检索结果-内蒙古大学图书馆

10th International Conference on Wireless Networks and Mobile Communications, WINCOM 2023

作者： Gouhail, Mohamed Mazoudi, El Houssin El Issam, Salhi Doubabi, Said Cadi Ayyad University Faculy of Sciences and Techniques Departement of Applied Physics Laboratory of Computer Control for Intelligent Systems and Green Energies Marrakech Morocco University of Technology of Belfort-Montbéliard Energy Department FEMTO-ST Belfort France

ISBN: (纸本)9798350329674

This paper presents a transformation method capable of analytically converting the given differential equations of dynamic models for a four-phase interleaved boost converter (IBC) coupled with a PEMFC into a Takagi-Sugeno fuzzy inference model (TS fuzzy model). This transformation enables the utilization of various parallel distributed compensation (PDC) controller design techniques. By combining the transformation method with PDC techniques, a framework for controller design is established. The proposed controller aims to improve the robustness and stabilization of the output voltage equilibrium point while minimizing the PEMFC current overshoot within a specified limit of the PEMFC current ripple, thereby providing protection. The stability of the proposed controller is proven using the Lyapunov theorem. An LMI condition is developed to synthesize the controller gains. The effectiveness of the PDC controller is further evaluated using Matlab Simulink. © 2023 IEEE.

关键词： Proton exchange membrane fuel cells (PEMFC)

来源：评论

学校读者我要写书评

暂无评论

Key Mention Pairs Guided Document-Level Relation Extraction 29

Key Mention Pairs Guided Document-Level Relation Extraction

引用

29th International Conference on Computational Linguistics, COLING 2022

作者： Jiang, Feng Niu, Jianwei Mo, Shasha Fan, Shengda State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China School of Cyber Science and Technology Beihang University Beijing100191 China

Document-level Relation Extraction (DocRE) aims at extracting relations between entities in a given document. Since different mention pairs may express different relations or even no relation, it is crucial to identify key mention pairs responsible for the entity-level relation labels. However, most recent studies treat different mentions equally while predicting the relations between entities, leading to sub-optimal performance. To this end, we propose a novel DocRE model called Key Mention pairs Guided Relation Extractor (KMGRE) to directly model mention-level relations, containing two modules: a mention-level relation extractor and a key instance classifier. These two modules could be iteratively optimized with an EM-based algorithm to enhance each other. We also propose a new method to solve the multi-label problem in optimizing the mention-level relation extractor. Experimental results on two public DocRE datasets demonstrate that the proposed model is effective and outperforms previous state-of-the-art models. © 2022 Proceedings - International Conference on Computational Linguistics, COLING. All rights reserved.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

INCREASE: Inductive Graph Representation Learning for Spatio-Temporal Kriging 23

INCREASE: Inductive Graph Representation Learning for Spatio...

引用

2023 World Wide Web Conference, WWW 2023

作者： Zheng, Chuanpan Fan, Xiaoliang Wang, Cheng Qi, Jianzhong Chen, Chaochao Chen, Longbiao Fujian Key Laboratory of Sensing and Computing for Smart Cities School of Informatics Xiamen University Xiamen China School of Computing and Information Systems University of Melbourne Melbourne Australia College of Computer Science and Technology Zhejiang University Hangzhou China

ISBN: (纸本)9781450394161

Spatio-temporal kriging is an important problem in web and social applications, such as Web or Internet of Things, where things (e.g., sensors) connected into a web often come with spatial and temporal properties. It aims to infer knowledge for (the things at) unobserved locations using the data from (the things at) observed locations during a given time period of interest. This problem essentially requires inductive learning. Once trained, the model should be able to perform kriging for different locations including newly given ones, without retraining. However, it is challenging to perform accurate kriging results because of the heterogeneous spatial relations and diverse temporal patterns. In this paper, we propose a novel inductive graph representation learning model for spatio-temporal kriging. We first encode heterogeneous spatial relations between the unobserved and observed locations by their spatial proximity, functional similarity, and transition probability. Based on each relation, we accurately aggregate the information of most correlated observed locations to produce inductive representations for the unobserved locations, by jointly modeling their similarities and differences. Then, we design relation-aware gated recurrent unit (GRU) networks to adaptively capture the temporal correlations in the generated sequence representations for each relation. Finally, we propose a multi-relation attention mechanism to dynamically fuse the complex spatio-temporal information at different time steps from multiple relations to compute the kriging output. Experimental results on three real-world datasets show that our proposed model outperforms state-of-the-art methods consistently, and the advantage is more significant when there are fewer observed locations. Our code is available at https://***/zhengchuanpan/INCREASE. © 2023 ACM.

关键词： Kriging

来源：评论

学校读者我要写书评

暂无评论

CETA: A Consensus Enhanced Training Approach for Denoising in Distantly Supervised Relation Extraction 29

CETA: A Consensus Enhanced Training Approach for Denoising i...

引用

29th International Conference on Computational Linguistics, COLING 2022

作者： Liu, Ruri Mo, Shasha Niu, Jianwei Fan, Shengda School of Cyber Science and Technology Beihang University Beijing100191 China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China

Distantly supervised relation extraction aims to extract relational facts from texts but suffers from noisy instances. Existing methods usually select reliable sentences that rely on potential noisy labels, resulting in wrongly selecting many noisy training instances or underutilizing a large amount of valuable training data. This paper proposes a sentence-level DSRE method beyond typical instance selection approaches by preventing samples from falling into the wrong classification space on the feature space. Specifically, a theorem for denoising and the corresponding implementation, named Consensus Enhanced Training Approach (CETA), are proposed in this paper. By training the model with CETA, samples of different classes are separated, and samples of the same class are closely clustered in the feature space. Thus the model can easily establish the robust classification boundary to prevent noisy labels from biasing wrongly labeled samples into the wrong classification space. This process is achieved by enhancing the classification consensus between two discrepant classifiers and does not depend on any potential noisy labels, thus avoiding the above two limitations. Extensive experiments on widely-used benchmarks have demonstrated that CETA significantly outperforms the previous methods and achieves new state-of-the-art results. © 2022 Proceedings - International Conference on Computational Linguistics, COLING. All rights reserved.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Currents in a HV cable in the presence of a conductive contaminant 2

Currents in a HV cable in the presence of a conductive conta...

引用

2nd International Conference on Advanced Electrical Engineering, ICAEE 2022

作者： Boudiaf, A. Bouazabia, S. Harid, N. Houari Boumediène University of Science and Technology Electric and Industrial Systems Laboratory Algiers Algeria Khalifa University of Science and Technology Department of Electrical and Computer Engineering Abu Dhabi United Arab Emirates

ISBN: (数字)9781665417419

ISBN: (纸本)9781665417419

The presence of a conductive contaminant within the insulation of a high voltage cable is at the origin of a conduction current likely to heat the insulation and lead to its *** the gas cavity (insulating defect), a very small conductive contaminant generates a very high electrical electric field. These fields are harmful and favor the creation of electrical trees. © 2022 IEEE.

关键词： Deterioration

来源：评论

学校读者我要写书评

暂无评论

SVDFed: Enabling Communication-Efficient Federated Learning via Singular-Value-Decomposition 42

SVDFed: Enabling Communication-Efficient Federated Learning ...

引用

42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Wang, Haolin Liu, Xuefeng Niu, Jianwei Tang, Shaojie Beihang University State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beijing China Zhongguancun Laboratory Beijing China Zhengzhou University Zhengzhou University Research Institute of Industrial Technology School of Information Engineering Zhengzhou China Naveen Jindal School Management University of Texas at Dallas Richardson United States

ISBN: (纸本)9798350334142

Federated learning (FL) is an emerging paradigm of distributed machine learning. However, when applied to wireless network scenarios, FL usually suffers from high communication cost because clients need to transmit their updated gradients to a server in every training round. Although many gradient compression techniques like sparsification and quantization are proposed, they compress clients' gradients independently, without considering the correlations among gradients. In this paper, we propose SVDFed, a collaborative gradient compression framework for FL. SVDFed utilizes Singular Value Decomposition (SVD) to find a few basis vectors, whose linear combination can well represent clients' gradients at a certain round. Due to the correlations among gradients, these basis vectors can still well approximate new gradients in many subsequent rounds. With the help of basis vectors, clients only need to upload the coefficients of the linear combination to the server, which greatly reduces communication cost. In addition, SVDFed leverages the classical PID (Proportional, Integral, Derivative) control to determine the proper time to update basis vectors to maintain their representation ability. Through experiments, we demonstrate that SVDFed outperforms existing gradient compression methods in FL. For example, compared to a popular gradient quantization method QSGD, SVDFed can reduce the communication overhead by 66 % and pending time by 99 %. © 2023 IEEE.

关键词： Singular value decomposition

来源：评论

学校读者我要写书评

暂无评论

Video-Based Real-Time Heart Rate Detection for Drivers Inside the Cabin Using a Smartphone

Video-Based Real-Time Heart Rate Detection for Drivers Insid...

引用

2022 IEEE International Conference on Internet of Things and Intelligence systems, IoTaIS 2022

作者： Othman, Walaa Kashevnik, Alexey Itmo University Information Technology and Programming Faculty St. Petersburg Russia Laboratory of Computer-aided Integrated Systems Spc Ras St. Petersburg Russia

ISBN: (数字)9798350396454

ISBN: (纸本)9798350396454

Developing vehicles with the Internet of Thing technology including driver health monitoring systems, driver safety systems, and accident prevention has drawn the attention of researchers in the last few years. The monitoring system should prevent any dangerous situation and be comfortable for the driver inside the cabin. In this paper, we introduce a remote video-based method for detecting the heart rate in real-time using smartphone cameras, which can be used for the analysis of the driver's physiological parameters to enhance driving safety. We propose to use 3DDFA for automatic facial landmarks detection to extract the driver's face and a 3d-classification-based model for detecting the heart rate. The experiments showed good results with mean absolute error (MAE) equal to 6.8 on the LGI-PPGI dataset and 18.68 on our DriverMVT dataset that was recorded in the wild. © 2022 IEEE.

关键词： Smartphones

来源：评论

学校读者我要写书评

暂无评论

Volumetric B1+ field homogenization in 7 Tesla brain MRI using metasurface scattering

arXiv

引用

arXiv 2024年

作者： Yoon, Gyoungsub Yu, Sunkyu Lee, Jongho Park, Namkyoo Photonic Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Intelligent Wave Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Laboratory for Imaging Science and Technology Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of

Ultrahigh field magnetic resonance imaging (UHF MRI) has become an indispensable tool for human brain imaging, offering excellent diagnostic accuracy while avoiding the risks associated with invasive modalities. When the radiofrequency magnetic field of the UHF MRI encounters the multifaceted complexity of the brain—characterized by wavelength-scale, dissipative, and random heterogeneous materials—detrimental mesoscopic challenges such as B1+ field inhomogeneity and local heating arise. Here we develop the metasurface design inspired by scattering theory to achieve the volumetric field homogeneity in the UHF MRI. The method focuses on finding the scattering ansatz systematically and incorporates a pruning technique to achieve the minimum number of participating modes, which guarantees stable practical implementation. Using full-wave analysis of realistic human brain models under a 7 Tesla MRI, we demonstrate more than a twofold improvement in field homogeneity and suppressed local heating, achieving better performance than even the commercial 3 Tesla MRI. The result shows a noninvasive generalization of constant intensity waves in optics, offering a universal methodology applicable to higher Tesla MRI. © 2024, CC BY.

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

Multi-Agent Moth-Flame Reinforcement Learning based Broadcast Beam Optimization

引用

IEEE Transactions on Mobile Computing 2025年

作者： Huang, Shan Yao, Haipeng Mai, Tianle Wu, Di Xu, Jiaqi Yu, F. Richard Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Carleton University Depart. Systems Computer Engineering Ottawa Canada

Currently, beamforming antenna array technologies are of utmost importance in 5G communication systems. These technologies are essential for optimizing the coverage and signal quality of the cellular network. However, the optimization of broadcast beams presents significant challenges due to the complex strategy profile space. Each beam can be configured with different widths and heights, making it difficult for conventional algorithms to handle. To address this issue, we propose a novel approach called Multi-Agent Moth-Flame Reinforcement Learning (MAMF-RL) algorithm for broadcast beam optimization. MAMF-RL combines reinforcement learning and moth-flame optimization algorithms to interactively search for the optimal broadcast beams. By decomposing the problem into multiple single-sector antenna configuration problems, MAMF-RL effectively reduces the algorithm complexity. We conducted experiments utilizing real data in an 18-sector wireless coverage area. To evaluate the performance of our proposed method, we compared it with traditional methods such as the particle swarm algorithm. The results demonstrate that our MAMF-RL model achieves an average coverage rate of 1.82% higher and a 13.74% lower overlapping coverage rate compared to traditional methods. © 2025 IEEE. All rights reserved.

关键词： 5G mobile communication systems

来源：评论

学校读者我要写书评

暂无评论

Finite Dimensional Koopman Form of Polynomial Nonlinear systems

arXiv

引用

arXiv 2023年

作者： Iacob, Lucian Cristian Schoukens, Maarten Tóth, Roland Control Systems Group Eindhoven University of Technology Eindhoven Netherlands Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

The Koopman framework is a popular approach to transform a finite dimensional nonlinear system into an infinite dimensional, but linear model through a lifting process, using so-called observable functions. While there is an extensive theory on infinite dimensional representations in the operator sense, there are few constructive results on how to select the observables to realize them. When it comes to the possibility of finite Koopman representations, which are highly important form a practical point of view, there is no constructive theory. Hence, in practice, often a data-based method and ad-hoc choice of the observable functions is used. When truncating to a finite number of basis, there is also no clear indication of the introduced approximation error. In this paper, we propose a systematic method to compute the finite dimensional Koopman embedding of a specific class of polynomial nonlinear systems in continuous-time such that, the embedding, without approximation, can fully represent the dynamics of the nonlinear system. © 2023, CC BY-NC-SA.

关键词： Nonlinear systems

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：