检索结果-内蒙古大学图书馆

Research Square 2021年

作者： Lin, Xiaochuan Hong, Rongjing Wang, Yawen Peng, Yun Ren, Xiaolei School of Mechanical and Power Engineering Nanjing Tech University Nanjing211816 China Jiangsu Key Laboratory of Digital Manufacturing for Industrial Equipment and Control Technology Nanjing Tech University Nanjing211816 China No.30 Puzhu Sothern Road Pukou District Jiangsu Nanjing China Department of Mechanical and Aerospace Engineering University of Texas at Arlington 701 S Nedderman Dr ArlingtonTX76019 United States College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics No.29 Yudao Road Qinhuai District Nanjing210016 China Department of Computer Science and Engineering University of Texas at Arlington 701 S Nedderman Dr ArlingtonTX76019 United States

This paper investigates the influence of the workpiece pose errors on gear skiving accuracy. First, based on the theory of homogeneous coordinate transformation, the mapping relationship between the tooth flank of the workpiece and the skiving tool is established according to the principle of gear skiving. Second, the workpiece pose errors are defined, and the relationship between each workpiece pose error and cutting depth is analyzed. According to the kinematic chain of the machine tool, a method for measuring the workpiece pose errors based on actual inverse kinematics is proposed. Third, the tooth deviations from individual workpiece pose errors, and the coupling workpiece pose errors are studied. The sensitive errors are obtained from the tooth deviation by numerical simulation. Finally, the numerical analysis is verified by gear skiving experiments, and the proposed method can be used to identify the possible workpiece pose errors. Furthermore, the PSO algorithm is introduced to guide the workpiece setting pose errors in the gear skiving process. © 2021, CC BY.

关键词： Inverse kinematics

来源：评论

学校读者我要写书评

暂无评论

Ultimate Boundedness control for Networked Systems with Redundant Channel under Quantization Effects

Ultimate Boundedness Control for Networked Systems with Redu...

引用

第三十八届中国控制会议

作者： Zhongyi Zhao Zidong Wang Lei Zou Hongli Dong College of Electrical Engineering and Automation Shandong University of Science and Technology Department of Computer Science Brunel University London Institute of Complex Systems and Advanced Control Northeast Petroleum University

This paper investigates the ultimate boundedness control problem for a class of networked systems with redundant channels under uniform quantization effects. Quantized output of concerned NCSs is transmitted to remote controller through a communication channel. For the purpose of improving communication quality, a redundant channel connected with a more precise quantizer is also employed, where the time to accomplish quantizing task is also considered. The transmission delays of such a redundant channel are modelled by a sequence of independent and identically distributed(i.i.d.) stochastic variable. An output feedback controller is developed under which the exponentially ultimate boundedness in mean square could be *** the virtue of stochastic analysis technology and Lyapunov-like method, sufficient conditions are established to ensure the existence of the desired controller, and the desired gain matrices are then obtained by solving a set of linear matrix ***, the effectiveness of designed controller is demonstrated through a simulation example.

关键词： Networked systems uniform quantization redundant channel ultimate boundedness control linear matrix inequal ities

来源：评论

学校读者我要写书评

暂无评论

Three-dimensional spin Hall effect of light in tight focusing

引用

Physical Review A 2020年第2期101卷 023819-023819页

作者： Weixing Shu Chuyang Lin Jun Wu Shizhen Chen Xiaohui Ling Xinxing Zhou Hailu Luo Shuangchun Wen Key Laboratory for Micro/Nano Optoelectronic Devices of Ministry of Education & Hunan Provincial Key Laboratory of Low-Dimensional Structural Physics and Devices School of Physics and Electronics Hunan University Changsha 410082 China Key Laboratory of Low Dimensional Quantum Structures and Quantum Control of Ministry of Education Hunan Normal University Changsha 410081 China College of Computer Science and Electronic Engineering Hunan University Changsha 410082 China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application College of Physics and Electronic Engineering Hengyang Normal University Hengyang 421002 China

We theoretically propose the realization of a three-dimensional (3D) spin Hall effect (SHE) of light by tightly focusing a linearly polarized light. Owing to the spin-orbital interaction in focusing, the left and right circularly polarized components of light are partly converted into each other, acquiring opposite vortex phases. As the superposition of the vortex and the initial vortex-free light, the two polarized components exhibit spiral intensity patterns which rotate oppositely around the propagation axis. Consequently, the two spin components are distributed alternatively in both the azimuthal and the longitudinal directions, leading to a 3D array of split spin components, and the transverse intensity is also spit asynchronously. Moreover, that array is rotatable by the incident polarization, and the longitudinal spacing in the array can be controlled by the numerical aperture of the lens. The 3D SHE of light finds an additional degree of freedom available to control the spin state of the photon, which may be valuable in optical manipulation and quantum information.

关键词： Classical optics

来源：评论

学校读者我要写书评

暂无评论

A Pipelining Loop Optimization Method for Dataflow Architecture

引用

Journal of computer science & Technology 2018年第1期33卷 116-130页

作者： Xu Tan Xiao-Chun Ye Xiao-Wei Shen Yuan-Chao Xu Da Wang Lunkai Zhang Wen-Ming Li Dong-Rui Fan Zhi-Min Tang State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing 1000J9 China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125 China College of Information Engineering Capital Normal University Beijing 100048 China Department of Computer Science The University of Chicago Chicago IL 60637 U.S.A.

With the coming of exascale supercomputing era, power efficiency has become the most important obstacle to build an exascale system. Dataflow architecture has native advantage in achieving high power efficiency for scientific applications. However, the state-of-the-art dataflow architectures fail to exploit high parallelism for loop processing. To address this issue, we propose a pipelining loop optimization method （PLO）, which makes iterations in loops flow in the processing element （PE） array of dataflow accelerator. This method consists of two techniques, architecture-assisted hardware iteration and instruction-assisted software iteration. In hardware iteration execution model, an on-chip loop controller is designed to generate loop indexes, reducing the complexity of computing kernel and laying a good f（mndation for pipelining execution. In software iteration execution model, additional loop instructions are presented to solve the iteration dependency problem. Via these two techniques, the average number of instructions ready to execute per cycle is increased to keep floating-point unit busy. Simulation results show that our proposed method outperforms static and dynamic loop execution model in floating-point efficiency by 2.45x and 1.1x on average, respectively, while the hardware cost of these two techniques is acceptable.

关键词： dataflow model control-flow model loop optimization exascale computing scientific application

来源：评论

学校读者我要写书评

暂无评论

An Adaptive Strategy via Reinforcement Learning for the Prisoner＇s Dilemma Game

引用

IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 301-310页

作者： Lei Xue Changyin Sun Donald Wunsch Yingjiang Zhou Fang Yu Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing 210096 China Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO 65409 USA College of Automation Nanjing University of Posts and Telecommunications Nanjing 210023 China Institute of Logistics Science and Engineering Shanghai Maritime University Shanghai 210096 China IEEE

The iterated prisoner's dilemma(IPD) is an ideal model for analyzing interactions between agents in complex networks. It has attracted wide interest in the development of novel strategies since the success of tit-for-tat in Axelrod's tournament. This paper studies a new adaptive strategy of IPD in different complex networks, where agents can learn and adapt their strategies through reinforcement learning method. A temporal difference learning method is applied for designing the adaptive strategy to optimize the decision making process of the agents. Previous studies indicated that mutual cooperation is hard to emerge in the IPD. Therefore, three examples which based on square lattice network and scale-free network are provided to show two features of the adaptive strategy. First, the mutual cooperation can be achieved by the group with adaptive agents under scale-free network, and once evolution has converged mutual cooperation, it is unlikely to shift. Secondly, the adaptive strategy can earn a better payoff compared with other strategies in the square network. The analytical properties are discussed for verifying evolutionary stability of the adaptive strategy.

关键词： Complex network prisoner’s dilemma reinforcement learning temporal differences learning

来源：评论

学校读者我要写书评

暂无评论

BNAS: An efficient neural architecture search approach using broad scalable architecture

arXiv

引用

arXiv 2020年

作者： Ding, Zixiang Chen, Yaran Li, Nannan Zhao, Dongbin Sun, Zhiquan Philip Chen, C.L. State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China School of Automation and Electric Engineering University of Science and Technology Beijing Beijing100083 China School of Computer Science & Engineering South China University of Technology Guangzhou Guangdong510006 China College of Navigation Dalian Maritime University Dalian116026 China

Efficient Neural Architecture Search (ENAS) achieves novel efficiency for learning architecture with high-performance via parameter sharing and reinforcement learning. In the phase of architecture search, ENAS employs deep scalable architecture as search space whose training process consumes most of search cost. Moreover, time consuming of model training is proportional to the depth of deep scalable architecture. Through experiments using ENAS on CIFAR-10, we find that layer reduction of scalable architecture is an effective way to accelerate the search process of ENAS but suffers from prohibitive performance drop in the phase of architecture estimation. In this paper, we propose Broad Neural Architecture Search (BNAS) where we elaborately design broad scalable architecture dubbed Broad Convolutional Neural Network (BCNN) to solve the above issue. On one hand, the proposed broad scalable architecture has fast training speed due to its shallow topology. Moreover, we also adopt reinforcement learning and parameter sharing used in ENAS as the optimization strategy of BNAS. Hence, the proposed approach can achieve higher search efficiency. On the other hand, the broad scalable architecture extracts multi-scale features and enhancement representations, and feeds them into global average pooling layer to yield more reasonable and comprehensive representations. Therefore, the performance of broad scalable architecture can be promised. In particular, we also develop two variants for BNAS who modify the topology of BCNN. In order to verify the effectiveness of BNAS, several experiments are performed and experimental results show that 1) BNAS delivers 0.19 days which is 2.37x less expensive than ENAS who ranks the best in reinforcement learning-based NAS approaches, 2) compared with small-size (0.5 millions parameters) and medium-size (1.1 millions parameters) models, the architecture learned by BNAS obtains state-of-the-art performance (3.58% and 3.24% test error) on CIFAR-1

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

Wide-angle giant photonic spin Hall effect

arXiv

引用

arXiv 2022年

作者： Chen, Zhihao Chen, Yu Wu, Yaodong Zhou, Xinxing Sun, Handong Low, Tony Chen, Hongsheng Lin, Xiao Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control Ministry of Education Synergetic Innovation Center for Quantum Effects and Applications School of Physics and Electronics Hunan Normal University Changsha410081 China International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology Engineering Technology Research Center for 2D Material Information Function Devices and Systems of Guangdong Province Institute of Microscale Optoelectronics Shenzhen University Shenzhen518060 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China International Joint Innovation Center ZJU-UIUC Institute The Electromagnetics Academy at Zhejiang University Zhejiang University Haining314400 China

Photonic spin Hall effect is a manifestation of spin-orbit interaction of light and can be measured by a transverse shift δ of photons with opposite spins. The precise measurement of transverse shifts can enable many spin-related applications, such as precise metrology and optical sensing. However, this transverse shift is generally small (i.e. δ/λ -1, λ is the wavelength), which impedes its precise measurement. To-date proposals to generate giant spin Hall effect (namely with δ/λ > 102) have severe limitations, particularly its occurrence only over a narrow angular cone (with a width of ∆0 70◦ by exploiting the interface between free space and uniaxial epsilon-near-zero media. The underlying mechanism is ascribed to the almost-perfect polarization splitting between s and p polarized waves at the designed interface. Remarkably, this almost-perfect polarization splitting does not resort to the interference effect and is insensitive to the incident angle, which then gives rise to the wide-angle giant photonic spin Hall effect. Copyright © 2022, The Authors. All rights reserved.

关键词： Polarization

来源：评论

学校读者我要写书评

暂无评论

Fast Fuzzy Clustering Algorithm for Time Series in Industrial Processes

Fast Fuzzy Clustering Algorithm for Time Series in Industria...

引用

International Conference on computer and Communications (ICCC)

作者： He Ji Jinkuan Wang Yinghua Han Qiang Zhao College of Information Science and Engineering Northeastern University Shenyang China School of Computer and Communication Engineering Northeastern University at Qinhuangdao Qinhuangdao China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China

ISBN: (数字)9781728147437

ISBN: (纸本)9781728147444

Process industry data is often continuously measured to capture fluctuations and changes of a production processes, and this sequentially dataset can be looked as time series. We usually don't know the correlation and classification between these data in advance. Clustering is an effective way to solve this problem, and it have been used in many fields in recent years. There are many different fuzzy clustering methods have been proposed, fuzzy c-means clustering (FCM) and fuzzy c-medoids clustering (FCMdd) are most common algorithm among them. But all of these algorithms use Euclidean distance as the similarity measure and align two times series time-by-time. These methods cannot adapt to the complex industrial environment. In this paper, dynamic time warping (DTW) is selected as the distance of the FCMdd method to adapt to complex industrial production environments, and a type of constraint is introduced to speed up it. The novel clustering method we proposed can not only speed up the clustering algorithm, but also improve the accuracy in some case. Three sets of open source sensor and simulated datasets are selected to evaluate this algorithm and achieved satisfactory results.

关键词： Time series analysis Clustering algorithms Euclidean distance Heuristic algorithms Industries Time measurement Production

来源：评论

学校读者我要写书评

暂无评论

Profiling Adaptive Immunity: A Quantitative Framework for Immune Repertoire Dynamics and Clinical Diagnostics

引用

Fundamental Research 2025年

作者： Yexing Chen Haiwen Ni Yongjie Li Jin Ma Chen Huang Sixian Yang Xiangfei Xie Haitao Lv Min Li Peng Cao State Key Laboratory of Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture Nanjing University of Chinese Medicine Nanjing 210000 China Jiangsu Provincial Medical Innovation Center Affiliated Hospital of Integrated Traditional Chinese and Western Medicine Nanjing University of Chinese Medicine Nanjing 210000 China Department of Hematology Affiliated Hospital of Nanjing University of Chinese Medicine The First Clinical College of Nanjing University of Chinese Medicine Nanjing 210000 China Children’s Hospital of Soochow University Suzhou 215000 China Key Laboratory of Quantum Information University of Science and Technology of China Hefei 230000 China Department of Computer Science College of Engineering and Applied Science University of Cincinnati Cincinnati 45221 USA Department of Oncology Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine Nanjing 210000 China

While immune repertoire(IR) dynamics encode critical disease signatures, existing models fail to capture the non-equilibrium processes that governing clonal selection and somatic hypermutation (SHM). We develop a biophysical framework that mathematically reconstructs IR evolution through energy landscape optimization, where 1) clonal emergence probabilities map to metastable states, 2) repertoire transitions obey non-equilibrium dynamics, and 3) inter-IR distances quantify the distribution transformation costs via optimal transport theory. This model enables macroscopic immune state detection from 10k cells by resolving critical fluctuations in sparse sampling regimes. Experimental validation across murine/human cohorts demonstrates precise unsupervised stratification of immune stages and disease states without prior clinical annotations. By bridging stochastic SHM kinetics with deterministic repertoire shifts, our approach establishes quantitative metrics for tracking immunological trajectories and pathological progression. This paradigm shift from static pattern recognition to dynamic process decoding empowers sensitive immunomonitoring and personalized therapeutic design through ultra-low-input clinical sampling.

关键词： Deductive reasoning Immune repertoire analysis Repertoire shift quantification Early disease screening Systemic immunity inference Kawasaki disease Colorectal cancer

来源：评论

学校读者我要写书评

暂无评论

Generative Adversarial Networks (GAN) powered fast magnetic resonance imaging - Mini review, comparison and perspectives

arXiv

引用

arXiv 2021年

作者： Yang, Guang Lv, Jun Chen, Yutong Huang, Jiahao Zhu, Jin National Heart & Lung Institute Imperial College London LondonSW7 2AZ United Kingdom Cardiovascular Research Centre Royal Brompton Hospital LondonSW3 6NP United Kingdom School of Computer and Control Engineering Yantai University Yantai China Department of Physiology Development and Neuroscience University of Cambridge CB2 3EG United Kingdom School of Optics and Photonics Beijing Institute of Technology Beijing China Department of Computer Science and Technology University of Cambridge CambridgeCB3 0FD United Kingdom

Magnetic Resonance Imaging (MRI) is a vital component of medical imaging. When compared to other image modalities, it has advantages such as the absence of radiation, superior soft tissue contrast, and complementary multiple sequence information. However, one drawback of MRI is its comparatively slow scanning and reconstruction compared to other image modalities, limiting its usage in some clinical applications when imaging time is critical. Traditional compressive sensing based MRI (CS-MRI) reconstruction can speed up MRI acquisition, but suffers from a long iterative process and noise-induced artefacts. Recently, Deep Neural Networks (DNNs) have been used in sparse MRI reconstruction models to recreate relatively high-quality images from heavily undersampled k-space data, allowing for much faster MRI scanning. However, there are still some hurdles to tackle. For example, directly training DNNs based on L1/L2 distance to the target fully sampled images could result in blurry reconstruction because L1/L2 loss can only enforce overall image or patch similarity and does not take into account local information such as anatomical sharpness. It is also hard to preserve fine image details while maintaining a natural appearance. More recently, Generative Adversarial Networks (GAN) based methods are proposed to solve fast MRI with enhanced image perceptual quality. The encoder obtains a latent space for the undersampling image, and the image is reconstructed by the decoder using the GAN loss. In this chapter, we review the GAN powered fast MRI methods with a comparative study on various anatomical datasets to demonstrate the generalisability and robustness of this kind of fast MRI while providing future *** Codes 68T01 Copyright © 2021, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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：