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第34届中国过程控制会议

作者： Jie Song Tao Zhang Mi Li Department of Automation Faculty of Information TechnologyBeijing University of Technology Beijing International Collaboration Base on Brain Informatics and Wisdom Services Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Engineering Research Center of Digital Community Ministry of Education

Depression is a widespread emotional disorder that is marked by a lasting and intense feeling of sadness,diminished enthusiasm,an absence of joy,and difficulty in *** this study,we first constructed a fuzzy RBF neural network model that conforms to fuzzy reasoning logic for depression symptom *** then employed the fuzzy c-means technique to establish the starting values for the three crucial parameters of the ***,grounded in the traits of parameter training,we proposed a method to optimize network parameter *** the practical application of depression symptom evaluation,we collected emotional conflict decision-making behavior data from 86 patients with *** this basis,we completed feature construction,feature normalization and feature dimensionality *** emotional conflict features and fuzzy RBF neural network to predict the PHQ-9 scores of patients with depression,we finally obtained an MAE of 3.84 and an RMSE of 4.98.

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What is the cost and potential of low carbon electricity transition in the MENA region?

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Energy Strategy Reviews 2025年 59卷

作者： Bamisile, Olusola Xing, Yankai Acen, Caroline Cai, Dongsheng Zhang, Guangdou Adun, Humphrey Staffell, Iain Electrical Engineering Department College of Nuclear Science and Automation Engineering Chengdu University of Technology Sichuan China Centre for Environmental Policy Faculty of Natural Science Imperial College London United Kingdom Energy and Environmental Science Division CEPMLP University of Dundee United Kingdom Department of Electrical Engineering State Key Laboratory of Power System Operation and Control Tsinghua University China Operational Research Centre in Healthcare Near East University TRNC Mersin 10 Nicosia99138 Turkey

Replacing fossil fuels with renewable energy sources, including wind and solar power, is a validated approach for mitigating carbon emissions. To maximize renewable energy potential and account for costs and impacts of low carbon energy transitions, research models or modelling tools must provide an accurate representation of the technological and economic capabilities of renewable energy technologies. Hence, this study assesses the electricity generation potential, and costs associated with onshore and offshore wind power, and solar photovoltaic (PV) system, in the Middle East and North Africa (MENA) region based on wind and solar atlas datasets. Unlike existing works in literature, the assessment of offshore wind energy potential and the calculation of the levelized cost of electricity (LCOE) in this study incorporates factors like water depth, distance from shore, and wind speed. Also, the potential of onshore wind energy and solar photovoltaic systems is evaluated by considering variables such as population density, availability of suitable land area, and geographical location, for every grid cell in the MENA region. We found that the average LCOE can be as low as US$40/MWh for solar PV and US$45/MWh for wind power, achieved in Saudi Arabia and Kuwait respectively. This work contributes to existing literature by providing reliable LCOE, capacity factor, and productivity data for solar and wind energy potential estimation in the MENA region. © 2025 The Authors

关键词： Solar fuels

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NanoNeRF: Robot-assisted Nanoscale 360° reconstruction with neural radiance field under scanning electron microscope

NanoNeRF: Robot-assisted Nanoscale 360° reconstruction with...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Xiang Fu Yifan Xu Shudong Wang Haojian Lu Jiaqi Li Youfu Li Hu Su Song Liu School of Information Science and Technology ShanghaiTech University Shanghai China School of Electrical Engineering Xian Jiaotong University and With State Key Laboratory of Electrical Insulation and Power Equipment Xi an School of the College of Control Science and Engineering Zhejiang University China Institute of Cyber-Systems and Control Hangzhou Department of Mechanical Engineering City University of Hong Kong Kowloon HK Institute of Automation Chinese Academy of Sicence Beijing China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

The pursuit of 3D reconstruction from 2D images for nanomanipulation under scanning electron microscopy stands as a critical research endeavor. Previous methods either necessitates additional lighting which is difficult in standard SEM devices or relies on feature matching with low resolution and precision, further constraining reconstruction performance. In this paper, we propose a novel robot-assisted nanoscale 360° reconstruction approach, which simplifies SEM setups and maximizes the utilization of robot motion and feedback. By harnessing a nanorobotic system, we capture 360°multi-view images automatically with precise mapping information and camera postures. Sequentially, neural radiance field reconstruct the pixel-wise structure and synthesizing images from diverse perspectives. Experimental results using two real datasets demonstrates our approach’s efficacy, achieving PSNR of 28.1 and SSIM of 0.93 for nanotube reconstruction, and PSNR of 32.8 and SSIM of 0.98 for AFM cantilever reconstruction. These results validate the reliability and robustness of our proposed robot-assisted reconstruction method.

关键词： Robot motion Scanning electron microscopy Three-dimensional displays Robot kinematics Robot vision systems Neural radiance field Robustness Nanoscale devices Image reconstruction Standards

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Hardware-in-the-Loop Simulation of Vehicle-Manipulator Systems for Physical Interaction Tasks

Hardware-in-the-Loop Simulation of Vehicle-Manipulator Syste...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Hemjyoti Das Bjørn Kåre Sæbø Kristin Y. Pettersen Christian Ott Faculty of Electrical Engineering and Information Technology Automation and Control Institute (ACIN) Technical University of Vienna TU Wien Vienna Austria Department of Engineering Cybernetics Centre for Autonomous Marine Operations and Systems (NTNU AMOS) NTNU Norwegian University of Science and Technology Trondheim Norway German Aerospace Center Institute of Robotics and Mechatronics Wessling Germany

Hardware-in-the-loop simulation (HILS) allows a more realistic evaluation of control approaches than what is possible with pure software simulations, but without the actual complexity of the complete system. This is important for some complex systems such as orbital robots, where testing of the system is typically not possible after its launch, and an on-ground replica is used to validate the performance of such a system. In this article, an impedance-matching approach is presented to match the end-effector dynamics of a fixed-base robot manipulator with that of a target vehicle-manipulator system (VMS), while taking into account the redundant nullspace dynamics in a connected real-time simulation framework. This approach ensures that the forces and torques exerted by the system on the environment matches with that of the simulated system. The contact wrenches used in our approach are not obtained from numerical simulations, but rather from real physical interaction, which is one of the main advantages of our approach. The effectiveness of our method is validated by demonstrating various physical interaction tasks with the environment, using a suspended aerial manipulator as the target system.

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Research on two-dimensional code scanning and automatic recording device for human body temperature measurement based on stm32

Research on two-dimensional code scanning and automatic reco...

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Electronic information engineering and Computer technology (EIECT), International Conference on

作者： XueYan Lie XiaoPeng Huang HuanYu Liu YanLong Li Hua Zhong FeiFei Gao Department of Electrical Engineering and Automation University of South China China Department of Electronic Information Engineering University of South China China Department of Measurement and Control Technology University of South China China

With the outbreak and normal development of COVID-19, the effective detection and recording of body temperature has become a new focus of our attention. At present, there is no complete system to measure temperature, automatic record and specific information at home and abroad. To this end, combined with professional knowledge, our team designed a two-dimensional code scanning and human body temperature automatic recording device with STM32F1 as the core. The device STM32F1 development board is the main control chip. By connecting the WIFI module through the serial port, STM32F1 uses the function of wireless communication. Through the communication protocol, the link between the router and the ESC cloud server of Ali Cloud is utilized. The router or mobile data is transmitted to the user side (APP, applets) according to the specified communication protocol. Inside the development board, the code of each part is written to complete the device integrating code scanning and temperature measurement, which can be displayed and alarm through the node (OLED display screen). This will play a good role in preventing the spread of COVID-19. The system can be used in hospitals, communities, railway stations, shopping malls and many other public places.

关键词： Temperature measurement COVID-19 Wireless communication Codes Clouds Routing protocols Real-time systems

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Solar Radiation Forecasting Based on Random Forest and XGBoost

Solar Radiation Forecasting Based on Random Forest and XGBoo...

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International Conference on Green technology and Sustainable Development (GTSD)

作者： Nhat-Truong Nguyen Thai Cat Tuong Dao Le Nhut Tuyen Nguyen Thanh-Dat Nguyen Minh-Vuong Le Isobel Timothea French Van-Tuong Doan Van Hoang Kim Vo Nghi C. Tran Duc-Hung Pham Van-Trung Nguyen Department of Renewable Energy Ho Chi Minh City University of Technology and Education Vietnam Department of Control Engineering and Automation Ho Chi Minh City Industry and Trade College Vietnam LILAMA2 International Technology College Dongnai Viet Nam Institute of Cognitive Neuroscience National Central University Taiwan College of Information and Communication Technology Can Tho University Viet Nam Faculty Electrical and Electronic Engineering Hung Yen University of Technology and Education VietNam

ISBN: (数字)9798350386073

ISBN: (纸本)9798350386080

Renewable energy offers a viable alternative to depleting fossil fuels, contributing to global warming and greenhouse gas emissions. Thus, solar energy is widely favored as a renewable energy source. However, the output power of solar systems is unstable and is highly dependent on environmental circumstances such as radiation, humidity, temperature, and wind. Therefore, accurately estimating solar radiation is crucial for successful integration of the solar system into existing electrical grid systems. In this study, two different machine learning models, XGBoost and Random Forest, were used to predict solar radiation data in Ho Chi Minh City, Vietnam. The results show that RMSE and MAE of the Random Forest model (61.09 and 24.37) is smaller compared to XGBoost (61.31 and 25.08). Regression value of the two models is close to 0.955. In summary, this paper demonstrates that these two machine learning algorithms effectively forecast solar radiation, with the Random Forest model showing better performance.

关键词： Renewable energy sources Temperature distribution Temperature dependence Urban areas Humidity Predictive models Solar system

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Code Converters Based on a Dynamic Optical RAM for information System Facilities

Code Converters Based on a Dynamic Optical RAM for Informati...

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IEEE International Conference on Electronics and Nanotechnology (ELNANO)

作者： Andriy Semenov Serhii Tsyrulnyk Olena Semenova Anton Khloba Andrii Rudyk Serhii Baraban Faculty of Information Electronic Systems Vinnytsia National Technical University Vinnytsia Ukraine Department of Computer Science and Economic Cybernetics Vinnytsia National Agrarian University Vinnytsia Ukraine Department of Automation Electrical Engineering and Computer-Integrated Technologies National University of Water and Environmental Engineering Rivne Ukraine Faculty of Computing and Telecommunications Poznan University of Technology Poznan Poland

ISBN: (数字)9798350368178

ISBN: (纸本)9798350368185

In this paper, the authors propose a new dynamic optical RAM based on a fiber-optic line. This device significantly increases the speed of information flows by reducing the time required to operate the RAM by 10. The proposed optical RAM increases the productivity and efficiency of information exchange between slow and fast devices of information and communication systems without software costs, which reduces the probability of failure by two times with the same buffer memory capacity. The authors proposed variants of the practical application of the new dynamic optical RAM. On its basis, a shift register, a serial-to-parallel code converter, a parallel-to-serial code converter, and a TDM switch for information system facilities were created. The time characteristics of signals in code converters based on a dynamic optical RAM are presented.

关键词： Optical fibers Codes Optical switches Optical buffering Random access memory Time division multiplexing Shift registers Optical fiber devices High-speed optical techniques information systems

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Two-Operation Buffering based on Dynamic Optical RAM

Two-Operation Buffering based on Dynamic Optical RAM

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International Conference on Modern Problems of Radio engineering, Telecommunications and Computer Science

作者： Andriy Semenov Serhii Tsyrulnyk Serhii Baraban Olena Semenova Andrii Rudyk Anton Khloba Faculty of Information Electronic Systems Vinnytsia National Technical University Vinnytsia Ukraine Department of Computer Sciences and Digital Economy Vinnytsia National Agrarian University Vinnytsia Ukraine Faculty of Computing and Telecommunications Poznan University of Technology Poznan Poland Department of Automation Electrical Engineering and Computer-Integrated Technologies National University of Water and Environmental Engineering Rivne Ukraine

ISBN: (数字)9798331520564

ISBN: (纸本)9798331520571

The authors of this paper propose a block diagram for a dual-operating buffer on a dynamic optical RAM. The buffer consists of two dynamic optical RAMs, each controlled separately to allow for simultaneous writing and reading of data, thereby improving performance. This setup enables data to be read from the buffer while new data is being written to it. Implementing a dual-operating buffer on a dynamic optical RAM has the potential to enhance the performance of high-speed data transmission in telecommunications networks. The authors conducted numerical calculations to compare failure probabilities between single-operation and dual-operation buffers on dynamic optical RAM. The results indicated that using a dual-operating buffer significantly reduces the probability of failure with the same buffer memory capacity compared to a single-operating buffer. Additionally, the authors analyzed the effectiveness of the proposed dual-operating buffer. The analysis confirmed that exploiting dynamic optical memory for buffering enhances data transfer speed and efficiency due to the inherent properties of optical data transfer, such as high bandwidth and low latency.

关键词： Optical buffering Random access memory Probability Optical fiber networks Writing Data transfer Software Telecommunications High-speed optical techniques Capacity planning

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Reconstruction of Particle Flow Energy Distribution Using Deep Learning Algorithms

arXiv

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arXiv 2024年

作者： Zhang, Han Lin, Shengxiang Zhang, Xingyi Wang, Yu Zhang, Yangguang College of Aritificial Intelligence and Automation Hohai University Nanjing211100 China Faculty of Electronic and Information Engineering Xi’an Jiaotong University Xi’an710049 China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China School of Control and Computer Engineering North China Electric Power University Beijing071003 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China

In high-energy particle physics, extracting information from complex detector signals is crucial for energy reconstruction. Recent advancements involve using deep learning to process calorimeter images from various sub-detectors in experiments like the Large Hadron Collider (LHC) for energy map reconstruction. This paper compares classical algorithms—MLP, CNN, U-Net, and RNN—with variants that include self-attention and 3D convolution modules to evaluate their effectiveness in reconstructing the initial energy distribution. Additionally, a test dataset of jet events is utilized to analyze and compare models’ performance in handling anomalous high-energy events. The analysis highlights the effectiveness of deep learning techniques for energy image reconstruction and explores their potential in this area. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep learning

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Spirometer and sEMG respiratory patterns for clinical decision support system

Spirometer and sEMG respiratory patterns for clinical decisi...

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IEEE Instrumentation and Measurement technology Conference

作者： Amit Krishan Kumar Mansour H. Assaf Voicu Z. Groza Emil M. Petriu Faculty of Electrical-Electronic Engineering Duy Tan University Da Nang Vietnam Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing China School of Information Technology Engineering Mathematics and Physics The University of the South Pacific Suva Republic of Fiji School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

To improve support system for subjects with respiratory ailments, this work analyses the respiratory patterns from spirometer and surface electromyography (sEMG). The patterns are integrated with risk and biochemical systems model to optimise the clinical decision support system (CDSS). The work considers terminal events for the spirometer and sEMG. The events and their associated patterns are correlated and projected on a hyperspace prior implementing it in decision support system. The proposed method shows that the different characteristics of breathing indicate some essential hidden information which when used as 4D scattered projection, optimises the decision making in CDSS. The analysis shows the effectiveness of bimodal respiratory patterns for different breathing capacities, which is promising for the modelled conditions.

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