检索结果-内蒙古大学图书馆

Vibration-Based Fault Diagnosis for Railway Point Machines Using VMD and Multiscale Fluctuation-Based Dispersion Entropy

引用

Chinese Journal of Electronics 2024年第3期33卷 803-813页

作者： Yongkui SUN Yuan CAO Peng LI Guo XIE Tao WEN Shuai SU National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University School of Electronic and Information Engineering Beijing Jiaotong University Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University

As one of the most important railway signaling equipment,railway point machines undertake the major task of ensuring train operation *** fault diagnosis for railway point machines becomes a hot *** the advantage of the anti-interference characteristics of vibration signals,this paper proposes an novel intelligent fault diagnosis method for railway point machines based on vibration signals.A feature extraction method combining variational mode decomposition(VMD) and multiscale fluctuation-based dispersion entropy is developed,which is verified a more effective tool for feature ***,a two-stage feature selection method based on Fisher discrimination and ReliefF is proposed,which is validated more powerful than single feature selection ***,support vector machine is utilized for fault *** comparisons show that the proposed method performs *** diagnosis accuracies of normal-reverse and reverse-normal switching processes reach 100% and 96.57% ***,it is a try to use new means for fault diagnosis on railway point machines,which can also provide references for similar fields.

关键词： Fault diagnosis Railway point machine Vibration signal Variational mode decomposition Two-stage feature selection

来源：评论

学校读者我要写书评

暂无评论

Improving Fake News Detection of Influential Domain via Domain- and Instance-Level Transfer 29

Improving Fake News Detection of Influential Domain via Doma...

引用

29th International Conference on Computational Linguistics, COLING 2022

作者： Nan, Qiong Wang, Danding Zhu, Yongchun Sheng, Qiang Shi, Yuhui Cao, Juan Li, Jintao Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China

Both real and fake news in various domains, such as politics, health, and entertainment are spread via online social media every day, necessitating fake news detection for multiple domains. Among them, fake news in specific domains like politics and health has more serious potential negative impacts on the real world (e.g., the infodemic led by COVID-19 misinformation). Previous studies focus on multi-domain fake news detection, by equally mining and modeling the correlation between domains. However, these multi-domain methods suffer from a seesaw problem: the performance of some domains is often improved at the cost of hurting the performance of other domains, which could lead to an unsatisfying performance in specific domains. To address this issue, we propose a Domain- and Instance-level Transfer Framework for Fake News Detection (DITFEND), which could improve the performance of specific target domains. To transfer coarse-grained domain-level knowledge, we train a general model with data of all domains from the meta-learning perspective. To transfer fine-grained instance-level knowledge and adapt the general model to a target domain, we train a language model on the target domain to evaluate the transferability of each data instance in source domains and re-weigh each instance’s contribution. Offline experiments on two datasets demonstrate the effectiveness of DITFEND. Online experiments show that DITFEND brings additional improvements over the base models in a real-world scenario. © 2022 Proceedings - International Conference on Computational Linguistics, COLING. All rights reserved.

关键词： Fake detection

来源：评论

学校读者我要写书评

暂无评论

Generalized-Extended-State-Observer and Equivalent-Input-Disturbance Methods for Active Disturbance Rejection: Deep Observation and Comparison

引用

IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 957-968页

作者： Jinhua She Kou Miyamoto Qing-Long Han Min Wu Hiroshi Hashimoto Qing-Guo Wang School of Engineering Tokyo University of TechnologyHachiojiTokyo 192-0982Japan K.Miyamoto is with the Institute of Technology Shimizu CorporationKotoTokyo 135-0044Japan School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia School of Automation China University of GeosciencesWuhan 430074 Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China School of Industrial Technology Advanced Institute of Industrial TechnologyTokyo 140-0011Japan Institute of Artificial Intelligence and Future Networks Beijing Normal UniversityZhuhai 519087 Guangdong Key Lab of AI and Multi-Modal Data Processing Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNUHKBU United International College Zhuhai 519087China

Active disturbance-rejection methods are effective in estimating and rejecting disturbances in both transient and steady-state *** paper presents a deep observation on and a comparison between two of those methods:the generalized extended-state observer(GESO)and the equivalent input disturbance(EID)from assumptions,system configurations,stability conditions,system design,disturbance-rejection performance,and extensibility.A time-domain index is introduced to assess the disturbance-rejection performance.A detailed observation of disturbance-suppression mechanisms reveals the superiority of the EID approach over the GESO method.A comparison between these two methods shows that assumptions on disturbances are more practical and the adjustment of disturbance-rejection performance is easier for the EID approach than for the GESO method.

关键词： Active disturbance-rejection control(ADRC) disturbance observer(DOB) equivalent input disturbance(EID) extendedstate observer(ESO) generalized extended-state observer(GESO)

来源：评论

学校读者我要写书评

暂无评论

OSAP‐Loss:Efficient optimization of average precision via involving samples after positive ones towards remote sensing image retrieval

引用

CAAI Transactions on Intelligence technology 2023年第4期8卷 1191-1212页

作者： Xin Yuan Xin Xu Xiao Wang Kai Zhang Liang Liao Zheng Wang Chia‐Wen Lin School of Computer Science and Technology Wuhan University of Science and TechnologyWuhanChina Hubei Province Key Laboratory of Intelligent Information Processing and Real‐time Industrial System Wuhan University of Science and TechnologyWuhanChina Nanyang Technological University SingaporeSingapore School of Computer Science Wuhan UniversityWuhanChina Department of Electrical Engineering Industrial Technology Research InstituteNational Tsing Hua UniversityHsinchuChina

In existing remote sensing image retrieval(RSIR)datasets,the number of images among different classes varies dramatically,which leads to a severe class imbalance *** studies propose to train the model with the ranking‐based metric(e.g.,average precision[AP]),because AP is robust to class ***,current AP‐based methods overlook an important issue:only optimising samples ranking before each positive sample,which is limited by the definition of AP and is prone to local *** achieve global optimisation of AP,a novel method,namely Optimising Samples after positive ones&AP loss(OSAP‐Loss)is proposed in this ***,a novel superior ranking function is designed to make the AP loss differentiable while providing a tighter upper ***,a novel loss called Optimising Samples after Positive ones(OSP)loss is proposed to involve all positive and negative samples ranking after each positive one and to provide a more flexible optimisation strategy for each ***,a graphics processing unit memory‐free mechanism is developed to thoroughly address the non‐decomposability of AP *** experimental results on RSIR as well as conventional image retrieval datasets show the superiority and competitive performance of OSAP‐Loss compared to the state‐of‐the‐art.

关键词： computer vision image retrieval metric learning

来源：评论

学校读者我要写书评

暂无评论

Research on financial social public opinion communication model based on variation mechanism 22

Research on financial social public opinion communication mo...

引用

Proceedings of the 2022 6th International Conference on Electronic Information technology and Computer Engineering

作者： Maojun Huang Mei Hong Lin Dong Da Yuan Key Laboratory of Intelligent Information Processing Shandong Technology and Business University China

ISBN: (纸本)9781450397148

In the context of rapid development of the Internet, the place of spreading financial public opinion is converted from traditional offline places to major online social platforms. Mastering the development mechanism of financial social opinion dissemination on online social media can effectively estimate the length of influence of public opinion and the scope of affected people, and provide effective guidance to relevant staff. Based on the Susceptible Infected Recovered Model, this paper divides the people involved in opinion diffusion into commenters and discussers, and introduces the variation mechanism to design the Susceptible-comment-discussion-removal model, then simulates the model to study the effects of different initial states and parameters on the model, and finally verifies the validity of the model by combining the real data of stock bars. The simulation experiments and validation show that the model can effectively describe the spread of public opinion among the user groups of financial social platforms when it occurs, and provide a valid reference for related workers. However, the content of public opinion, the personal influence of communicators, and the lag effect of communication all have an impact on communication, and these issues need to be addressed in future research.

关键词： variation mechanism financial social opinion SIR model public opinion dissemination SCDR model

来源：评论

学校读者我要写书评

暂无评论

Topic-BiGRU-U-Net for Document-level Relation Extraction from Biomedical Literature

Topic-BiGRU-U-Net for Document-level Relation Extraction fro...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Zhao, Yali Yan, Rong Inner Mongolia University College of Computer Science Hohhot China Inner Mongolia Key Laboratory of Mongolian Information Processing Technology Hohhot China Natl. Loc. Jt. Eng. Research Center of Intelligent Information Processing Technology for Mongolian Hohhot China

ISBN: (纸本)9798350337488

Document-level biomedical relation extraction refers to extract relationship facts from unstructured biomedical literature. Due to the fact that many relationship facts span multiple sentences and involve complex interactions between entities, it requires models with strong logical reasoning capabilities. However, previous methods have had limitations in terms of logical reasoning, such as lack logical reasoning and the entities merely based on a single granularity. Although other efforts are based on multiple granularity, including mention pairs and entity pairs, the inference mechanism is weak. In this paper, we propose a module to enhance the model's logical reasoning capabilities from four kinds of granularity (mention, entity, mention pairs, and entity pairs). Specifically, we encode the entities and mentions separately using BiGRU to capture contextual features. Simultaneously, we employ a U-Net network to model entity pairs and mention pairs, and enhance inter-sentence reasoning abilities. Additionally, to support the model's reasoning capabilities, we introduce topic nodes into the traditional heterogeneous graph to fully extract document information. Experimental results on CDR and GDA datasets in the biomedical field demonstrate the outstanding performance of the proposed model. © 2023 IEEE.

关键词： BiGRU document-level relation extraction information extraction U-Net

来源：评论

学校读者我要写书评

暂无评论

Federated Learning Based User Scheduling for Real-Time Multimedia Tasks in Edge Devices 1

引用

3rd EAI International Conference on Edge Computing and IoT, EAI ICECI 2022

作者： Wen, Wenkan Liu, Yiwen Gao, Yanxia Zhu, Zhirong Shi, Yuanquan Peng, Xiaoning School of Computer and Artificial Intelligence Huaihua University Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Hunan Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Hunan Huaihua418000 China

ISBN: (数字)9783031289903

ISBN: (纸本)9783031289897

Edge networks are highly volatile and the quality of device communication and computational resources change not only over time but also according to the movement of users. Current federation learning suffers from poor device network state and failure of devices to upload models in a timely manner. To address these problems, an intelligent scheduling mechanism that uses the predicted device state based on device information to select the appropriate device for federated learning is proposed in this paper. By focusing on information such as communication quality, computational resources, and location information, the information of edge devices is collected to analyze and predict the device network and computing resources to further analyze the state of devices in depth. Experiments are conducted on real datasets, and the experimental results show that the proposed scheduling method can make the global model fit faster than without the algorithm, which significantly improves the training efficiency of federated learning. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Skin-Friendly Large Matrix Iontronic Sensing Meta-Fabric for Spasticity Visualization and Rehabilitation Training via Piezo-Ionic Dynamics

引用

Nano-Micro Letters 2025年第4期17卷 291-307页

作者： Ruidong Xu Tong Xu Minghua She Xinran Ji Ganghua Li Shijin Zhang Xinwei Zhang Hong Liu Bin Sun Guozhen Shen Mingwei Tian Research Center for Intelligent and Wearable Technology College of Textiles and ClothingState Key Laboratory of Bio-Fibers and Eco-TextilesHealth&Protective Smart Textile Research Center of QingdaoQingdao UniversityQingdao 266071People’s Republic of China Academy of Arts&Design of Qingdao University Qingdao 266071People’s Republic of China College of Electronics and Information Qingdao UniversityQingdao 266071People’s Republic of China School of Integrated Circuits and Electronics Beijing Institute of TechnologyBeijing 100081People’s Republic of China

Rehabilitation training is believed to be an effectual strategy that canreduce the risk of dysfunction caused by ***,achieving visualizationrehabilitation training for patients remains clinically ***,wepropose visual rehabilitation training system including iontronic meta-fabrics withskin-friendly and large matrix features,as well as high-resolution image modules fordistribution of human muscle *** to the dynamic connection and dissociationof the meta-fabric,the fabric exhibits outstanding tactile sensing properties,such as wide tactile sensing range(0~300 kPa)and high-resolution tactile perception(50 Pa or 0.058%).Meanwhile,thanks to the differential capillary effect,the meta-fabric exhibits a“hitting three birds with one stone”property(dryness wearing experience,long working time and cooling sensing).Based on this,the fabrics can be integrated with garmentsand advanced data analysis systems to manufacture a series of large matrix structure(40×40,1600 sensing units)training ***,the tunability of piezo-ionic dynamics of the meta-fabric and the programmability of high-resolution imaging modules allowthis visualization training strategy extendable to various common disease ***,we believe that our study overcomes theconstraint of standard spasticity rehabilitation training devices in terms of visual display and paves the way for future smart healthcare.

关键词： Skin-friendly Large matrix Iontronic meta-fabric Spasticity visualization rehabilitation training

来源：评论

学校读者我要写书评

暂无评论

Fabrication and Characterization of Pressure Sensors Based on Xanthan Gum and Pullulan

Fabrication and Characterization of Pressure Sensors Based o...

引用

作者： Ya-Qi Zhang Shi-Yao Liu Yong-Zhen Tao State Key Laboratory for Textile Materials and Advanced Processing Technology Wuhan Textile University College of Material Science and Engineering Wuhan Textile University

Conductive hydrogels based on biopolymers have potential applications in the field of wearable devices,implantable devices, and human-machine interfaces due to their biocompatibility as well as ***, hydrogels are prone to water loss under dry atmospheres. In this paper, a biopolymer-based pressure sensor with water retention was designed. Xanthan gum(XG) and pullulan(P) were cross-linked with sodium trimetaphosphate(STMP) to prepare XG5-P-STMP, and polyethylene glycol with a molecular weight of 200(PEG200) was added into hydrogels to improve moisture retention. The mechanical properties of the hydrogels were investigated by rheologic measurements such as time sweep, frequency sweep, and strain sweep. The results showed that the addition of PEG200 enhanced strength and moisture retention of the hydrogels, and high PEG200 content hindered the recovery property of the hydrogels. Furthermore, the XG5-P-PEG-STMP hydrogel with ionic conductivity and recoverability was explored as a pressure sensor, and the resistance change ratio exhibited repeatable profile. This work provides some valuable information for further applications of natural polysaccharides as intelligent flexible elections.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Novel Approach Combining Decoupling Training with Prototype-based Contrastive Learning for Tracking Long-Tailed Recording in Optical Aerial Imagery

A Novel Approach Combining Decoupling Training with Prototyp...

引用

Signal, Information and Data processing (ICSIDP), IEEE International Conference on

作者： Jianlin Xie Guanqun Wang Tong Zhang Shilong Fan Yin Zhuang He Chen National Key Laboratory of Science & Technology on Space-Born Intelligent Information Processing (SBIIP) Beijing Institute of Technology Beijing China National Key Laboratory for Multimedia Information Processing Peking University Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Scene classification is a classical task in optical aerial imagery. In practical applications, it is difficult to obtain a balanced training samples supporting model training. Therefore, the dataset usually follow the Long-Tailed distribution, which is challenge for classification task, especially for multi-categories scene classification. It would make model intend to learn the representation of head classes with majority samples, which lead to under-represent middle and tail classes with minority samples and affect a better classifier construction for long-tailed classification. In this article, a novel Prototypical Supervised Contrastive Learning Based on Decoupling Framework called PSCL-DF is proposed for Long-Tailed Classification in Optical Remote Sensing Imagery to make a better feature learning and better classifier leaning. Finally, extensive tests are performed on the two artificially generated long-tailed datasets, demonstrating the robustness and effectiveness of the proposed methods. Our results show that decoupling feature extraction and classification achieve significant performance gains.

关键词： Training Integrated optics Scene classification Heavily-tailed distribution Optical recording Contrastive learning Optical imaging Feature extraction Optical sensors Remote sensing

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：