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Enhancement effect of casing on underwater explosion shock wave and bubble

Applied Ocean Research 2025年 158卷

作者： Zhang, Zhifan Zhang, Jingyuan Li, Hailong Liu, Gangwei Wang, Longkan Zhang, Guiyong State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment School of Naval Architecture Engineering Dalian University of Technology Dalian116024 China Naval University of Engineering Wuhan430030 China Xi'an Modern Chemistry Research Institute Xi'an710065 China Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration Shanghai200240 China China Ship Research and Development Academy Beijing100192 China

The casing is a critical design factor for underwater weapons, significantly influencing the energy output of underwater explosion (UNDEX) charges. In this study, a numerical model for cased charge UNDEX was developed using the coupled Eulerian-Lagrangian (CEL) method. To optimize the shock wave and bubble energy outputs, the effects of the thickness ratio n and casing material on load characteristics were systematically investigated, and optimal parameters were derived. First, the enhancement effects of the thickness ratio n on shock wave and bubble loads were examined at varying distance parameters δ. Subsequently, the influence of n on the spatial distribution of shock wave and bubble loads was analyzed using a two-way analysis of variance (ANOVA) model. Four typical underwater weapon casing materials - Ti6%Al4%V, Cu-OFHC, Al 6061-T6, Q235 - were selected. Their impacts on key parameters, including peak shock wave overpressure, bubble radius, bubble period, bubble shape, and pulsation pressure, were thoroughly evaluated. This study aims to elucidate the spatial and temporal evolution laws of shock wave and bubble loads for different types of cased charges, providing insights into the design and optimization of underwater weapons. © 2025

关键词： Ternary alloys

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REFUGE2 CHALLENGE: A TREASURE TROVE FOR MULTI-DIMENSION ANALYSIS AND EVALUATION IN GLAUCOMA SCREENING

arXiv

引用

arXiv 2022年

作者： Fang, Huihui Li, Fei Wu, Junde Fu, Huazhu Sun, Xu Son, Jaemin Yu, Shuang Zhang, Menglu Yuan, Chenglang Bian, Cheng Lei, Baiying Zhao, Benjian Xu, Xinxing Li, Shaohua Fumero, Francisco Sigut, José Almubarak, Haidar Bazi, Yakoub Guo, Yuanhao Zhou, Yating Baid, Ujjwal Innani, Shubham Guo, Tianjiao Yang, Jie Orlando, José Ignacio Bogunović, Hrvoje Zhang, Xiulan Xu, Yanwu The REFUGE2 Challenge Australia State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-Sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science Guangzhou China Intelligent Healthcare Unit Baidu Inc. Beijing China The Institute of High Performance Computing Agency for Science Technology and Research Singapore Yatiris Group PLADEMA Institute CONICET UNICEN Tandil Argentina Christian Doppler Lab for Artificial Intelligence in Retina Department of Ophthalmology and Optometry Medical University of Vienna Vienna Austria VUNO Inc Seoul Korea Republic of Tencent HealthCare Tencent Shenzhen China Computer Vision Institute College of Computer Science and Software Engineering of Shenzhen University Shenzhen China School of Biomedical Engineering Health Science Center Shenzhen University China Xiaohe Healthcare ByteDance Guangdong Guangzhou510000 China School of Biomedical Engineering Shenzhen University China College of Computer Science & Software Engineering Shenzhen University China Department of Computer Science and Systems Engineering Universidad de La Laguna Spain Saudi Electronic University Saudi Arabia King Saud University Saudi Arabia Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China SGGS Institute of Engineering and Technology India Institute of Medical Robotics Shanghai Jiao Tong University China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

With the rapid development of artificial intelligence (AI) in medical image processing, deep learning in color fundus photography (CFP) analysis is also evolving. Although there are some open-source, labeled datasets of CFPs in the ophthalmology community, large-scale datasets for screening only have labels of disease categories, and datasets with annotations of fundus structures are usually small in size. In addition, labeling standards are not uniform across datasets, and there is no clear information on the acquisition device. Here we release a multi-annotation, multi-quality, and multi-device color fundus image dataset for glaucoma analysis on an original challenge-Retinal Fundus Glaucoma Challenge 2nd Edition (REFUGE2). The REFUGE2 dataset contains 2000 color fundus images with annotations of glaucoma classification, optic disc/cup segmentation, as well as fovea localization. Meanwhile, the REFUGE2 challenge sets three sub-tasks of automatic glaucoma diagnosis and fundus structure analysis and provides an online evaluation framework. Based on the characteristics of multi-device and multi-quality data, some methods with strong generalizations are provided in the challenge to make the predictions more robust. This shows that REFUGE2 brings attention to the characteristics of real-world multi-domain data, bridging the gap between scientific research and clinical application. © 2022, CC BY-NC-ND.

关键词： Color

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Key Technique of Constructing Collaborating Environment Based on OPENMBEE

Key Technique of Constructing Collaborating Environment Base...

引用

International Conference on computer and Communications (ICCC)

作者： Junjie Xue Junhua Zhou Guoqiang Shi Yanhong Jiang Shuying Xu Hongyan Quan State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing China School of Software Engineering East China Normal University Shanghai China School of Computer Science and Technology East China Normal University Shanghai China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

With the development of integrated design and manufacturing technology, it is necessary to consider how to integrate a variety of modeling tools in the procedure of complex product design driven by the model-centric conception. In this work, we explored the development technology of multi-tool integration based on the Open Model Based Engineering Environment (OpenMBEE). We provide a multi-tool integration system solution, in which the integration schemes under different environments of LAN and virtual machine are designed, and the system scheme of multi-tool integration is also studied. From the idea of model design conception, we integrate the requirement analysis tools Cameo. On the basis, Model Management System (MMS) and View Editor(VE), as well as the specific model analysis tool MATLAB and 3D visual simulation tool Creo are also integrated seamlessly. The effectiveness of the proposed integration strategies is verified by some practical instances. That is verified that our study can provide an effective design idea for complex production.

关键词： Analytical models Solid modeling Computational modeling Tools Product design Mathematical model Matlab

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Towards 6G wireless communication networks:vision, enabling technologies, and new paradigm shifts

引用

Science China(Information Sciences) 2021年第1期64卷 5-78页

作者： Xiaohu YOU Cheng-Xiang WANG Jie HUANG Xiqi GAO Zaichen ZHANG Mao WANG Yongming HUANG Chuan ZHANG Yanxiang JIANG Jiaheng WANG Min ZHU Bin SHENG Dongming WANG Zhiwen PAN Pengcheng ZHU Yang YANG Zening LIU Ping ZHANG Xiaofeng TAO Shaoqian LI Zhi CHEN Xinying MA Chih-Lin I Shuangfeng HAN Ke LI Chengkang PAN Zhimin ZHENG Lajos HANZO Xuemin (Sherman) SHEN Yingjie Jay GUO Zhiguo DING Harald HAAS Wen TONG Peiying ZHU Ganghua YANG Jun WANG Erik G.LARSSON Hien Quoc NGO Wei HONG Haiming WANG Debin HOU Jixin CHEN Zhe CHEN Zhangcheng HAO Geoffrey Ye LI Rahim TAFAZOLLI Yue GAO H.Vincent POOR Gerhard P.FETTWEIS Ying-Chang LIANG National Mobile Communications Research Laboratory School of Information Science and EngineeringSoutheast University Purple Mountain Laboratories Shanghai Institute of Fog Computing Technology (SHIFT) ShanghaiTech University Research Center for Network Communication Peng Cheng Laboratory State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications National Engineering Laboratory for Mobile Network Technologies Beijing University of Posts and Telecommunications National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China (UESTC) China Mobile Research Institute School of Electronics and Computer Science University of Southampton Department of Electrical and Computer Engineering University of Waterloo Global Big Data Technologies Centre (GBDTC) University of Technology Sydney School of Electrical and Electronic Engineering The University of Manchester LiFi Research and Development Centre Institute for Digital CommunicationsSchool of EngineeringThe University of Edinburgh Huawei Technologies Canada Co. Ltd. Huawei Technologies Department of Electrical Engineering (ISY) Link?ping University Institute of Electronics Communications & Information Technology (ECIT)Queen's University Belfast State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast University School of Electrical and Computer Engineering Georgia Institute of Technology 5G Innovation Centre University of Surrey Princeton University Vodafone Chair Mobile Communications Systems Technische Universit?t Dresden Center for Intelligent Networking and Communications (CINC) University of Electronic Science and Technology of China (UESTC)

The fifth generation(5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability,and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation(6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle(UAV) communication networks, thus achieving a space-airground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6GHz, millimeter wave(mmWave), terahertz(THz),and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence(AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable f

关键词： 6G vision network architecture air interface and transmission technologies space-air-ground-sea integrated network all spectra artificial intelligence network security

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Recommending more suitable music based on users’ real context 14th

Recommending more suitable music based on users’ real conte...

引用

14th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2018

作者： Yang, Qing Zhan, Le Han, Li Zhang, Jingwei Bi, Zhongqin School of Electronic Engineering and Automation Guilin University of Electronic Technology Guilin541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin541004 China College of Computer Science and Technology Shanghai University of Electronic Power Shanghai200090 China

ISBN: (纸本)9783030129804

Music recommendation is an popular function for personalized services and smart applications since it focuses on discovering users’ leisure preference. The traditional music recommendation strategy captured users’ music preference by analyzing their historical behaviors to conduct personalized recommendation. However, users’ current states, such as in busy working or in a leisure travel, etc., have an important influence on their music enjoyment. Usually, those existing methods only focus on pushing their favorite music to users, which may be not the most suitable for current scenarios. Users’ current states should be taken into account to make more perfect music recommendation. Considering the above problem, this paper proposes a music recommendation method by considering both users’ current states and their historical behaviors. First, a feature selection process based on ReliefF method is applied to discover the optimal features for the following recommendation. Second, we construct different feature groups according to the feature weights and introduce Naive Bayes model and Adaboost algorithm to train these feature groups, which will output a base classifier for each feature group. Finally, a majority voting strategy decides the optimal music type and each user will be recommended more suitable music based on their current context. The experiments on the real datasets show the effectiveness of the proposed method. © 2019, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Adaptive boosting

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A Model Based Heterogeneous Data Collaboration Method

A Model Based Heterogeneous Data Collaboration Method

引用

IEEE International Conference on Electronics and Communication Engineering (ICECE)

作者： Junjie Xue Junhua Zhou Guoqiang Shi Yanhong Jiang Bowen Wei Hongyan Quan Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center Beijing China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing China Beijing Simulation Center Science and Technology on Space System Simulation Laboratory Beijing China School of Software Engineering East China Normal University Shanghai China School of Computer Science and Technology East China Normal University Shanghai China

ISBN: (数字)9781728192581

ISBN: (纸本)9781728192598

Model based heterogeneous data collaboration is important in the integrated design and manufacturing technology. In this work, we propose a systematic method of collaborative design method for heterogeneous data sources. In our method, we use the Open Model Based Engineering Environment (OpenMBEE) to study. In our work, we setup environment and construct the integrated multi-tools achieving consistency design, and then we successfully design and implement a reasonable scheme to parameterize the model in requirement analysis and store the extracted parameters in Model Management System (MMS) for transporting to the visualization tool for further simulation. We integrate the mathematical analysis tools of MATLAB, and successfully design the interface in the tool integration, and realize the model consistency in the problem of integrating multiple tools in the design based on model center. The effectiveness of the proposed integration strategies is verified by some practical instances. That is verified that our provided study can an effective design idea for complex production.

关键词： Analytical models Collaboration Production Tools Data models Mathematical model Matlab

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development of Smart 3D Object Detection using LiDAR Cloud-Data Collection

引用

Journal of Physics: Conference Series 2021年第1期2128卷

作者： Essam M. Abd Elhamied Sherin M. Youssef Team Leader Development Software Information and Documentation Center Arab Academy for Science & Technology (AAST). Alexandria EGYPT. Department of Computer Engineering Arab Academy for Science & Technology (AAST). Alexandria EGYPT

Smart cities are made up of autonomous vehicle and they communicate and interact with their environment and require high precision computer vision to maintain driver and pedestrian safety. This paper presents a cost-efficient, non-intrusive and easy to use method for collecting data traffic counts using LiDAR technology. The proposed method incorporates a LiDAR sensor, a Convolutional Neural Network (CNN) and a Hybrid SVM into a single traffic counting framework. As the technology is economical and readily accessible, LiDAR is adopted. The distance data obtained are translated into the signals. Due to the difficulty of urban scenes, automatic detection of objects from remotely sensed data within urban areas is difficult. While recent advances in computer vision have shown that CNNs are very suitable for this task, the design and training of CNNs of this kind remained demanding and time consuming, given the challenge of collecting a large and well-annotated dataset and the specificity of every task. Hybrid SVM is a supervised data classification and regression machine learning tool. In the methodology the Hybrid SVM is used in detection and non-detection cases of highly complex distance data points obtained from the sensor. In order to examine the performance of the proposed method, the test is carried out in three different locations in Alexandria, Egypt. The results of tests show that the pro-imposed method achieves acceptable results in vehicle collection, which results in a precision of 85–89%. The exactness of the method proposed is determined by the colour of a vehicle's external surface.

关键词：

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A Framework of Blockchain-Based Security for WBANs

A Framework of Blockchain-Based Security for WBANs

引用

Smart BlockChain (SmartBlock), International Conference on

作者： Han Deng Xiangwei Meng Jun Guo Erhui Xi Hui Zhao Big Data Development and Research Center Guangzhou College of Technology and Business Guangzhou China School of Computer science and Engineering Hunan University of Science and Technology Xiangtan China School of Software Engineering Quanzhou University of Information Engineering Quanzhou China Guangzhou College of Technology and Business Guangzhou China Educational Information Technology Laboratory Henan University Kaifeng China

Purposed to collect and store human physiological data, WBANs as a telemedicine system play a significant role in sensor networks. The complex network environment presents a formidable challenge to the stability of the system and the security of the database. The traditional centralized architecture is to store the registration data of the sensor node and the patient's physiological data in the hub node. When the hub node is subjected to Denial of Service attacks (DoS) and Distributed Denial of Service attacks (DDoS), there will be a single point of failure, so that the sensor node cannot establish a communication connection with the hub node. In this paper, a cloud server layer architecture based on blockchain technology is proposed for WBNAs to ensure system stability and patient data security. Meanwhile, Ciphertext-Policy Attribute-Based Encryption (CP-ABE) scheme is used to ensure patient physiological data safety.

关键词： Wireless communication Cloud computing Architecture Distributed databases Blockchain Medical services Permission

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Multi-View Partial (MVP) Point Cloud Challenge 2021 on Completion and Registration: Methods and Results

arXiv

引用

arXiv 2021年

作者： Pan, Liang Wu, Tong Cai, Zhongang Liu, Ziwei Yu, Xumin Rao, Yongming Lu, Jiwen Zhou, Jie Xu, Mingye Luo, Xiaoyuan Fu, Kexue Gao, Peng Wang, Manning Wang, Yali Qiao, Yu Zhou, Junsheng Wen, Xin Xiang, Peng Liu, Yu-Shen Han, Zhizhong Yan, Yuanjie An, Junyi Zhu, Lifa Lin, Changwei Liu, Dongrui Li, Xin Gómez-Fernández, Francisco Wang, Qinlong Yang, Yang S-Lab Nanyang Technological University Singapore SenseTime-CUHK Joint Lab The Chinese University of Hong Kong Hong Kong Sensetime Research Shanghai AI Laboratory China Department of Automation Tsinghua University China University of Chinese Academy of Sciences China ShenZhen Key Lab of Computer Vision and Pattern Recognition SIAT-SenseTime Joint Lab Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Digital Medical Research Center School of Basic Medical Science Fudan University China School of Software BNRist Tsinghua University China *** Wayne State University State Key Laboratory for Novel Software Technology Nanjing University China DeepGlint Shanghai Jiao Tong University China Sichuan University China Xi'an Jiaotong University China

As real-scanned point clouds are mostly partial due to occlusions and viewpoints, reconstructing complete 3D shapes based on incomplete observations becomes a fundamental problem for computer vision. With a single incomplete point cloud, it becomes the partial point cloud completion problem. Given multiple different observations, 3D reconstruction can be addressed by performing partial-to-partial point cloud registration. Recently, a large-scale Multi-View Partial (MVP) point cloud dataset has been released, which consists of over 100,000 high-quality virtual-scanned partial point clouds. Based on the MVP dataset, this paper reports methods and results in the Multi-View Partial Point Cloud Challenge 2021 on Completion and Registration. In total, 128 participants registered for the competition, and 31 teams made valid submissions. The top-ranked solutions will be analyzed, and then we will discuss future research directions. Copyright © 2021, The Authors. All rights reserved.

关键词： Surface measurement

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Synchronous Motion Generation of Multiple Continuum Robots Based on a Jacobian-Estimation Strategy

Synchronous Motion Generation of Multiple Continuum Robots B...

引用

IEEE International Conference on Robotics and Biomimetics

作者： Ning Tan Ruikun Hu Yuyang Wu Xinyu Zhang Fenglei Ni Zhenglong Sun School of Computer Science and Engineering Sun Yat-sen University Guangzhou PR China State Key Laboratory of Robotics and Systems (HIT) Harbin PR China Engineering Research Center of Software/Hardware Co-Design Technology and Application Ministry of Education (East China Normal University) Shanghai PR China School of Science and Engineering The Chinese University of Hong Kong Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China

ISBN: (纸本)9781665405362

In this paper, a novel model-free control scheme is proposed for synchronous motion control of multiple continuum robots. The control problem is formulated as two convex optimization routines in an adaptive and model-free closed-loop framework. The proposed approach is heading to address cooperative task execution for multiple continuum robots. The model-free feedback control guarantees the high portability for a wide range of continuum robots. Simulation studies are conducted on two kinds of tasks, which are cooperative task execution with two robots and simultaneously tracking control with three robots. Besides, the superiority of proposed approach is validated through comparisons with other methods. Simulation results prove the high accuracy and efficiency of this model-free feedback control scheme.

关键词： Jacobian matrices Adaptation models Tracking Simulation Conferences Convex functions Feedback control

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