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Online Optimization in Power Systems With High Penetration of Renewable Generation:Advances and Prospects

IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 839-858页

作者： Zhaojian Wang Wei Wei John Zhen Fu Pang Feng Liu Bo Yang Xinping Guan Shengwei Mei Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of AutomationShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Power System and the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Institute of High Performance Computing(IHPC) Agency for Science Technology and Research(A*STAR)Singapore 138632Singapore

Traditionally,offline optimization of power systems is acceptable due to the largely predictable loads and reliable *** increasing penetration of fluctuating renewable generation and internet-of-things devices allowing for fine-grained controllability of loads have led to the diminishing applicability of offline optimization in the power systems domain,and have redirected attention to online optimization ***,online optimization is a broad topic that can be applied in and motivated by different settings,operated on different time scales,and built on different theoretical *** paper reviews the various types of online optimization techniques used in the power systems domain and aims to make clear the distinction between the most common techniques *** particular,we introduce and compare four distinct techniques used covering the breadth of online optimization techniques used in the power systems domain,i.e.,optimization-guided dynamic control,feedback optimization for single-period problems,Lyapunov-based optimization,and online convex optimization techniques for multi-period ***,we recommend some potential future directions for online optimization in the power systems domain.

关键词： optimization Lyapunov optimization online convex optimization online optimization optimization-guided control

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Blood pressure monitoring via double sandwich-structured triboelectric sensors and deep learning models

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Nano Research 2022年第6期15卷 5500-5509页

作者： Xu Ran Fangyuan Luo Zhiming Lin Zhiyuan Zhu Chuanjun Liu Bin Chen Chongqing Key Laboratory of Non-linear Circuit and Intelligent Information Processing College of Electronic and Information EngineeringSouthwest UniversityChongqing 400715China Research Laboratory U.S.E.Co.Ltd.Shibuya-kuTokyo 150-0013Japan

Real-time blood pressure monitoring is essential for the timely diagnosis and treatment of cardiovascular *** traditional prediction methods estimate blood pressure by measuring multiple sets of physiological signals with energyconsuming ***,a continuous,cuffless and self-powered blood pressure monitoring system was developed based on a new double sandwich-structured triboelectric sensor and a novel blood pressure method estimation.A pyramid-patterned sensor based on the double sandwich structure realizes a sensitivity of 0.89 V/kPa in a linear range of 0–35 kPa,which is more than twice of the conventional single electrode *** sensor processes a low pressure detection limit of 1 g andfast response time of 32 ***,it can easily capture the pulse signal at the radial ***,a novel method for estimating blood pressure using pulse waves accompanied by the user’s background information was *** method measures only one set of pulse signals and is portable.A deep learning model with multi-network structures was developed to improve the estimation *** mean absolute error and standard deviation of error for systolic and diastolic blood pressure(SBP and DBP)estimations were 3.79±5.27 and 3.86±5.18 mmHg,*** work reveals a new sensing structure of triboelectric sensors and offers a novel method for blood pressure estimation.

关键词： triboelectric nanogenerator self-powered sensor blood pressure monitoring deep learning

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AlphaFold2 and its applications in the fields of biology and medicine

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Signal Transduction and Targeted Therapy 2023年第4期8卷 1630-1643页

作者： Zhenyu Yang Xiaoxi Zeng Yi Zhao Runsheng Chen West China Biomedical Big Data Center West China HospitalSichuan UniversityChengdu 610041China Key Laboratory of Intelligent Information Processing Advanced Computer Research CenterInstitute of Computing TechnologyChinese Academy of SciencesBeijing 100190China Key Laboratory of RNA Biology Center for Big Data Research in HealthInstitute of BiophysicsChinese Academy of SciencesBeijing 100101China Pingshan Translational Medicine Center Shenzhen Bay LaboratoryShenzhen 518118China

AlphaFold2(AF2)is an artificial intelligence(AI)system developed by DeepMind that can predict three-dimensional(3D)structures of proteins from amino acid sequences with atomic-level *** structure prediction is one of the most challenging problems in computational biology and chemistry,and has puzzled scientists for 50 *** advent of AF2 presents an unprecedented progress in protein structure prediction and has attracted much *** release of structures of more than 200 million proteins predicted by AF2 further aroused great enthusiasm in the science community,especially in the fields of biology and ***2 is thought to have a significant impact on structural biology and research areas that need protein structure information,such as drug discovery,protein design,prediction of protein function,et *** the time is not long since AF2 was developed,there are already quite a few application studies of AF2 in the fields of biology and medicine,with many of them having preliminarily proved the potential of *** better understand AF2 and promote its applications,we will in this article summarize the principle and system architecture of AF2 as well as the recipe of its success,and particularly focus on reviewing its applications in the fields of biology and *** of current AF2 prediction will also be discussed.

关键词： system fields Fold

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Integrating Conjugate Gradients Into Evolutionary Algorithms for Large-Scale Continuous Multi-Objective Optimization

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1801-1817页

作者： Ye Tian Haowen Chen Haiping Ma Xingyi Zhang Kay Chen Tan Yaochu Jin the Information Materials and Intelligent Sensing Laboratory of Anhui Province Institutes of Physical Science and Information TechnologyAnhui UniversityHefei 230601China the Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230601China IEEE the Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial IntelligenceAnhui UniversityHefei 230601China the Department of Computing The Hong Kong Polytechnic UniversityHong Kong SARChina the Faculty of Technology Bielefeld UniversityBielefeld 33619Germany

Large-scale multi-objective optimization problems(LSMOPs)pose challenges to existing optimizers since a set of well-converged and diverse solutions should be found in huge search *** evolutionary algorithms are good at solving small-scale multi-objective optimization problems,they are criticized for low efficiency in converging to the optimums of *** contrast,mathematical programming methods offer fast convergence speed on large-scale single-objective optimization problems,but they have difficulties in finding diverse solutions for ***,how to integrate evolutionary algorithms with mathematical programming methods to solve LSMOPs remains *** this paper,a hybrid algorithm is tailored for LSMOPs by coupling differential evolution and a conjugate gradient *** the one hand,conjugate gradients and differential evolution are used to update different decision variables of a set of solutions,where the former drives the solutions to quickly converge towards the Pareto front and the latter promotes the diversity of the solutions to cover the whole Pareto *** the other hand,objective decomposition strategy of evolutionary multi-objective optimization is used to differentiate the conjugate gradients of solutions,and the line search strategy of mathematical programming is used to ensure the higher quality of each offspring than its *** comparison with state-of-the-art evolutionary algorithms,mathematical programming methods,and hybrid algorithms,the proposed algorithm exhibits better convergence and diversity performance on a variety of benchmark and real-world LSMOPs.

关键词： Conjugate gradient differential evolution evolutionary computation large-scale multi-objective optimization mathematical programming

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Experiment on protection performance of plasma array to 6GHz high-power microwave

Experiment on protection performance of plasma array to 6GHz...

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2023 Advanced Fiber Laser Conference, AFL 2023

作者： Liu, Yang Lv, Shouye Li, Jinzhou Meng, Gang Liao, Shuai Shi, Jiaming Satellite Information Intelligent Processing and Application Research Laboratory Beijing Institute of Remote Sensing Information Beijing100192 China State Key Laboratory of Pulsed Power Laser Technology National University of Defense Technology Hefei230037 China

ISBN: (纸本)9781510677661

For purpose of the electromagnetic pulse (EMP) protection research, a double-layer barrier of cylindrical plasma array was designed, and its protective performance to 6GHz high-power microwave (HPM) was conducted experimentally. Combining the distribution of the discharge plasma array, the shielding effectiveness of the double-layer plasma on 6GHz HPM pulse was studied. The main research contents and conclusions are as follows: The transmission energy of HPM decreased as the increase of plasma electron density, indicating an improved protection effect, with both double-layer and single-layer plasma array. Besides, the results showed that the transmission attenuation of HPM in double-layer structure was greater than that in single-layer structure because of the interlayer reflection. In addition, an interesting phenomenon was discovered during the experiment, which was that the boundary plasma units had a significant impact on the HPM transmission. The shielding effect of HPM was better with opening seven plasma units than that with opening whole plasma array. Finally, the spectral characteristics and transmission coefficients of the HPM were presented by Fourier transform, and the results of the protective performance were consistent with the above-mentioned time-domain analysis. The experiment results in this paper are of great significance in protecting against HPM based on plasma. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Carrier concentration

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Fundamental Limits of Multiple-Access Integrated Sensing and Communication Systems

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IEEE Transactions on information Theory 2025年第6期71卷 4317-4341页

作者： Liu, Yao Li, Min Liu, An Ong, Lawrence Yener, Aylin Zhejiang University College of Information Science and Electronic Engineering Zhejiang Provincial Key Laboratory of Multi-Modal Communication Networks and Intelligent Information Processing Hangzhou310027 China University of Newcastle School of Engineering CallaghanNSW2308 Australia The Ohio State University Department of Electrical and Computer Engineering ColumbusOH43210 United States

A state-dependent discrete memoryless multiple access channel is considered to model an integrated sensing and communication system, where two transmitters wish to convey messages to a receiver while simultaneously estimating the state parameter sequences through echo signals. In particular, the sensing state parameters are assumed to be correlated with the channel state. In this setup, improved inner and outer bounds for capacity-distortion region are derived. The inner bound is based on an achievable scheme that combines message cooperation and joint compression of past transmitted codewords and echo signals at each transmitter, resulting in unified cooperative communication and sensing. The outer bound is based on the ideas of dependence balance for communication rate, genie-aided state estimator and rate-limited constraints on sensing distortion. The proposed inner and outer bounds are proved to improve the state-of-the-art bounds. Finally, numerical examples are provided to demonstrate that our new inner and outer bounds strictly improve the existing results. © 1963-2012 IEEE.

关键词： Signal distortion

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Deep Learning Algorithm for Person Re-Identification Based on Dual Network Architecture

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Computers, Materials & Continua 2025年第5期83卷 2889-2905页

作者： Meng Zhu Xingyue Wang Honge Ren Abeer Hakeem Linda Mohaisen College of Information Engineering Harbin UniversityHarbin150086China Heilongjiang Provincial Key Laboratory of the Intelligent Perception and Intelligent Software Harbin UniversityHarbin150086China College of Computer and Control Engineering Northeast Forestry UniversityHarbin150040China Heilongjiang Forestry Intelligent Equipment Engineering Research Center Northeast Forestry UniversityHarbin150040China Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia

Changing a person’s posture and low resolution are the key challenges for person re-identification(ReID)in various deep learning *** this paper,we introduce an innovative architecture using a dual attention network that includes an attentionmodule and a joint measurement module of spatial-temporal *** proposed approach can be classified into two main ***,the spatial attention feature map is formed by aggregating features in the spatial ***,the same operation is carried out on the channel dimension to formchannel attention ***,the receptive field size is adjusted adaptively tomitigate the changing person posture ***,we use a joint measurement method for the spatial-temporal information to fully harness the data,and it can also naturally integrate the information into the visual features of supervised ReID and hence overcome the low resolution *** experimental results indicate that our proposed algorithm markedly improves the accuracy in addressing changing human postures and low-resolution issues compared with contemporary leading *** proposed method shows superior outcomes on widely recognized benchmarks,which are the Market-1501,MSMT17,and DukeMTMC-reID ***,the proposed algorithmattains a Rank-1 accuracy of 97.4% and 94.9% mAP(mean Average Precision)on the Market-1501 ***,it achieves a 94.2% Rank-1 accuracy and 91.8% mAP on the DukeMTMC-reID dataset.

关键词： Person reidentification ReID computer vision self-attention spatial-temporal information

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MCIF-Transformer Mask RCNN:Multi-Branch Cross-Scale Interactive Feature Fusion Transformer Model for PET/CT Lung Tumor Instance Segmentation

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Computers, Materials & Continua 2024年第6期79卷 4371-4393页

作者： Huiling Lu Tao Zhou School of Medical Information&Engineering Ningxia Medical UniversityYinchuan750004China School of Computer Science and Engineering North Minzu UniversityYinchuan750021China Key Laboratory of Image and Graphics Intelligent Processing of State Ethnic Affairs Commission NorthMinzu UniversityYinchuan750021China

The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided ***,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are complex,the edges are blurred,and the sample numbers are *** solve these problems,this paper proposes a Multi-branch Cross-scale Interactive Feature fusion Transformer model(MCIF-Transformer Mask RCNN)for PET/CT lung tumor instance segmentation,The main innovative works of this paper are as follows:Firstly,the ResNet-Transformer backbone network is used to extract global feature and local feature in lung *** pixel dependence relationship is established in local and non-local fields to improve the model perception ***,the Cross-scale Interactive Feature Enhancement auxiliary network is designed to provide the shallow features to the deep features,and the cross-scale interactive feature enhancement module(CIFEM)is used to enhance the attention ability of the fine-grained ***,the Cross-scale Interactive Feature fusion FPN network(CIF-FPN)is constructed to realize bidirectional interactive fusion between deep features and shallow features,and the low-level features are enhanced in deep semantic ***,4 ablation experiments,3 comparison experiments of detection,3 comparison experiments of segmentation and 6 comparison experiments with two-stage and single-stage instance segmentation networks are done on PET/CT lung medical image *** results showed that APdet,APseg,ARdet and ARseg indexes are improved by 5.5%,5.15%,3.11%and 6.79%compared with Mask RCNN(resnet50).Based on the above research,the precise detection and segmentation of the lesion region are realized in this *** method has positive significance for the detection of lung tumors.

关键词： PET/CT images instance segmentation mask RCNN interactive fusion transformer

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Unveiling High-speed Follow-up Consultation for Chronic Disease Treatment: A Pediatric Hospital Case in China

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Proceedings of the ACM on Human-Computer Interaction 2022年第CSCW2期6卷 1-29页

作者： Fu, Jiaojiao Zhou, Yangfan Wang, Xin School of Computer Science Fudan University China Shanghai Key Laboratory of Intelligent Information Processing 220 Handan Rd. Shanghai200433 China

In developing countries suffering from a severe shortage of physicians, the follow-up clinical consultation of long-term chronic care becomes a high-speed collaborative work, which has to be conducted in a few minutes. Although much existing work studies how time factors affect physicians' workflows and requirements for information systems, high-speed chronic care is yet to be well investigated. This work bridges the gap by presenting a case of a pediatric hospital in China. We focus on the processes of follow-up consultations, the factors enabling physicians to complete consultation in several minutes, as well as the challenges faced by physicians and patients. Through observations and interviews, we find that physicians conduct multiple tasks (information acquisition, patient-provider communication, and medical data documentation) simultaneously to reduce the consultation duration. Adopting an information summary alternative is the key to fast information acquisition. Templates and references in EMR contribute to rapid documentation and prescription. However, multitasking brings physicians a heavy cognitive load. It also severely compresses the duration of patient-provider communication. As a result, some of the patients' needs, especially emotional ones, are neglected. Based on these findings, we discuss the characteristics and requirements of high-speed chronic care and accordingly propose design suggestions. © 2022 ACM.

关键词： Hospitals

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Improving millimeter-wave imaging quality using the vortex phase method

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Defence Technology（防务技术） 2024年第9期39卷 193-202页

作者： Nairui Hu Feng Qi Yelong Wang Zhaoyang Liu Pengxiang Liu Weifan Li Key Laboratory of Terahertz Imaging and Sensing Shenyang 110169China Shenyang Aerospace University Shenyang 110136China Key Laboratory of Opto-Electronic Information Processing Chinese Academy of SciencesShenyang 110169China Shenyang Institute of Automation Chinese Academy of SciencesShenyang 110169China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China University of Chinese Academy of Sciences Beijing 100049China

This paper investigates a new vortex wave imaging approach to improve the imaging quality of small metal targets of size less than 1.5 *** with different spiral phase plates are designed to efficiently transmit vortex beams with orbital angular momentums(OAMs).By analyzing the OAM spectrum of the target,it was discovered that the predominant reflection contains a particular OAM mode that carries abundant azimuthal *** can be explained by the OAM selectivity of the target and the guidance of the vortex transmitting beam.A simple reflection vortex imaging system was designed to capture the phase *** results show that the high image contrast reaches 14.9%,which is twice as high as that of the imaging without *** of simulations and experiments demonstrate that the vortex phase imaging approach proposed in this paper can effectively improve the imaging quality at 80 *** approach is suitable for other millimeter wave imaging systems and is helpful to improve the resolution in anti-terrorism security checks.

关键词： Orbital angular momentums(OAMs)beams Focal plane imaging Spiral phase plates(SPPs) Vortex spectrum

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