persistent contaminants and the generation of hydrogen peroxide. In this study, we successfully constructed an S-type heterojunction by in situ growing Bi2O3 nanocrystals and NH2-MIL-101(Fe) onto surface-modified g-C3N4. The process of charge transfer in the S-type heterojunction was confirmed using ISI-XPS, DFT calculations, capture experiments, and EPR signals. The combined influence of the heterojunction and MOF demonstrated remarkable photocatalytic performance in the breakdown of tetracycline (TC) and the generation of hydrogen peroxide (H2O2). In the enhanced setup (10%–NH2–MIL-101(Fe)@MCN/Bi2O3), full degradation of TC was accomplished within 50 min under visible light exposure. Additionally, a notable H2O2 yield of 655.63 μmol/g was attained, all achieved without the necessity of sacrificial agents or supplementary oxygen. Based on the outcomes of the dual functionality, the exceptional performance of the ternary composite material can be ascribed to the collaborative influence of the heterojunction and MOF. This collaborative effect expands the light absorption range in the visible region, suppresses the recombination of electron-hole pairs, and enhances the photocatalytic redox ability. The system demonstrates significant potential in the efficient in situ production of H2O2 and removal of recalcitrant organic pollutants in pure water. © 2023 Elsevier Ltd

关键词： Heterojunctions

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Hybrid RAG-empowered Multi-modal LLM for Secure Data Management in Internet of Medical Things: A Diffusion-based Contract Approach

arXiv

引用

arXiv 2024年

作者： Su, Cheng Wen, Jinbo Kang, Jiawen Wang, Yonghua Su, Yuanjia Pan, Hudan Zhong, Zishao Hossain, M. Shamim School of Automation The GuangdongHongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangdong University of Technology Guangzhou510006 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing210016 China School of Automation The Guangdong Basic Research Center of Excellence for Ecological Security and Green Development Key Laboratory for City Cluster Environmental Safety Green Development The Ministry of Education Guangdong University of Technology Guangzhou510006 China School of Automation The Key Laboratory of Intelligent Detection and IoT in Manufacturing Ministry of Education Guangdong University of Technology Guangzhou510006 China School of Automation Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education Guangdong University of Technology Guangzhou510006 China Guangzhou University of Traditional Chinese Medicine State Key Laboratory of Traditional Chinese Medicine Syndrome The Second Affiliated Hospital of Guangzhou University of Chinese Medicine Chinese Medicine Guangdong Laboratory Hengqin 519000 China Second Affiliated Hospital of Guangzhou University of Chinese Medicine Chinese Medicine Guangdong Laboratory Hengqin 519000 China Department of Software Engineering College of Computer and Information Sciences King Saud University Riyadh12372 Saudi Arabia

Secure data management and effective data sharing have become paramount in the rapidly evolving healthcare landscape, especially with the growing integration of the Internet of Medical Things (IoMT). The rise of generative artificial intelligence has further elevated Multi-modal Large Language Models (MLLMs) as essential tools for managing and optimizing healthcare data in IoMT. MLLMs can support multi-modal inputs and generate diverse types of content by leveraging large-scale training on vast amounts of multi-modal data. However, critical challenges persist in developing medical MLLMs, including security and freshness issues of healthcare data, affecting the output quality of MLLMs. To this end, in this paper, we propose a hybrid Retrieval-Augmented Generation (RAG)-empowered medical MLLM framework for healthcare data management. This framework leverages a hierarchical cross-chain architecture to facilitate secure data training. Moreover, it enhances the output quality of MLLMs through hybrid RAG, which employs multi-modal metrics to filter various unimodal RAG results and incorporates these retrieval results as additional inputs to MLLMs. Additionally, we employ age of information to indirectly evaluate the data freshness impact of MLLMs and utilize contract theory to incentivize healthcare data holders to share their fresh data, mitigating information asymmetry during data sharing. Finally, we utilize a generative diffusion model-based deep reinforcement learning algorithm to identify the optimal contract for efficient data sharing. Numerical results demonstrate the effectiveness of the proposed schemes, which achieve secure and efficient healthcare data management. Copyright © 2024, The Authors. All rights reserved.

关键词： Information management

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Online Non-Contact Weighing Duck Carcasses Using 2d Images and Deep Learning

SSRN

引用

SSRN 2022年

作者： Zhao, Yuliang Tian, Kaixuan Chen, Ruoyu Yang, Yongliang School of Control Engineering Northeastern University Hebei Qinhuangdao066001 China Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Qinhuangdao066004 China School of Cyber Security University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China

In the poultry meat processing industry, non-contact weighing methods based on computer vision have become increasingly popular due to their low costs and high efficiency. However, the accuracy of the traditional 2D image weighing techniques is reduced by the overlap and sway of carcasses. In this paper, we propose a more accurate regression model, Vggx, to weigh duck carcasses through image processing and deep learning. We adopt an image segmentation technique to obtain 2D images of a single duck section under a complex background. The images of the same duck are fused together to estimate its 3D information. Then, we use a convolutional neural network regression model to estimate the weight of duck carcass with the acquired 3D information. The Mean Absolute Percentage Error of our model is 1.46% and the average weight error of our model is 23.1 gram. Experimental results demonstrate that our method is high performance. © 2022, The Authors. All rights reserved.

关键词： Image segmentation

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THE THERMAL DECOMPOSITION CHARACTERISTICS OF HFO1234ze(E) GAS FOR MV EQUIPMENT 22

THE THERMAL DECOMPOSITION CHARACTERISTICS OF HFO1234ze(E) GA...

引用

22nd International Symposium on High Voltage Engineering, ISH 2021

作者： Li, Long Li, Zhen Li, Ke Yao, Qiang Xiao, Song Li, Yi Lin, Chao Wu, Haoying State Grid Chongqing Electric Power Company Electric Power Research Institute Jiangbei District Chongqing401123 China School of Electrical Engineering and Automation Wuhan University Wuhan430072 China State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing University Chongqing400044 China

ISBN: (纸本)9781839536052

Gas insulating medium SF6, which is widely used in high voltage electrical equipment, has serious greenhouse effect. HFO1234ze(E) has very low greenhouse effect, low liquefaction temperature (-19°C) and excellent insulation performance, so it has great application potential as a new eco-friendly insulation gas. In this paper, the partial overheating decomposition characteristics of HFO1234ze(E) gas under different temperatures (150-400°C) were explored through experiments. It was found that HFO1234ze(E) did not decompose at 150°C to 200°C, and the isomer HFO1234ZE (Z) was produced at 250°C. With the increase of temperature from 250°C to 300°C, the yield of HFO1234ze(Z) did not increase much. When the temperature was higher than 350°C, the decomposition of HFO1234ze(E) intensified, and when the temperature reached 400°C, the gas would decompose violently, and other decomposition products would be produced. Meanwhile, the decomposition mechanism of HFO1234ze(E) under partial overheating fault was investigated using density functional theory (DFT). The research conclusions in this article provide theoretical guidance for the application of HFO1234ze(E). © 2021 The Institution of Engineering and technology.

关键词： Greenhouse effect

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Characteristics of Glass Insulator Hot Water Deicing 3

Characteristics of Glass Insulator Hot Water Deicing

引用

3rd International Conference on Electrical Materials and Power Equipment, ICEMPE 2021

作者： Ma, Xiaohong He, Bingzhe Zhang, Zhijin Yang, Qi Zhang, Lusong Huang, Huan Electric Power Research Institute State Guizhou Power Grid Co. Ltd Guizhou China Chongqing University State Key Laboratory of Power Transmission Equipment System Security and New Technology Chongqing China Electric Power Research Institute Guizhou Power Grid Co. Ltd Guizhou China

ISBN: (纸本)9781665418409

Hot water is a kind of deicing medium with wide sources, and the impact force of its ejection is easy to control to avoid damaging the surface of glass insulator. In order to reveal the influencing factors of hot water deicing and their effect on the deicing time of glass insulator, an experiment was conducted where LXY-120 glass insulator was selected to measure the hot water deicing time under different circumstances. The results show that initial water temperature has significant effect on deicing time. At certain range, deicing time can be greatly reduced as initial water temperature increases, and it also affects deicing time increasement caused by heavier ice weight. Ejection distance and outlet pressure both have near linear relation with deicing time. It concluded that when conducting hot water deicing, on the premise of ensuring safety distance, shortening deicing distance, optimizing outlet pressure and initial water temperature can improve the ice melting efficiency. © 2021 IEEE.

关键词： Snow and ice removal

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Aerodynamic load extraction in the real-time hybrid model test for floating wind turbine

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Ocean Engineering 2025年 333卷

作者： Jiang, Zhihao Gao, Yuning Tian, Xinliang Chen, Gang Wen, Binrong Peng, Zhike Zhang, Wei Yang, Mindong Gao, Yang State Key Laboratory of Ocean Engineering Shanghai Jiao Tong University Shanghai200240 China SJTU Yazhou Bay Institute of Deepsea Technology Sanya57200 China State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai200240 China School of Mechanical Engineering Ningxia University Yinchuan750021 China CPI Xinjiang Energy & Chemical Group Bozhou Co. Ltd Bozhou833400 China China Energy Engineering Group Guangdong Electric Power Design Institute Co. Ltd. Guangzhou510663 China Goldwind Sci & Tech Co. Ltd. Beijing100176 China

Physical model test is of great importance in testing new concepts in the field of ocean engineering, and floating wind turbine (FWT), a newly emerging renewable energy developing equipment, is of no exception. However, with the development trend of FWTs towards deeper waters and larger sizes, challenges and higher demands of physical model test are raised. Therefore, the real-time hybrid testing (RTHT) method is a new approach to breakthrough. And the RTHT method in wind tunnel can be applied to evaluate the aerodynamic performance, the control strategy of the wind turbine and the coupling effects between the wind turbine and floating support. This technical route highly relies on the real-time data interaction and aerodynamic load extraction. In the work of this paper, the aerodynamic load extraction method based on load and acceleration measurements is adopted. The performance of the method was evaluated under both steady wind and turbulent wind cases. Then the influence of parametric errors in mass and inertia of the model wind turbine on the RTHT system operation was studied through turbulent wind and irregular wave joint cases. The results indicate that the adopted load extraction method can properly identify the aerodynamic load in the real time. The studied RTHT system is more sensitive to gravitational parameter error than to the inertial parameter error. Under the same level of error, the reproduction of pitch motion is more sensitive among the 3 main discussed degrees of freedom. The study in this paper provides references and support for the data interaction and processing during the practice of the RTHT in wind tunnel. © 2025 Elsevier Ltd

关键词： Ocean engineering

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