检索结果-内蒙古大学图书馆

Spinning from Nature:Engineered Preparation and Application of High-Performance Bio-Based Fibers

engineering 2022年第7期8卷 100-112页

作者： Zongpu Xu Mingrui Wu Qi Ye Dong Chen Kai Liu Hao Bai State Key Laboratory of Chemical Engineering College of Chemical and Biological EngineeringZhejiang UniversityHangzhou 310027China Institute of Applied Bioresources College of Animal SciencesZhejiang UniversityHangzhou 310058China State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China Institute of Process Equipment College of Energy EngineeringZhejiang UniversityHangzhou 310027China State Key Laboratory of Rare Earth Resource Utilization Changchun Institute of Applied ChemistryChinese Academy of SciencesChangchun 130022China

Many natural fibers are lightweight and display remarkable strength and *** properties originate from the fibers’hierarchical structures,assembled from the molecular to macroscopic *** natural spinning systems that produce such fibers are highly energy efficient,inspiring researchers to mimic these processes to realize robust artificial *** developments have been achieved in recent years toward the preparation of high-performance bio-based *** excellent mechanical properties,bio-based fibers can be functionalized with a series of new features,thus expanding their sophisticated applications in smart textiles,electronic sensors,and biomedical ***,recent progress in the construction of bio-based fibers is *** bioinspired spinning methods,strengthening strategies for mechanically strong fibers,and the diverse applications of these fibers are ***,challenges in reproducing the mechanical performance of natural systems and understanding their dynamic spinning process are ***,a perspective on the development of biological fibers is given.

关键词： Bio-based fiber Hierarchical structure Bioinspired spinning Strengthening strategy Fiber applications

来源：评论

学校读者我要写书评

暂无评论

Accelerating Data Transfer in Dataflow Architectures Through a Look-Ahead Acknowledgment Mechanism

引用

Journal of computer Science & Technology 2022年第4期37卷 942-959页

作者： Yu-Jing Feng De-Jian Li Xu Tan Xiao-Chun Ye Dong-Rui Fan Wen-Ming Li Da Wang Hao Zhang Zhi-Min Tang State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China Beijing Smartchip Microelectronics Technology Company Limited Beijing 100000China School of Computer and Control Engineering University of Chinese Academy of SciencesBeijing 100190China

The dataflow architecture,which is characterized by a lack of a redundant unified control logic,has been shown to have an advantage over the control-flow architecture as it improves the computational performance and power efficiency,especially of applications used in high-performance computing(HPC).Importantly,the high computational efficiency of systems using the dataflow architecture is achieved by allowing program kernels to be activated in a simultaneous ***,a proper acknowledgment mechanism is required to distinguish the data that logically belongs to different *** solutions include the tagged-token matching mechanism in which the data is sent before acknowledgments are received but retried after rejection,or a handshake mechanism in which the data is only sent after acknowledgments are ***,these mechanisms are characterized by both inefficient data transfer and increased area *** performance of the dataflow architecture depends on the efficiency of data *** order to optimize the efficiency of data transfer in existing dataflow architectures with a minimal increase in area and power cost,we propose a Look-Ahead Acknowledgment(LAA)*** accelerates the execution flow by speculatively acknowledging ahead without *** simulation analysis based on a handshake mechanism shows that our LAA increases the average utilization of computational units by 23.9%,with a reduction in the average execution time by 17.4%and an increase in the average power efficiency of dataflow processors by 22.4%.Crucially,our novel approach results in a relatively small increase in the area and power consumption of the on-chip logic of less than 0.9%.In conclusion,the evaluation results suggest that Look-Ahead Acknowledgment is an effective improvement for data transfer in existing dataflow architectures.

关键词： dataflow model control-flow model high-performance computing application data transfer power efficiency

来源：评论

学校读者我要写书评

暂无评论

A Sample Selection Method Based on Deep Bayesian Active Learning

A Sample Selection Method Based on Deep Bayesian Active Lear...

引用

2022 Chinese Automation Congress, CAC 2022

作者： Ma, Shuangshuang Zhou, Fan Wang, Linqing Zhao, Jun Ministry of Education Key Laboratory of Intelligent Control and Optimization for Industrial Equipment China School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9781665465335

The production process of iron and steel enterprises has accumulated a large number of historical data. Because of the continuity of production conditions, these data have a large number of redundancy, which severely affects the training time and generalization capability of the model. Therefore, this study proposes a fast sample selection method based on deep Bayesian active learning. The method uses Bayesian neural network (BNN) as a priori modelling, and adopts Gaussian process to infer the posterior distribution of the network prediction, and achieves the selection of redundant samples based on maximizing the probability of the posterior distribution. To address the problem of excessive computational complexity of the Gaussian process as a sampling function, a sparse Gaussian method is used to improve the traditional Gaussian process and achieve faster sampling. In order to verify the effectiveness of the method in this paper, experiments were conducted using historical coke oven data from a domestic iron and steel enterprise. The results indicate that the proposed method can not only effectively reduce the number of samples, but also has better prediction accuracy and has obvious advantages in terms of algorithm running time. © 2022 IEEE.

关键词： Gaussian distribution

来源：评论

学校读者我要写书评

暂无评论

STFormer: A dual-stage transformer model utilizing spatio-temporal graph embedding for multivariate time series forecasting

引用

Journal of Intelligent and Fuzzy Systems 2024年第3期46卷 6951-6967页

作者： Xiao, Yuteng Liu, Zhaoyang Yin, Hongsheng Wang, Xingang Zhang, Yudong Jinan China Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Xuzhou University of Technology Xuzhou China School of Information and Control Engineering China University of Mining and Technology Xuzhou China School of Computing and Mathematical Sciences University of Leicester LeicesterLE1 7RH United Kingdom School of Computer Science and Engineering Southeast University Jiangsu Nanjing China

Multivariate Time Series (MTS) forecasting has gained significant importance in diverse domains. Although Recurrent Neural Network (RNN)-based approaches have made notable advancements in MTS forecasting, they do not effectively tackle the challenges posed by noise and unordered data. Drawing inspiration from advancing the Transformer model, we introduce a transformer-based method called STFormer to address this predicament. The STFormer utilizes a two-stage Transformer to capture spatio-temporal relationships and tackle the issue of noise. Furthermore, the MTS incorporates adaptive spatio-temporal graph structures to tackle the issue of unordered data specifically. The Transformer incorporates graph embedding to combine spatial position information with long-term temporal connections. Experimental results based on typical finance and environment datasets demonstrate that STFormer surpasses alternative baseline forecasting models and achieves state-of-the-art results for single-step horizon and multistep horizon forecasting. © 2024 - IOS Press. All rights reserved.

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

Multi-dimension and multi-modal rolling mill vibration prediction model based on multi-level network fusion

引用

Journal of Central South University 2024年第9期31卷 3329-3348页

作者： CHEN Shu-zong LIU Yun-xiao WANG Yun-long QIAN Cheng HUA Chang-chun SUN Jie School of Electrical Engineering Yanshan UniversityQinhuangdao 066004China Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan UniversityQinhuangdao 066004China Shougang Jingtang United Iron&Steel Co. Ltd.Tangshan 063200China State Key Laboratory of Rolling and Automation Northeastern UniversityShenyang 110819China

Mill vibration is a common problem in rolling production,which directly affects the thickness accuracy of the strip and may even lead to strip fracture accidents in serious *** existing vibration prediction models do not consider the features contained in the data,resulting in limited improvement of model *** address these challenges,this paper proposes a multi-dimensional multi-modal cold rolling vibration time series prediction model(MDMMVPM)based on the deep fusion of multi-level *** the model,the long-term and short-term modal features of multi-dimensional data are considered,and the appropriate prediction algorithms are selected for different data *** on the established prediction model,the effects of tension and rolling force on mill vibration are *** the 5th stand of a cold mill in a steel mill as the research object,the innovative model is applied to predict the mill vibration for the first *** experimental results show that the correlation coefficient(R^(2))of the model proposed in this paper is 92.5%,and the root-mean-square error(RMSE)is 0.0011,which significantly improves the modeling accuracy compared with the existing *** proposed model is also suitable for the hot rolling process,which provides a new method for the prediction of strip rolling vibration.

关键词： rolling mill vibration multi-dimension data multi-modal data convolutional neural network time series prediction

来源：评论

学校读者我要写书评

暂无评论

Matrix Coding Enabled Impact Mitigation against Primary False Data Injection Attacks in Cyber-Physical Microgrids

引用

IEEE Transactions on Power Systems 2025年

作者： Liu, Mengxiang Zhang, Xin Zhao, Chengcheng Deng, Ruilong University of Sheffield School of Electrical and Electronic Engineering Sheffield United Kingdom Zhejiang University State Key Laboratory of Industrial Control Technology The College of Control Science and Engineering Hangzhou China

The impact mitigation against false data injection attacks (FDIAs) has become a prevailing topic in enhancing the cyber resilience of microgrids. In particular, the primary FDIA (PFDIA) injecting biases into the sensor channel of the primary controller can fake the real physical states and result in devastating control commands to the power conversion device. Nevertheless, existing impact mitigation schemes cannot handle the PFDIA due to the primary control's strict real-time requirement. Therefore, this paper proposes a time- and cost-efficient impact mitigation scheme against the PFDIA by alternately encoding the transmitted measurement with an invertible coding matrix. Specifically, when the PFDIA is detected by unknown input observers (UIOs), two additional half-downsampled UIOs, which only require simple multiplication, addition, and subtraction operations within each control cycle, will be triggered to obtain the residuals under encoded and unencoded data. The complete bias vector can be then reconstructed recursively from these two residuals, and the bias will be removed from the compromised data to eliminate the malicious attack impact. Based on the theoretical analysis of reconstruction performance, the coding matrix is optimised to minimise the system noises' impact on reconstruction accuracy subject to the reconstruction stability and the encoding's hiddenness from the adversary. Finally, extensive experimental studies are conducted to validate the effectiveness, superiority, robustness, and lightweightness of the proposed impact mitigation scheme. © 1969-2012 IEEE.

关键词： Encoding (symbols)

来源：评论

学校读者我要写书评

暂无评论

Forming Circle Formations of Multi-agent Systems Under Actuator Faults 5th

Forming Circle Formations of Multi-agent Systems Under Actu...

引用

5th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2021

作者： Liu, Jiajun Ru, Xinfeng Xia, Weiguo Wang, Chen China National Aeronautical Radio Electronic Research Institute and National Key Laboratory of Science and Technology on Avionics System Integration Shanghai China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and School of Control Science and Engineering Dalian University of Technology Dalian China National Engineering Research Center of Software Engineering and the State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China

ISBN: (纸本)9789811939976

A distributed fault-tolerant formation control law is designed in this paper for multi-agent systems under external disturbances and actuator faults including time-varying loss of effectiveness faults. The initial position of each agent is already on a circle and the control purpose is to form a desired formation on this circle. Based on this local information, a distributed adaptive formation control law is designed by employing the congelation of variables method to deal with time-varying actuator faults. Finally, a simulation example is given to verify the effectiveness of the adaptive fault-tolerant control design method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

PATH OPTIMIZATION FOR DYNAMIC OBSTACLE AVOIDANCE OF PIONEER ROBOT BASED ON DDPG SMART AGENT

引用

UPB Scientific Bulletin, Series D: Mechanical engineering 2023年第2期85卷 29-42页

作者： Zheng, Qingchun Peng, Zhi Zhu, Peihao Zhao, Yangyang Ma, Wenpeng Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin300384 China China School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China

To improve the path efficiency for dynamic obstacle avoidance algorithms of Pioneer robots, this paper proposes an approach to create deep deterministic policy gradient (DDPG) smart agents with recurrent neural networks (RNN) to optimize the path strategy. This approach is realized by training RNN with the backpropagation (BP) algorithm to train the agent. First, the SolidWorks model and obstacle avoidance model of the Pioneer robot is established. The LIDAR sensor is used to obtain environmental information. Further, deep reinforcement learning obstacle avoidance algorithm based on RNN is presented. The dynamic obstacle avoidance path of the Pioneer robot is further simulated in two different virtual robot experiment platform (V-REP) scenarios. The simulation results show that the proposed algorithm shortens the training time by 26.3% compared with the DDPG algorithm. Our proposed scheme can improve the path efficiency for dynamic obstacle avoidance of the Pioneer robot. © 2023, Politechnica University of Bucharest. All rights reserved.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Multi-task Collaborative Network for Image-Text Retrieval 1

引用

30th International Conference on MultiMedia Modeling, MMM 2024

作者： Qin, Xueyang Li, Lishuang Hao, Jing Ge, Meiling Huang, Jiayi Pang, Guangyao School of Computer Science and Technology Dalian University of Technology Dalian116024 China School of Computer Engineering Weifang University Weifang261061 China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Wuzhou543002 China

ISBN: (数字)9783031533112

ISBN: (纸本)9783031533105

Image-text retrieval aims to capture semantic relevance between images and texts. Most existing approaches rely solely on the image-text pairs to learn visual-semantic representation through fine-grained alignments while neglecting the potential beneficial impact of unimodal tasks on cross-modal retrieval. To this end, we present a Multi-Task Collaborative Network (MTCN) that leverages the synergy between multiple tasks to enhance the performance of image-text retrieval. Specifically, we introduce three unimodal tasks, including text-text matching, image multi-label classification, and text multi-label classification, and train together with target task image-text retrieval from the perspective of semantic constraints. Additionally, we employ a modality interaction module for image-text retrieval to discover interrelationships between these two modalities. Subsequently, a cascaded graph convolutional network combined with a multi-layer perceptron is used to infer the correlation scores between images and texts. We conduct comprehensive experiments on two benchmark datasets, Flickr30K and MSCOCO, and the quantitative and qualitative experimental results demonstrate the effectiveness of the proposed method. The source code is available at https://***/FlyCuteBird/MTCN. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

A Microwave Sensor for Detection of Heavy Metals in Traditional Chinese Medicine 12

A Microwave Sensor for Detection of Heavy Metals in Traditio...

引用

12th IEEE Asia-Pacific Conference on Antennas and Propagation, APCAP 2024

作者： Wu, Jing Li, Hua-Feng Xu, Ming-Feng He, Jin-Peng Zhang, Zhong-Qi Chen, Min Chen, Rui-Sen Huang, Guan-Long Pang, Zi-Yu Tam, Kam-Weng Foshan University School of Electronic and Information Engineering Guangdong Foshan528225 China Foshan University Guangdong Provincial Key Laboratory of Industrial Intelligent Inspection Technology Foshan528225 China University of Macau Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350351019

This paper presents a microwave sensor for the detection of heavy metals in traditional Chinese medicine decoctions. The sensor is composed of interdigital capacitors (IDC), a split-ring resonators (SRR) coupled with a microstrip line on the substrate, and a test substance placed above the sensor. By altering the dielectric constant of the liquid, the sensor demonstrates a frequency shift, enabling the detection of heavy metal content. This design offers a high-sensitivity, non-invasive detection method suitable for real-time monitoring of heavy metals in traditional Chinese medicine decoctions. © 2024 IEEE.

关键词： Microwave sensors

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：