检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Li, Yansheng Wu, Yuning Cheng, Gong Tao, Chao Dang, Bo Wang, Yu Zhang, Jiahao Zhang, Chuge Liu, Yiting Tang, Xu Ma, Jiayi Zhang, Yongjun Information and computing science from Shandong University Weihai China Pattern recognition and intelligent system from the Huazhong University of Science and Technology Wuhan China Computer science and technology from Wuhan University Wuhan China Xidian University Xi’an China Pattern recognition and intelligent systems from Northwestern Polytechnical University Xi’an China School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan China Institute for Pattern Recognition and Artificial Intelligence Huazhong China University of Science and Technology Remote sensing science and technology from Wuhan University Wuhan China School of Remote Sensing and Information Engineering Wuhan University Wuhan China Electronic circuit and system from Xidian University Xi’an China University of Colorado at Boulder BoulderCO United States Control science and engineering from the Huazhong University of Science and Technology Wuhan China Geodesy and photography from Wuhan University Wuhan China

Accurate fine-grained geospatial scene classification using remote sensing imagery is essential for a wide range of applications. However, existing approaches often rely on manually zooming remote sensing images at different scales to create typical scene samples. This approach fails to adequately support the fixed-resolution image interpretation requirements in real-world scenarios. To address this limitation, we introduce the Million-scale finE-grained geospatial scEne classification dataseT (MEET), which contains over 1.03 million zoom-free remote sensing scene samples, manually annotated into 80 fine-grained categories. In MEET, each scene sample follows a scene-in-scene layout, where the central scene serves as the reference, and auxiliary scenes provide crucial spatial context for fine-grained classification. Moreover, to tackle the emerging challenge of scene-in-scene classification, we present the Context-Aware Transformer (CAT), a model specifically designed for this task, which adaptively fuses spatial context to accurately classify the scene samples. CAT adaptively fuses spatial context to accurately classify the scene samples by learning attentional features that capture the relationships between the center and auxiliary scenes. Based on MEET, we establish a comprehensive benchmark for fine-grained geospatial scene classification, evaluating CAT against 11 competitive baselines. The results demonstrate that CAT significantly outperforms these baselines, achieving a 1.88% higher balanced accuracy (BA) with the Swin-Large backbone, and a notable 7.87% improvement with the Swin-Huge backbone. Further experiments validate the effectiveness of each module in CAT and show the practical applicability of CAT in the urban functional zone mapping. The source code and dataset will be publicly available at https://***/project/***. Copyright © 2025, The Authors. All rights reserved.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

OPTIMAL SEARCH FOR A MARKOVIAN TARGET

引用

NAVAL RESEARCH LOGISTICS 1991年第4期38卷 531-554页

作者： OHSUMI, A Control and System Science Group Department of Mechanical and System Engineering Kyoto Institute of Technology Matsugasaki Sakyo Kyoto 606 Japan

This article is concerned with an optimal search method for detecting a randomly moving target whose dynamics are described by a stochastic differential equation. The key notions are formulating the problem as one of optimal control and establishing the searcher's strategy by finding the control signal minimizing the probability that the searcher fails to detect the target. The search equation and the search function are derived, and sufficient conditions are given for the existence of an optimal search control. Finally, in order to circumvent difficulties arising in the realization of the optimal search algorithm, a successive approximation is presented with simulation studies.

关键词：

来源：评论

学校读者我要写书评

暂无评论

DERIVATION OF THE NON-LINEAR SCHRODINGER-EQUATION FROM STOCHASTIC OPTIMAL-control

引用

INTERNATIONAL JOURNAL OF control 1989年第3期49卷 841-849页

作者： OHSUMI, A Control and Systems Science Group Department of Mechanical and System Engineering Kyoto Institute of Technology Kyoto Matsugasaki Sakyo Japan

The quantum-mechanical formulation of a class of stochastic optimal control problems is investigated and two versions of non-linear Schrödinger equation are derived. First, a wave-function is introduced which connects the probability density function of a diffusion process with the minimum cost functional of the stochastic optimal control problem associated with the diffusion process. It is then demonstrated that this wave-function satisfies a kind of Schrödinger-Langevin equation in quantum physics. Finally, the probabilistic interpretation of the wave-function is discussed.

关键词： control systems, Optimal

来源：评论

学校读者我要写书评

暂无评论

Dielectric Nanocavity Enhanced Fluorescence Emission for Ultrasensitive Wavelength-Multiplexed Detection

引用

Nano Letters 2025年 2025 May 20页

作者： Fu, Bowen Yuan, Zhiyi Fang, Guocheng Wang, Wen-Jie Xiong, Zhongshu Chen, Yu-Cheng School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore 639798 Singapore Institute for Digital Molecular Analytics and Science (IDMxS) Nanyang Technological University 59 Nanyang Drive Singapore 636921 Singapore Key Lab of Advanced Transducers and Intelligent Control System of Ministry of Education Taiyuan University of Technology Taiyuan 030024 China

This study demonstrates a novel biosensing platform utilizing a dielectric nanocavity to enhance fluorescence emission for the ultrasensitive detection of biomolecules. By coupling a silver (Ag) nanocube with a distributed Bragg reflector (DBR) mirror, we achieved a substantial fluorescence enhancement reaching a maximum enhancement factor of up to 855-fold and having quasi-single molecule sensitivity. The platform was successfully applied for multiplexed detection of four different miRNA biomarkers, showcasing its ability to detect multiple targets simultaneously with high sensitivity. The simplicity, rapid speed, and small detection volume (down to 0.5 μL) of this system make it suitable for high-throughput and large-area nanocavity imaging. Our findings offer a promising solution for ultrasensitive, multiplexed biosensing with potential applications in disease diagnosis, personalized medicine, and digital molecular diagnostics. © 2025 American Chemical Society.

关键词： dielectric-coupled nanocavity fluorescence enhancement high-throughput biosensing multiplexed detection nanoparticle quasi-single molecule level detection

来源：评论

学校读者我要写书评

暂无评论

A Risk-Averse Just-In-Time Scheme for Learning-Based Operation of Microgrids With Coupled Electricity-Hydrogen-Ammonia Under Uncertainties

引用

IEEE Transactions on Sustainable Energy 2025年

作者： Li, Longyan Ning, Chao Pan, Guangsheng Zhang, Leiqi Gu, Wei Zhao, Liang Du, Wenli Shahidehpour, Mohammad Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China School of Electrical Engineering Southeast University Nanjing210096 China Zhejiang Key Laboratory of Distributed Generations and Microgrid Technology State Grid Zhejiang Electric Power Research Institute Hangzhou310014 China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology China Department of Electrical and Computer Engineering Illinois Institute of Technology ChicagoIL60616 United States

This paper proposes a Risk-Averse Just-In-Time (RAJIT) operation scheme for Ammonia-Hydrogen-based Micro-Grids (AHMGs) to boost electricity-hydrogen-ammonia coupling under uncertainties. First, an off-grid AHMG model is developed, featuring a novel multi-mode ammonia synthesis process and a hydrogen-ammonia dual gas turbine with tunable feed-in ratios. Subsequently, a state-behavior mapping strategy linking hydrogen storage levels with the operation modes of ammonia synthesis is established to prevent cost-ineffective shutdowns. The proposed model substantially improves operational flexibility but results in a challenging nonlinear fractional program. Based upon this model, a data-driven RAJIT scheme is developed for the real-time rolling optimization of AHMGs. Unlike conventional one-size-fits-all schemes using one optimization method throughout, the data-driven RAJIT intelligently switches between cost-effective deterministic optimization and risk-averse online-learning distributionally robust optimization depending on actual risk profiles, thus capitalizing on the respective strengths of these two optimization methods. To facilitate the solution of the resulting nonlinear program, we develop an equivalent-reformulation-based solution methodology by leveraging a constraint-tightening technique. Numerical simulations demonstrate that the proposed scheme guarantees safety and yields an overall cost reduction up to 14.6% compared with several state-of-the-art methods. © 2025 IEEE.

关键词： Ammonia

来源：评论

学校读者我要写书评

暂无评论

The Binary and Ternary Quantization Can Improve Feature Discrimination

arXiv

引用

arXiv 2025年

作者： Lu, Weizhi Chen, Mingrui Li, Weiyu School of Control Science and Engineering Shandong University Key Laboratory of Machine Intelligence and System Control Ministry of Education China School of Control Science and Engineering Shandong University China Zhongtai Securities Institute for Financial Studies Shandong University National Center for Applied Mathematics in Shandong China

In machine learning, quantization is widely used to simplify data representation and facilitate algorithm deployment on hardware. Given the fundamental role of classification in machine learning, it is crucial to investigate the impact of quantization on classification. Current research primarily focuses on quantization errors, operating under the premise that higher quantization errors generally result in lower classification performance. However, this premise lacks a solid theoretical foundation and often contradicts empirical findings. For instance, certain extremely low bit-width quantization methods, such as {0, 1}-binary quantization and {0, ±1}-ternary quantization, can achieve comparable or even superior classification accuracy compared to the original non-quantized data, despite exhibiting high quantization errors. To more accurately evaluate classification performance, we propose to directly investigate the feature discrimination of quantized data, instead of analyzing its quantization error. Interestingly, it is found that both binary and ternary quantization methods can improve, rather than degrade, the feature discrimination of the original data. This remarkable performance is validated through classification experiments across various data types, including images, speech, and texts. © 2025, CC BY.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

The DRTS-Net Framework: Enhanced Probabilistic Health Perception for Wind Turbine Bearings Under Complex Operating Conditions With Improved Interpretability

引用

IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Yang, Tongguang Li, Guanchen Huo, Jinzhao Li, Xiaoyong Zhou, Xianwen Han, Qingkai Northeastern University School of Mechanical Engineering and Automation Shenyang110819 China Johns Hopkins University Department of Mechanical Engineering BaltimoreMD21218 United States Foshan University School of Mechatronic Engineering and Automation Foshan528225 China SCNU Environmental Research Institute Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety MOE Key Laboratory of Theoretical Chemistry of Environment South China Normal University School of Environment Guangzhou510006 China SCNU Qingyuan Institute of Science and Technology Innovation Company Ltd. Qingyuan511517 China Northeastern University Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Shenyang110819 China

Health perception in mechanical systems is a crucial aspect of prognostics and health management (PHM). Deep learning models have been successfully applied to health perception in wind turbine bearings. However, due to the time-varying, redundant, and noisy characteristics of time-series data representing bearing wear, existing models face significant challenges, particularly in terms of generalization and interpretability. Moreover, although most current models have provided health perceptions, they overlook the strong stochastic nature of bearing degradation data, and thus fail to deliver reliable predictions of uncertainty information. To address these technical challenges, this study introduces a novel Deep residual temporal-spatial framework (DRTS-Net) for probabilistic health perception of wind turbine bearing wear states. This article creatively designs spatiotemporal information fusion module for extracting features from bearing degradation data. Inspired by improvements in residual network structures, the DRTS-Net integrates an attention mechanism and a soft thresholding mechanism from the deep residual shrinkage network to optimize the feature extraction process. This integration aims to mitigate the interference from minor redundant features in the degradation data. The framework incorporates Gaussian process regression in the output layer to yield the probability distribution of single-health perception values for bearing features. A comparative study was conducted using the same bearing health state dataset against current mainstream deep learning methods for bearing health assessment. Results demonstrate that the proposed DRTS-Net achieves superior performance in high-precision health perception, high-reliability probabilistic health perception. © 1963-2012 IEEE.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

Tracking for near space nonballistic target based on several filter algorithms 34

Tracking for near space nonballistic target based on several...

引用

第三十四届中国控制会议

作者： QIN Lei ZHOU Di LI Jun-long Beijing Institute of Electronic System Engineering Department of Control Science and Engineering Harbin Institute of Technology

ISBN: (纸本)9781467374439

Recently, different countries have made rapid developments in the field of near space hypersonic vehicles. Among which successful hypersonic vehicle flight tests of X-51 A and HTV-2 are representative. They often adopt the way of nonballistic maneuver flight with characteristics of high speed and lift-to-drag ratio, flying in atmosphere for a long time. Their motion trajectory is sometimes characterized by "hopping", which induces difficulties of nonballistic target acceleration estimation, trajectory tracking and prediction. This paper introduces four typical nonballistic maneuver models of near space targets, and then introduces target ballistic equation and design of tracking filter. At last, four tracking filters are used to estimate target acceleration. Simulation results show that particle filter algorithm is the best one to guarantee the target tracking accuracy within allowable ranges.

关键词： Nonballistic target Near space Target maneuver Tracking filter

来源：评论

学校读者我要写书评

暂无评论

Tracking Filter for Nonballistic Targets in the Near Space Based on Modified Variable Structure Interacting Multiple Model 29

Tracking Filter for Nonballistic Targets in the Near Space B...

引用

第29届中国控制与决策会议

作者： Lei Qin Di Zhou Jun-long Li Beijing Institute of Electronic System Engineering Department of Control Science and Engineering Harbin Institute of Technology

ISBN: (纸本)9781509046584

As the representative of hypersonic vehicles in the near space,X-51 A and HTV-2 with high speed and irregular acceleration often adopt nonballistic maneuver flight motion,which is hard to be accurately *** paper focuses on three typical nonballistic maneuver models of near space targets,and proposes a new Modified Variable Structure Interacting Multiple Model(MVSIMM) *** the three nonballistic maneuver models,simulation results show that the MVSIMM algorithm is better than Fixed-Structure Interacting Multiple Model(FSIMM) filter algorithms.

关键词： Nonballistic Near Space Mathematical Models of Maneuver Motion Modified Variable Structure Interacting Multiple Model(MVSIMM)

来源：评论

学校读者我要写书评

暂无评论

Switching control of morphing aircraft based on Q-learning

引用

Chinese Journal of Aeronautics 2020年第2期33卷 672-687页

作者： Ligang GONG Qing WANG Changhua HU Chen LIU School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100083China Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control EngineeringBeijing 100190China Xi’an Institute of High Technology Xi’an 710025China School of Aeronautic Science and Engineering Beihang UniversityBeijing 100083China Beijing Institute of Electric System Engineering Beijing 100854China

This paper investigates a switching control strategy for the altitude motion of a morphing aircraft with variable sweep wings based on *** morphing process is regarded as a function of the system states and a related altitude motion model is ***,the designed controller is divided into the outer part and inner part,where the outer part is devised by a combination of the back-stepping method and command filter technique so that the’explosion of complexity’problem is ***,the integrator structure of the altitude motion model is exploited to simplify the back-stepping design,and disturbance observers inspired from the idea of extended state observer are devised to obtain estimations of the system *** control input switches from the outer part to the inner part when the altitude tracking error converges to a small value and linear approximation of the altitude motion model is *** inner part is generated by the Q-learning algorithm which learns the optimal command in the presence of unknown system matrices and *** is proved rigorously that all signals of the closed-loop system stay bounded by the developed control method and controller switching occurs only ***,comparative simulations are conducted to validate improved control performance of the proposed scheme.

关键词： Back-stepping Command filter Disturbance observer Morphing aircraft Q-learning Switching control

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：