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埋入式传感、图像处理技术和机器学习方法在路面监测与分析中应用的最新研究进展

engineering 2021年第6期 309-334页

作者：侯越李秋晗张晨陆国阳叶周景陈逸涵汪林兵曹丹丹 Beijing Key Laboratory of Traffic Engineering Beijing University of Technology National Center for Materials Service Safety University of Science and Technology Beijing School of Transportation Southeast University Department of Civil and Environmental Engineering The Hong Kong Polytechnic University Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Beijing Jiaotong University Department of Civil and Environmental Engineering Virginia Tech

在现代交通系统中,道路作为车辆和行人使用频率最高的民用基础设施之一,其服役状况和使用寿命直接影响通行体验和效率。因此,在路面发生不可逆损伤之前进行路面健康监测和及时养护,对于保障公共交通服务质量以及通行安全至关重要。通过... 详细信息

在现代交通系统中,道路作为车辆和行人使用频率最高的民用基础设施之一,其服役状况和使用寿命直接影响通行体验和效率。因此,在路面发生不可逆损伤之前进行路面健康监测和及时养护,对于保障公共交通服务质量以及通行安全至关重要。通过路面结构动力响应监测和路面状况评估可有效表征路面损伤状况。埋入式传感器、图像处理和机器学习是目前常用的三种路面结构动力响应监测技术和分析方法。本文综述了近年来上述三种技术在路面工程中的应用现状,并阐述了这些技术在未来路面工程监测与分析中的发展方向。

关键词：路面监测与分析最新的研究进展埋入式传感器图像处理技术机器学习方法

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Neutrino Rocket Jet Model: An Explanation of High-velocity Pulsars and Their Spindown Evolution

arXiv

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arXiv 2022年

作者： Li, Zheng Peng, Qiu-He Kang, Miao Liu, Xiang Zhang, Ming Huang, Yong-Feng Chou, Chih-Kang Xinjiang Astronomical Observatory Chinese Academy of Sciences 150 Science 1-Street Urumqi830011 China Key Laboratory for Radio Astronomy Chinese Academy of Sciences 2 West Beijing Road Nanjing210008 China University of Chinese Academy of Sciences 19A Yuquan Road Beijing100049 China College of Big Data and Information Engineering Guizhou University Guiyang550025 China School of Astronomy and Space Science Nanjing University Nanjing210023 China Key Laboratory of Radio Astrophysics in Xinjiang Province Urumqi830011 China School of Physics and Electronics Henan University Kaifeng China Ministry of Education Nanjing210023 China National Astronomical Observatories Chinese Academy of Sciences Beijing China

The fact that the spatial velocity of pulsars is generally higher than that of their progenitor stars has bothered astronomers for nearly 50 years. It has been extensively argued that the high pulsar velocity should be acquired during a natal kick process on a timescale of 100 ms-10 s in the supernova explosion, in which some asymmetrical dynamical mechanism plays a key role. However, a satisfactory picture generally is still lacking. In this study, it is argued that the neutrino rocket model can well account for the high speed as well as the long-term evolution behaviors of pulsars. The neutrinos are emitted from superfluid vortex neutrons through the neutrino cyclotron radiation mechanism. The unique characters of left-handed neutrinos and right-handed antineutrinos resulting from the nonconservation of parity in weak interactions play a major role in the spatial asymmetry. The continuous acceleration of pulsars can be naturally explained by this model, which yields a maximum velocity surpassing 1000 kms-1. The alignment between the spinning axis and the direction of motion observed for the Crab pulsar (PSR 0531) and the Vela pulsar (PSR 0833) can be well accounted for. The observed correlation between the spin-down rate and the period of long-period pulsars with P0.5 s can also be satisfactorily explained. Copyright © 2022, The Authors. All rights reserved.

关键词： Pulsars

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FeatureBand: A feature selection method by combining early stopping and genetic local search 3rd

FeatureBand: A feature selection method by combining early s...

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3rd APWeb and WAIM Joint Conference on Web and big data, APWeb-WAIM 2019

作者： Xue, Huanran Jiang, Jiawei Shao, Yingxia Cui, Bin Center for Data Science National Engineering Laboratory for Big Data Analysis and Applications Peking University Beijing China Peking University Beijing China Tencent Inc. Shenzhen China Beijing Key Lab of Intelligent Telecommunications Software and Multimedia BUPT Beijing China

ISBN: (纸本)9783030260743

Feature selection is an important problem in machine learning and data mining. In reality, the wrapper methods are broadly used in feature selection. It treats feature selection as a search problem using a predictor as a black-box. However, most wrapper methods are time-consuming due to the large search space. In this paper, we propose a novel wrapper method, called FeatureBand, for feature selection. We use the early stopping strategy to terminate bad candidate feature subsets and avoid wasting of training time. Further, we use a genetic local search to generate new subsets based on previous ones. These two techniques are combined under an iterative framework in which we gradually allocate more resources for more promising candidate feature subsets. The experimental result shows that FeatureBand achieves a better trade-off between search time and search accuracy. It is 1.45 × to 17.6 × faster than the state-of-the-art wrapper-based methods without accuracy loss. © 2019, Springer Nature Switzerland AG.

关键词： Feature Selection

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An overview of image-based person re-identification

An overview of image-based person re-identification

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International Conference on Applications and Techniques in Cyber Intelligence, ATCI 2018

作者： Zhou, Shuren Ke, Maolin Luo, Peng Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology Changsha410114 China School of Computer and Communication Engineering Changsha University of Science and Technology Changsha410114 China

ISBN: (纸本)9783319987750

Person re-identification (person re-ID) is refers to pedestrians matching under a multi camera network in a non-overlapping field of view, that is, whether the pedestrian targets taken by different cameras are the same. In this paper, the image based traditional person re-ID is introduced from feature description and metric learning. In addition, with the extensive application of the deep learning algorithm in recent years, it also brings about the change of person re-ID algorithm. From the three aspects of loss function design, local feature and data augmentation, this paper introduces some work of person re-ID algorithm based on deep learning. Finally, it summarizes the development of pedestrian datasets in recent years, and looks forward to the future development trend of person re-ID. © Springer Nature Switzerland AG 2019.

关键词： Learning algorithms

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The Complex System of Geographical Conditions and Its Hierarchical Regionalization Analysis 4th

The Complex System of Geographical Conditions and Its Hierar...

引用

4th International Conference on Intelligent, Interactive Systems and Applications, IISA2019

作者： Mingxia, Xie Jianzhong, Guo Li, Zhang Changjiang Institute of Survey Planning Design and Research Wuhan430010 China Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Land and Resources Shenzhen518034 China Changjiang Spatial Information Technology Engineering Co. Ltd Wuhan430010 China Henan Institute of Spatiotemporal Big Data Industry Technology Kaifeng475000 China The College of Environment and Planning of Henan University Kaifeng475000 China

ISBN: (纸本)9783030343866

This investigation analyzes the basic characteristics of the geographical conditions and the complex system. Based on this, the concept of complex system of geographical conditions (CSGC) is put forward. The hierarchical regionalization model of CSGC is constructed combined with DPSIR model and the method of TOPSIS. Based on the data of Henan Province’s geographic and national conditions census, the statistical yearbook and urban planning data of Henan Province, prefecture-level cities and cities, the coordination degree evaluation and analysis experiments of CGCS in Henan Province are carried out. The results show that: (1) There is little difference in the development status of social and resource subsystems among each city in Henan Province, and there is great difference in the development status of economic and ecological subsystems. (2) On the whole, the coordination of CGCS in Henan Province shows a zonal pattern of development, which gradually develops from both ends to the middle, and is positively correlated in the overall geographic space. In coordinating regional development of geographical conditions, scientifically recognizing geographical conditions and promoting regional coordination and sustainable development of geographical conditions, feasible strategies for balanced regional development of geographical conditions can be formulated according to the similarities and differences of the development structure of geographical conditions of various cities. © 2020, Springer Nature Switzerland AG.

关键词： Coordination reactions

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Non-Hermiticity-induced quantum control of localization in quantum walks

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Physical Review A 2020年第2期102卷 022218-022218页

作者： Rui Zhang Yi-Fan Liu Tian Chen National Engineering Laboratory for Public Safety Risk Perception and Control by Big Data China Academy of Electronics and Information Technology Beijing 100041 China Department of Physics and Astronomy University of California Riverside California 92521 USA Beijing Key Laboratory of Nanophotonics and Ultrafine Optoelectronic Systems School of Physics Beijing Institute of Technology Beijing 100081 China

Non-Hermiticity-induced quantum control is an unique phenomenon, which cannot be observed in Hermitian quantum systems. Here we study the quantum control of localization in non-Hermitian QW systems. When a phase defect is introduced to a specific site of non-Hermitian QW, the walker will not only be localized at the site of phase defect but also at its neighboring sites. Moreover, we find that as the system transforms from the PT-symmetry-unbroken regime to PT-symmetry-broken regime, most of probability distributions can be found at the positions far away from the phase defect in a long period of time. Our discoveries about the control of walker in non-Hermitian QW can provide valuable references for the study of quantum search in dissipative quantum systems.

关键词： Angular momentum of light Localization PT-symmetric quantum mechanics Quantum phase transitions Quantum walks

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An improved person reidentification method by selective convolutional descriptor aggregation

An improved person reidentification method by selective conv...

引用

International Conference on Applications and Techniques in Cyber Intelligence, ATCI 2018

ISBN: (纸本)9783319987750

Person re-identification (person re-ID) is refers to pedestrians matching under a multi camera network in a non-overlapping field of view, that is, whether the pedestrian targets taken by different cameras are the same. Therefore, person re-ID is also a sub problem of image retrieval. In this paper, fine grained image retrieval method SCDA (Selective Convolutional Descriptor Aggregation) is used in person re-ID, and the framework of identification-verification is improved. The method can select useful deep descriptors, at the same time, remove background by localizing the main object. © Springer Nature Switzerland AG 2019.

关键词： Computer vision

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CT Scan Synthesis for Promoting Computer-Aided Diagnosis Capacity of COVID-19 16th

CT Scan Synthesis for Promoting Computer-Aided Diagnosis Cap...

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16th International Conference on Intelligent Computing, ICIC 2020

作者： Li, Heng Hu, Yan Li, Sanqian Lin, Wenjun Liu, Peng Higashita, Risa Liu, Jiang School of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Big Data Research Center University of Electronic Science and Technology of China Chengdu611731 China Tomey Corporation Nagoya451-0051 Japan Department of Computer Science and Engineering Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Southern University of Science and Technology Shenzhen518055 China Ningbo Institute of Industrial Technology Chinese Academy of Sciences Ningbo China

ISBN: (纸本)9783030608019

Nowadays, with the rapid spread of Corona Virus Disease 2019 (COVID-19), this epidemic has become a threatening risk for global public health. Medical workers and researchers all over the world are struggling against the novel coronavirus in the front line. Because the computed tomography (CT) images from infected patients exposure characteristic abnormalities, automatic CT analyzers based on AI-based algorithms are extensively employed as effective weapons to aid clinicians. However, unbalanced data and lack of annotations obstruct AI-based algorithms applying in aided diagnosis because of their low performance. Therefore, in order to solve the above problems, a general-purpose solution is proposed to synthesize COVID-19 CT scans from non-COVID-19 data for providing high-quality negative-positive paired CT scans. Particularly, we introduce an elastic registration algorithm of CT images to manufacture paired training data. Then, a conditional Generative Adversarial Networks (GANs) based image-to-image translation model is implemented to synthesize COVID-19 CT scans from non-COVID-19 data. The effectiveness of our proposed algorithm used in COVID-19 aided diagnosis is verified in the experiments, and the identification and detection capacities of the classification models have been enhanced with the generated CT scans. Specifically, the precise lesion location is achieved by the generated data with a weakly supervised algorithm of class activation mapping (CAM). The model and code of this paper are publicly available at https://***/lihengbit/Synthesis-of-COVID-19-CT-Scan. © 2020, Springer Nature Switzerland AG.

关键词： Computer aided diagnosis

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Research on Pre-view Method of Safety Level of Cascading Trip for Power Grid 6th

Research on Pre-view Method of Safety Level of Cascading Tri...

引用

6th International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2021

作者： Deng, Huiqiong Li, Qinbin Zheng, Rongjin Li, Peiqiang Chang, Kuo-Chi School of Information Science and Engineering Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou Fujian350118 China Fujian Provincial University Engineering Research Center of Smart Grid Simulation Analysis and Integrated Control Fuzhou Fujian350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou Fujian350118 China College of Mechanical & Electrical Engineering National Taipei University of Technology No. 1 Section 3 Zhongxiao East Road Taipei10608 Taiwan Department of Business Administration North Borneo University College Lot 47 Block-F Alamesra Permai Plaza 2 Jln Sulaman Kota Kinabalu Sabah88400 Malaysia

ISBN: (纸本)9783030697167

This article introduces a method by which the power grid's security level can be observed in advance based on the expected initial failure. Firstly, based on the general form of cascading trip, this paper gives a mathematical expression of grid tripping based on cascading trip relay protection action behavior. According to the mathematical expression, the relationship between grid tripping and grid node injection power is discussed. According to this relationship, the distance between the node injection power under the current operation state and the nearest critical state node injection power is taken as the index to measure the power grid's security for cascading trip. According to this index, combined with various power grid constraints before and after the initial fault, a mathematical model for obtaining this safety index is given. This model is an optimized mathematical model. For the model, this paper gives a solution idea based on particle swarm. Finally, a few cases are performed in the IEEE-14 node system, and the calculations of the cases proved the accuracy of the proposed model and method. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Electric load flow

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Cross-domain object detection through coarse-to-fine feature adaptation

arXiv

引用

arXiv 2020年

作者： Zheng, Yangtao Huang, Di Liu, Songtao Wang, Yunhong Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University State Key Laboratory of Software Development Environment Beihang University School of Computer Science and Engineering Beihang University Beijing100191 China

Recent years have witnessed great progress in deep learning based object detection. However, due to the domain shift problem, applying off-the-shelf detectors to an unseen domain leads to significant performance drop. To address such an issue, this paper proposes a novel coarseto-fine feature adaptation approach to cross-domain object detection. At the coarse-grained stage, different from the rough image-level or instance-level feature alignment used in the literature, foreground regions are extracted by adopting the attention mechanism, and aligned according to their marginal distributions via multi-layer adversarial learning in the common feature space. At the fine-grained stage, we conduct conditional distribution alignment of foregrounds by minimizing the distance of global prototypes with the same category but from different domains. Thanks to this coarse-to-fine feature adaptation, domain knowledge in foreground regions can be effectively transferred. Extensive experiments are carried out in various cross-domain detection scenarios. The results are state-of-the-art, which demonstrate the broad applicability and effectiveness of the proposed approach. Copyright © 2020, The Authors. All rights reserved.

关键词： Object recognition

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