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Proceedings of the 2019 the 9th International Conference on communication and Network Security

作者： Xinli Xiong Linru Ma Chao Cui Army Engineering University of People's Liberation Army Nanjing Jiangsu China National Key Laboratory of Science and Technology on Information System Security Beijing China Beijing Institute of Control Engineering Beijing China

ISBN: (纸本)9781450376624

In this paper, a simulation environment for evaluating the effectiveness and performance cost of moving target defense (MTD) is presented. This simulation environment is based on SimPy, which is a process-based discrete-event simulation framework worked on standard Python. In our MTD simulation environment, we develop a typical topology to contain different deployments of moving target (MT) techniques. Meanwhile, processes of attackers, defenders, services, and users are analyzed and modeled in the simulation environment, which also provides an extendable interface for MT technologies in the future. In the case study, we quantify the effectiveness and performance of MTD in the proposed simulation environment under several typical scenarios, none-MTD deployment, high-security strategy, high-performance strategy. The average attacking time, average processed requests, and average request's processing time are used as metrics to assess different MTD strategies. Results show that our simulation environment provides an efficient and intuitionistic method for evaluating the effectiveness and performance of MTD and helping to choose a more optimal strategy set for MTD.

关键词： Discrete event simulation Performance quantification Moving target defense SimPy

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Simulation environment of evaluation and optimization for moving target defense: A SiMpy approach 9

Simulation environment of evaluation and optimization for mo...

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9th International Conference on communication and Network Security, ICCNS 2019

作者： Xiong, Xinli Ma, Linru Cui, Chao Army Engineering University of People's Liberation Army Nanjing Jiangsu China National Key Laboratory of Science and Technology on Information System Security Beijing China Beijing Institute of Control Engineering Beijing China

ISBN: (纸本)9781450376624

In this paper, a simulation environment for evaluating the effectiveness and performance cost of moving target defense (MTD) is presented. This simulation environment is based on SimPy, which is a process-based discrete-event simulation framework worked on standard Python. In our MTD simulation environment, we develop a typical topology to contain different deployments of moving target (MT) techniques. Meanwhile, processes of attackers, defenders, services, and users are analyzed and modeled in the simulation environment, which also provides an extendable interface for MT technologies in the future. In the case study, we quantify the effectiveness and performance of MTD in the proposed simulation environment under several typical scenarios, none-MTD deployment, high-security strategy, high-performance strategy. The average attacking time, average processed requests, and average request’s processing time are used as metrics to assess different MTD strategies. Results show that our simulation environment provides an efficient and intuitionistic method for evaluating the effectiveness and performance of MTD and helping to choose a more optimal strategy set for MTD. © 2019 Association for Computing Machinery.

关键词： Discrete event simulation

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Time-delay assisted mechanism and adaptive LSTM hybrid train braking model of heavy haul trains

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control Engineering Practice 2025年 163卷

作者： Qiang Liu Kexuan Xu Yating Fu Jiang Liu Ling Liu State Key Laboratory of Synthetical Automation for Process Industries (Northeastern University) Shenyang 110819 China Key Laboratory of Advanced Control and Optimization of Jiangxi Province Nanchang 330013 China School of Electrical and Automation Engineering East China Jiaotong University Nanchang 330013 China Frontiers Science Center for Smart High-speed Railway System Beijing 100044 China School of Electronic and Information Engineering Beijing Jiaotong University Beijing 100044 China Beijing National Railway Research & Design Institute of Signal Communication Group Company Beijing 100070 China

The train braking model (TBM) that describes the dynamic relations of operation speed, mileage, and control force is essential for achieving stable operation and precise stopping of heavy haul trains (HHTs). However, it is difficult to establish the TBM of HHTs due to complex characteristics: (i) the long body and air braking process of the HHTs may lead to unexpected time-delays of control force; and (ii) there are significant unmodeled dynamics caused by rough tracks and external poor environment. Traditional TBM does not take into account the unmodeled dynamics and time-delays caused by air transmission during braking. To address these issues, this study proposes a data mechanism hybrid modeling strategy, which incorporates a braking time-delay assisted mechanism model and an adaptive long and short-term memory (LSTM) model. A new Bayesian optimization based time-delay estimation method is first proposed to determine unknown time-delays of each carriage and the estimated time-delays are incorporated to generate the multi-point-mass kinetic mechanism model. Moreover, the error of the mechanism-driven model is adaptively compensated by a sliding window LSTM model to conduct the unmodeled dynamics. The effectiveness of the proposed method is demonstrated using the field data.

关键词： Railroad transportation

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Distinguishing the main climatic drivers of terrestrial vegetation carbon dynamics in pan-Arctic ecosystems

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Ecological Informatics 2025年

作者： Chengfeng Meng Hao Zhou Xichuan Liu Jiao Zheng Jun Wang Qingwei Zeng Shuai Hu College of Meteorology and Oceanography National University of Defense Technology Changsha 410073 China Key Laboratory of High Impact Weather (Special) China Meteorological Administration (CMA) Changsha 410073 China Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science & Technology (NUIST) Nanjing 210044 China Frontiers Science Center for Critical Earth Material Cycling International Institute for Earth System Science Nanjing University Nanjing 210023 China

Pan-Arctic terrestrial ecosystems have experienced widespread greening over the past few decades due to climate warming. However, the dynamic variations and climatic causes of such greening in the pan-Arctic are still unclear due to limitations in high-latitude ground-based measurements. The study first evaluated the applicability of three satellite-based vegetation indices (VIs) for pan-Arctic carbon dynamics in previous decades compared with multisource observations. Three VIs presented significant increasing trends up to 0.0005–0.0017 yr −1 for pan-Arctic ecosystems in the past 23 years, and near-infrared reflectance of vegetation (NIRv) could better capture pan-Arctic terrestrial carbon dynamic variations (e.g., increasing trends) than other VIs among most vegetation types, such as grasslands. The separate contributions of climatic factors to satellite-based NIRv variability were further quantified using partial correlation and ridge regression analysis over pan-Arctic ecosystems from 2001 to 2023. Carbon dioxide (CO 2 ) and air temperature (AT) presented positive partial correlations with the satellite-based NIRv over entire pan-Arctic ecosystems, due to fertilization and warming effects. However, the vapor pressure deficit (VPD) showed positive (negative) partial correlations with NIRv variations in high (low) pan-Arctic ecosystems because of diverse stomatal responses to air dryness. Therefore, increases in VPD contributed 11.2 % of the pan-Arctic NIRv variability, although positive (negative) effects were detected for high (low) pan-Arctic ecosystems. These findings highlight the advantages of the NIRv for representing terrestrial carbon dynamics in fragile ecosystems (e.g., the pan-Arctic) and reveal the diverse effects of the regional climate (e.g., air dryness) on pan-Arctic ecosystems under climate warming.

关键词： Pan-Arctic Vegetation index Climate change CO 2 VPD

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Optimized Resource Allocation in Scalable Video Broadcasting Using LDM and BDM

Optimized Resource Allocation in Scalable Video Broadcasting...

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IEEE International Symposium on Broadband Multimedia systems and Broadcasting (BMSB)

作者： Haining Duan Yu Zhang Jian Song Beijing National Research Center for Information Science and Technology (BNRist) Tsinghua University Beijing China Key Laboratory of Digital TV System of Guangdong Province and Shenzhen City Research Institute of Tsinghua University in Shenzhen Shenzhen P.R. China Science and Technology on Communication Networks Laboratory

ISBN: (数字)9781728157849

ISBN: (纸本)9781728157856

Combining non-orthogonal multiple access (NOMA) with scalable video coding (SVC) is an efficient transmission method to improve spectrum efficiency for the next generation digital broadcasting systems. As two candidate technologies of NOMA in physical layer, both bit division multiplexing (BDM) and layer division multiplexing (LDM) are discussed and compared in this paper. By analyzing the relationships among SNR thresholds, channel resources and capacities, we propose a novel resource allocation algorithm aiming at eliminating the coverage mismatch and maximizing the aggregated data rate (ADR) across the system. We start with the simple two-layer optimization problem, then extend the results to the multi-layer cases, which can be solved iteratively. Simulation results verify the advantages of the proposed algorithm in terms of better coverage performance and higher ADR.

关键词： NOMA Static VAr compensators Broadcasting Resource management Multimedia communication Layered division multiplexing Signal to noise ratio

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communication-efficient coordinated RSS-based distributed passive localization via drone cluster

arXiv

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arXiv 2021年

作者： Cheng, Xin Shi, Weiping Cai, Wenlong Zhu, Weiqiang Shen, Tong Shu, Feng Wang, Jiangzhou School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing210094 China The 8511 Research Institute China Aerospace Science and Industry Corporation Nanjing210007 China The National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing Aerospace Automatic Control Institute Beijing100854 China The School of Information and Communication Engineering Hainan University Haikou570228 China The School of Engineering and Digital Arts University of Kent CanterburyCT2 7NT United Kingdom

Recently, passive unmanned aerial vehicle (UAV) localization has become popular due to mobility and convenience. In this paper, we consider a scenario of using distributed drone cluster to estimate the position of a passive emitter via received signal strength (RSS). First, a distributed majorizeminimization (DMM) RSS-based localization method is proposed. To accelerate its convergence, a tight upper bound of the objective function from the primary one is derived. Furthermore, to reduce communication overhead, a distributed estimation scheme using the Fisher information matrix (DEF) is presented, with only requiring one-round communication between edge UAVs and center UAV. Additionally, a local search solution is used as the initial value of DEF. Simulation results show that the proposed DMM performs better than the existing distributed Gauss-Newton method (DGN) in terms of root of mean square error (RMSE) under a limited low communication overhead constraint. Moreover, the proposed DEF performs much better than MM in terms of RMSE, but has a higher computational complexity than the latter. Copyright © 2021, The Authors. All rights reserved.

关键词： Mean square error

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Calibration and orientation of industrial online photogrammetry systems in situ

Calibration and orientation of industrial online photogramme...

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7th International Symposium on Test Automation and Instrumentation, ISTAI 2018

作者： Sun, Peng Lu, Naiguang Dong, Mingli Wang, Jun Yan, Bixi Institute of Information Photonics and Optical Communication Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory: Measurement and Control of Mechanical Electrical System Beijing Information Science and Technology University Beijing China School of Instrument Science and Optoelectronics Engineering Beijing Information Science and Technology University Beijing China

This study proposes an analytical method for calibrating and orienting online photogrammetric systems using a scale bar. The primary idea is building control lengths in the measurement volume by moving and rotating the scale bar and then conducting a self-calibration bundle adjustment using images of the control lengths. In this study, the five-point relative orientation method is used to provide estimations of the exterior camera parameters. Additionally, this study elaborates the model of the lengths constrained self-calibration bundle adjustment, the block computation algorithm and the accuracy assessment. This method obtains both the interior and the exterior orientation parameters of the two cameras, and provides spatial bar length reconstruction precision as the performance evaluation. Simulations are conducted to analyze the calibration accuracy and the results show that the method achieves comparable accuracy and precision against the state-of-the-art method. However, the method does not need steady and well distributed 3D points and is easy to operate. Real data experimental results show that the maximum length measurement error of this method in a volume of 5 m × 4 m × 2 m is © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Photogrammetry

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A Human-Robot Skill Transfer Framework of Mobile Medical Robots for Autonomous Motion with Teaching by Demonstration

A Human-Robot Skill Transfer Framework of Mobile Medical Rob...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Jiehao Li Junzheng Wang Shoukun Wang Hui Peng Qi Wen Longbin Zhang Meina Lin Politecnico di Milano Milan Italy State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China College of Intelligence Science and Technology National University of Defense Technology Changsha China BioMEx Center KTH Mechanics KTH Royal Institute of Technology Stockholm Sweden Guangdong Key Laboratory of IoT Information Technology Guangdong University of Technology Guangzhou China

ISBN: (数字)9781728164793

ISBN: (纸本)9781728164809

The accuracy of autonomous motion is the main challenge for mobile medical robots, especially running in narrow space conditions to transport the casualties in the hospital. This article mainly centers on the human-robot transmission of the mobile medical robot for narrow space autonomous motion. In order to enable mobile medical robots to autonomously and smoothly transport hospital casualties through narrow aisles, in this paper, we present a robot skill transfer technology, namely a human-robot skill transfer framework of mobile medical robots for autonomous motion with teaching by demonstration, which is that a smooth optimal path is planned through the human motion, and then the Kinect sensor is used to detect human bone movement to learn its motion trajectory so as to achieve trajectory tracking control. Meanwhile, using the Remote Center of Motion (RCM) constraint to minimize the error between the actual trajectory of the medical robot and the tracking reference path to control the motion trajectory accurately, human-computer interactive mobile medical robots can smoothly pass through narrow channels. Through research and analysis, it is demonstrated that the mobile medical robot proposed in this paper has great feasibility, which is of great reference value in the field of medical rescue.

关键词： Medical robotics Education Trajectory Mobile robots Tracking Hospitals

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Multiple residual dense networks for reconfigurable intelligent surfaces cascaded channel estimation

arXiv

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arXiv 2021年

作者： Jin, Yu Zhang, Jiayi Huang, Chongwen Yang, Liang Xiao, Huahua Ai, Bo Wang, Zhiqin The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China Zhejiang Provincial Key Lab of Information Processing Communication and Networking Zhejiang University Hangzhou310007 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518055 China China Academy of Information and Communications Technology Beijing100191 China

Reconfigurable intelligent surface (RIS) constitutes an essential and promising paradigm that relies programmable wireless environment and provides capability for space-intensive communications, due to the use of low-cost massive reflecting elements over the entire surfaces of man-made structures. However, accurate channel estimation is a fundamental technical prerequisite to achieve the huge performance gains from RIS. By leveraging the low rank structure of RIS channels, three practical residual neural networks, named convolutional blind denoising network, convolutional denoising generative adversarial networks and multiple residual dense network, are proposed to obtain accurate channel state information, which can reflect the impact of different methods on the estimation performance. Simulation results reveal the evolution direction of these three methods and reveal their superior performance compared with existing benchmark schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Channel estimation

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The Droplet Activation Parameterization for Black Carbon-Containing Particles in Steady State

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Geophysical Research Letters 2025年第11期52卷

作者： Zhouyang Zhang Jiandong Wang Nicole Riemer Jiaping Wang Chao Liu Yuzhi Jin Zeyuan Tian Sunan Shen Bin Wang Ganzhen Chen Bin Zhao Jianlin Hu Minghuai Wang Hang Su Shuxiao Wang Yafang Cheng Aijun Ding State Key Laboratory of Climate System Prediction and Risk Management Nanjing University of Information Science and Technology Nanjing China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters School of Atmospheric Physics Nanjing University of Information Science and Technology Nanjing China Department of Climate Meteorology and Atmospheric Sciences University of Illinois Urbana-Champaign Urbana IL USA Joint International Research Laboratory of Atmospheric and Earth System Sciences School of Atmospheric Sciences Nanjing University Nanjing China National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta Nanjing China State Key Laboratory of Regional Environment and Sustainability Beijing China School of Environment Tsinghua University Beijing China Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Centre of Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology Nanjing China Institute for Climate and Global Change Research Nanjing University Nanjing China State Key Laboratory of Atmospheric Environment and Extreme Meteorology Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China Aerosol Chemistry Department Max Planck Institute for Chemistry Mainz Germany

The model representation of black carbon (BC) mixing state—referring to how BC is combined with other aerosol components within individual particles—introduces significant uncertainty in estimating BC's climate impacts. The cloud condensation nuclei (CCN) properties of BC-containing (BCc) particles are influenced by the amount of secondary aerosol coating, which is unevenly distributed across BC cores. This distribution complicates accurate predictions of CCN activities. The size distribution of BCc particles remains approximately unchanged as they continuously undergo both growth and deposition, forming a steady state. Based on this, we develop a droplet activation parameterization to predict the number distribution of BCc particles with respect to hygroscopicity and dry particle diameter. The predicted results demonstrate good agreement with those directly obtained from observations and simulations. This study evaluates the BC activation behavior accurately by using a few parameters, facilitating improved assessment of BC's indirect radiative effects in large-scale models. The number distribution of black carbon (BC)-containing particles with respect to hygroscopicity and dry particle diameter can be well predicted Results from our parameterization demonstrate good agreement with observational and particle-resolved simulation results The parameterization precisely evaluates the BC activation behavior by utilizing minimal computational resources Black carbon-containing (BCc) particles in liquid clouds play a role in affecting the Earth's climate, contributing to an indirect radiative forcing that ranges from −0.64 to 0.23 W/m 2 . However, this effect is highly uncertain, mainly because it is difficult to measure how many of these particles interact with water and become cloud droplets. This process, known as activation of cloud condensation nuclei, is critical for understanding BC's impact on climate. In climate models, the activation process is often simplified, i

关键词： black carbon cloud condensation nuclei mixing state parameterization

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