检索结果-内蒙古大学图书馆

Generation of super-resolved optical needle and multifocal array using graphene oxide metalenses

Opto-Electronic Advances 2021年第2期4卷 1-11页

作者： Hongtao Wang Chenglong Hao Han Lin Yongtian Wang Tian Lan Chengwei Qiu Baohua Jia Centre for Translational Atomaterials Faculty of ScienceEngineering and TechnologySwinburne University of TechnologyP.O.Box 218Hawthorn VIC 3122Australia Key Laboratory of Photoelectronic Imaging Technology and System Ministry of Education of ChinaSchool of Optics and PhotonicsBeijing Institute of TechnologyBeijing 100081China Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117583Singapore Engineering Product Development Pillar Singapore University of Technology and Design8 Somapah Road487372Singapore

Ultrathin flat metalenses have emerged as promising alternatives to conventional diffractive lenses,offering new possibilities for myriads of miniaturization and interfacial ***-based materials can achieve both phase and amplitude modulations simultaneously at a single position due to the modification of the complex refractive index and thickness by laser conversion from graphene oxide into graphene like *** this work,we develop graphene oxide metalenses to precisely control phase and amplitude modulations and to achieve a holistic and systematic lens design based on a graphene-based material *** experimentally validate our strategies via demonstrations of two graphene oxide metalenses:one with an ultra-long(~16λ)optical needle,and the other with axial multifocal spots,at the wavelength of 632.8 nm with a 200 nm thin *** proposed graphene oxide metalenses unfold unprecedented opportunities for accurately designing graphene-based ultrathin integratable devices for broad applications.

关键词： femtosecond laser reduction graphene oxide metalens multifocal spots optical needle

来源：评论

学校读者我要写书评

暂无评论

Polarimetric bias correction of alternate-arranged V-dipole array 5

Polarimetric bias correction of alternate-arranged V-dipole ...

引用

IET International Radar Conference 2020, IET IRC 2020

作者： Zhou, Jian Pang, Chen Li, Yongzhen Wang, Xuesong State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System National University of Defense Technology Hunan Changsha410073 China College of Electronic Science and Engineering National University of Defense Technology Hunan Changsha410073 China

ISBN: (纸本)9781839535635

This paper aims to eliminate the polarimetric biases of V-dipole phased array antennas using lower measurement cost. We analyze the polarization characteristics of the V-dipole with the integration method. An alternate-arranged 8×8 V-dipole array is designed and simulated. Based on the analysis of mutual coupling, the polarimetric performance of the array is presented. To correct the polarimetric biases using lower measurement cost, a cluster-based method is proposed to reconstruct the array pattern. The method uses partial elements to design polarimetric correction and treats the selection of elements as a clustering problem. The results prove the method helpful to minimize the biases using limited measurement cost. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Polarimeters

来源：评论

学校读者我要写书评

暂无评论

A comparative study of neural network techniques for automatic software vulnerability detection

arXiv

引用

arXiv 2021年

作者： Tang, Gaigai Meng, Lianxiao Wang, Huiqiang Ren, Shuangyin Wang, Qiang Yang, Lin Cao, Weipeng School of computer science and technology Harbin Engineering University Harbin China National Key Laboratory of Science and Technology on Information System Security Institute of System Engineering Chinese Academy of Military Science Beijing China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

Software vulnerabilities are usually caused by design flaws or implementation errors, which could be exploited to cause damage to the security of the system. At present, the most commonly used method for detecting software vulnerabilities is static analysis. Most of the related technologies work based on rules or code similarity (source code level) and rely on manually defined vulnerability features. However, these rules and vulnerability features are difficult to be defined and designed accurately, which makes static analysis face many challenges in practical applications. To alleviate this problem, some researchers have proposed to use neural networks that have the ability of automatic feature extraction to improve the intelligence of detection. However, there are many types of neural networks, and different data preprocessing methods will have a significant impact on model performance. It is a great challenge for engineers and researchers to choose a proper neural network and data preprocessing method for a given problem. To solve this problem, we have conducted extensive experiments to test the performance of the two most typical neural networks (i.e., Bi-LSTM and RVFL) with the two most classical data preprocessing methods (i.e., the vector representation and the program symbolization methods) on software vulnerability detection problems and obtained a series of interesting research conclusions, which can provide valuable guidelines for researchers and engineers. Specifically, we found that 1) the training speed of RVFL is always faster than Bi-LSTM, but the prediction accuracy of Bi-LSTM model is higher than RVFL;2) using doc2vec for vector representation can make the model have faster training speed and generalization ability than using word2vec;and 3) multi-level symbolization is helpful to improve the precision of neural network models. © 2021, CC BY.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Recent Advances in Triboelectric Nanogenerators: From Technological Progress to Commercial Applications

引用

ACS Nano 2023年第12期17卷 11087-11219页

作者： Choi, Dongwhi Lee, Younghoon Lin, Zong-Hong Cho, Sumin Kim, Miso Ao, Chi Kit Soh, Siowling Sohn, Changwan Jeong, Chang Kyu Lee, Jeongwan Lee, Minbaek Lee, Seungah Ryu, Jungho Parashar, Parag Cho, Yujang Ahn, Jaewan Kim, Il-Doo Jiang, Feng Lee, Pooi See Khandelwal, Gaurav Kim, Sang-Jae Kim, Hyun Soo Song, Hyun-Cheol Kim, Minje Nah, Junghyo Kim, Wook Menge, Habtamu Gebeyehu Park, Yong Tae Xu, Wei Hao, Jianhua Park, Hyosik Lee, Ju-Hyuck Lee, Dong-Min Kim, Sang-Woo Park, Ji Young Zhang, Haixia Zi, Yunlong Guo, Ru Cheng, Jia Yang, Ze Xie, Yannan Lee, Sangmin Chung, Jihoon Oh, Il-Kwon Kim, Ji-Seok Cheng, Tinghai Gao, Qi Cheng, Gang Gu, Guangqin Shim, Minseob Jung, Jeehoon Yun, Changwoo Zhang, Chi Liu, Guoxu Chen, Yufeng Kim, Suhan Chen, Xiangyu Hu, Jun Pu, Xiong Guo, Zi Hao Wang, Xudong Chen, Jun Xiao, Xiao Xie, Xing Jarin, Mourin Zhang, Hulin Lai, Ying-Chih He, Tianyiyi Kim, Hakjeong Park, Inkyu Ahn, Junseong Huynh, Nghia Dinh Yang, Ya Wang, Zhong Lin Baik, Jeong Min Choi, Dukhyun Kyung Hee University Gyeonggi Yongin17104 Korea Republic of Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Department of Mechanical Engineering Soft Robotics Research Center Seoul National University Seoul08826 Korea Republic of Department of Mechanical Engineering Gachon University Seongnam13120 Korea Republic of Department of Biomedical Engineering National Taiwan University Taipei10617 Taiwan Frontier Research Center on Fundamental and Applied Sciences of Matters National Tsing Hua University Hsinchu30013 Taiwan School of Advanced Materials Science & Engineering Sungkyunkwan University Suwon16419 Korea Republic of Sungkyunkwan University 2066 Seobu-ro Gyeonggi Suwon16419 Korea Republic of Department of Chemical and Biomolecular Engineering National University of Singapore 4 Engineering Drive 4 117585 Singapore Division of Advanced Materials Engineering Jeonbuk National University 567 Baekje-daero Jeonbuk Jeonju54896 Korea Republic of Jeonbuk National University 567 Baekje-daero Jeonbuk Jeonju54896 Korea Republic of Department of Physics Inha University 100 Inha-ro Incheon22212 Korea Republic of School of Materials Science & Engineering Yeungnam University Gyeongbuk Gyeongsan38541 Korea Republic of 291 Daehak-ro Daejeon34141 Korea Republic of School of Materials Science and Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore Institute of Flexible Electronics Technology of Tsinghua Zhejiang Jiaxing314000 China Nanomaterials and System Lab Major of Mechatronics Engineering Faculty of Applied Energy System Jeju National University Jeju632-43 Korea Republic of School of Engineering University of Glasgow GlasgowG128QQ United Kingdom Seoul02792 Korea Republic of Department of Physics Inha University Incheon22212 Korea Republic of Suwon16419 Korea Republic of Department of

Serious climate changes and energy-related environmental problems are currently critical issues in the world. In order to reduce carbon emissions and save our environment, renewable energy harvesting technologies will serve as a key solution in the near future. Among them, triboelectric nanogenerators (TENGs), which is one of the most promising mechanical energy harvesters by means of contact electrification phenomenon, are explosively developing due to abundant wasting mechanical energy sources and a number of superior advantages in a wide availability and selection of materials, relatively simple device configurations, and low-cost processing. Significant experimental and theoretical efforts have been achieved toward understanding fundamental behaviors and a wide range of demonstrations since its report in 2012. As a result, considerable technological advancement has been exhibited and it advances the timeline of achievement in the proposed roadmap. Now, the technology has reached the stage of prototype development with verification of performance beyond the lab scale environment toward its commercialization. In this review, distinguished authors in the world worked together to summarize the state of the art in theory, materials, devices, systems, circuits, and applications in TENG fields. The great research achievements of researchers in this field around the world over the past decade are expected to play a major role in coming to fruition of unexpectedly accelerated technological advances over the next decade. © 2023 The Authors. Published by American Chemical Society

关键词： Nanogenerators

来源：评论

学校读者我要写书评

暂无评论

A transfer learning based geometric position-driven machining error prediction method for different working conditions*

A transfer learning based geometric position-driven machinin...

引用

International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Teng Zhang Hao Sun Lin Zhou Shengqiang Zhao Fangyu Peng Rong Yan National NC System Engineering Research Center School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China Wuhan Digital Design and Manufacturing Innovation Center Co. Ltd China Wuhan China State Key Laboratory of Digital Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781665431545

Machining error is one of the most important indicators to evaluate the processing quality of thin-walled parts. With the development of Data science, the data-driven methods have become popular. But the condition that the model can work accurately on a new task is that the feature space and distribution of the data are the same. A sample-based transfer learning method driven by geometric position is utilized to quickly predict the machining errors of thin-walled parts under different working conditions. This method can fully learn the knowledge related to machining errors contained in the data through model training, and can apply this knowledge to accurately and quickly forecast machining errors under new working conditions. In the experimental scenario, this method has outstanding predictive performance. The average determination coefficient of the four groups of target domain experiments reached 0.96, and the average root mean square error is less than the machining error acquisition time to 22% of the original, reducing the dependence on time-consuming and expensive measurements greatly.

关键词： Employee welfare Training Mechatronics Transfer learning Machining Predictive models Data models

来源：评论

学校读者我要写书评

暂无评论

Disjoint-Path and Golden-Pin Based Irregular PCB Routing with Complex Constraints 23

Disjoint-Path and Golden-Pin Based Irregular PCB Routing wit...

引用

Proceedings of the 60th Annual ACM/IEEE design Automation Conference

作者： Qinghai Liu Qinfei Tang Jiarui Chen Chuandong Chen Ziran Zhu Huan He Jianli Chen Yao-Wen Chang Center for Discrete Mathematics Fuzhou University Fuzhou China and Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou China Center for Discrete Mathematics Fuzhou University Fuzhou China College of Computer and Date Science Fuzhou University Fuzhou China Department of Microelectronics Fuzhou University Fuzhou China Department of Microelectronics Southeast University Nanjing China Hangzhou Huawei Enterprises Telecommunication Technologies Co. Ltd Hangzhou China State Key Lab of ASIC & System Fudan University Shanghai China Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan and Department of Electrical Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)9798350323481

PCB routing becomes time-consuming as the complexity of PCB design increases. Unlike traditional schemes that treat the two essential PCB routing processes separately, namely, escape and bus routing, we consider the continuity between them and present a golden-pin-based routing scheme to find the desired solution with angle and topology constraints. Further, conventional rip-up and reroute methods are often ineffective and inefficient for congestion alleviation and routability optimization. We construct a component graph by modeling components as vertices and applying the minimum weight vertex covering method to improve the routability. A self-adaptable ordering method is presented for escape routing to arrange the pin order on the component boundary, guaranteeing successful bus routing. In addition, escape routing is performed based on a disjoint path method. We construct a dynamic Hanan grid in bus routing and utilize a novel congestion adjustment technique to improve solution quality. Compared with FreeRouting and Allegro, the experiment results show that our algorithm achieves high routability and a significant 90% runtime reduction.

关键词： escape routing

来源：评论

学校读者我要写书评

暂无评论

Tool wear parameters identification in precision milling using a hybrid model combining cutting forces analytical model and Gaussian process regression method*

Tool wear parameters identification in precision milling usi...

引用

International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Shengqiang Zhao Lin Zhou Hao Sun Fangyu Peng Rong Yan Teng Zhang National NC System Engineering Research Center School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China Wuhan Digital Design and Manufacturing Innovation Center Co. Ltd China Wuhan China State Key Laboratory of Digital Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781665431545

In precision milling, tool wear has a significant impact on tool life prediction, machining accuracy and surface quality evaluation of workpiece. Tool wear pattern generally includes the increase of the tool flank wear width, as well as the expansion of the edge radius in precision process. Therefore, two tool wear parameters in precision milling have been generalized in this paper. The milling cutting force analytical model considering tool wear is set up to generate the data related to cutting force and tool wear parameters, which can be used as the dataset to construct and train the Gaussian process regression model. Finally, the trained regression model can output the prediction of tool flank wear width and edge radius as measured cutting forces treated as input values, which is helpful to realize the online monitoring of tool wear in the processing site environment. Consequently, the average relative prediction errors of tool flank wear width and edge radius are controlled within 2%, with the prediction time within 100ms.

关键词： Training Analytical models Parameter estimation Machine learning algorithms Force Milling Gaussian processes

来源：评论

学校读者我要写书评

暂无评论

A hybrid mechanism-based and data-driven approach for the calibration of physical properties of Ni-based superalloy GH3128*

A hybrid mechanism-based and data-driven approach for the ca...

引用

International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Hao Sun Lin Zhou Shengqiang Zhao Teng Zhang Fangyu Peng Rong Yan National NC System Engineering Research Center School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China Wuhan Digital Design and Manufacturing Innovation Center Co. Ltd China Wuhan China State Key Laboratory of Digital Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781665431545

Within the finite element simulation model of metal manufacturing processes, the setting of physical properties of the materials will significantly affect the final simulation results. In this paper, a hybrid approach to integrate mechanical models and experimental data is proposed to identify the constitutive parameters and tool-chip friction coefficient of superalloy GH3128. Firstly, mechanical model is established and the relation between the constitutive parameters and the measured shear flow stress is determined. Combined with Bayesian inference, the fast inverse identification of the above parameters is realized. Then, a finite element surrogate model and Bayesian framework are fused for calibrating tool-chip friction coefficient. Finally, the effectiveness of the proposed approach is verified through milling experiments. The prediction accuracy of the prediction model are significantly improved by considering the uncertainties of physical properties. The relative error of the model in direction and direction are 11.4681% and 4.2989%, respectively.

关键词： Uncertainty Friction Simulation Metals Milling Predictive models Finite element analysis

来源：评论

学校读者我要写书评

暂无评论

Time-dependent fatigue reliability estimation and optimal design of scraper chains under corrosive wear effect

引用

Mechanics Based design of Structures and Machines 2024年第10期52卷

作者： Shuai Li Zhencai Zhu Hao Lu Yujun Xue Gang Shen a School of Mechatronics Engineering Henan University of Science and Technology Luoyang Chinab Henan Key Laboratory for Machinery Design and Transmission System Henan University of Science and Technology Luoyang Chinac Longmen Laboratory Luoyang China d School of Mechatronic Engineering Jiangsu Key Laboratory of Mine Mechanical and Electrical Equipment China University of Mining and Technology Xuzhou China

Fatigue damage is one of the main failures of the scraper chain. Moreover, corrosive wear has a detrimental effect on fatigue crack propagation. It is so essential to study the fatigue reliability of the scraper chain considering the interaction of corrosive wear and fatigue. This paper is intended to propose a reliability-based estimation and optimal design of the scraper chain considering the performance degradation of the scraper chain under the interaction of corrosive wear and fatigue. First, the dynamic model of the scraper conveyor is established based on the finite element method. Second, Paris Low is used to empirically describe the occurrence of cracking with corrosion effects. Furthermore, the time-dependent reliability of scraper chains under the interaction of the corrosive wear and fatigue crack propagation is addressed by the fourth-moment saddlepoint approximation (FMSA) method, and the reliability-based design optimization (RBDO) of the scraper chain is then carried out. Finally, the applicability of the proposed method is verified by the SGZ1000/1400 scraper conveyor.

关键词： Fatigue reliability scraper chain saddlepoint approximation reliability based design optimization

来源：评论

学校读者我要写书评

暂无评论

Integration of Mixture of Experts and Multimodal Generative AI in Internet of Vehicles: A Survey

arXiv

引用

arXiv 2024年

作者： Xu, Minrui Niyato, Dusit Kang, Jiawen Xiong, Zehui Jamalipour, Abbas Fang, Yuguang Kim, Dong In Shen, Xuemin The School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore The School of Automation Guangdong University of Technology Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education Guangzhou510006 China Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou510006 China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore487372 Singapore The School of Electrical and Information Engineering University of Sydney SydneyNSW2006 Australia Department of Computer Science City University of Hong Kong Kowloon Hong Kong The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of The Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

Generative AI (GAI) can enhance the cognitive, reasoning, and planning capabilities of intelligent modules in the Internet of Vehicles (IoV) by synthesizing augmented datasets, completing sensor data, and making sequential decisions. In addition, the mixture of experts (MoE) can enable the distributed and collaborative execution of AI models without performance degradation between connected vehicles. In this survey, we explore the integration of MoE and GAI to enable Artificial General Intelligence in IoV, which can enable the realization of full autonomy for IoV with minimal human supervision and applicability in a wide range of mobility scenarios, including environment monitoring, traffic management, and autonomous driving. In particular, we present the fundamentals of GAI, MoE, and their interplay applications in IoV. Furthermore, we discuss the potential integration of MoE and GAI in IoV, including distributed perception and monitoring, collaborative decision-making and planning, and generative modeling and simulation. Finally, we present several potential research directions for facilitating the integration. © 2024, CC BY.

关键词： Integration

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：