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第三十九届中国控制会议

作者： Minghui Shi Yong Heng Liang Han Qingdong Li Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing Institute of Electronic System Engineering School of Sino-French Engineer Beihang University Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University

Correlation filter-based trackers have achieved competitive results in the field of visual tracking, but the abilities to deal with the multi-scale and keep the tracking stability still need to be improved. In this article, the complex background tracking problems are studied based on the kernel correlation filter. In order to address the fixed size limitation, we present an improved scheme, which can not only realize scale adaption, but also retain the advantages of the original algorithm. In addition, the adaptive update learning rate of the model is achieved by using the peak sidelobe ratio as an indicator to measure the filter performance. Using the index, we can selectively reduce the model interference to low precision information. Moreover, we design a redetection mechanism that runs automatically when the tracking evaluation indicator is low. Compared with the radical model update methods, those conservative update strategies can effectively decrease the model pollution and ensure the tracking effect. Extensive verifications based on OTB-100 benchmark show that the optimized algorithm improves the accuracy, robustness, and generalization ability of target tracking.

关键词： Target tracking Kernel correlation filter Scale adaption Peak sidelobe ratio Learning rate adaption

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Manipulating density of magnetic skyrmions via multilayer repetition and thermal annealing

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Physical Review B 2021年第6期104卷 064421-064421页

作者： Xinran Wang Anni Cao Sai Li Jin Tang Ao Du Houyi Cheng Yiming Sun Haifeng Du Xueying Zhang Weisheng Zhao Fert Beijing Institute School of Integrated Circuit Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 China Beihang-Goertek Joint Microelectronics Institute Qingdao Research Institute Beihang University Qingdao 266000 China Beijing Microelectronics Technology Institute Beijing 100076 China Anhui Province Key Laboratory of Condensed Matter Physics at Extreme Conditions High Magnetic Field Laboratory of Chinese Academy of Sciences and University of Science and Technology of China Hefei 230031 China

The magnetic skyrmion, a tiny magnetic texture that holds promise as the next-generation information carrier, has been widely studied in recent years. A fine tunability of skyrmion density is required for its real applications in novel memory and logic devices. Here, we report on the manipulation of skyrmion density at room temperature in a Pt/Co/Ta/MgO system composed of multiple repetitions with perpendicular magnetic anisotropy. Néel-type skyrmions are observed by performing Lorentz transmission electron microscopy and magnetic force microscopy. The influence of structure repetition on skyrmions is experimentally investigated and further understood by micromagnetic simulations. The variation of skyrmion density with repetition number is mainly attributed to magnetic anisotropy. Meanwhile, thermal annealing is utilized to regulate the skyrmion density, where skyrmion-related properties exert a competitive effect. Our findings provide alternative means to manipulate skyrmion density, further allowing for optimized engineering of skyrmion-based devices.

关键词： Magnetic interactions Magnetic texture Skyrmions Spintronics Multilayer thin films Brillouin scattering & spectroscopy Lorentz microscopy Magnetic force microscopy

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Crafting the future: Enhancing gas separation with nanoarchitectonics of bimetallic Ni–Co-ZIF-67 in polysulfone-based mixed matrix membranes

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Case Studies in Chemical and Environmental engineering 2024年 9卷

作者： Sulistiono, Dety Oktavia Ali, Badrut Tamam Ibnu Widyanto, Alvin Rahmad Ediati, Ratna Widiastuti, Nurul Lestari, Witri Wahyu Akhlus, Syafsir Iqbal, Rendy Muhamad Senda, Semuel Pati Fansuri, Hamzah Department of Chemistry Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Sukolilo Surabaya 60111 Indonesia Automotive Engineering Engineering Department Politeknik Negeri Jember Jember 68101 Indonesia Center for Process and Manufacturing Industry Technology National Research and Innovation Agency Technology Energy Cluster PUSPIPTEK 625 Building South Tangerang Indonesia Department of Applied Chemistry Shibaura Institute of Technology 3-7-5 Toyosu Koto-ku Tokyo 135-8548 Japan Department of Chemistry Faculty of Mathematics and Natural Sciences Universitas Sebelas Maret Jl. Ir. Sutami No. 36A Kentingan Jebres Surakarta 57126 Indonesia Department of Chemistry Faculty of Mathematics and Natural Sciences Universitas Palangka Raya Kampus UPR Tunjung Nyaho Palangkaraya 73111 Indonesia Advanced Membrane Technology Research Center (AMTEC) Faculty of Chemical and Energy Engineering Universiti Teknologi Malaysia Johor Skudai 81310 Malaysia

In response to global clean energy demands, this study develops mixed matrix membranes (MMMs) for gas separation in renewable energy applications. MMMs are produced through phase inversion by employing polysulfone and bimetallic-ZIF (Ni–Co-ZIF-67). Bimetallic-ZIF, formed in-situ by Co and Ni metals in water solvent with triethylamine, enhances gas selectivity. MMMs with 4 wt% bimetallic-ZIF, Co: Ni ratio of 9:1 (4Ni10Z67), exhibit remarkable selectivity: CO₂/CH₄ (21.19), H₂/N₂ (1.47), H₂/CH₄ (44.82), and N₂/CH₄ (30.40). Strong interactions between bimetallic-ZIF and CO₂, facilitated by molecular sieving and Ni–Co sites, contribute to these results. © 2024 The Authors

关键词： Bimetallic-ZIF CO2 capture Gas emissions Metal substitution Renewable energy

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Design of a Linear Quantum Projection Filter

Design of a Linear Quantum Projection Filter

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Peng Zhang Qing Gao Jinhu Lv Daoyi Dong School of Automation Science and Electrical Engineering Beihang University Beijing China School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China School of Engineering and Information Technology University of New South Wales Canberra Australia

ISBN: (数字)9781728125473

ISBN: (纸本)9781728125480

In order to reduce the computational cost for online calculation of the quantum filter, in this paper, a linear quantum projection filtering scheme is developed by projecting the time evolution trajectory of quantum system state onto a lower-dimensional linear submanifold spanned by a set of basis matrices. The lower-dimensional submanifold is obtained through an extended singular value decomposition algorithm. Compared with the existing works on quantum projection filtering, the proposed approach requires no prior knowledge on the structure of the submanifold, and thus can be used to deal with general open quantum systems. Simulation results demonstrate that the proposed linear projection filter is able to approximate the high-dimensional quantum filter within acceptable accuracy.

关键词： Filtering theory Optical filters Nonlinear filters Maximum likelihood detection Information filters Quantum computing Mathematical model

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Towards 6G wireless communication networks:vision, enabling technologies, and new paradigm shifts

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science China(Information sciences) 2021年第1期64卷 5-78页

作者： Xiaohu YOU Cheng-Xiang WANG Jie HUANG Xiqi GAO Zaichen ZHANG Mao WANG Yongming HUANG Chuan ZHANG Yanxiang JIANG Jiaheng WANG Min ZHU Bin SHENG Dongming WANG Zhiwen PAN Pengcheng ZHU Yang YANG Zening LIU Ping ZHANG Xiaofeng TAO Shaoqian LI Zhi CHEN Xinying MA Chih-Lin I Shuangfeng HAN Ke LI Chengkang PAN Zhimin ZHENG Lajos HANZO Xuemin (Sherman) SHEN Yingjie Jay GUO Zhiguo DING Harald HAAS Wen TONG Peiying ZHU Ganghua YANG Jun WANG Erik G.LARSSON Hien Quoc NGO Wei HONG Haiming WANG Debin HOU Jixin CHEN Zhe CHEN Zhangcheng HAO Geoffrey Ye LI Rahim TAFAZOLLI Yue GAO H.Vincent POOR Gerhard P.FETTWEIS Ying-Chang LIANG National Mobile Communications Research Laboratory School of Information Science and EngineeringSoutheast University Purple Mountain Laboratories Shanghai Institute of Fog Computing Technology (SHIFT) ShanghaiTech University Research Center for Network Communication Peng Cheng Laboratory State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications National Engineering Laboratory for Mobile Network Technologies Beijing University of Posts and Telecommunications National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China (UESTC) China Mobile Research Institute School of Electronics and Computer Science University of Southampton Department of Electrical and Computer Engineering University of Waterloo Global Big Data Technologies Centre (GBDTC) University of Technology Sydney School of Electrical and Electronic Engineering The University of Manchester LiFi Research and Development Centre Institute for Digital CommunicationsSchool of EngineeringThe University of Edinburgh Huawei Technologies Canada Co. Ltd. Huawei Technologies Department of Electrical Engineering (ISY) Link?ping University Institute of Electronics Communications & Information Technology (ECIT)Queen's University Belfast State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast University School of Electrical and Computer Engineering Georgia Institute of Technology 5G Innovation Centre University of Surrey Princeton University Vodafone Chair Mobile Communications Systems Technische Universit?t Dresden Center for Intelligent Networking and Communications (CINC) University of Electronic Science and Technology of China (UESTC)

The fifth generation(5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability,and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation(6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle(UAV) communication networks, thus achieving a space-airground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6GHz, millimeter wave(mmWave), terahertz(THz),and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence(AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable f

关键词： 6G vision network architecture air interface and transmission technologies space-air-ground-sea integrated network all spectra artificial intelligence network security

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A Multi-source Information Fusion Fault Diagnosis Method for Vectoring Nozzle Control System Based on Bayesian Network

A Multi-source Information Fusion Fault Diagnosis Method for...

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Advanced Reliability and Maintenance Modeling (APARM), Asia-Pacific International Symposium on

作者： Youyou Zhang Jian Shi Shaoping Wang Yang Zhang School of Automation Science and Electrical Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beihang University Beijing School of Energy and Power Engineering Beihang University Beijing China

ISBN: (数字)9781728171029

ISBN: (纸本)9781728171036

The vectoring nozzle control system has a complex structure, with many excitation sources and strong fault correlation. To improve the accuracy of fault diagnosis, this paper presents an approach combining multi-source information fusion and Bayesian network to detect and identify the fault of vectoring nozzle control system. The multi-source diagnosis framework is established to fuse the characteristic information collected by different sensors of system. Based on the collected data, a multi-fault Bayesian network is constructed to fuse the time-frequency feature evidence body. In addition, a Bayesian classifier is designed to identify the fault type according to the maximum posterior probability criterion. Finally, a case study is designed to verify the method proposed in this paper, and the results show that the proposed method can detect the fault accurately, with an accuracy of not less than 90%. The diagnostic results are more reliable and have low uncertainty, which illustrates the validity of the proposed method and shows a broad practical application value in other comparable control systems.

关键词： Actuators Fault diagnosis Bayes methods Circuit faults Sensors Feature extraction

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Hierarchical Decomposition and Prescribed Performance Bound based Adaptive Control for Leader-Follower Formation of Uncertain Nonholonomic Mobile Robots

Hierarchical Decomposition and Prescribed Performance Bound ...

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International Conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Jiajun Shen Wei Wang Jinhu Lü Chao Deng School of Automation Science and Electrical Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China School of Electrical and Electronic Engineering Nanyang Technological University Singapore

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

In this paper, the cooperative formation control problem is investigated for multiple two-wheeled mobile robots with unknown parameters. By combining the hierarchical decomposition and prescribed performance bound (PPB) technique, distributed adaptive formation controllers are designed based on dynamic surface control. It is proved in the Lyapunov sense that all the closed-loop signals are semi-globally bounded and the tracking error converges to a compact set, which can be made arbitrarily small by adjusting the design parameters appropriately. Furthermore, formation maintenance, connectivity preservation and collision avoidance can be achieved with the proposed control scheme. Simulations are also given to verify the effectiveness of the theoretical results.

关键词： Mobile robots Robot kinematics Wheels Collision avoidance Directed graphs Kinematics Information processing

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Investigating dynamic routing in tree-structured LSTM for sentiment analysis 9

Investigating dynamic routing in tree-structured LSTM for se...

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2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019

作者： Wang, Jin Yu, Liang-Chih Robert Lai, K. Zhang, Xuejie School of Information Science and Engineering Yunnan University Yunnan China Department of Information Management Yuan Ze University Taiwan Department of Computer Science and Engineering Yuan Ze University Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taiwan

ISBN: (纸本)9781950737901

Deep neural network models such as long short-term memory (LSTM) and tree-LSTM have been proven to be effective for sentiment analysis. However, sequential LSTM is a bias model wherein the words in the tail of a sentence are more heavily emphasized than those in the header for building sentence representations. Even tree-LSTM, with useful structural information, could not avoid the bias problem because the root node will be dominant and the nodes in the bottom of the parse tree will be less emphasized even though they may contain salient information. To overcome the bias problem, this study proposes a capsule tree-LSTM model, introducing a dynamic routing algorithm as an aggregation layer to build sentence representation by assigning different weights to nodes according to their contributions to prediction. Experiments on Stanford Sentiment Treebank (SST) for sentiment classification and EmoBank for regression show that the proposed method improved the performance of tree-LSTM and other neural network models. In addition, the deeper the tree structure, the bigger the improvement. © 2019 Association for Computational Linguistics

关键词： Long short-term memory

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Novel Metabolomic and Adiposity Markers Enhance Prediction of Obstructive Sleep Apnea: A Prospective Analysis from the China Human Phenobank

SSRN

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SSRN 2025年

作者： Wu, Yudan Ba, Yihan Chen, Chen Wang, Qi Chen, Qinsheng Zhang, Jinxian Chen, Longlong Zhao, Yining Shi, Biru Ye, Lisong Chen, Wei Wang, Chengyan Hu, Zixin Zhang, Jun Feng, Kai Wang, Yan Liu, Yuehua Qi, Yuan Tang, Huiru Luo, Jingchun Tian, Mei State Key Laboratory of Genetic Engineering School of Life Sciences Human Phenome Institute Zhangjiang Fudan International Innovation Center Fudan University Shanghai201203 China Department of Endocrinology and Metabolism Zhongshan Hospital Fudan University Shanghai200032 China Department of Orthodontics Shanghai Stomatological Hospital School of Stomatology Fudan University Shanghai200001 China Chinese Academy of Sciences Key Laboratory of Computational Biology Bio-Med Big Data Center Shanghai Institute of Nutrition and Health University of the Chinese Academy of Sciences Chinese Academy of Sciences Shanghai200031 China Fudan University Shanghai201203 China Department of Radiology Huashan Hospital State Key Laboratory of Medical Neurobiology National Center for Neurological Disorders Fudan University Shanghai200040 China Department of Preventive Dentistry Shanghai Stomatological Hospital School of Stomatology Fudan University Shanghai200001 China Shanghai Key Laboratory of Craniomaxillofacial Development and Diseases Fudan University Shanghai200433 China Shanghai Academy of Artificial Intelligence for Science Shanghai200232 China

Background: Obstructive sleep apnea (OSA) prevalence is increasing among Asian populations, yet effective biomarker-based screening tools remain underdeveloped. Metabolic dysregulation and adiposity patterns show potential as novel biomarkers for OSA risk stratification, but their predictive utility has not been comprehensively evaluated in Chinese populations. We aimed to identify key metabolic and adiposity biomarkers for OSA and subsequently develop an integrated prediction model to enhance risk assessment in a Chinese ***: In this prospective cohort study (2018-2023), we enrolled 972 adults (aged 20-60 years) from the China Human Phenobank. All participants underwent overnight polysomnography, sleep questionnaires, metabolomic profiling (1,840 metabolites), and DXA-derived body fat distribution analysis (58 adiposity parameters). OSA was defined according to international clinical criteria as apnea hypopnoea index (AHI) ≥5/h accompanied by characteristic symptoms (excessive daytime sleepiness, fatigue, or impaired cognition) or associated comorbidities. Participants were randomly allocated to training (n=777) and test (n=195) cohorts. We employed a multi-staged feature selection approach integrating differential analysis, correlation filtering, and machine learning algorithms (mRMR and LASSO) to identify key biomarkers. Selected features were integrated into a predictive model combining clinical, metabolomic, and adiposity data. Metabolic pathway enrichment analysis identified biological mechanisms underlying OSA *** identified two critical fat distribution markers (visceral adipose tissue volume and gynoid fat) and ten metabolic signatures (including specific TAG-FAs, lipoprotein subtypes, and steroid derivatives) significantly associated with OSA. The gender-specific fat distribution patterns and protective effects of gynoid fat distribution provided new insights into OSA pathophysiology. Notably, we identified H2FC, a specific H

关键词： Risk assessment

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Illuminating the cathodic reaction kinetics of Al-Zn-Mg-Cu alloy on corroded surfaces in chloride environment

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Surfaces and Interfaces 2025年 71卷

作者： Mingtao Wang Shengen Zhang Yucheng Ji Sen Du Zhengfeng Lv Zhiyuan Xu Bo Liu Institute for Advanced Materials and Technology University of Science and Technology Beijing Beijing 100083 China School of Physics and Materials Science Nanchang University Nanchang 330031 China Beijing Advanced Innovation Center for Materials Genome Engineering National Materials Corrosion and Protection Data Center Institute for Advanced Materials and Technology University of Science and Technology Beijing Beijing 100083 China Shandong Nanshan Aluminum Co. Ltd. Longkou City Shandong 265713 China Xinjiang Research Institute for Nonferrous Metals Urumqi 830009 China

Through quantitative analysis of polarization curves, variations in the electrochemical parameters of the Al-Zn-Mg-Cu alloy in a chlorine-containing solution were determined. The findings indicate that the cathodic kinetics of the alloy, including the hydrogen evolution reaction (HER) and oxygen reduction reaction (ORR), are accelerated during the degradation process. Notably, the exchange current density associated with the HER exhibits a significant increase. This phenomenon is attributed to the enhanced catalytic activity of the damaged surface, likely caused by the dealloying of intermetallic compounds, which serve as preferential sites for cathodic reactions. Furthermore, the Al₂CuMg present on the alloy surface was substantially reduced through an optimized heat treatment process, leading to diminished electrochemical activity and improved corrosion resistance of the alloy.

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