检索结果-内蒙古大学图书馆

23rd International Conference on Machine Learning and Cybernetics, ICMLC 2024

作者： Yang, Runmin Yang, Rongni Ma, Renjie Zhu, Yanzheng Shi, Peng School of Control Science and Engineering Shandong University Jinan250061 China Harbin Institute of Technology State Key Laboratory of Robotics and Systems Harbin150001 China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao266590 China School of Electrical and Mechanical Engineering University of Adelaide AdelaideSA5005 Australia

ISBN: (纸本)9798331528041

This paper studies the stabilization problem of discrete-time two-dimensional (2-D) systems represented by Roesser based on available data. First of all, based on the pre-collected input-state data, the original system is transformed into a data-based form. Then a set is established to represent all systems capable of generating the given data, thereby indirectly stabilizing the original system by stabilizing all systems within this set. Next, by utilizing the S-procedure, sufficient conditions are established for the resultant closed-loop systems that incorporate a state feedback controller based on collected data. Finally, an example is given to demonstrate the effectiveness of the proposed approach. © 2024 IEEE.

关键词： Discrete time control systems

来源：评论

学校读者我要写书评

暂无评论

Low Rank Approximation Approach for Microwave Radar Coincidence Imaging

Low Rank Approximation Approach for Microwave Radar Coincide...

引用

2023 International Applied Computational Electromagnetics Society Symposium, ACES-China 2023

作者： Nian, Yiheng Zhu, Shitao Zhang, Anxue Zhang, Tao Mo, Xiuci School of Information and Communication Engineering Xi'an Jiaotong University Xi'an China Avic Leihua Electronic Technology Institute Aviation Key Laboratory of Science and Technology on Aisss Wuxi China

ISBN: (纸本)9781733509657

A low rank approximation algorithm for the Microwave Radar Coincidence Imaging (MRCI) is proposed in this paper. As a novel method of the radar imaging, the MRCI has the characteristics of high resolution and strong antiinference. Nevertheless, the imaging result will be aggravated when the Signal Noise Ratio (SNR) is low due to the illcondition of the reference matrix. Hence, a low rank approximation approach combined with conventional sparse reconstruction algorithm is proposed to improve the performance of the MRCI in the low SNR environment. First, the reference matrix is decomposed into the product of two matrices and the ranks of two matrices are analyzed. Then the low rank approximation approach is adopted and a new approximate imaging equation is estimated. Combined with SBL algorithm, the performance of reconstructed image is improved especially when the SNR is low. Simulation results are presented to validate the whole analysis and the proposed approach. © 2023 Applied Computational Electromagnetics Society (ACES).

关键词： Radar imaging

来源：评论

学校读者我要写书评

暂无评论

A Novel Capsule Robot Drive Module with Translational Motion Functions 20

A Novel Capsule Robot Drive Module with Translational Motion...

引用

20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Yao, Long Guo, Shuxiang The Key Laboratory of Convergence Biomedical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology Beijing Institute of Technology Beijing100081 China Southern University of Science and Technology The Department of Electronic and Electrical Engineering Guangdong Shenzhen518055 China

ISBN: (纸本)9798350320831

Wireless endoscopic robots, which are often used in gastrointestinal diseases, are difficult to integrate multiple functions simultaneously due to their limited size. Based on the functional modular working concept of capsule robots previously proposed. The drive module supports and navigates the functional modules for specific diagnosis or treatment, and the two can form new structures through docking mechanisms. The drive module developed so far has a simple structure and can realize basic transportation work, but the motion state is only a single axial rotation. In this study, we will introduce a magnetic drive module of a gastrointestinal capsule robot with forward translation movement ability, which can ensure horizontal forward movement under the condition of maintaining stability at one end, and the rotation surface of the external control magnetic field is replaced from a plane perpendicular to the direction of motion to a plane parallel to it, which is conducive to the utilization of the rotation degrees of freedom of the vertical plane by the functional module that matches it. Experiments show that the drive module can advance stably within the error range. © 2023 IEEE.

关键词： Magnetic fields

来源：评论

学校读者我要写书评

暂无评论

Towards Efficient Deep Spiking Neural Networks Construction with Spiking Activity based Pruning 41

Towards Efficient Deep Spiking Neural Networks Construction ...

引用

41st International Conference on Machine Learning, ICML 2024

作者： Li, Yaxin Xu, Qi Shen, Jiangrong Xu, Hongming Chen, Long Pan, Gang School of Computer Science and Technology Dalian University of Technology Dalian China Guangdong Laboratory of Artificial Intelligence and Digital Economy Shenzhen China College of Computer Science and Technology Zhejiang University Hangzhou China Centre for Systems Engineering and Innovation Imperial College London London United Kingdom

The emergence of deep and large-scale spiking neural networks (SNNs) exhibiting high performance across diverse complex datasets has led to a need for compressing network models due to the presence of a significant number of redundant structural units, aiming to more effectively leverage their low-power consumption and biological interpretability advantages. Currently, most model compression techniques for SNNs are based on unstructured pruning of individual connections, which requires specific hardware support. Hence, we propose a structured pruning approach based on the activity levels of convolutional kernels named Spiking Channel Activity-based (SCA) network pruning framework. Inspired by synaptic plasticity mechanisms, our method dynamically adjusts the network's structure by pruning and regenerating convolutional kernels during training, enhancing the model's adaptation to the current target task. While maintaining model performance, this approach refines the network architecture, ultimately reducing computational load and accelerating the inference process. This indicates that structured dynamic sparse learning methods can better facilitate the application of deep SNNs in low-power and high-efficiency scenarios. Copyright 2024 by the author(s)

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Research on entity extraction method for rehabilitation medicine knowledge management

Research on entity extraction method for rehabilitation medi...

引用

IEEE International Conference on Data science in Cyberspace (DSC)

作者： Weijie Deng Zhaoyun Ding Junqi Chen Yi Wang National Key Laboratory of Information Systems Engineering National University of Defense Technology China

ISBN: (数字)9798350391367

ISBN: (纸本)9798350391374

At present, the total number of disabled people in China is 85.914 million, and the number of elderly people over 60 is about 297 million, and the demand for rehabilitation and medical treatment is increasing day by day. However, there are still pain points, such as lack of cognition and shortage of talents in rehabilitation medicine, and there is a certain degree of disconnect with the huge demand. Therefore, it is very important to alleviate the imbalance between supply and demand of rehabilitation medical care through a new generation of information technology. However, due to the complexity and diversity of rehabilitation medicine literature and the differences among rehabilitation patients, the task of entity extraction is currently facing many challenges. At home and abroad, the research on medical entity extraction has achieved certain results. However, relatively little research has been done on this specific area of rehabilitation medicine. This study aims to fill this gap and provide an effective entity extraction method for knowledge management in rehabilitation medicine.(1)In order to solve the problems in the recognition of rehabilitation medicine terms, this paper carried out BIO standardized labeling of rehabilitation medicine data. Considering the complexity of rehabilitation medicine terminology, this paper introduces a named entity recognition framework that combines pre-training models, Bi-LSTM, and CRF to improve the performance of entity recognition tasks.(2)In order to evaluate the effectiveness of the named entity recognition model, contrast and ablation experiments were set up in this study. The results of comparative experiments show that the model has achieved remarkable performance improvement in the entity extraction task of rehabilitation medicine. Ablation experiments further verified the effectiveness of each component in the model.

关键词： Supply and demand Terminology Pain Biological system modeling Precision medicine Named entity recognition People with disabilities Knowledge management Complexity theory Data mining

来源：评论

学校读者我要写书评

暂无评论

Life Cycle Assessment and LCOE optimization of 12 MW wind farm 3

Life Cycle Assessment and LCOE optimization of 12 MW wind fa...

引用

3rd International Conference on Sustainable Mobility Applications, Renewables and technology, SMART 2024

作者： Tahtah, Abdelkarim Vido, Lionel Raouti, Driss Meziane, Rachid Abdelkrim, Bouanane Electrotechnical Engineering Laboratory University of Saida Dr Taher Moulay Saida20000 Algeria Lab. of Information and Energy Technology Systems and Application CY Cergy Paris University Cergy-Pontoise95000 France

ISBN: (纸本)9798331532925

The manufacture and installation of onshore wind farms is increasingly seen as a major investment. This growth is subject to significant economic and environmental constraints. The economic and environmental assessment depends on the life cycle stages and the levelized cost of electricity (LCOE) of wind farms. In this context, a mathematical model based on LCOE and Life Cycle Assessment (LCA) methodologies is developed to evaluate the size of wind turbines and the impact of the quantities of materials used in their manufacture on the total economic and environmental costs. The results show that the LCOE and greenhouse gas (GHG) emissions of wind farms are significantly influenced by the weight of materials, and the optimal size of the wind turbine needs to be selected. © 2024 IEEE

关键词： Windmill

来源：评论

学校读者我要写书评

暂无评论

Sparse Bayesian Learning Underwater Source Localization Method Based on Matched Beam

Sparse Bayesian Learning Underwater Source Localization Meth...

引用

2023 IEEE International Conference on Electrical, Automation and Computer engineering, ICEACE 2023

作者： Li, Qingji Han, Xiao Zhu, Guangping Wei, Zexun Harbin Engineering University Acoustic Science and Technology Laboratory Harbin150001 China Key Laboratory of Marine Information Acquisition Ministry of Industry and Information Technology Harbin150001 China College of Underwater Acoustic Engineering Harbin Engineering University Harbin150001 China First Institute of Oceanography Ministry of Natural Resources Qingdao China

ISBN: (纸本)9798350309614

In recent years, compressed sensing algorithms have received great attention in underwater passive source localization, but the classic sparse Bayesian learning localization method does not take into account the situation of environmental mismatch. To solve this problem, this paper proposes sparse Bayesian learning underwater source localization method based on matched beam (MBP-SBL). The method converts the pressure data received by the array into the beam domain through beamforming technology, and improves its robustness and resolution through beam filtering and sparse iteration in the beam domain. Simulation data and sea trial data in north Elba island are used to verify the proposed method. The results show that, compared with the classical Bartlett, MBP, MV-EPC and MFP-SBL methods, the method proposed in this paper is more tolerant to environmental mismatch while ensuring the localization result of high resolution and low side lobe. © 2023 IEEE.

关键词： environmental mismatch matched beam matched field processing passive source localization sparse Bayesian learning

来源：评论

学校读者我要写书评

暂无评论

HybridFL: Hybrid Approach Toward Privacy-Preserving Federated Learning 6th

HybridFL: Hybrid Approach Toward Privacy-Preserving Federate...

引用

6th International Conference on Security and Privacy in New Computing Environments, SPNCE 2023

作者： Ali, Sheraz Mamoon, Saqib Usman, Areeba Abidin, Zain ul Zhao, Chuan School of Information Science and Engineering University of Jinan Jinan250022 China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China University of Sargodha Sargodha Pakistan Shandong Provincial Key Laboratory of Network-Based Intelligent Computing University of Jinan Jinan250022 China Shandong Provincial Key Laboratory of Software Engineering University of Jinan Jinan250022 China

ISBN: (纸本)9783031736988

In this study, we introduce a novel Hybrid Federated Learning (HybridFL) approach aimed at enhancing privacy and accuracy in collaborative machine learning scenarios. Our methodology integrates Differential Privacy (DP) and secret sharing techniques to address inference risks during training and protect against information leakage in the output model. Drawing inspiration from recent advances, we present a HybridFL framework that combines the strengths of Homomorphic Encryption (HE) and Multi-Party Computation (MPC) to achieve secure computation without the computational overhead of pure HE methods. Our contributions include a privacy-preserving design for Federated Learning (FL) that ensures local data privacy through secret sharing while leveraging DP mechanisms for noise addition. The system offers resilience against unreliable participants and is evaluated using various machine learning models, including Convolutional Neural Networks (CNN), Multi-Layer Perceptrons (MLP), and linear regression. Furthermore, we address potential external threats by deploying predictive model outputs as robust services against inference attacks. Experimental results demonstrate improved accuracy and convergence speed, establishing the viability of HybridFL as an effective solution for collaborative machine learning with enhanced privacy guarantees. © ICST Institute for Computer sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

engineering strong spin-frustration at the surface of three-dimensional graphene

引用

science Bulletin 2024年第18期69卷 2816-2819页

作者： Wenjing Li Ken Chen Menglei Li Huiying Gao Jize Zhao Fawei Zheng Wenhui Duan Center for Quantum Physics Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement(MOE)School of PhysicsBeijing Institute of TechnologyBeijing 100081China Beijing Key Lab of Nanophotonics&Ultrafine Optoelectronic Systems School of PhysicsBeijing Institute of TechnologyBeijing 100081China School of Physical Science and Technology Key Laboratory of Quantum Theory and Applications of MOELanzhou UniversityLanzhou 730000China Lanzhou Center for Theoretical Physics Key Laboratory of Theoretical Physics of Gansu ProvinceLanzhou UniversityLanzhou 730000China Department of Physics Capital Normal UniversityBeijing 100048China State Key Laboratory of Low Dimensional Quantum Physics Department of PhysicsTsinghua UniversityBeijing 100084China Institute for Advanced Study Tsinghua UniversityBeijing 100084China Frontier Science Center for Quantum Information Beijing 100084China Beijing Academy of Quantum Information Sciences Beijing 100193China

Since the first successful fabrication in 2004[1],graphene has received tremendous attention due to its extremely simple atomic structure and alluring physical *** example,its massless low energy excitations have a linear dispersion and thus its transport property is governed by Dirac equation instead of Schr?dinger *** special electronic structures suppress the intra-valley and inter-valley backscatterings,leading to the half-integer and fractional quantum Hall effect[2]under magnetic field and the relativistic quantum tunneling described by the Klein paradox[3].

关键词： properties equation quantum

来源：评论

学校读者我要写书评

暂无评论

Attention-Based Deep Learning Model for Image Desaturation of SDO/AIA

引用

Research in Astronomy and Astrophysics 2023年第8期23卷 92-102页

作者： Xinze Zhang Long Xu Zhixiang Ren Xuexin Yu Jia Li State Key Laboratory of Space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Peng Cheng Laboratory Shenzhen 518000China Department of Automation Tsinghua UniversityBeijing 100084China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

The Atmospheric Imaging Assembly(AIA)onboard the Solar Dynamics Observatory(SDO)captures full-disk solar images in seven extreme ultraviolet wave *** a violent solar flare occurs,incoming photoflux may exceed the threshold of an optical imaging system,resulting in regional saturation/overexposure of ***,the lost signal can be partially retrieved from non-local unsaturated regions of an image according to scattering and diffraction principle,which is well consistent with the attention mechanism in deep ***,an attention augmented convolutional neural network(AANet)is proposed to perform image desaturation of SDO/AIA in this *** is built on a U-Net backbone network with partial convolution and adversarial *** addition,a lightweight attention model,namely criss-cross attention,is embedded between each two convolution layers to enhance the backbone *** results validate the superiority of the proposed AANet beyond state-of-the-arts from both quantitative and qualitative comparisons.

关键词： techniques image processing-Sun atmosphere-Sun flares

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：