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TechRxiv 2022年

作者： Liu, Xin Zhang, Dawei Li, Yingsong Huang, Zhixiang College of Information and Communication Engineering Harbin Engineering University Harbin150001 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230601 China Anhui Province Key Laboratory of Target Recognition and Feature Extraction Lu'An230088 China

In this paper, a super-broadband (SBB) rectifier using a wideband resistance compression network (WRCN) and harmonic cycling is proposed, simulated, fabricated, measured and analyzed in detail for the harvesting of ambient Radio frequency (RF) energy. Meanwhile, impedance compression and matching are achieved to implement the SBB using WRCN and impedance operation networks. Additionally, harmonic cycling structure and bending technology are employed to improve the power conversion efficiency (PCE) and reduce the size, respectively. For demonstration, a prototype of the proposed rectifier is fabricated and measured. The measured results are in good accordance with the simulated ones, indicating that the rectifier can provide high efficiency and ultra-broadband rectification characteristics. A PCE over 50% is realized at 3.5 GHz with an input power range of 6–24 dBm, and a PCE of 75% is obtained at an input power of 18 dBm. The PCE is greater than 50% at 17 dBm with an input frequency of 2.7–4.6 GHz. This work can find significant applications in the development of RF-harvesting. © 2022, CC BY.

关键词： Harvesting

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The Frequency-Time Pre-Allocation in Unlicensed Spectrum Based on the Games Learning

The Frequency-Time Pre-Allocation in Unlicensed Spectrum Bas...

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International Conference on Cognitive Radio Oriented Wireless Networks and communications

作者： Kun Han Jinlong Li Ping Zhu Xufa Wang Anhui Province Key Laboratory of Software in Computing and Communication Department of Computer Science and Technology University of Science and Technology Hefei China Department of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (纸本)9781424408146;1424408156

In the wireless network of finite spectrum resource, some communication users probably do not allocate the spectrum so that their communication should be delayed. Thus it is necessary to arrange the communication time of the systems when we allocate the communication frequency. We construct a frequency-time spectrum model and propose a joint pre-allocation in a two-dimension space. Through the distributed games learning algorithm, each system could obtain its communication schedule, which makes the bandwidth utilization achieve a quite high level and arranges the global communication time as short as possible. The experiments show that our results have obvious superiorities in both bandwidth utilization and temporal performance relative to other allocation algorithms.

关键词： Frequency Radio spectrum management Resource management Wireless networks Bandwidth Delay Laboratories Computer networks Computer science Scheduling algorithm

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A Novel Method for Semantic Segmentation on Lidar Point Clouds 19th

A Novel Method for Semantic Segmentation on Lidar Point Clou...

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19th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2023

作者： Wang, Fei Wan, Liangtian Zhu, Yan Sun, Lu Zhao, Xiaowei Zheng, Jianbo Wang, Xianpeng Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province School of Software Dalian University of Technology Dalian116620 China Artificial Intelligence Research Institute Shenzhen MSU-BIT University Guangdong Shenzhen518172 China Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing Shenzhen MSU-BIT University Guangdong Shenzhen518172 China Department of Communication Engineering Institute of Information Science Technology Dalian Maritime University Dalian116026 China School of Information and Communication Engineering Hainan University Haikou570228 China

ISBN: (纸本)9783031651250

Autonomous driving relies on multiple sensors, such as lidar and cameras, to perceive the surrounding environment and the vehicle’s own position. Among them, lidar point cloud segmentation is a crucial and challenging task for 3D scene understanding. In this paper, we propose a novel deep learning method RPNet for lidar point cloud segmentation that combines range image-based segmentation and point based segmentation. Our method extracts point cloud features from range images and predicts 3D point cloud labels from point clouds. The segmentation results of both branches are fused to improve accuracy. We evaluate our method on the Semantic KITTI dataset and show that it outperforms other fusion algorithms in terms of effectiveness and robustness. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Semantic Segmentation

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A CPK-Based Identity Authentication Scheme for IoT

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Computer Systems Science & engineering 2022年第3期40卷 1217-1231页

作者： Mingming Zhang Jiaming Mao Yuanyuan Ma Liangjie Xu Chuanjun Wang Ran Zhao Zhihao Li Lu Chen Wenbing Zhao State Grid Jiangsu Electric Power Co. Ltd.Information&Telecommunication BranchNanjing210008China State Grid Key Laboratory of Information&Network Security Institute of Information and CommunicationGlobal Energy Interconnection Research InstituteNanjing210003China Anhui Jiyuan Software Co.Ltd SGITGHefei230088China Engineering Research Center of Post Big Data Technology and Application of Jiangsu Province Research and Development Center of Post Industry Technology of the State Posts Bureau(Internet of Things Technology)Engineering Research Center of Broadband Wireless Communication Technology of the Ministry of EducationNanjing University of Posts and TelecommunicationsNanjing210003China Department of Electrical Engineering and Computer Science Cleveland State UniversityCleveland44115USA

As the power Internet of Things(IoT)enters the security construction stage,the massive use of perception layer devices urgently requires an identity authentication scheme that considers both security and *** existing public key infrastructure(PKI)-based security authentication scheme is currently difficult to apply in many terminals in *** key distribution and management costs are high,which hinders the development of power IoT security *** Public key(CPK)technology uses a small number of seeds to generate unlimited public *** is very suitable for identity authentication in the power Internet of *** this paper,we propose a novel identity authentication scheme for power *** scheme combines the physical unclonable function(PUF)with improved CPK technology to achieve mutual identity authentication between power IoT terminals and *** proposed scheme does not require third-party authentication and improves the security of identity authentication for power ***,the scheme reduces the resource consumption of power IoT *** improved CPK algorithm solves the key collision problem,and the third party only needs to save the private key and the public key *** results show that the amount of storage resources occupied in our scheme is *** proposed scheme is more suitable for the power IoT.

关键词： Power Internet of Things terminal equipment identity authentication CPK PUF

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A low-cost pedestrian-detection system with a single optical camera

A low-cost pedestrian-detection system with a single optical...

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作者： Cao, Xian-Bin Qiao, Hong Keane, John IEEE Department of Computer Science and Technology University of Science and Technology of China Hefei 230026 China Anhui Province Key Laboratory of Software in Computing and Communication Hefei 230026 China Laboratory of Complex Systems and Intelligent Science Institute of Automation Chinese Academy of Sciences Beijing 100080 China School of Informatics University of Manchester M60 1QD Manchester United Kingdom University of Manchester M13 9PL Manchester United Kingdom

The ultimate purpose of a pedestrian-detection system (PDS) is to reduce pedestrian-vehicle-related injury. Most such systems tend to adopt expensive sensors, such as infrared devices, in expectation of better performance. In comparison, a low-cost optical-camera-based system has much potential practical value, including a greater detection range, and can easily be trained to detect other objects. However, such low-cost systems are difficult to design (e.g., little original information can be collected, and the scene is very complex). To address these problems, an effective and reliable classifier is needed. The classifier should have a proper structure, its features need to be well selected, and a large number of high-quality samples are necessary for training. In this paper, we present a low-cost PDS which only uses a single optical camera. We design a cascade classifier to achieve an effective and reliable detection. First, our system scans two sequential frames at each zoom scale with a sliding window. Second, with each window, both appearance and motion features are extracted. A well-trained cascade classifier, combining statistical learning with a decomposed support-vector-machine classifier, then determines whether the window contains a human body. At the same time, to provide as much information as possible about the pedestrian, a small-scale weighted template tree trained by a coevolutionary algorithm is adopted to identify each pedestrian's direction, and the distance of each from the vehicle is also provided using an estimation algorithm. During the training procedure, we select key features by using the AdaBoost algorithm and a large number of high-quality samples. Experimental results demonstrate that the system is suitable for pedestrian detection in city traffic: The detection speed is more than 10 ft/s, the detection rate reaches 80%, and the false positive rate is no more than 0.3‰. © 2008 IEEE.

关键词： Pedestrian safety

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Investigation on ULA Fitting Promoting Low Coupling Sparse Arrays

Investigation on ULA Fitting Promoting Low Coupling Sparse A...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Yichang Yao Wanlu Shi Yingsong Li Zhixiang Huang Guohui Yang Kuang Zhang College of Information and Communication Engineering Harbin Engineering University Harbin China Anhui Province Key Laboratory of Target Recognition and Feature Extraction LuAn China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

A low coupling sparse array (LCSA) is presented, analyzed and discussed on the basis of the recent proposed uniform linear array (ULA) fitting scheme with close-expressions, and its performance with different uniform subarrays in the basic layer is investigated via parameter estimation like direction-of-arrival(DOA). The results gives a superior performance for the presented LCSA.

关键词： Couplings Mutual coupling Direction-of-arrival estimation Fitting Estimation Computational electromagnetics

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Bias analyses of spontaneous facial expression database

Bias analyses of spontaneous facial expression database

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International Conference on Pattern Recognition

作者： Zhaoyu Wang Shangfei Wang Yachen Zhu Qiang Ji Key Laboratory of Computing and Communicating Software of Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui China Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY USA

ISBN: (纸本)9781467322164

In this paper, cross-corpora evaluations are used to analyze the bias of spontaneous facial expression databases. Local binary pattern, Gabor, eigenface and fisherface features are extracted and applied to the four spontaneous expression databases: USTC-NVIE, VAM, Belfast Naturalistic and SEMAINE to recognize arousal (high/low) and valance (positive/negative) respectively. Experimental results indicate that there exists bias among different spontaneous expression databases. The emotion-induction methods, the variety of subjects and the quantity of raters may have caused such a bias.

关键词： Databases Feature extraction Face recognition Videos Principal component analysis Training

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Scheduling Aircraft Landing Based on Clonal Selection Algorithm and Receding Horizon Control

Scheduling Aircraft Landing Based on Clonal Selection Algori...

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International Conference on Intelligent Transportation

作者： Xiaolan Jia Xianbin Cao Yuanping Guo Hong Qiao Jun Zhang Province Key Laboratory of Software Computing and Communication University of Science and Technology Hefei Anhui China University of Manchester Institute of Science and Technology UK Institute of Automation Chinese Academy and Sciences Beijing China School of Electronic and Information Engineering Beihang University Beijing China

The task of aircraft landing scheduling (ALS) is to give a landing sequence and landing times for a given set of aircrafts where many constraints must be satisfied. ALS is an NP-hard problem with large-scale and multi-constraint characteristics, thus it is hard to find optimal solution efficiently. In this paper, a hybrid algorithm of Clonal Selection Algorithm (CSA) and Receding Horizon Control (RHC) was proposed for ALS problem. In details, constrained CSA based on infeasibility degree (IFD) schedules aircrafts in current receding horizon, and then RHC repeats that optimization procedure using excellent gene segment spread (EGSS) until all aircrafts have landed. Comparative experiments show that the CSA-RHC hybrid algorithm is able to obtain an optimal landing sequence and landing times rapidly and effectively.

关键词： Aircraft Aerospace control Scheduling algorithm Air traffic control Processor scheduling Computational intelligence Sequences Intelligent transportation systems Linear programming Constraint optimization

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Accelerating Vehicle Detection in Low-Altitude Airborne Urban Video

Accelerating Vehicle Detection in Low-Altitude Airborne Urba...

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International Conference on Image and Graphics (ICIG)

作者： Xianbin Cao Renjun Lin Pingkun Yan Xuelong Li Anhui Province Key Laboratory of Software in Computing and Communication School of Computer Science and Technology University of Science and Technology Hefei Anhui China Center of OPTical IMagery Analysis and Learning (OPTIMAL) State Key Laboratory of Transient Optics and Photonics Xi'an Institute of Optics and Precision Mechanics Chinese Academy and Sciences Xi'an Shaanxi China

The limitation of the existing methods of traffic data collection is that they rely on techniques that are strictly local in nature. The airborne system in unmanned aircrafts provides the advantages of wider view angle and higher mobility. However, detecting vehicles in airborne videos is a challenging task because of the scene complexity and platform movement. Most of the techniques used in stationary platforms cannot perform well in this situation. A new and efficient method based on Bayes model is proposed in this paper. This method can be divided into two stages, attention focus extraction and vehicle classification. Experimental results demonstrated that, compared with other representative algorithms, our method obtained better performance with higher detection rate, lower false positive rate and faster detection speed.

关键词： Vehicles Feature extraction Vehicle detection Road transportation Cameras Atmospheric modeling Classification algorithms

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KLT Feature Based Vehicle Detection and Tracking in Airborne Videos

KLT Feature Based Vehicle Detection and Tracking in Airborne...

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International Conference on Image and Graphics (ICIG)

作者： Xianbin Cao Jinhe Lan Pingkun Yan Xuelong Li Anhui Province Key Laboratory of Software in Computing and Communication School of Computer Science and Technology University of Science and Technology Hefei Anhui China Center of OPTical IMagery Analysis and Learning (OPTIMAL) State Key Laboratory of Transient Optics and Photonics Xi'an Institute of Optics and Precision Mechanics Chinese Academy and Sciences Xi'an Shaanxi China

Airborne vehicle detection and tracking systems equipped on unmanned aerial vehicles (UAVs) are difficult to develop because of factors like UAV motion, scene complexity and so on. In this paper, we propose a new framework of multi-motion layer analysis to detect and track moving vehicles in airborne platform. Moving vehicles are firstly detected by registration and temporal differencing to establish motion layers. After motion layers are constructed, they are maintained over time for tracking vehicles. All vehicles are tracked by maintaining their corresponding motion layers. Our experimental results showed that compared with other previous algorithms, our method can achieve better results in terms of detection and tracking performance.

关键词： Vehicles Tracking Videos Feature extraction Vehicle detection Maintenance engineering Motion segmentation

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