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The northern boundary of the Asian summer monsoon and division of westerlies and monsoon regimes over the Tibetan Plateau in present-day

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science China Earth sciences 2023年第4期66卷 882-893页

作者： Lingxin HUANG Jie CHEN Kun YANG Yujie YANG Wei HUANG Xu ZHANG Fahu CHEN Key Laboratory of Western China’s Environmental Systems(Ministry of Education) College of Earth and Environmental SciencesLanzhou UniversityLanzhou 730000China Group of Alpine Paleoecology and Human Adaptation(ALPHA) State Key Laboratory of Tibetan Plateau Earth SystemEnvironment and Resources(TPESER)Institute of Tibetan Plateau Research(ITPCAS)Chinese Academy of Sciences(CAS)Beijing 100101China College of Atmospheric Sciences Lanzhou UniversityLanzhou 730000China Department of Earth System Science Ministry of Education Key Laboratory for Earth System ModelingInstitute for Global Change StudiesTsinghua UniversityBeijing 100084China National Tibetan Plateau Data Center State Key Laboratory of Tibetan Plateau Earth SystemEnvironment and Resources(TPESER)Institute of Tibetan Plateau Research(ITPCAS)Chinese Academy of Sciences(CAS)Beijing 100101China

Precipitation patterns and their variations over the Tibetan Plateau(TP) are mainly dominated by the Asian summer monsoon, westerlies, and their interactions. The exact extent of the Asian summer monsoon’s influence, however, remains undetermined. Referencing the climatological northern boundary index of the East Asian summer monsoon, we demonstrate that the 300 mm precipitation isoline from May to September can be utilized as an indicator of the northern boundary of the Asian summer monsoon over the TP, allowing for an analysis of the spatial distribution characteristics of the climatological and interannual northern boundary. Our results indicate that the climatological northern boundary of the Asian summer monsoon over the TP lies along the eastern Qilian Mountains-Tanggula Mountains-Qiangtang Plateau-Gangdise Mountains-Western Himalayas during 2001–2020. This position corresponds well with the position of the convergence of westerly(westerlies) and southerly wind(monsoon) in the lower troposphere, representing the interface between dry and wet regions in the rainy season over the TP. There is a significant positive correlation between changes in the zonal/meridional water vapor budget and variations in precipitation to the north/south of the climatological northern boundary, respectively. Additionally, a close relationship exists between the interannual fluctuation range of the northern boundary and the distribution of vegetation across the TP. Compared to the northern boundary of the summer monsoon defined by meteorological criteria, which is established based on 5-day(pentad)mean precipitation(exceeding 4 mm day^(-1)), our climatological northern boundary offers a more objective portrayal of the region that experiences persistent influence from the summer monsoon. These indicate that climatological northern boundary has a clear significance for natural geographical distribution such as the westerlies-monsoon circulation, ecology, and climate. Based on the inte

关键词： Tibetan Plateau Asian summer monsoon Climatological northern boundary index Westerlies domain Monsoon domain

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Haptic-Aided Navigation Vehicle: Enhancing Obstacle Detection in Blind Spots and Transparent Object Scenarios

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Journal of Shanghai Jiaotong University (science) 2025年 1-9页

作者： Li, Mingwang Li, Xinde Zhang, Zhentong Zhang, Zeyu Zhao, Haoming School of Software Southeast University Suzhou Jiangsu215000 China School of Automation Southeast University Nanjing210018 China School of Cyber Science and Engineering Southeast University Nanjing211102 China Key Laboratory of Measurement and Control of Complex Systems of Engineering of Ministry of Education Nanjing214135 China Nanjing Center for Applied Mathematics Nanjing211135 China Southeast University Shenzhen Research Institute Shenzhen Guangdong518063 China

As autonomous mobile robots are increasingly deployed in complex environments, traditional vision sensors and LiDAR encounter considerable limitations, particularly in detecting obstacles in blind spots or transparent objects. To address the issue of blind spots, we design a specialized haptic sensing structure and develop the haptic-aided navigation vehicle (HANV). This system integrates haptic sensors and LiDAR to deliver comprehensive perception, significantly enhancing close-range obstacle detection in areas that are typically beyond the range of conventional sensors. To tackle the challenge of transparent obstacles, which are often undetected by both vision and LiDAR sensors, we employ a fusion of haptic sensors and LiDAR. The haptic system provides physical contact feedback, ensuring reliable detection of transparent obstacles such as glass, while LiDAR offers long-range sensing capabilities. This combination enables HANV to navigate effectively in environments with transparent obstacles, overcoming the limitations of traditional sensing systems. Experiment results indicate that the proposed haptic and LiDAR integration substantially improves obstacle detection in both blind spots and environments with transparent obstacles. HANV achieves high success rates, minimal collisions, and efficient obstacle avoidance, particularly excelling in complex, confined spaces where conventional systems prove inadequate. These findings emphasize the efficacy of our approach in enhancing navigation performance in dynamic and challenging environments. (Figure presented.) © Shanghai Jiao Tong University 2025.

关键词： Mobile robots

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A Client Selection Method Based on Loss Function Optimization for Federated Learning

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Computer Modeling in Engineering & sciences 2023年第10期137卷 1047-1064页

作者： Yan Zeng Siyuan Teng Tian Xiang Jilin Zhang Yuankai Mu Yongjian Ren Jian Wan School of Computer Science and Technology Hangzhou Dianzi UniversityHangzhou310018China Key Laboratory of Complex System Modeling and Simulation Ministry of EducationHangzhou310018China Zhejiang Engineering Research Center of Data Security Governance Hangzhou310018China Intelligent Robotics Research Center Zhejiang LabHangzhou311100China HDU-ITMO Joint Institute Hangzhou Dianzi UniversityHangzhou310018China

Federated learning is a distributedmachine learningmethod that can solve the increasingly serious problemof data islands and user data privacy,as it allows training data to be kept locally and not shared with other *** trains a globalmodel by aggregating locally-computedmodels of clients rather than their ***,the divergence of local models caused by data heterogeneity of different clients may lead to slow convergence of the global *** this problem,we focus on the client selection with federated learning,which can affect the convergence performance of the global model with the selected local *** propose FedChoice,a client selection method based on loss function optimization,to select appropriate local models to improve the convergence of the global *** firstly sets selected probability for clients with the value of loss function,and the client with high loss will be set higher selected probability,which can make them more likely to participate in ***,it introduces a local control vector and a global control vector to predict the local gradient direction and global gradient direction,respectively,and calculates the gradient correction vector to correct the gradient direction to reduce the cumulative deviationof the local gradient causedby *** experiments to verify the validity of FedChoice on CIFAR-10,CINIC-10,MNIST,EMNITS,and FEMNIST datasets,and the results show that the convergence of FedChoice is significantly improved,compared with FedAvg,FedProx,and FedNova.

关键词： Federated learning model aggregation Non-IID

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Cross-Modality Prompts: Few-Shot Multi-Label Recognition With Single-Label Training

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IEEE Transactions on Multimedia 2025年 27卷 3023-3033页

作者： Ding, Zixuan Zhou, Zihan Chen, Hui Hao, Tianxiang Xiong, Yizhe Zhao, Sicheng Zhang, Qiang Han, Jungong Xidian University State Key Laboratory of Electromechanical Integrated Manufacturing of High-Performance Electronic Equipments Xi'an710071 China Xidian University Center for Complex Systems School of Mechano-Electronic Engineering Xi'an710071 China Tsinghua University School of Software Beijing100190 China Tsinghua University Beijing National Research Center for Information Science and Technology Beijing100190 China Tsinghua University Department of Automation Beijing100190 China

Few-shot multi-label recognition (FS-MLR) presents a significant challenge due to the need to assign multiple labels to images with limited examples. Existing methods often struggle to balance the learning of novel classes and the retention of knowledge from base classes. To address this issue, we propose a novel Cross-Modality Prompts (CMP) approach. Unlike conventional methods that rely on additional semantic information to mitigate the impact of limited samples, our approach leverages multimodal prompts to adaptively tune the feature extraction network. A new FS-MLR benchmark is also proposed, which includes single-label training and multi-label testing, accompanied by benchmark datasets constructed from MS-COCO and NUS-WIDE. Extensive experiments on these datasets demonstrate the superior performance of our CMP approach, highlighting its effectiveness and adaptability. Our results show that CMP outperforms CoOp on the MS-COCO dataset with a maximal improvement of 19.47% and 23.94% in mAPharmonic for 5-way 1-shot and 5-way 5-shot settings, respectively. © 1999-2012 IEEE.

关键词： Zero-shot learning

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BOUNDEDNESS OF A CLASS OF MULTILINEAR OPERATORS AND THEIR ITERATED COMMUTATORS ON MORREY-BANACH FUNCTION SPACES

arXiv

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arXiv 2025年

作者： Tan, Jiawei Wang, Jiahui Xue, Qingying Guangxi Colleges Universities Key Laboratory of Data Analysis and Computation Guilin541004 China School of Mathematical Sciences Beijing Normal University Laboratory of Mathematics and Complex Systems Ministry of Education Beijing100875 China

This paper investigates the boundedness of a broad class of operators within the framework of generalized Morrey-Banach function spaces. This class includes multilinear operators such as multilinear ω-Calderón-Zygmund operators, multilinear maximal singular integral operators, multilinear pseudo-differential operators, and multilinear square functions, as well as linear operators such as rough singular integral operators, nonintegral operators, and Stein’s square functions. The boundedness of this class of operators and their commutators on Morrey-Banach spaces is established provided they satisfy either a pointwise sparse domination assumption or the Wr property (Lerner, Lorist and Ombrosi, Math. Z. 2024), which significantly generalize the classical theory of Morrey spaces. As an application, the boundedness of iterated commutators of this class of multilinear operators is extended to Morrey-Lorentz spaces and Morrey spaces with variable *** Codes 42B35 © 2025, CC BY.

关键词： Banach spaces

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SenseDSE: Sensitivity-Based Performance Evaluation for Design Space Exploration of Microarchitecture

SenseDSE: Sensitivity-Based Performance Evaluation for Desig...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Zheng Wu Xiaoling Yi Li Shang Fan Yang State Key Lab of Integrated Circuits and Systems School of Microelectronics Fudan University. Shanghai Key Laboratory of Data Science School of Computer Science Fudan University.

ISBN: (数字)9783981926385

ISBN: (纸本)9798350348606

The design of modern processors is driven by plenty of benchmarks. As processors evolve and applications expand, the complexity of benchmark programs grows, which increases the computational cost of architecture design space exploration (DSE). To accelerate performance evaluations of processors in DSE, we developed a sensitivity-based framework for performance evaluation of a large set of benchmarks. The framework avoids simulating the insensitive benchmarks to the adjusted parameters during the exploration of designs. We developed a sampling algorithm based on evolutionary strategies to provide learning data for the sensitivity analysis and enhance the performance of the fast performance evaluation algorithm. We integrated this framework into a RISe-V processor architecture exploration framework. Our experiments revealed that we could achieve a significant acceleration in runtime with negligible accuracy loss in DSE.

关键词： Performance evaluation Program processors Runtime Microarchitecture Sensitivity analysis Computer architecture Benchmark testing

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Interval Type-2 Fuzzy Hierarchical Adaptive Cruise Following-Control for Intelligent Vehicles

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1658-1672页

作者： Hong Mo Yinghui Meng Fei-Yue Wang Dongrui Wu the College of Electric and Information Engineering Changsha University of Science and TechnologyChangsha 410114China the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Qingdao Academy of Intelligent Industries Qingda 266109 the Center of China Economic and Social Security University of Chinese Academy of SciencesBeijing 100190China the Ministry of Education Key Laboratory on Image Information Processing and Intelligent Control the School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China

Intelligent vehicles can effectively improve traffic congestion and road traffic *** cruise followingcontrol(ACFC)is a vital part of intelligent *** this paper,a new hierarchical vehicle-following control strategy is presented by synthesizing the variable time headway model,type-2 fuzzy control,feedforward+fuzzy proportion integration(PI)feedback(F+FPIF)control,and inverse longitudinal dynamics model of ***,a traditional variable time headway model is improved considering the acceleration of the lead ***,an interval type-2 fuzzy logic controller(IT2 FLC)is designed for the upper structure of the ACFC system to simulate the driver's operating *** reduce the nonlinear influence and improve the tracking accuracy for the desired acceleration,the control strategy of F+FPIF is given for the lower control ***,the lower control method proposed in this paper is compared with the fuzzy PI control and the traditional method(no lower controller for tracking desired acceleration)***,the proportion integration differentiation(PID),linear quadratic regulator(LQR),subsection function control(SFC)and type-1 fuzzy logic control(T1 FLC)are respectively compared with the IT2 FLC in control performance under different ***,the simulation results show the effectiveness of IT2 FLC for the upper structure and F+FPIF control for the lower structure.

关键词： Adaptive cruise following-control(ACFC) feedforward+fuzzy proportion integration(PI)feedback(F+FPIF) type-2 fuzzy control variable time headway

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A Multi-Objective Evolutionary Machine Learning Method for the Yield Strength Prediction of Strip Steel in Continuous Annealing

A Multi-Objective Evolutionary Machine Learning Method for t...

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IISE Annual Conference and Expo 2024

作者： Liu, Chang Tang, Lixin Zhang, Kainan Guo, Jiajing National Frontiers Science Center for Industrial Intelligence and Systems Optimization North-eastern University Shenyang110819 China Ministry of Education Shenyang110819 China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Shenyang110819 China Liaoning Key Laboratory of Manufacturing System and Logistics Optimization Shenyang110819 China

ISBN: (纸本)9781713877851

In the continuous annealing process, the yield strength is the key property index to evaluate the quality of strip steel and guide the production. It is difficult to perform online quality measurement for numerous products in the steel industry, this brings significant challenges for process monitoring and operation optimization. In this paper, a multiobjective evolutionary machine learning method is proposed for the yield strength prediction of strip steel in continuous annealing. First, the factors affecting the yield strength of strip steel are analyzed and the prediction model based on a hybrid kernel support vector regression (HKSVR) is established. To improve the prediction accuracy, a multi-objective evolutionary optimization algorithm with a knee solution strategy is used to optimize the key parameters of the HKSVR. It is verified by the actual production data that the proposed method has high prediction accuracy and can meet the actual production demand. Moreover, the proposed method can help practitioners to construct quality analytics models for many other similar production lines, providing assurance for quality control and optimization with a good generalization. © IISE Annual Conference and Expo *** rights reserved.

关键词： Prediction models

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MFANet: Mixed Feature Attention Network for Port Lane Detection 42

MFANet: Mixed Feature Attention Network for Port Lane Detect...

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42nd Chinese Control Conference, CCC 2023

作者： Zhang, Jinwei Su, Jinya Yi, Dewei Yang, Jun Ministry of Education The School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing210096 China University of Aberdeen Department of Computing Science AberdeenAB24 3UE United Kingdom

ISBN: (纸本)9789887581543

With the advancement of industrial automation and artificial intelligence technology, unmanned port autonomy has gained increasing attention. Port automatic driving technology is a critical component of unmanned autonomous systems, enabling rubber tire gantry cranes (RTGs) to autonomously navigate by detecting port lanes and implementing control commands. In this study, a deep learning-based method is proposed for detecting port lanes in complex port scenes. The method employs the Inception module and attention mechanism to enhance lane feature extraction, and a structural loss is introduced to explicitly constrain the detection results and incorporate the prior characteristics of port lanes. A novel Mixed Feature Attention Network (MFANet) is proposed to implement the method for port lane detection. Experimental results demonstrate that MFANet effectively improves the accuracy of port lane detection while maintaining high computational efficiency. Furthermore, the performance of MFANet is evaluated in a real-world application scenario. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Computational efficiency

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TWO INEQUALITIES FOR COMMUTATORS OF SINGULAR INTEGRAL OPERATORS SATISFYING HÖRMANDER CONDITIONS OF YOUNG TYPE

arXiv

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arXiv 2025年

作者： Li, Yuru Tan, Jiawei Xue, Qingying School of Mathematical Sciences Beijing Normal University Laboratory of Mathematics and Complex Systems Ministry of Education Beijing100875 China Guangxi Colleges Universities Key Laboratory of Data Analysis and Computation Guilin541004 China

In this paper, we systematically study the Fefferman-Stein inequality and Coifman-Fefferman inequality for the general commutators of singular integral operators that satisfy Hörmander conditions of Young type. Specifically, we first establish the pointwise sparse domination for these operators. Then, relying on the dyadic analysis, the Fefferman-Stein inequality with respect to arbitrary weights and the quantitative weighted Coifman-Fefferman inequality are demonstrated. We decouple the relationship between the number of commutators and the index Ε, which essentially improved the results of Pérez and Rivera-Ríos (Israel J. Math., 2017). As applications, it is shown that all the aforementioned results can be applied to a wide range of operators, such as singular integral operators satisfying the Lr-Hörmander operators, ω-Calderón-Zygmund operators with ω satisfying a Dini condition, Calderón commutators, homogeneous singular integral operators and Fourier *** Codes 42B20, 42B25 © 2025, CC BY.

关键词： Choquet integral

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