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2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2022

作者： Xu, Yichao Zhang, Jian Zhang, Yufeng Southeast University School of Civil Engineering Nanjing211189 China Jsti Group Nanjing211000 China State Key Laboratory of Safety and Health for In-Service Long Span Bridge Nanjing210012 China Ctr. of Data Measured by Struct. Health Monitoring System of Long-Span Bridge in Province of Jiangsu Nanjing210012 China

ISBN: (纸本)9781665409025

The existing vehicle-bridge coupled vibration analysis of the vehicle model cannot accurately consider the vehicle dynamic characteristics and the impact of flexible tires on the vehicle-bridge coupled vibration response. This paper analyzes the surface contact on the vehicle-bridge coupled vibration by establishing a new three-dimensional wheel model The contact surface between the wheel and the road surface is simulated as a rectangle, and the vehicle-bridge coupled vibration equation is established through the coordinated displacement conditions and force interaction between the contact surfaces. The vertical acceleration of bridges and car bodies is significantly affected by track irregularities. Improving line conditions can effectively improve the comfort of trains;at the same time, the higher the speed, the greater the root mean square of the random response of bridges and vehicles, which is caused by track irregularities. The greater the dispersion of the vibration response of the coupled system. © 2022 IEEE.

关键词： Big data

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The Weakest Link of Certificate Transparency: Exploring the TLS/HTTPS Configurations of Third-Party Monitors 18

The Weakest Link of Certificate Transparency: Exploring the ...

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18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/13th IEEE International Conference on Big data Science and engineering, TrustCom/BigdataSE 2019

作者： Li, Bingyu Chu, Dawei Lin, Jingqiang Cai, Quanwei Wang, Congli Meng, Lingjia State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Data Assurance and Communications Security Center Chinese Academy of Sciences Beijing100093 China School of Cyber Security University of Chinese Academy of Sciences Beijing100049 China Headquarter of Chinese Academy of Sciences Beijing100864 China

ISBN: (纸本)9781728127767

In order to enhance the accountability of certification authorities (CAs), certificate transparency (CT) is proposed to record CA-signed certificates in public logs. A certificate is accepted by CT-compliant browsers only if it is recorded in the logs, so that any fraudulent certificate will be detected by the domain owner in the public-visible logs. In practice, third-party monitors fetch certificates in the public logs to provide certificate search services, and the domain owner regularly searches all certificates issued for its domain from the third-party monitors to watch for suspicious ones among them. In this paper, we study the links of the CT framework among CAs, browsers, domain owners (or websites), third-party monitors, and log servers, and then analyze the security designs of each link. As an essential link of the CT framework which is proposed against TLS man-in-the-middle (MitM) attacks, the services of a thirdparty monitor shall be protected well against such attacks. We explore the TLS/HTTPS configurations of 8 well-known monitors and find that there are vulnerabilities of TLS MitM attacks. Thus, the attackers might first launch the MitM attacks on the very limited number of third-party monitors on the Internet and return manipulated certificate search results to domain owners, to conceal fraudulent certificates. The overall security guarantees of CT are jeopardized due to the weak protections of third-party monitors. © 2019 IEEE.

关键词： Transparency

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An obstacle avoidance design of UAV based on genetic algorithm 3

An obstacle avoidance design of UAV based on genetic algorit...

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3rd International Conference on Mechanical, Electric and Industrial engineering, MEIE 2020

作者： Hu, Xusheng Liu, Juan Key Laboratory of Unmanned Aerial Vehicle Development Data Application of Anhui Higher Education Institutes Wanjiang University of Technology Ma'anshan243031 China Ma'anshan Engineering Technology Research Center for Wireless Sensor Network and IntelliSense Ma'anshan243031 China Ma'anshan Technical College Ma'anshan243030 China

In order to improve the effect of obstacle avoidance, a PID control algorithm combined with genetic algorithm is proposed. By establishing the mathematical model of UAV, the auxiliary control system of UAV is analyzed, and then the control system is optimized by genetic algorithm. Taking STM32 as the control platform, the obstacle avoidance experiment was carried out by building the experimental platform. The experimental results show that the algorithm can avoid obstacles effectively. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Genetic algorithms

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Convolutional Neural Network Image Classification Method Integrating Classic Image Features

Convolutional Neural Network Image Classification Method Int...

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International Conference on Computational Intelligence and Applications (ICCIA)

作者： Qi Hao Jie Huang Bin Wang Feng Zhou Cyber Science and Engineering Southeast University Nanjing China Zhejiang Key Laboratory of Artificial Intelligence of Things Network and Data Security Hangzhou China

ISBN: (数字)9798350352214

ISBN: (纸本)9798350352221

Classic image features were once widely used in image classification but have been almost entirely replaced by neural networks today. While the performance of neural networks, especially convolutional neural networks (CNNs), is indisputable, their lack of interpretability has become a significant limitation in recent years. This paper explores the effective combination of classic image features and convolutional image features, investigating their differences and similarities. Through a series of experiments, a method is proposed to effectively integrate these two types of features by employing a multiplicative attention mechanism. This approach combines standardized MPEG-7 descriptors with convolutional features before feeding them into the fully connected layer for classification. The final model demonstrates an improvement in classification accuracy and indicates the potential of learning traditional image features from the integrated features.

关键词： Attention mechanisms Accuracy Computational modeling Neural networks Transform coding Convolutional neural networks Computational intelligence Image classification

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Compact and Accurate Adaptive Width Radial Basis Function Neural Network with Discriminative Features for Thyroid Gland Segmentation

Compact and Accurate Adaptive Width Radial Basis Function Ne...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Haijun You Junying Chen School of Software Engineering South China University of Technology Key Laboratory of Big Data and Intelligent Robot (SCUT) Ministry of Education Guangzhou China

The goal of this work is to develop a fast, compact, accurate, and robust neural network for automatic thyroid gland segmentation in medical ultrasound images when the computational resources are limited, such as portable intelligent medical diagnostic devices or robots. An adaptive width radial basis function neural network model with discriminative features is proposed in this work. The model combines the local characteristics and global context of the entire feature space, which improves the performance of the automatic thyroid gland segmentation, and enhances the data fitting capability and robustness of the neural network. A new feature selection method combining the measurements of area under the curve values and Pearson correlation coefficients is proposed to select six discriminative and low correlated features from a set of handcrafted features, which helps to construct a compact yet accurate radial basis function neural network. The proposed method is experimented on thyroid ultrasound images using five-fold cross validation. The proposed method achieves an average accuracy of 0.9770 and an average IoU of 0.7841, achieving competitive segmentation performance compared to convolutional neural networks, with thousands of times faster training speed on a CPU.

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Container lifecycle-aware scheduling for serverless computing

Container lifecycle-aware scheduling for serverless computin...

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作者： Wu, Song Tao, Zhiheng Fan, Hao Huang, Zhuo Zhang, Xinmin Jin, Hai Yu, Chen Cao, Chun National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing China

Elastic scaling in response to changes on demand is a main benefit of serverless computing. When bursty workloads arrive, a serverless platform launches many new containers and initializes function environments (known as cold starts), which incurs significant startup latency. To reduce cold starts, platforms usually pause a container after it serves a request, and reuse this container for subsequent requests. However, this reuse strategy cannot efficiently reduce cold starts because the schedulers are agnostic of container lifecycle. For example, it may ignore soon available containers or evict soon needed containers. We propose a container lifecycle-aware scheduling strategy for serverless computing, CAS. The key idea is to control distribution of requests and determine creation or eviction of containers according to different lifecycle phases of containers. We implement a prototype of CAS on OpenWhisk. Our evaluation shows that CAS reduces 81% cold starts and therefore brings a 63% reduction at 95th percentile latency compared with native scheduling strategy in OpenWhisk when there is worker contention between workloads, and does not add significant performance overhead. © 2021 John Wiley & Sons Ltd.

关键词： Containers

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A Cloud Computing User Experience Focused Load Balancing Method Based on Modified CMA-ES Algorithm 18th

A Cloud Computing User Experience Focused Load Balancing Met...

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18th International Conference on Green, Pervasive, and Cloud Computing, GPC 2023

作者： Luo, Jihai Dong, Chen Chen, Zhenyi Xu, Li Chen, Tianci College of Computer and Data Science - Fuzhou University Xueyuan Road Fujian Fuzhou360108 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China Department of Computer Science and Engineering University of South Florida TampaFL33620 United States College of Computer and Cyber Security Fujian Normal University Fuzhou350007 China

ISBN: (纸本)9789819998951

The development of the software and hardware has brought about the abundance and overflow of computing resources. Many Internet companies can lease idle computing resources based on the peak and valley cycles of usage load to provide IaaS service. After the surging development, more and more companies are gradually paying attention to the specific user experience in cloud computing. But there are few works about that aspect in load balance problem. Therefore, we consider the load balancing resource allocation problem, from the perspective of user experience, mainly based on geographical distance and regional Equilibrium, combined with user usage habits, in multiple service periods. A detailed mathematical definition has been established for this problem. This article proposes a mathematical model for the problem, along with an modified CMA-ES (Covariance Matrix Adaptation Evolution Strategy) algorithm, called WS-ESS-CMA-ES algorithm, to allocate computing resources and solve the above problem. The process of using the proposed algorithm to solve the problem of cloud computing resource allocation in real scenarios is simulated, and compared with some other algorithms. The experiment results show that our algorithm performs well. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Cloud computing

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GRIDLESS TOMOGRAPHIC SAR IMAGING BASED ON ACCELERATED ATOMIC NORM MINIMIZATION WITH EFFICIENCY

GRIDLESS TOMOGRAPHIC SAR IMAGING BASED ON ACCELERATED ATOMIC...

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2022 International Conference on Radar Systems, RADAR 2022

作者： Gao, Silin Zhang, Zhe Zhang, Bingchen Wu, Yirong Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Intelligent Aerospace Big Data Application Technology Suzhou215123 China Suzhou Aerospace Information Research Institute Suzhou215123 China

ISBN: (纸本)9781839537776

Synthetic aperture radar (SAR) tomography (TomoSAR) enables the reconstruction and three-dimensional (3D) localization of targets based on multiple two-dimensional (2D) observations of the same scene. The resolving along the elevation direction can be treated as a line spectrum estimation problem. However, traditional super-resolution spectrum estimation algorithms require multiple snapshots and uncorrelated targets. Meanwhile, as the most popular TomoSAR imaging method in modern years, compressed sensing (CS) based methods suffer from the gridding mismatch effect which markedly degrades the imaging performance. As a gridless CS approach, atomic norm minimization can avoid the gridding effect but requires enormous computing resources. Addressing the above issues, this paper proposes an improved fast ANM algorithm to TomoSAR elevation focusing by introducing the IVDST-ANM algorithm, which reduces the huge computational complexity of the conventional time-consuming semi-positive definite programming (SDP) by the iterative Vandermonde decomposition and shrinkage-thresholding (IVDST) approach, and retains the benefits of ANM in terms of gridless imaging and single snapshot recovery. We conducted experiments using simulated data to evaluate the performance of the proposed method, and reconstruction results of an urban area from the SARMV3D-Imaging 1.0 dataset are also presented. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Compressed sensing

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Mobile laser scanning systems for GPS/GNSS-denied environment mapping

Mobile laser scanning systems for GPS/GNSS-denied environmen...

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2018 ISPRS Technical Commission I Midterm Symposium on Innovative Sensing - From Sensors to Methods and Applications

作者： Wen, Chenglu Xia, Yan Lian, Yuhan Dai, Yudi Tan, Jinbin Wang, Cheng Li, Jonathan Fujian Key Laboratory of Sensing and Computing for Smart City School of Information Science and Engineering Xiamen University Xiamen361005 China Fujian Collaborative Innovation Center for Big Data Applications in Governments Fuzhou350003 China Faculty of Environment University of Waterloo WaterlooONN2L 3G1 Canada

Indoor 3D mapping provides a useful three-dimensional structure via an indoor map for many applications. To acquire highly efficient and relatively accurate mapping for large-scale GPS/GNSS-denied scene, we present an upgraded backpacked laser scanning system and a car-mounted indoor mobile laser scanning system. The systems provide both 3D laser scanning point cloud and camera images. In this paper, a simultaneous extrinsic calibration approach for multiple multi-beam LIDAR and multiple cameras is also proposed using the Simultaneous Localization and Mapping (SLAM)-based algorithm. The proposed approach uses the SLAM-based algorithm to achieve a large calibration scene using mobile platforms, registers an acquired multi-beam LIDAR point cloud to the terrestrial LIDAR point cloud to acquire denser points for corner feature extraction, and finally achieves simultaneous calibration. With the proposed mapping and calibration algorithms, we can provide centimetre-lever coloured point cloud with relatively high efficiency and accuracy. © Authors 2018. CC BY 4.0 License.

关键词： Mapping

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A cooperative spectrum sensing scheme based on extension theory for cognitive radio sensor networks

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Open Electrical and Electronic engineering Journal 2014年第1期8卷 64-70页

作者： Ouyang, Sheng Wan, Pin Wang, Yonghua Wang, Liyuan Wang, Qinruo School of Automation Guangdong University of Technology Guangdong China School of Electronic and Information Engineering South China University of Technology Guangzhou China Shenzhen Key Laboratory of High Performance Data Mining Shenzhen China

This paper proposes a cooperative censoring spectrum sensing scheme based on dependent function of extension theory for Cognitive Radio Sensor Networks (CRSN). The scheme uses the dependent function of Extension theory to identify the presence or absence of the licensed user's (LU) signal, and then calculate the related degree through dependent function to identify the initial test results of licensed users, and then send these results to the fusion center. Use a trust evaluation scheme based on noise jamming and channel attenuation for each node, and then this trust evaluation result of each node is sent to the fusion center. The fusion center makes the final decision by the K-M rule. Simulation results show that the proposed scheme could improve the detect probability effectively. © Ouyang et al.;Licensee Bentham Open.

关键词： Sensor networks

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