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13th International Symposium on Antennas, Propagation and EM Theory, ISAPE 2021

作者： Zhang, Fan Xu, Lili Zhang, Jianqiang Nan, Pulong Jin, Xiaofan Pan, Gaofeng Science and Technology on Communication Information Security Control Laboratory Zhejiang Jiaxing314033 China Huawei Technologies Co. Ltd Guangdong Shenzhen518063 China

ISBN: (纸本)9781665418126

A Ka-band quasi-elliptic bandpass filter (BPF) based on stereolithography apparatus (SLA) 3-D printing technique is proposed. The filter consists of four coupled resonators with three direct couplings between adjacent resonators and a cross coupling between the first and fourth resonators. Benefited from this feature, a pair of transmission zeros (TZs) can be produced in the stopband to enhance the passband selectivity significantly. Additionally, two waveguide bends are incorporated with the input and output waveguides to facilitate experimental test. For demonstration, a 3-D printed BPF prototype with center frequency of 30 GHz, bandwidth of 1.4 GHz, and return loss better than 20 dB is implemented and tested. The weight of the filter is 9.8 g only. The measured results demonstrate that the passband return loss is better than 10 dB, and the average in-band insertion loss is less than 2 dB. © 2021 IEEE.

关键词： Bandpass filters

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Tunable Cascaded Trisection Bandpass Filter with Constant Absolute Bandwidth 13

Tunable Cascaded Trisection Bandpass Filter with Constant Ab...

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13th International Conference on Microwave and Millimeter Wave technology, ICMMT 2021

作者： Yang, JingJing Xiang, Qianyin Jia, Dinghong Huang, Xiaoguo Feng, Quanyuan Southwest Jiaotong University School Of Information Science And Technology Chengdu611756 China He 41st Institute Of CETC Qingdao266555 China Science And Technology On Communication Information Security Control Laboratory Jiaxing314033 China

ISBN: (纸本)9781665434379

A novel cascade trisection (CT) coupling structure based on half-wavelength resonators is proposed for designing constant absolute bandwidth (CABW) tunable bandpass filters. Third-order tunable bandpass filter (BPF) which can realize CABW and a high side cross coupling transmission zero (Tz) is designed based on the proposed CT structure. Measurement results show that the central frequency tuning range of desinged filter is from 1.47 GHz to 1.83 GHz with -3dB bandwidth of 108.75±2.05 MHz, and the high side 3dB to 25dB attenuation slope is 327.32623.57 dB/GHz. © 2021 IEEE.

关键词： Bandwidth

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Defend Against Jamming Attacks Using Deep Reinforcement Learning 13

Defend Against Jamming Attacks Using Deep Reinforcement Lear...

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13th International Symposium on Antennas, Propagation and EM Theory, ISAPE 2021

作者： Shen, Weiguo Wang, Wei Jin, Hu Zhang, Weifeng Science and Technology on Communication Information Security Control Laboratory China National University of Defense Technology China Jiaxing University China Jiaxing Deep Intelligence Technology Co. Ltd China

ISBN: (纸本)9781665418126

Cognitive radio network has the learning ability to adjust transmission behavior to adapt to dynamic electromagnetic environment, and it has become a research hotspot in the field of the new generation of intelligent wireless communication systems. However, recent research results show that cognitive radio networks are vulnerable to interference attacks, resulting in a serious decline in spectrum utilization. In this paper, an intelligent anti-jamming scheme based on deep reinforcement learning is proposed, and the anti-jamming decision of the communication party is modeled as a Markov decision chain. This method can help the communication transmitter to learn a combination of communication parameters that can maximize the probability of communication success. In the specific implementation, we use Double DQN as the communication decision-making brain, and specially designed a convolutional neural network suitable for the communication spectrum as input to accurately estimate the action value function. The simulation results show that our method has better performance than the traditional anti-jamming method based on reinforcement learning. © 2021 IEEE.

关键词： Reinforcement learning

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TSGN: Transaction Subgraph Networks Assisting Phishing Detection in Ethereum

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IEEE Transactions on Dependable and Secure Computing 2025年

作者： Wang, Jinhuan Chen, Pengtao Xu, Xinyao Wu, Jiajing Shen, Meng Xuan, Qi Yang, Xiaoniu Zhejiang University of Technology Institute of Cyberspace Security College of Information Engineering Hangzhou310023 China ZJUT Binjiang Institute of Artificial Intelligence Hangzhou310056 China Fudan University Adaptive Networks and Control Lab Department of Electronic Engineering School of Information Science and Technology Shanghai200433 China Sun Yat-sen University School of Computer Science and Engineering Guangzhou510006 China Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100081 China Shenzhen518066 China National Key Laboratory of Electromagnetic Space Security Jiaxing314033 China

Due to the decentralized and public nature of the blockchain ecosystem, malicious activities on the Ethereum platform impose immeasurable losses on users. At the same time, the transparency of cryptocurrency transactions provides a unique opportunity to analyze illegal activities, such as phishing scams, from a network perspective. Most existing phishing scam detection methods focus primarily on analyzing account interaction networks, which limits their ability to uncover transaction behavior patterns embedded within transaction interactions. To address this, we construct the Transaction SubGraph Network (TSGN) by using transaction subgraphs as basic elements and further propose a novel framework for Ethereum phishing account detection. Specifically, we rebuild the graph structures via three well-designed mapping mechanisms, yielding TSGN and its two variants, i.e., Directed-TSGN and Temporal-TSGN, to obtain direction-aware and time-aware transfer flow features. By further incorporating the mapping strategy into transaction multidigraphs, we develop the Multiple-TSGN, which could preserve more transaction flow features while concurrently reducing the time consumption of modeling large-scale networks. TSGN models based on transaction subgraph interactions can capture complex higher-order dependencies, which lay beyond the reach of models that exclusively capture pairwise account interactions. As a general framework, our model can incorporate various feature extraction methods to improve the performance of phishing detection. Extensive experimental results on Ethereum datasets show that our method achieves superior performance in phishing detection, yielding 3.27%∼6.71% relative improvement over previous state-of-the-art. © 2004-2012 IEEE.

关键词： Phishing

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Task Offloading and Primary Node Selection in Blockchain, Digital Twin, and MEC Enabled Internet of Vehicles 100

Task Offloading and Primary Node Selection in Blockchain, Di...

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100th IEEE Vehicular technology Conference, VTC 2024-Fall

作者： Du, Jianbo Fang, Huifang Li, Shulei Du, Pengfei Kong, Ziwen Kang, Jiawen Niyato, Dusit Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security School of Communications and Information Engineering Xi'an China Xidian University School of Communications Engineering Xi'an710071 China Tianyuan Ruixin Communication Technology Co. LTD. Xi'an710071 China Xihua University Engineering Research Center of Intelligent Airground Integrated Vehicle and Traffic Control Ministry of Education Chengdu610039 China Guangdong University of Technology School of Automation China Nanyang Technological University School of Computer Science and Engineering Singapore

ISBN: (纸本)9798331517786

In this paper, we investigate the safe task offloading and primary node selection in blockchain, digital twin (DT) and Multi-access Edge Computing (MEC) enabled Internet of Vehicles (IoV). Edge servers centers provide computing power for task processing for Mobile Vehicles (MVs), while blockchain can provide security guarantees for MVs during task offloading. Based on the above system, we propose a joint optimization scheme for vehicle task offloading decision and the Practical Byzantine Fault Tolerance (PBFT) consensus process. Due to the large number of optimization variables and constraints, the problem becomes more complex. Traditional convex optimization and dynamic programming methods are difficult to effectively solve this problem. To address this issue, we propose a deep reinforcement learning based algorithm that utilizes Proximal Policy Optimization (PPO). The experimental results show that the algorithm proposed in this paper outperforms the benchmark algorithm in terms of convergence and other aspects. © 2024 IEEE.

关键词： Dynamic programming

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Multi-view infrared small target recognition based on YOLOv5

Multi-view infrared small target recognition based on YOLOv5

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Chinese Automation Congress (CAC)

作者： Hua Gong Shasha Liu Song Guan Kuaikuai Yu Fang Liu College of Science Shengyang Ligong University Shenyang China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjing China

In order to improve the recognition accuracy of small infrared targets in complex environment, a SyluInfrared dataset is built by taking multi-view infrared images with the Frock TiX600 infrared thermal imager. Seven image enhancement algorithms including image brightening, contrast adjustment, image blurring, image flipping and image scaling are designed to improve the image quality of small infrared targets. The YOLOv5 deep learning model is used to identify small infrared targets with multiple views to improve the recognition accuracy of small infrared targets. The experimental results show that the accuracy of multi-view infrared small target recognition model for YOLOv5 deep network is 97.7%, which is 6.6% higher than that of single-view infrared small target recognition model based on YOLOv5. The multi-view target recognition strategy significantly improves the infrared small target recognition performance.

关键词： Image quality Deep learning Image recognition Automation Target recognition Object detection Data models

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Infrared Target Detection Based on the Fusion of Mask R-CNN and Image Enhancement Network

Infrared Target Detection Based on the Fusion of Mask R-CNN ...

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Chinese Automation Congress (CAC)

作者： Fang Liu Song Guan Kuaikuai Yu Hua Gong College of Science Shengyang Ligong University Shenyang China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjing China

In this paper, we focus on the problem of the infrared image detection. Aiming at the problem of the low contrast of the infrared images, an adaptive gamma transformation algorithm (AGT) is established to intelligently improve the contrast of the infrared images. Aiming at the problem of the weak edge information of the infrared images, an improved Sobel operator edge enhancement algorithm (ISOEE) is designed to enrich the edge features of the infrared images. In order to solve the problem that the traditional infrared image detection algorithm relies on expert experience, the fusion infrared images detection model AIE-Mask R-CNN based on Mask R-CNN, AGT algorithm and ISOEE algorithm is proposed. This fusion model can realize accurate and intelligent detection for the infrared images. The experimental results show that the fusion model AIE-Mask R-CNN improves the detection accuracy of the infrared images.

关键词： Adaptation models Automation Image edge detection Object detection Detection algorithms Image enhancement

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Automatic Detection of Morse with Wideband Receiver 21

Automatic Detection of Morse with Wideband Receiver

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21st IEEE International Conference on Communication technology, ICCT 2021

作者： Cheng, Hui Wang, Feng Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China The 36th Research Institute of China Electronics Technology Group Corporation Jiaxing314033 China

ISBN: (纸本)9781665432061

Morse communication is widely used in the field of land, water and air transportation and military communication, and especially plays a great role in military communication as a necessary means. Morse signals have noise interference inevitably in the process of HF channel transmission. Because of the noise has greatly harmed to human body, it increases the Labor intensity of copy personnel, especially for that long time engaged in HF Morse copy work. To solve the problem that receiving of Morse signals requires manual operation, this paper presents a solution to automatically detect Morse signals with a wideband receiver. The solution features equipment miniaturization, enables Morse signals to be received in full frequency and time domain and gets rid of manual work. It also allows real-time access to the situation of HF Morse signals. © 2021 IEEE.

关键词： Air transportation

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A USRP-Based Testbed for Dual Mode Passive Radar 21

A USRP-Based Testbed for Dual Mode Passive Radar

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21st IEEE International Conference on Communication technology, ICCT 2021

作者： Zhu, Huijie Zhang, Lan Wang, Yiteng Shen, Libo Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China The 36th Research Institute of China Electronics Technology Group Corporation Jiaxing314033 China

ISBN: (纸本)9781665432061

This paper presents a dual mode passive radar with alternative localization mechanisms of time difference of arrival (TDOA)-direction of arrival (DOA) mode and multi-TDOA mode. For demonstration and validation, a high-performance testbed is needed with the characteristics of wide dynamic range, multichannel, time-frequency synchronization and flexible local oscillator mechanism. To realize these features, an Ettus X310 universal software radio peripheral (USRP) is utilized for integration in the passive radar hardware platform. Processing algorithms for the multi-channel signals acquired by the X310 is implemented in real-time with the graphics processing unit (GPU) embedded in a server computer. Outdoor detections of small unmanned aerial vehicle with the dual mode operation of the testbed show a meter-level accuracy. © 2021 IEEE.

关键词： Graphics processing unit

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The Multi-Dimensional Scaling Algorithm with Centroid as Reference Point for Location in Wireless Senso Network 21

The Multi-Dimensional Scaling Algorithm with Centroid as Ref...

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21st IEEE International Conference on Communication technology, ICCT 2021

作者： Bin, Jiang An'Nan, Lu Mingyi, You Yunxia, Ye Kai, Huang Binhua, Shi Science and Technology on Communication Information Security Control Laboratory Zhejiang Jiaxing China The 36th Research Institute of China Electronics Technology Group Corporation Zhejiang Jiaxing China

ISBN: (纸本)9781665432061

The multi-dimensional scaling(MDS) method is a kind of method used to analyze distance matrix or dissimilarity matrix to form data points in low-dimensional space. MDS algorithm uses the distance information between nodes in wireless sensor networks to estimate the relative location of nodes. Classical multi-dimensional scaling algorithm chooses any node in the network as reference point to estimate node location. With the increase of distance measurement error, the node position error estimated by this method also increases significantly. In order to improve the location performance, this paper proposes an MDS algorithm based on the centroid of all nodes in the network as a reference point, and derives the calculation formula of MDS algorithm based on centroid as reference point. Compared with the classical MDS algorithm, the simulation results show that the MDS algorithm base on centroid as the reference point has better positioning results. © 2021 IEEE.

关键词： Location

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