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Machine learning for online control of particle accelerators

science China(Physics,Mechanics & Astronomy) 2025年第2期68卷 94-104页

作者： Xiaolong Chen Zhijun Wang Yuan He Hong Zhao Chunguang Su Shuhui Liu Weilong Chen Xiaoying Zhao Xin Qi Kunxiang Sun Chao Jin Yimeng Chu Hongwei Zhao Institute of Modern Physics Chinese Academy of SciencesLanzhou 730000China School of Nuclear science and Technology Lanzhou UniversityLanzhou 730000China School of Nuclear science and Technology University of Chinese Academy of SciencesBeijing 100049China Advanced Energy science and Technonlogy Guangdong Laboratory Huizhou 516000China department of Physics Xiamen UniversityXiamen 361005China

Particle accelerators play a critical role in modern scientific ***,existing manual beam control methods heavily rely on experienced operators,leading to significant time consumption and potential challenges in managing next-generation accelerators characterized by higher beam current and stronger nonlinear *** this paper,we establish a dynamical foundation for designing the online adaptive controller of accelerators using machine *** provides a guarantee for dynamic controllability for a class of scientific instruments whose dynamics are described by spatial-temporal equations of motion but only part variables along the instruments under steady states are *** necessity of using historical time series of beam diagnostic data is *** strategies involve also employing a well-established virtual beamline of accelerators,by which various beam calibration scenarios that actual accelerators may encounter are *** the reinforcement learning algorithm is adopted to train the controller with the interaction to the virtual ***,the controller is seamlessly transitioned to real ion accelerators,enabling efficient online adaptive control and ***,the controller demonstrates significant robustness,effectively managing beams with diverse charge mass ratios without requiring *** a controller allows us to achieve the global control within the entire superconducting section of the China Accelerator Facility for Superheavy Elements.

关键词： nonlinear complex system adaptive control machine learning particle accelerator simulation to reality

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A Support Vector Machine(SVM)Model for Privacy Recommending data Processing Model(PRDPM)in Internet of Vehicles

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Computers, Materials & Continua 2025年第1期82卷 389-406页

作者： Ali Alqarni department of Computer science and Artificial Intelligence College of Computing and Information TechnologyUniversity of BishaBisha61922Saudi Arabia

Open networks and heterogeneous services in the Internet of Vehicles(IoV)can lead to security and privacy *** key requirement for such systems is the preservation of user privacy,ensuring a seamless experience in driving,navigation,and *** privacy needs are influenced by various factors,such as data collected at different intervals,trip durations,and user *** address this,the paper proposes a Support Vector Machine(SVM)model designed to process large amounts of aggregated data and recommend privacy preserving *** model analyzes data based on user demands and interactions with service providers or neighboring *** aims to minimize privacy risks while ensuring service continuity and *** SVMmodel helps validate the system’s reliability by creating a hyperplane that distinguishes between maximum and minimum privacy *** results demonstrate the effectiveness of the proposed SVM model in enhancing both privacy and service performance.

关键词： Support vector machine big data IoV privacy-preserving

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Text-Image Feature Fine-Grained Learning for Joint Multimodal Aspect-Based Sentiment Analysis

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Computers, Materials & Continua 2025年第1期82卷 279-305页

作者： Tianzhi Zhang Gang Zhou Shuang Zhang Shunhang Li Yepeng Sun Qiankun Pi Shuo Liu School of data and Target Engineering Information Engineering UniversityZhengzhou450001China Information Engineering department Liaoning Provincial College of CommunicationsShenyang110122China School of Computer and Artificial Intelligence Zhengzhou UniversityZhengzhou450000China

Joint Multimodal Aspect-based Sentiment Analysis(JMASA)is a significant task in the research of multimodal fine-grained sentiment analysis,which combines two subtasks:Multimodal Aspect Term Extraction(MATE)and Multimodal Aspect-oriented Sentiment Classification(MASC).Currently,most existing models for JMASA only perform text and image feature encoding from a basic level,but often neglect the in-depth analysis of unimodal intrinsic features,which may lead to the low accuracy of aspect term extraction and the poor ability of sentiment prediction due to the insufficient learning of intra-modal *** this problem,we propose a Text-Image Feature Fine-grained Learning(TIFFL)model for ***,we construct an enhanced adjacency matrix of word dependencies and adopt graph convolutional network to learn the syntactic structure features for text,which addresses the context interference problem of identifying different aspect ***,the adjective-noun pairs extracted from image are introduced to enable the semantic representation of visual features more intuitive,which addresses the ambiguous semantic extraction problem during image feature ***,the model performance of aspect term extraction and sentiment polarity prediction can be further optimized and *** on two Twitter benchmark datasets demonstrate that TIFFL achieves competitive results for JMASA,MATE and MASC,thus validating the effectiveness of our proposed methods.

关键词： Multimodal sentiment analysis aspect-based sentiment analysis feature fine-grained learning graph convolutional network adjective-noun pairs

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Unsupervised Meteorological Downscaling Based on Dual Learning and Subgrid-scale Auxiliary Information

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Advances in Atmospheric sciences 2025年第1期42卷 53-66页

作者： Jing HU Jialing MU Xiaomeng HUANG Xi WU department of Computer science Chengdu University of Information TechnologyChengdu 610225China department of Earth System science Ministry of Education Key Laboratory for Earth System ModelingInstitute for Global Change StudiesTsinghua UniversityBeijing 100084China

Climate downscaling is used to transform large-scale meteorological data into small-scale data with enhanced detail,which finds wide applications in climate modeling,numerical weather forecasting,and renewable *** deeplearning-based downscaling methods effectively capture the complex nonlinear mapping between meteorological data of varying scales,the supervised deep-learning-based downscaling methods suffer from insufficient high-resolution data in practice,and unsupervised methods struggle with accurately inferring small-scale specifics from limited large-scale inputs due to small-scale *** article presents DualDS,a dual-learning framework utilizing a Generative Adversarial Network–based neural network and subgrid-scale auxiliary information for climate *** a learning method is unified in a two-stream framework through up-and downsamplers,where the downsampler is used to simulate the information loss process during the upscaling,and the upsampler is used to reconstruct lost details and correct errors incurred during the *** dual learning strategy can eliminate the dependence on high-resolution ground truth data in the training process and refine the downscaling results by constraining the mapping *** findings demonstrate that DualDS is comparable to several state-of-the-art deep learning downscaling approaches,both qualitatively and ***,for a single surface-temperature data downscaling task,our method is comparable with other unsupervised algorithms with the same dataset,and we can achieve a 0.469 dB higher peak signal-to-noise ratio,0.017 higher structural similarity,0.08 lower RMSE,and the best correlation *** summary,this paper presents a novel approach to addressing small-scale uncertainty issues in unsupervised downscaling processes.

关键词： downscaling unsupervised deep learning dual learning auxiliary information

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PD-YOLO:Colon Polyp Detection Model Based on Enhanced Small-Target Feature Extraction

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Computers, Materials & Continua 2025年第1期82卷 913-928页

作者： Yicong Yu Kaixin Lin Jiajun Hong Rong-Guei Tsai Yuanzhi Huang New Engineering Industry College Putian UniversityPutian351100China Engineering Research Center of Big data Application in Private Health Medicine(Putian University) Fujian Province UniversityPutian351100China Computer College Guangdong University of Science&TechnologyDongguan523668China

In recent years,the number of patientswith colon disease has increased *** polyps are the precursor lesions of colon *** not diagnosed in time,they can easily develop into colon cancer,posing a serious threat to patients’lives and health.A colonoscopy is an important means of detecting colon ***,in polyp imaging,due to the large differences and diverse types of polyps in size,shape,color,etc.,traditional detection methods face the problem of high false positive rates,which creates problems for doctors during the diagnosis *** order to improve the accuracy and efficiency of colon polyp detection,this question proposes a network model suitable for colon polyp detection(PD-YOLO).This method introduces the self-attention mechanism CBAM(Convolutional Block Attention Module)in the backbone layer based on YOLOv7,allowing themodel to adaptively focus on key information and ignore the unimportant *** help themodel do a better job of polyp localization and bounding box regression,add the SPD-Conv(Symmetric Positive Definite Convolution)module to the neck layer and use deconvolution instead of *** results indicate that the PD-YOLO algorithm demonstrates strong robustness in colon polyp *** to the original YOLOv7,on the Kvasir-SEG dataset,PD-YOLO has shown an increase of 5.44 percentage points in AP@0.5,showcasing significant advantages over other mainstream methods.

关键词： Polyp detection YOLOv7 SPD-Conv CBAM deconvolution

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Control Structures and Algorithms for Force Feedback Bilateral Teleoperation Systems: A Comprehensive Review

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Computer Modeling in Engineering & sciences 2025年第2期142卷 973-1019页

作者： Jiawei Tian Yu Zhou Lirong Yin Salman A.AlQahtani Minyi Tang Siyu Lu Ruiyang Wang Wenfeng Zheng department of Computer science and Engineering Major in Bio Artificial IntelligenceHanyang UniversityAnsan-si15577Republic of Korea department of Geography and Anthropology Louisiana State UniversityBaton RougeLA 70803USA department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11574Saudi Arabia School of Automation University of Electronic Science and Technology of ChinaChengdu610054China

Force feedback bilateral teleoperation represents a pivotal advancement in control technology,finding widespread application in hazardous material transportation,perilous environments,space and deep-sea exploration,and healthcare *** paper traces the evolutionary trajectory of force feedback bilateral teleoperation from its conceptual inception to its current *** elucidates the fundamental principles underpinning interaction forces and tactile exchanges,with a specific emphasis on the crucial role of tactile *** this review,a quantitative analysis of force feedback bilateral teleoperation development trends from 2011 to 2024 has been conducted,utilizing published journal article data as the primary source of *** review accentuates classical control frameworks and algorithms,while also delving into existing research advancements and prospec-tive breakthrough ***,it explores specific practical scenarios ranging from intricate surgeries to hazardous environment exploration,underscoring the technology’s potential to revolutionize industries by augmenting human manipulation of remote *** underscores the pivotal role of force feedback bilateral teleoperation as a transformative human-machine interface,capable of shaping flexible control strategies and addressing technological *** research endeavors in force feedback bilateral teleoperation are expected to prioritize the creation of more immersive experiences,overcoming technical hurdles,fortifying human-machine collaboration,and broadening application domains,particularly within the realms of medical intervention and hazardous *** the continuous progression of technology,the integration of human intelligence and robotic capabilities is expected to produce more innovations and breakthroughs in the field of automatic control.

关键词： Force feedback bilateral teleoperation robot development history application prospect

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Edge Coalition Construction Based on a Novel Market Equilibrium Price

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China Communications 2025年第03期 288-305页

作者： Wang Xiaolong Dang Jianwu Zhao Shuxu Wang Yangping Zhang Zhanping Hao Zhanjun School of Electronic and Information Engineering Lanzhou Jiaotong University Big data Center of Gansu Province School of Mathematics and Information Engineering Longdong University College of Computer science and Engineering Northwest Normal University

The emergence of multi-access edge computing(MEC) aims at extending cloud computing capabilities to the edge of the radio access network. As the large-scale internet of things(IoT) services are rapidly growing, a single edge infrastructure provider(EIP) may not be sufficient to handle the data traffic generated by these services. Most of the existing work addressed the computing resource shortage problem by optimizing tasks schedule, whereas others overcome such issue by placing computing resources on demand. However, when considering a multiple EIPs scenario, an urgent challenge is how to generate a coalition structure to maximize each EIP's gain with a suitable price for computing resource block corresponding to a container. To this end, we design a scheme of EIPs collaboration with a market price for containers under a scenario that considers a collection of service providers(SPs) with different budgets and several EIPs distributed in geographical ***, we bring in the net profit market price model to generate a more reasonable equilibrium price and select the optimal EIPs for each SP by a convex program. Then we use a mathematical model to maximize EIP's profits and form stable coalitions between EIPs by a distributed coalition formation algorithm. Numerical results demonstrate that our proposed collaborative scheme among EIPs enhances EIPs' gain and increases users' surplus.

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From Static and Dynamic Perspectives:A Survey on Historical data Benchmarks of Control Performance Monitoring

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 300-316页

作者： Pengyu Song Jie Wang Chunhui Zhao Biao Huang the State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University IEEE the department of Chemical and Materials Engineering University of Alberta

In recent decades, control performance monitoring(CPM) has experienced remarkable progress in research and industrial applications. While CPM research has been investigated using various benchmarks, the historical data benchmark(HIS) has garnered the most attention due to its practicality and effectiveness. However, existing CPM reviews usually focus on the theoretical benchmark, and there is a lack of an in-depth review that thoroughly explores HIS-based methods. In this article, a comprehensive overview of HIS-based CPM is provided. First, we provide a novel static-dynamic perspective on data-level manifestations of control performance underlying typical controller capacities including regulation and servo: static and dynamic properties. The static property portrays time-independent variability in system output, and the dynamic property describes temporal behavior driven by closed-loop feedback. Accordingly,existing HIS-based CPM approaches and their intrinsic motivations are classified and analyzed from these two ***, two mainstream solutions for CPM methods are summarized, including static analysis and dynamic analysis,which match data-driven techniques with actual controlling behavior. Furthermore, this paper also points out various opportunities and challenges faced in CPM for modern industry and provides promising directions in the context of artificial intelligence for inspiring future research.

关键词： Control performance monitoring (CPM) data-driven method historical data benchmark (HIS) industrial process performance index static and dynamic analysis

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Superradiant growth anomaly magnification in evolution of vector bosonic condensates bounded by a Kerr black hole with near-horizon reflection

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science China(Physics,Mechanics & Astronomy) 2025年第04期Mechanics & Astronomy) .卷 66-85页

作者： Nayun Jia Yin-Da Guo Gui-Rong Liang Zhan-Feng Mai Xin Zhang department of Physics Southern University of Science and Technology Key Laboratory of Cosmology and Astrophysics (Liaoning) & College of sciences Northeastern University Institute of Frontier and Interdisciplinary science Key Laboratory of Particle Physics and Particle Irradiation (Ministry of Education)Shandong University School of Materials science and Physics China University of Mining and Technology Kavli Institute for Astronomy and Astrophysics Peking University Guangxi Key Laboratory for Relativistic Astrophysics School of Physical Science and TechnologyGuangxi University Key Laboratory of data Analytics and Optimization for Smart Industry (Ministry of Education) Northeastern University National Frontiers science Center for Industrial Intelligence and Systems Optimization Northeastern University

Ultralight vector particles can form evolving condensates around a Kerr black hole （BH） due to superradiant *** study the effect of near-horizon reflection on the evolution of this system:by matching three pieces of asymptotic expansions of the Proca equation in Kerr metric and considering the leading order in the electric mode,we present explicit analytical expressions for the corrected spectrum and the superradiant instability ***,in high-spin BH cases,we identify an anomalous situation where the superradiance rate is temporarily increased by the reflection parameter R,which also occurs in the scalar scenario,but is largely magnified in vector condensates due to a faster growth rate in dominant *** point out that the conditio√n for the growth anomaly in the adiabatic case is that information carried per particle exceeds a certain value■.We further construct several featured quantities to illustrate it,and formalize the anomalyinduced gravitational wave strain deformation.

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Augmented Reality Navigation Using Surgical Guides Versus Conventional Techniques in Pedicle Screw Placement

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Journal of Shanghai Jiaotong university(science) 2025年第1期30卷 10-17页

作者： KONG Huiyang WANG Shuyi ZHANG Can CHEN Zan School of Health science and Engineering University of Shanghai for Science and TechnologyShanghai200093China department of Neurosurgery Xuanwu Hospital Capital Medical UniversityBeijing100053China China International Neuroscience Institute(China-INI) Beijing100052China

The aim of this study was to assess the potential of surgical guides as a complementary tool to augmented reality(AR)in enhancing the safety and precision of pedicle screw placement in spinal *** trainers were divided into the AR navigation group using surgical guides and the free-hand *** group consisted of a novice and an experienced spine surgeon.A total of 80 pedicle screws were ***,the AR group reconstructed the 3D model and planned the screw insertion route according to the computed tomography data of L2 lumbar ***,the Microsoft HoloLens™2 was used to identify the vertebral model,and the planned virtual path was superimposed on the real cone ***,the screw was placed according to the projected ***,Micron Tracker was used to measure the deviation of screws from the preoperatively planned trajectory,and pedicle screws were evaluated using the Gertzbein-Robbins *** the AR group,the linear deviations of the experienced doctor and the novice were(1.59±0.39)mm and(1.73±0.52)mm respectively,and the angle deviations were 2.72°±0.61°and 2.87°±0.63°*** the free-hand group,the linear deviations of the experienced doctor and the novice were(2.88±0.58)mm and(5.25±0.62)mm respectively,and the angle deviations were 4.41°±1.18°and 7.15°±1.45°*** kinds of deviations between the two groups were significantly different(P<0.05).The screw accuracy rate was 95%in the AR navigation group and 77.5%in the free-hand *** results of this study indicate that the integration of surgical guides and AR is an innovative technique that can substantially enhance the safety and precision of spinal surgery and assist inexperienced doctors in completing the surgery.

关键词： augmented reality(AR) pedicle screw placement surgery navigation surgical guide

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