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A Green Paradigm for Internet of Things: Ambient Backscatter Communications

China Communications 2019年第7期16卷 109-119页

作者： Wei Zhang Yao Qin Wenjing Zhao Minzheng Jia Qiang Liu Ruisi He Bo Ai Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology and also with Institute of Telecommunication Satellites China Academy of Space Technology (CAST) Beijing Key Lab of Transportation Data Analysis and Mining Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications School of Computer and Information Technology Beijing Jiaotong University Beijing 100044 China Department of Information Engineering Beijing Polytechnic College Beijing 100042 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 100044 China

Internet of Things (IoT) has attracted extensive interest from both academia and industries, and is recognized as an ultimate infrastructure to connect everything at anytime and anywhere. The implementation of IoT generally faces the challenges from energy constraint and implementation cost. In this paper, we will introduce a new green communication paradigm, the ambient backscatter (AmBC), that could utilize the environmental wireless signals for both powering a tiny-cost device and backscattering the information symbols. Specifically, we will present the basic principles of AmBC, analyze its features and advantages, suggest its open problems, and predict its potential applications for our future IoT.

关键词： ambient backscatter (AmBC) RF-powered device Internet of Things (IoT) battery-free tag wire-less sensor

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Nonzero-Dynamics Stealthy Attack and Its Impacts Analysis in DC Microgrids

Nonzero-Dynamics Stealthy Attack and Its Impacts Analysis in...

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American control Conference

作者： Mengxiang Liu Chengcheng Zhao Ruilong Deng Peng Cheng Wenhai Wang Jiming Chen State Key Lab. of Industrial Control Technology Zhejiang University Hangzhou 310027 P. R. China School of Computer Science and Engineering Nanyang Tec

ISBN: (纸本)9781538679012;9781538679265

In this paper, we explore the potential stealthy attacks in the DC microgrid (DCmG) equipped with unknown input observer (UIO) based detectors, which are widely adopted for the detection and identification of cyber-attacks. We first prove that once the attacker knows the bounds of the initial state estimation error and the measurement noise, he/she can launch the nonzero-dynamics stealthy (NDS) attack in the DCmG, which can affect the detection residual while keep stealthy. Considering the complexity of the multi-layer control framework in the DCmG, we simplify the primary control loops as static unit gains and obtain the systematic dynamic model of the DCmG under the NDS attack. Then, we obtain the analytical expressions of the Point of Common Coupling (PCC) voltages, which are utilized to analyze the effects of the NDS attack on voltage balancing and current sharing, respectively. Moreover, we prove that under the NDS attack, the voltage and current convergence can still be achieved exponentially in the DCmG. Finally, extensive simulations are conducted in Simulink/PLECS to validate our theoretical results.

关键词： distributed control distributed power generation observers power generation control power system protection power system state estimation voltage control power system state estimation power generation control Power system protection distributed power generation diazonaphthalenedisulfonic acid decentralised control Voltage regulation Observers impact assessment voltage balance

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CBLNER: A Multi-models Biomedical Named Entity Recognition System Based on Machine Learning 1

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15th International Conference on Intelligent Computing, ICIC 2019

作者： Lejun, Gong Xiaolin, Liu Xuemin, Yang Lipeng, Zhang Yao, Jia Ronggen, Yang Jiangsu Key Lab of Big Data Security and Intelligent Processing School of Computer Science Nanjing University of Posts and Telecommunications Nanjing210023 China Faculty Intelligent Science and Control Engineering Jinling Institute of Technology Nanjing211169 China

ISBN: (数字)9783030269692

ISBN: (纸本)9783030269685

Biomedical named entities is fundamental recognition task in biomedical text mining. This paper developed a system for identifying biomedical entities with four models including CRF, LSTM, Bi-LSTM and BiLSTM-CRF. The system achieved the following performance in test data Genia V3.02: CRF with an F score of 75.91%, LSTM with an F score of 71.69%, BiLSTM with a F score of 74.37%, BiLSTM-CRF with a F score of 76.81%. Experimental results show the performance of BiLSTM-CRF model is better than other three models. Compared with CRF model, Bi-LSTM-CRF model has better recognition effect for biological entities in long text and entities that modified by modifiers. Therefore, CBLNER system lays a foundation for further relationship and event extraction, and could also provide reference for entity recognition research in other fields. © 2019, Springer Nature Switzerland AG.

关键词： Character recognition

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PIDNet: An efficient network for dynamic pedestrian intrusion detection

arXiv

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arXiv 2020年

作者： Sun, Jingchen Chen, Jiming Chen, Tao Fan, Jiayuan He, Shibo State Key lab. of Industrial Control Technology Zhejiang University Hangzhou China Alibaba-ZJU Joint Research Institute of Frontier Technologies School of Information Science and Technology Fudan University Shanghai China Academy for Engineering and Technology Fudan University Shanghai China

Vision-based dynamic pedestrian intrusion detection (PID), judging whether pedestrians intrude an area-of-interest (AoI) by a moving camera, is an important task in mobile surveillance. The dynamically changing AoIs and a number of pedestrians in video frames increase the difficulty and computational complexity of determining whether pedestrians intrude the AoI, which makes previous algorithms incapable of this task. In this paper, we propose a novel and efficient multi-task deep neural network, PIDNet, to solve this problem. PIDNet is mainly designed by considering two factors: accurately segmenting the dynamically changing AoIs from a video frame captured by the moving camera and quickly detecting pedestrians from the generated AoI-contained areas. Three efficient network designs are proposed and incorporated into PIDNet to reduce the computational complexity: 1) a special PID task backbone for feature sharing, 2) a feature cropping module for feature cropping, and 3) a lighter detection branch network for feature compression. In addition, considering there are no public datasets and benchmarks in this field, we establish a benchmark dataset to evaluate the proposed network and give the corresponding evaluation metrics for the first time. Experimental results show that PIDNet can achieve 67.1% PID accuracy and 9.6 fps inference speed on the proposed dataset, which serves as a good baseline for the future vision-based dynamic PID study. Copyright © 2020, The Authors. All rights reserved.

关键词： Intrusion detection

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Dynamic behavior of coalbed methane flow along the annulus of single-phase production

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International Journal of Coal Science & Technology 2019年第4期6卷 547-555页

作者： Xinfu Liu Chunhua Liu Guoqiang Liu School of Mechanical and Automotive Engineering Qingdao University of TechnologyQingdao 266520ShandongChina Key Lab of Industrial Fluid Energy Conservation and Pollution Control(Qingdao University of Technology) Ministry of EducationQingdao 266520ShandongChina College of Mechanical and Electronic Engineering China University of Petroleum(East China)Qingdao 266580ShandongChina PetroChina Coalbed Methane Co. Ltd.Linfen BranchTaiyuan 041000ShanxiChina

Dynamic behavior of coalbed methane (CBM) flow will provide the theoretical basis to optimize production performance for a given well.A mathematical model is developed to simulate flowing pressures and pressure drops of CBM column from well head to bottom *** measured parameters and independent variables of flow rates,flowing pressures and temperatures are involved in CBM producing process along the *** developed relationships are validated against full-scale measured data in single-phase CBM *** proposed methodology can analyze the dynamic behavior in CBM reservoir and process of CBM flow with an overall accuracy of 2%.The calculating process of flowing pressures involves friction factor with variable Reynolds number and CBM temperature and compressibility factor with gravitational *** results showed that the effect of flowing pressure on CBM column was more obvious than that on CBM and water column accompanied by an increase of dynamic water *** ratios of flowing pressure on increment of CBM column to the whole column increased with the declined flow rates of water ***-hole pressure declined with the decreased flowing pressure of CBM column along the *** will lead to the results of the increased pressure drop of CBM column and CBM flow rate in single-phase CBM wellbores.

关键词： Dynamic characteristic Single-phase CBM wellbore Flowing pressure of CBM column Flow rate of CBM column

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Resilient Exponential Consensus with Time-Varying Adversary Attacks and Asynchronous Events

Resilient Exponential Consensus with Time-Varying Adversary ...

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IEEE Annual Conference on Decision and control

作者： Weiguo Xia Ji Liu Shuang Li Xi-Ming Sun Min Han Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and the School of Control Science and Engineering Dalian University of Technology China Department of Electrical and Computer Engineering Stony Brook University USA

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

This paper studies the resilient consensus problem with time-varying adversary attacks and asynchronous events. In the synchronous or asynchronous update case, all the nodes or only a fraction of nodes update their states at each time step, respectively. For the synchronous update case, the nodes under attack are time-varying but do not change after some finite time;for the asynchronous update case, the nodes under attack are time-invariant. For both cases, a resilient consensus can be reached exponentially fast under a network topology condition inspired by the notion of the scrambling matrix and an explicit expression for the convergence rate is provided. Numerical examples are given to validate the theoretical results and to compare the performance with an existing algorithm.

关键词： Optimization Convergence Heuristic algorithms Distributed algorithms Sun Network topology Estimation

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A Pricing Strategy for D2D Communication from a Prospect Theory Perspective

A Pricing Strategy for D2D Communication from a Prospect The...

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IEEE Conference on Vehicular Technology (VTC)

作者： Yichao Chen Shibo He Fen Hou State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China Department of Electrical and Computer Engineering University of Macau Macau China

Device-to-device (D2D) communication is efficient in traffic offloading in terms of transmission rate, energy cost, spectrum usage and etc. However, its unstable performance caused by spectrum reuse can drive users away, particularly when D2D users (DUs) are served as secondary users in cellular networks. Their low expectations on D2D services and frequent mode switch can block efficient D2D offloading, cause severe network congestion and result in poor quality of experience (QoE), especially in densely populated area. Hence, in this study, more than reducing the price to attract users, we propose a quality of service (QoS)- insured pricing strategy to promote D2D communication. In specific, to model users' decision-making process under the uncertainty of D2D performance, we introduce Prospect theory (PT) that captures irrational factors such as reference point, probability distortion and risk-aversion. Then, we design an insurance contract with terms of service price and insured QoS level to popularize D2D services and optimize operator's profit. Based on theoretical analysis, we propose an optimal QoS-insure pricing strategy algorithm, and discuss the practical implementation of the proposed strategy. The simulation results demonstrate the impacts of operation settings, individual irrationality and network conditions on operator's net profit from D2D offloading, and show the efficiency of the proposed strategy.

关键词： Device-to-device communication Quality of service Pricing Quality of experience Insurance Uncertainty Interference

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Pose Analysis of Humanoid Robot Imitation Process Based on Improved MLP Network

Pose Analysis of Humanoid Robot Imitation Process Based on I...

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WRC Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Shuhuan Wen Yang Liu Leibo Zheng Fuchun Sun Bin Fang Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China Dept. of Computer Science and Technology Tsinghua University Beijing China

This paper proposes a system, by which humanoid robots could imitate human movements to learn human behaviors. Considering the security problem during humanoid robot imitation process, a method of stability identification based on improved Multi-Layer Perception (MLP) is proposed. Firstly, the positions of the human joints are collected by a Kinect. Secondly, the human joints information is transformed into robot angles information by the inverse kinematics equation. Finally, the stability of the robot is identified by the deep neural network, which has the robot angles as its input. Simulations and experimental results demonstrate that compared with the Back Propagation neural network (BPnn), RBF neural network (RBFnn), Support Vector Machine (SVM) and Extreme Learning Machine (ELM), MLP neural network has the best identification accuracy. And the filters we used can overcome the problem of speed pulse, to some extent, and achieved an ideal imitation result.

关键词： Neural networks Humanoid robots Robot kinematics Stability analysis Torso Shoulder

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DPNet: Dynamic Pooling Network for Accurate and Efficient Size-Aware Tiny Object Detection

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IEEE Internet of Things Journal 2025年

作者： Gong, Luqi Chen, Haotian Chen, Yikun Yao, Tianliang Li, Chao Zhao, Shuai Han, Guangjie Beijing University of Posts and Telecommunications School of Computer Science Beijing China Zhejiang Lab Research Center for Space Computing System Hangzhou China Southwest Jiaotong University SWJTU-LEEDS Joint School Chengdu China LTD Guangdong Zhiyun City construction Technology Co Zhuhai China Tongji University College of Electronic and Information Engineering Department of Control Science and Engineering Shanghai China Hohai University Key Laboratory of Maritime Intelligent Network Information Technology Ministry of Education China

In unmanned aerial systems, especially in complex environments, accurately detecting tiny objects is crucial. Resizing images is a common strategy to improve detection accuracy, particularly for small objects. However, simply enlarging images significantly increases computational costs and the number of negative samples, severely degrading detection performance and limiting its applicability. This paper proposes a Dynamic Pooling Network (DPNet) for tiny object detection to mitigate these issues. DPNet employs a flexible down-sampling strategy by introducing a factor (df) to relax the fixed down-sampling process of the feature map to an adjustable one. Furthermore, we design a lightweight predictor to predict df for each input image, which will be used to decrease the resolution of feature map in backbone. Thus, we achieve input-aware down-sampling. We design an Adaptive Normalization Module (ANM) to make a unified detector well compatible with different dfs. At the same time, we also design a guidance loss to supervise the predictor’s training. DPNet realizes the dynamic allocation of computing resources to trade off detection accuracy and efficiency through this. Experiments on the TinyCOCO and TinyPerson datasets show that our DPNet can save over 35% and 25% GFLOPs, respectively, while maintaining comparable detection *** code will be made publicly available. © 2014 IEEE.

关键词： Object detection

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DPNet: Dynamic Pooling Network for Tiny Object Detection

arXiv

引用

arXiv 2025年

作者： Gong, Luqi Chen, Haotian Chen, Yikun Yao, Tianliang Li, Chao Zhao, Shuai Han, Guangjie School of Computer Science Beijing University of Posts and Telecommunications Beijing China Research Center for Space Computing System Zhejiang Lab Hangzhou China SWJTU-LEEDS Joint School Southwest Jiaotong University Chengdu China Guangdong Zhiyun City construction Technology Co. LTD Zhuhai China Department of Control Science and Engineering College of Electronic and Information Engineering Tongji University Shanghai China Key Laboratory of Maritime Intelligent Network Information Technology Ministry of Education Hohai University China

In unmanned aerial systems, especially in complex environments, accurately detecting tiny objects is crucial. Resizing images is a common strategy to improve detection accuracy, particularly for small objects. However, simply enlarging images significantly increases computational costs and the number of negative samples, severely degrading detection performance and limiting its applicability. This paper proposes a Dynamic Pooling Network (DPNet) for tiny object detection to mitigate these issues. DPNet employs a flexible down-sampling strategy by introducing a factor (df) to relax the fixed downsampling process of the feature map to an adjustable one. Furthermore, we design a lightweight predictor to predict df for each input image, which will be used to decrease the resolution of feature map in backbone. Thus, we achieve input-aware downsampling. We design an Adaptive Normalization Module (ANM) to make a unified detector well compatible with different dfs. At the same time, we also design a guidance loss to supervise the predictor’s training. DPNet realizes the dynamic allocation of computing resources to trade off detection accuracy and efficiency through this. Experiments on the TinyCOCO and TinyPerson datasets show that our DPNet can save over 35% and 25% GFLOPs, respectively, while maintaining comparable detection *** code will be made publicly available. Copyright © 2025, The Authors. All rights reserved.

关键词： Image coding

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