检索结果-内蒙古大学图书馆

A novel multi-modal tactile sensor design using thermochromic material

Science China(Information Sciences) 2019年第11期62卷 189-191页

作者： Fuchun SUN Bin FANG Hongxiang XUE Huaping LIU Haiming HUANG Department of Computer Science and Technology Tsinghua University Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University College of Information Engineering Shenzhen University

Tactile sensors are important for ensuring robotic perception [1], and their performance directly affects a robot’s capability for performing dexterous operations. These sensors mimic the tactile sensing capability of human hands. This is because the skin of human hands is involved in considerably meticulous works and can provide multi-

关键词： A novel multi-modal tactile sensor design using thermochromic material

来源：评论

学校读者我要写书评

暂无评论

Detection System of Remainder Particle for Space-borne Electronic Equipment Based on PIND

Detection System of Remainder Particle for Space-borne Elect...

引用

IEEE International Conference on Cyber Technology in Automation, control, and Intelligent Systems

作者： Zhishuai Jiang Chengzhong Yu Dongmei Yan Yuliang Zhao School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China Key Lab of Industrial Computer Control Engineering of Hebei Province School of Electrical Engineering Yanshan University Qinhuangdao China

Space-borne electronic equipment is an indispensable part of the space system, but the possible remainder particle in the sealed space-borne electronic equipment causes irreparable losses to the space system. How to detect the remainder particle for space-borne electronic equipment has always been a key problem affecting the stability of the spaceborne electronic equipment and the safety of space. Particle impact noise detection (PIND) is usually used to detect remainder particle. However, how to use PIND to design a convenient and fast system to detect the remainder particle for sealed space-borne electronic equipment has always been the focus of research. In the system, artificial vibration is used by us to provide vibration conditions for the tested parts, and the noise information is collected by acoustic emission sensor. Then the data acquisition card is used to collect the information to the host computer. In order to detect remainder particle, individual pulse is extracted to process the acquired noise information firstly. Next, analyze time domain features of single pulse to judge the quality and material of remainder particle. Simultaneously, distinguish component signal or signal of remainder particle by short-time Fourier transform. Through many experiments, the accuracy of the system can reach 100% by this method.

关键词： Vibrations Electronic equipment Fourier transforms Data acquisition Feature extraction Stability analysis Safety

来源：评论

学校读者我要写书评

暂无评论

Sinusoidal-Assisted Synchrosqueezing Transform: Algorithms and Biomedical Applications

SSRN

引用

SSRN 2023年

作者： Chen, Tao Zheng, Qian Xie, Lei Su, Hongye State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China College of Computer Science and Control Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Hangzhou Flexolink Technology Co. Ltd. Hangzhou China

Intermittent oscillation signals (IOSs) exist widely in biomedical systems. They are always contaminated by various randomness like noise and artifacts. Compared with traditional time-frequency analysis (TFA) methods, adaptive TFA methods show the significant advantages in separating IOSs. However, these methods are implemented by assuming that the signal is in a weakly noisy environment and have narrow-band limitation. Besides, it is difficult for these methods to alleviate the noise in the gap among time where IOSs happen. Therefore, in this paper, a new method called the sinusoidal-assisted synchrosqueezing transform (SASST) is proposed for separating IOSs in strongly noisy environment. The SASST method locates the IOSs with the aid of a sinusoidal signal. Such a sinusoidal signal fills the energy blank in the gap between time where IOSs happen. This enables that the ridge detection approach, which is the necessary tool for mode retrieval of SST-based methods, focuses on the assisted sinusoidal signal, rather than noise. Thus, the background noise in the gap is suppressed. Moreover, this sinusoidal-assisted framework can be introduced into any SST-based TFA methods. Depending on the characteristics of different biomedical signals, different SST-based methods are chosen to achieve better separation. As a result, SASST is capable of extracting both narrow- and wide-band IOSs in a strongly noisy environment. The effectiveness and advantages of the proposed algorithm are verified by both numerical simulations and real-world cases. Even in a strong noise environment of -10dB, SASST achieve output SNR of 12.66dB and 10.53dB in narrow- and wide-band simulation, respectively. © 2023, The Authors. All rights reserved.

关键词： Medical applications

来源：评论

学校读者我要写书评

暂无评论

NeurAR: Neural Uncertainty for Autonomous 3D Reconstruction with Implicit Neural Representations

arXiv

引用

arXiv 2022年

作者： Ran, Yunlong Zeng, Jing He, Shibo Chen, Jiming Li, Lincheng Chen, Yingfeng Lee, Gimhee Ye, Qi The College of Control Science and Engineering Zhejiang University Hangzhou China The College of Control Science and Engineering The State Key Laboratory of Industrial Control Technology Zhejiang University The Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province China Fuxi AI Lab NetEase Inc. Hangzhou China The Department of Computer Science National University of Singapore Singapore

Implicit neural representations have shown compelling results in offline 3D reconstruction and also recently demonstrated the potential for online SLAM systems. However, applying them to autonomous 3D reconstruction, where a robot is required to explore a scene and plan a view path for the reconstruction, has not been studied. In this paper, we explore for the first time the possibility of using implicit neural representations for autonomous 3D scene reconstruction by addressing two key challenges: 1) seeking a criterion to measure the quality of the candidate viewpoints for the view planning based on the new representations, and 2) learning the criterion from data that can generalize to different scenes instead of a hand-crafting one. To solve the challenges, firstly, a proxy of Peak Signal-to-Noise Ratio (PSNR) is proposed to quantify a viewpoint quality;secondly, the proxy is optimized jointly with the parameters of an implicit neural network for the scene. With the proposed view quality criterion from neural networks (termed as Neural Uncertainty), we can then apply implicit representations to autonomous 3D reconstruction. Our method demonstrates significant improvements on various metrics for the rendered image quality and the geometry quality of the reconstructed 3D models when compared with variants using TSDF or reconstruction without view planning. Project webpage https://***/NeurAR/. Copyright © 2022, The Authors. All rights reserved.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

Multiple α sub-variants and anisotropic mechanical properties of an additively-manufactured Ti-6Al-4V alloy

引用

Journal of Materials Science & Technology 2021年第11期70卷 113-124页

作者： Yinling Zhang Zhuo Chen Shoujiang Qu Aihan Feng Guangbao Mi Jun Shen Xu Huang Daolun Chen School of Materials Science and Engineering Tongji UniversityShanghai 201804China Department of Mechanical and Industrial Engineering Ryerson UniversityTorontoOntario M5B 2K3Canada Aerospace Hiwing(Harbin)Titanium Industrial Co. Ltd.Harbin High Tech ZoneHarbin 150028China Shanghai Key Lab.of D&A for Metal-Functional Materials School of Materials Science&EngineeringTongji UniversityShanghai 201804China Aviation Key Laboratory of Science and Technology on Advanced Titanium Alloys AECC Beijing Institute of Aeronautical MaterialsBeijing 100095China College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China

Additive manu facturing(AM)is a promising material processing method which gains significant momentum in the aerospace and biomedical ***,the anisotropy in the mechanical properties of additively-manufactured materials is still poorly *** study was aimed at elucidating crystallographic feature-anisotropy-mechanical property relationship for a Ti-6Al-4V alloy manufactured via selective electron beam melting(SEBM).Abundantαlamellae with six variants were present inside the columnar prior-βgrains with a<100>fiber texture duringβ→αphase *** sixαvariants followed the Burgers orientation relationship of{110}_(β)//{0001}_(α)and<1-11>_(β)//<11-20>_(α).Multiple sub-variants in eachαvariant were observed for the first *** anisotropy in the mechanical properties was mainly related to the relative amount of sixα*** the horizontally-oriented samples had a lower yield strength,they exhibited a higher ductility and longer fatigue life than the vertically-oriented *** softening occurred at higher strain amplitudes,and cyclic stabilization sustained at lower strain *** crack mainly initiated from the specimen surface at lower strain amplitudes,while multiple crack initiation tended to occur at higher strain *** propagation was characterized by fatigue striations along with some secondary cracks.

关键词： Titanium alloy 3D printing Deformation behavior Anisotropy Burgers orientation relationship

来源：评论

学校读者我要写书评

暂无评论

Mitigating the Negative Impact of Over-association for Conversational Query Production

arXiv

引用

arXiv 2024年

作者： Wang, Ante Song, Linfeng Min, Zijun Xu, Ge Wang, Xiaoli Yao, Junfeng Su, Jinsong School of Information Xiamen University Xiamen China Xiamen Key Laboratory of Intelligent Storage and Computing Xiamen China Tencent AI Lab BellevueWA United States College of Computer and Control Engineering Minjiang University Fuzhou China

Conversational query generation aims at producing search queries from dialogue histories, which are then used to retrieve relevant knowledge from a search engine to help knowledge-based dialogue systems. Trained to maximize the likelihood of gold queries, previous models suffer from the data hunger issue, and they tend to both drop important concepts from dialogue histories and generate irrelevant concepts at inference time. We attribute these issues to the over-association phenomenon where a large number of gold queries are indirectly related to the dialogue topics, because annotators may unconsciously perform reasoning with their background knowledge when generating these gold *** carefully analyze the negative effects of this phenomenon on pretrained Seq2seq query producers and then propose effective instance-level weighting strategies for training to mitigate these issues from multiple perspectives. Experiments on two benchmarks, Wizard-of-Internet and DuSinc, show that our strategies effectively alleviate the negative effects and lead to significant performance gains (2% ∼ 5% across automatic metrics and human evaluation). Further analysis shows that our model selects better concepts from dialogue histories and is 10 times more data efficient than the baseline. The code is available at https://***/DeepLearnXMU/QG-OverAsso. © 2024, CC BY.

关键词： Structured Query Language

来源：评论

学校读者我要写书评

暂无评论

Vulnerability of Machine Learning Approaches Applied in IoT-based Smart Grid: A Review

arXiv

引用

arXiv 2023年

作者： Zhang, Zhenyong Liu, Mengxiang Sun, Mingyang Deng, Ruilong Cheng, Peng Niyato, Dusit Chow, Mo-Yuen Chen, Jiming The State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guiyang550000 China The Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS10 2TN United Kingdom The State Key Laboratory of Industrial Control Technology the College of Control Science and Engineering Zhejiang University Hangzhou310027 China The School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore The UM SJTU Joint Institute Shanghai Jiao Tong University Shanghai200240 China

Machine learning (ML) sees an increasing prevalence of being used in the internet-of-things (IoT)-based smart grid. However, the trustworthiness of ML is a severe issue that must be addressed to accommodate the trend of ML-based smart grid applications (MLsgAPPs). The adversarial distortion injected into the power signal will greatly affect the system’s normal control and operation. Therefore, it is imperative to conduct vulnerability assessment for MLsgAPPs applied in the context of safety-critical power systems. In this paper, we provide a comprehensive review of the recent progress in designing attack and defense methods for MLsgAPPs. Unlike the traditional survey about ML security, this is the first review work about the security of MLsgAPPs that focuses on the characteristics of power systems. We first highlight the specifics for constructing the adversarial attacks on MLsgAPPs. Then, the vulnerability of MLsgAPP is analyzed from both the aspects of the power system and ML model. Afterward, a comprehensive survey is conducted to review and compare existing studies about the adversarial attacks on MLsgAPPs in scenarios of generation, transmission, distribution, and consumption, and the countermeasures are reviewed according to the attacks that they defend against. Finally, the future research directions are discussed on the attacker’s and defender’s side, respectively. We also analyze the potential vulnerability of large language model-based (e.g., ChatGPT) power system applications. Overall, we encourage more researchers to contribute to investigating the adversarial issues of MLsgAPPs. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

A Quantized Kernel Least-mean-square Algorithm Based on Echo State Network for Online Time-series Prediction 11

A Quantized Kernel Least-mean-square Algorithm Based on Echo...

引用

11th International Conference on Information Science and Technology, ICIST 2021

作者： Zhao, Chaochao Han, Min Wang, Jun Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian China Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian China

ISBN: (纸本)9781665412667

Kernel least mean square (KLMS) algorithm is a popular method for online time-series prediction. It has the advantages of high robustness, low computational complexity, model simplicity, and online learning ability. Unfortunately, as input data grows, its dictionary size increases and the computational complexity rises significantly. In addition, how to improve the adaptability in uncertain environments with noise is also one of the main challenges. In this paper, we propose a Quantized Kernel Least-mean-square Based on Echo State Network (ES-QKLMS) algorithm in response to the above problems. In the new algorithm, the reservoirs of the echo state network (ESN) are integrated with the KLMS algorithm for online prediction. The ESN reservoir can store the associated information of historical data, which improves the algorithm's ability to track temporal characteristics. Then, the vector quantization method is adopted to suppress the size of the KLMS dictionary. Moreover, the adaptive weight adjustment is used to improve the noise immunity in an uncertain environment. At last, The Lorenz time series and the El Nino-Southern Oscillation (ENSO) time series are discussed to demonstrate the efficacy of the ES-QKLMS algorithm. © 2021 IEEE.

关键词： Time series

来源：评论

学校读者我要写书评

暂无评论

An Aerial Image Stitching Algorithm Based on Long-distance Features 11

An Aerial Image Stitching Algorithm Based on Long-distance F...

引用

11th International Conference on Information Science and Technology, ICIST 2021

作者： Liu, Qiang Han, Min Wang, Jun Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian China Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian China

ISBN: (纸本)9781665412667

Aerial image stitching is very important in obtaining UAV information. The Speeded Up Robust Features Algorithm (SURF) is an image matching method with high robustness. However, the SURF algorithm subjects to the problems of inexact edge positioning and low matching accuracy. In order to obtain high-precision aerial stitching images with high efficiency, an aerial image stitching algorithm based on long-distance features is proposed in this paper. First, the Canny-SURF algorithm is used for feature detection. After that, the Long-Fast Retina keypoint (L-FREAK) binary symbol is used to describe and match the feature points. Finally, the Random Sample Consensus Algorithm (RANSAC) is used to compute the projection transformation model, and the weighted average fusion algorithm is used to fuse the pixels. Experimental results show that the proposed algorithm is outperform the SIFT, SURF, ORB, and BRISK algorithms. The proposed algorithm has good stitching accuracy, and can stitch aerial images with wide rotation characteristics. © 2021 IEEE.

关键词： Antennas

来源：评论

学校读者我要写书评

暂无评论

Actuator Fault Estimation Based On Adaptive Iterative Learning Algorithm For Nonlinear Periodic Systems

Actuator Fault Estimation Based On Adaptive Iterative Learni...

引用

第40届中国控制会议

作者： Ya-qi Liu Yi-ming Fang Le Liu Xing-da Li Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Engineering Research Center of the Education Ministry for Intelligent Control System and Intelligent Equipment Yanshan University

A actuator fault estimation algorithm based on adaptive iterative learning is proposed for a class of nonlinear periodic systems with actuator fault and ***,the proposed method designs a state observer and a fault estimator based on adaptive iterative *** Lyapunov stability theory and the optimization theory are employed to prove the convergence of the *** the LMI toolbox is utilized to obtain the results of the observer gain matrix and fault estimator parameter *** method combines the iterative learning strategy with the adaptive algorithm,and utilizes not only the state error signals of the last iteration learning,but also the output error signals of this *** makes the estimated fault approximate to the real fault gradually and realizes the accurate estimation of the time-varying fault and the intermittent ***,the validity and accuracy of the proposed method are verified by the simulation of a single-link robotic arm mold.

关键词： Iterative learning scheme Adaptive algorithm Fault estimation Actuator fault Linear matrix inequality

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：