检索结果-内蒙古大学图书馆

28th Microoptics Conference, MOC 2023

作者： Lin, Guoping Harbin Institute of Technology Min. of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System School of Science Shenzhen518055 China

ISBN: (纸本)9784863488045

We have successfully manufactured two magnesium fluoride whispering gallery mode microcavities with diameters as small as a few hundred micrometers. Stimulated Raman scattering experiments conducted using these microcavities revealed low threshold levels and ultrahigh quality factors, suggesting a promising potential for their application in nonlinear photonics. © 2023 The Japan Society of Applied Physics.

关键词： Microcavities

来源：评论

学校读者我要写书评

暂无评论

Fuzzy identification of nonlinear dynamic system based on selection of important input variables

引用

Journal of systems engineering and Electronics 2022年第3期33卷 737-747页

作者： LYU Jinfeng LIU Fucai REN Yaxue Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment Yanshan UniversityQinhuangdao 066004China School of Mathematics and Information Science and Technology Hebei Normal University of Science and TechnologyQinhuangdao 066004China

Input variables selection(IVS) is proved to be pivotal in nonlinear dynamic system modeling. In order to optimize the model of the nonlinear dynamic system, a fuzzy modeling method for determining the premise structure by selecting important inputs of the system is studied. Firstly, a simplified two stage fuzzy curves method is proposed, which is employed to sort all possible inputs by their relevance with outputs, select the important input variables of the system and identify the ***, in order to reduce the complexity of the model, the standard fuzzy c-means clustering algorithm and the recursive least squares algorithm are used to identify the premise parameters and conclusion parameters, respectively. Then, the effectiveness of IVS is verified by two well-known issues. Finally, the proposed identification method is applied to a realistic variable load pneumatic system. The simulation experiments indi cate that the IVS method in this paper has a positive influence on the approximation performance of the Takagi-Sugeno(T-S) fuzzy modeling.

关键词： Takagi-Sugeno(T-S)fuzzy modeling input variable selection(IVS) fuzzy identification fuzzy c-means clustering algorithm

来源：评论

学校读者我要写书评

暂无评论

A Novel All-phase Fast Fourier Transform-based Parameters Identification of High Frequency Oscillations 60

A Novel All-phase Fast Fourier Transform-based Parameters Id...

引用

60th IEEE/IAS Industrial and Commercial Power systems Technical Conference, I and CPS 2024

作者： Sun, Feiyu Cai, Dongsheng Zhang, Zhenyuan Huang, Qi University of Electronic Science and Technology of China Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control School of Mechanical and Electrical Engineering Chengdu611731 China Chengdu University of Technology College of Nuclear Technology and Automation Engineering 610059 China Southwest University of Science and Technology School of Information Engineering Sichuan Mianyang China

ISBN: (纸本)9798350345308

Wind and solar energy inverter-based resources (IBRs) has been employed extensively with the aim of carbon neutrality. Power systems also make extensive use of power electronic converters, leading to interactions between IBRs and with the grid, causing high frequency oscillation (HFO) problems. It damages equipment and jeopardizes the security of the system. To identify HFO components above 100 Hz, this research use Phasor Measurement Unit (PMU) instantaneous value data to determine the HFO associated characteristics. To reduce the influence of spectral leakage and the fence effect, as well as to improve the identification accuracy of the related parameters, this paper adopts the RV self-convolutional window based Discrete Fourier Transform (DFT) and the Hanning double-window based all-phase Fast Fourier Transform (apFFT) hybrid algorithm to identify the HFO modal parameters. We take into account the identification accuracy in complex cases, such as non-nominal frequencies, with noise effects and multiple HFO modes. The simulation results show that the proposed method has high identification bandwidth, accuracy and strong flexibility. © 2024 IEEE.

关键词： Discrete Fourier transforms

来源：评论

学校读者我要写书评

暂无评论

A Practical Predefined-Time Stability Criterion and Its Application to Uncertain Nonlinear systems

引用

Journal of systems science & Complexity 2024年第6期37卷 2556-2578页

作者： XU Hao YU Dengxiu SUI Shuai XU Bowen CHEN C.L.Philip Unmanned System Research Institute Northwestern Polytechnical UniversityXi'an 710072China College of Science Liaoning University of TechnologyJinzhou 121001China School of Artificial Intelligence Optics and ElectronicsNorthwestern Polytechnical UniversityXi'an 710072China School of Computer Science and Engineering South China University of Technology and Pazhou LabGuangzhou 510641China

In this paper,the singularity-free predefined-time fuzzy adaptive tracking control problem is studied for non-strict feedback(NSF)nonlinear systems considering mismatched external *** innovative practical predefined-time stability(PPTS)criterion is proposed to provide the theoretical basis for subsequent control *** to the existing predefined-time stability(PTS)criterion,this criterion has a broader application range and can solve the control design issues of nonlinear systems with system *** logic systems(FLSs)are employed to identify unknown nonlinear *** on the backstepping control technology,a singularity-free predefined-time control(PTC)design method is proposed,in which the hyperbolic tangent function is utilized to avoid the singular problem,and the nature of fuzzy basis function is adopted to resolve the algebraic loop *** PPTS of the closed-loop NSF nonlinear system is proven with the Lyapunov theory and the proposed PPTS ***,the efficiency of the presented PTC design method is verified by several sets of simulations on a single link manipulator system.

关键词： Fuzzy adaptive control nonlinear systems practical predefined-time stability predefinedtime control singularity-free control

来源：评论

学校读者我要写书评

暂无评论

An efficient retrieval of relational database information based on knowledge graph

引用

International Journal of information and Communication technology 2023年第3期23卷 201-214页

作者： Zhu, Hongqin Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System East China University of Technology Jiangxi Nanchang330013 China Department of Information Engineering East China University of Technology 418 Guanglan Avenue Jiangxi Province Nanchang330013 China

In order to optimise the effect of database information retrieval and overcome the problem of high index cost of traditional retrieval methods, an efficient retrieval design method of relational database based on knowledge graph is designed in this paper. Firstly, the distribution model of database information retrieval nodes is constructed to analyse the data structure, and the semantic characteristics of stored data of retrieval nodes are fused. Then the knowledge graph model analysis method is used to retrieve the database node attribute clustering and adaptive scheduling to realise the design of efficient information retrieval model for the database. The experimental results show that the index distance cost of this method is always below 5 × 1,010 byte, and the index distance cost is always below 40 s, which has certain application value. © 2023 Inderscience Enterprises Ltd.

关键词： information retrieval

来源：评论

学校读者我要写书评

暂无评论

Transformer fault diagnosis based on relational teacher-student network

引用

The Journal of China Universities of Posts and Telecommunications 2023年第3期30卷 41-54页

作者： Yin Sihan Li Yalei Liu Xiaoping Cui Xu Wang Huapeng College of Information Science and Engineering Northeastern UniversityShenyang 110819China Beijing Key Laboratory of Research and System Evaluation of Dispatching Automation Technology China Electric Power Research InstituteBeijing 100192China

The analysis of dissolved gas in oil can provide an important basis for transformer fault *** order to improve the accuracy of transformer fault diagnosis,a method based on the relational teacher-student network(R-TSN)is proposed by analyzing the relationship between the dissolved gas in the oil and the fault type.R-TSN replaces the original hard labels with soft labels,and uses it to measure the similarity between different samples in the space,to a certain extent,it can obtain the hidden feature information in the samples,and clarify the classification *** the identification experiment,the effect of R-TSN diagnosis model is analyzed,and the influence of the compound fault of discharge and thermal on the diagnosis model is *** paper compares R-TSN with support vector machines(SVMs),decision trees and multilayer perceptron models in transformer fault *** results show that R-TSN has better performance than the above *** adding compound faults in the sample set,the accuracy rate can still reach 86.0%.

关键词： fault diagnosis transformer relational teacher-student network(R-TSN) soft label gas analysis in oil

来源：评论

学校读者我要写书评

暂无评论

LibAMM: Empirical Insights into Approximate Computing for Accelerating Matrix Multiplication 38

LibAMM: Empirical Insights into Approximate Computing for Ac...

引用

38th Conference on Neural information Processing systems, NeurIPS 2024

作者： Zeng, Xianzhi Jiang, Wenchao Zhang, Shuhao National Engineering Research Center for Big DataTechnology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Nanyang Technological University Singapore Singapore University of Technology and Design Singapore

Matrix multiplication (MM) is pivotal in fields from deep learning to scientific computing, driving the quest for improved computational efficiency. Accelerating MM encompasses strategies like complexity reduction, parallel and distributed computing, hardware acceleration, and approximate computing techniques, namely AMM algorithms. Amidst growing concerns over the resource demands of large language models (LLMs), AMM has garnered renewed focus. However, understanding the nuances that govern AMM's effectiveness remains incomplete. This study delves into AMM by examining algorithmic strategies, operational specifics, dataset characteristics, and their application in real-world tasks. Through comprehensive testing across diverse datasets and scenarios, we analyze how these factors affect AMM's performance, uncovering that the selection of AMM approaches significantly influences the balance between efficiency and accuracy, with factors like memory access playing a pivotal role. Additionally, dataset attributes are shown to be vital for the success of AMM in applications. Our results advocate for tailored algorithmic approaches and careful strategy selection to enhance AMM's effectiveness. To aid in the practical application and ongoing research of AMM, we introduce LibAMM -a toolkit offering a wide range of AMM algorithms, benchmarks, and tools for experiment management. LibAMM aims to facilitate research and application in AMM, guiding future developments towards more adaptive and context-aware computational solutions. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Nodes2STRNet for structural dense displacement recognition by deformable mesh model and motion representation

引用

International Journal of Mechanical system Dynamics 2023年第3期3卷 229-250页

作者： Jin Zhao Hui Li Yang Xu Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology Harbin Institute of TechnologyHarbinChina Key Lab of Structures Dynamics Behavior and Control of the Ministry of Education Harbin Institute of TechnologyHarbinChina School of Civil Engineering Harbin Institute of TechnologyHarbinChina Department of System Design and Simulation Goldwind Science and Technology Co.Ltd.BeijingChina

Displacement is a critical indicator for mechanical systems and civil *** vision-based displacement recognition methods mainly focus on the sparse identification of limited measurement points,and the motion representation of an entire structure is very *** study proposes a novel Nodes2STRNet for structural dense displacement recognition using a handful of structural control nodes based on a deformable structural three-dimensional mesh model,which consists of control node estimation subnetwork(NodesEstimate)and pose parameter recognition subnetwork(Nodes2PoseNet).NodesEstimate calculates the dense optical flow field based on FlowNet 2.0 and generates structural control node ***2PoseNet uses structural control node coordinates as input and regresses structural pose parameters by a multilayer perceptron.A self-supervised learning strategy is designed with a mean square error loss and L2 regularization to train *** effectiveness and accuracy of dense displacement recognition and robustness to light condition variations are validated by seismic shaking table tests of a four-story-building *** studies with image-segmentation-based Structure-PoseNet show that the proposed Nodes2STRNet can achieve higher accuracy and better robustness against light condition *** addition,NodesEstimate does not require retraining when faced with new scenarios,and Nodes2PoseNet has high self-supervised training efficiency with only a few control nodes instead of fully supervised pixel-level segmentation.

关键词： structural dense displacement recognition deformable structural mesh model deep-learning-based monocular vision self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

Multi-level Multi-task representation learning with adaptive fusion for multimodal sentiment analysis

引用

Neural Computing and Applications 2025年第3期37卷 1491-1508页

作者： Zhu, Chuanbo Chen, Min Li, Haomin Zhang, Sheng Liang, Han Sun, Chao Liu, Yifan Chen, Jincai Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Hubei Wuhan430074 China School of Computer Science and Engineering South China University of Technology Guangdong Guangzhou510641 China Pazhou Laboratory Guangdong Guangzhou510640 China School of Computer Science and Technology Huazhong University of Science and Technology Hubei Wuhan430074 China Key Laboratory of Information Storage System Ministry of Education of China Hubei Wuhan430074 China

Multimodal sentiment analysis is an active task in multimodal intelligence, which aims to compute the user’s sentiment tendency from multimedia data. Generally, each modality is a specific and necessary perspective to express human sentiment, providing complementary and consensus information unavailable in a single modality. Nevertheless, the heterogeneous multimedia data often contain inconsistent and conflicting sentiment semantics that limits the model performance. In this work, we propose a Multi-level Multi-task Representation Learning with Adaptive Fusion (MuReLAF) network to bridge the semantic gap among different modalities. Specifically, we design a modality adaptive fusion block to adjust modality contributions dynamically. Besides, we build a multi-level multimodal representations framework to obtain modality-specific and modality-shared semantics by the multi-task learning strategy, where modality-specific semantics contain complementary information and modality-shared semantics include consensus information. Extensive experiments are conducted on four publicly available datasets: MOSI, MOSEI, SIMS, and SIMSV2(s), demonstrating that our model exhibits superior or comparable performance to state-of-the-art models. The achieved accuracies are 86.28%, 86.07%, 84.46%, and 82.78%, respectively, showcasing improvements of 0.82%, 0.84%, 1.75%, and 1.83%. Further analyses also indicate the effectiveness of our model in sentiment analysis. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Multi-task learning

来源：评论

学校读者我要写书评

暂无评论

Attention Enhanced Feature Fusion for Mental Stress Level Classification 21

Attention Enhanced Feature Fusion for Mental Stress Level Cl...

引用

21st International Computer Conference on Wavelet Active Media technology and information Processing, ICCWAMTIP 2024

作者： Sahlu, Ameneshewa Abush Yohannes, Gobena Mulugeta Dawit, Bekalu Nigus Teshome, Molla Woretaw School of Computer Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China School of Information and Software Engineering University of Electronic Science and Technology of China Sichuan Chengdu China

ISBN: (纸本)9798331519254

Mental stress poses significant health risks, manifesting in various psychological and physical issues such as depression, anxiety, and cardiovascular complications. Establishing a reliable method for swiftly and accurately classifying mental stress levels is crucial due to its widespread impact. Existing classification approaches predominantly rely on either data-intensive traditional machine learning algorithms or opaque deep learning models, hindering real-world use and interpretability. This study addresses these limitations by proposing a novel approach for stress level classification using the WESAD dataset. Our method combines an attention-based ResN et with CBAM. This innovative approach synergistically integrates shallow and deep features, harnessing both low-level details and high-level semantic information to effectively classify stress levels into four distinct states: baseline, stress, amusement, and meditation, or three states excluding the meditation state. The experimental result shows 92.74% accuracy and 91.19% F1 score for the 4-class setup, and 97.58% accuracy and 97.51 % F1 score for the 3-class setup. Our approach offers a more robust and interpretable framework for mental stress classification, with potential applications in health care and stress management. © 2024 IEEE.

关键词： Deep learning

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：