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arXiv 2021年

作者： Zhang, Hao Zhou, Fuhui Wu, Qihui Wu, Wei Hu, Rose Qingyang College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Nanjing University of Aeronautics and Astronautics Ministry of Industry and Information Technology Nanjing211106 China The Nanjing University of Posts and Telecommunications Nanjing210003 China The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China The Department of Electrical and Computer Engineering Utah State University LoganUT84322 United States

Automatic modulation classification enables intelligent communications and it is of crucial importance in today's and future wireless communication networks. Although many automatic modulation classification schemes have been proposed, they cannot tackle the intra-class diversity problem caused by the dynamic changes of the wireless communication environment. In order to overcome this problem, inspired by face recognition, a novel automatic modulation classification scheme is proposed by using the multi-scale network in this paper. Moreover, a novel loss function that combines the center loss and the cross entropy loss is exploited to learn both discriminative and separable features in order to further improve the classification performance. Extensive simulation results demonstrate that our proposed automatic modulation classification scheme can achieve better performance than the benchmark schemes in terms of the classification accuracy. The influence of the network parameters and the loss function with the two-stage training strategy on the classification accuracy of our proposed scheme are investigated. © 2021, CC BY.

关键词： Face recognition

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Integrated Response to Boost Distribution system Resilience Against Windstorms

Integrated Response to Boost Distribution System Resilience ...

引用

2019 IEEE Sustainable Power and Energy Conference, iSPEC 2019

作者： Wang, Gang Liu, Zhaoxi Wang, Lingfeng Hu, Bo Xie, Kaigui Yan, Jiahao Chongqing University State Key Laboratory of Power Transmission Equipment and System Security College of Electrical Engineering Chongqing400044 China University of Wisconsin-Milwaukee Department of Electrical Engineering and Computer Science MilwaukeeWI53211 United States

ISBN: (纸本)9781728149301

Improving distribution system resilience is one of the urgent tasks for the modern society. This paper proposes a novel integrated preventive and emergency response model for system operators to boost the distribution system resilience considering all possible component damage statuses. Topology reconfiguration and generation redispatch are allowed in both the preventive response (PR) and emergency response (ER), while load curtailment is only deployed in the ER. A two-stage stochastic mixed-integer optimization model is developed for the integrated optimization problem, which is solved by the progressive hedging (PH) algorithm. Case studies on the IEEE 33-bus system and a 69-bus distribution system validate the correctness and effectiveness of the proposed model. Sensitivity analysis is also carried out to evaluate the influence of the weather severity and generator availability. The key conclusions of this paper include the following: 1) integrated response (IR) improves distribution system resilience with the minimum expected cost;and 2) integrated response is preferable comparing with the individual PR or ER. © 2019 IEEE.

关键词： Sensitivity analysis

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Energy Management and Trajectory Optimization for UAV-Enabled Legitimate Monitoring systems

arXiv

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arXiv 2020年

作者： Hu, Shuyan Wu, Qingqing Wang, Xin State Key Laboratory of ASIC and System School of Information Science and Technology Fudan University Shanghai200433 China Department of Electrical and Computer Engineering National University of Singapore Singapore119077 Singapore State Key Laboratory of ASIC and System Shanghai Institute for Advanced Communication and Data Science Department of Communication Science and Engineering Fudan University Shanghai200433 China

Thanks to their quick placement and high flexibility, unmanned aerial vehicles (UAVs) can be very useful in the current and future wireless communication systems. With a growing number of smart devices and infrastructure-free communication networks, it is necessary to legitimately monitor these networks to prevent crimes. In this paper, a novel framework is proposed to exploit the flexibility of the UAV for legitimate monitoring via joint trajectory design and energy management. The system includes a suspicious transmission link with a terrestrial transmitter and a terrestrial receiver, and a UAV to monitor the suspicious link. The UAV can adjust its positions and send jamming signal to the suspicious receiver to ensure successful eavesdropping. Based on this model, we first develop an approach to minimize the overall jamming energy consumption of the UAV. Building on a judicious (re)formulation, an alternating optimization approach is developed to compute a locally optimal solution in polynomial time. Furthermore, we model and include the propulsion power to minimize the overall energy consumption of the UAV. Leveraging the successive convex approximation method, an effective iterative approach is developed to find a feasible solution fulfilling the Karush-Kuhn-Tucker (KKT) conditions. Extensive numerical results are provided to verify the merits of the proposed schemes. Copyright © 2020, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Formal analysis of QUIC handshake protocol using ProVerif

Formal analysis of QUIC handshake protocol using ProVerif

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IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)

作者： Jingjing Zhang Lin Yang Xianming Gao Qiang Wang College of Command and Control Engineering Army Engineering University of PLA Nanjing China National Key Laboratory of Science and Technology on Information System Security Chinese Academy of Military Science Beijing China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China

ISBN: (数字)9781728165509

ISBN: (纸本)9781728165516

This paper presents a formal analysis of the QUIC protocol. This newly proposed protocol is currently under the process of standardization, and it is still unknown whether the proposed protocol provides the claimed security guarantees. To fill this gap, we model the QUIC handshake protocol in the applied pi calculus and perform a comprehensive formal analysis using ProVerif. To the best of our knowledge, this is the first thorough study on the formal analysis of QUIC handshake protocol.

关键词： Security protocol QUIC Formal verification ProVerif formal analysis Formal verification Handshake Protocol pi calculus

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Improved Rotor Bar Structure in High-Voltage High-Power Induction Motors to Eliminate Local Thermal Spot and Avoid Broken Bar faults 12

Improved Rotor Bar Structure in High-Voltage High-Power Indu...

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12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020

作者： Zhao, Haisen Guo, Xinglan Dai, Xin Eldeeb, Hassan H. Zhan, Yang Xu, Guorui Kang, J. Mohammed, Osama North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing102206 China Yangzhong Jiangsu Province China Inner Mongolian Baotou Donghua Thermal Power Plant Baotou014000 China Florida International University Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9781728158266

Due to complex harmonic field effect and frequently starting operation conditions, broken bars are the most common fault in practice, for instance, in the auxiliary motor systems in the power plant. To solve this problem, this paper proposes an improved rotor slot structure of large-power and high-voltage induction motors in the re-manufacturing process, for eliminating the local thermal spot and avoiding broken bars. This structure adopts a novel harmonic field slot to eliminate the skin effect caused by high-frequency harmonic fields, and the optimal design of slot size, opening width, and height, air-gap length based on finite element analysis (FEA) are performed to verify its effectiveness. Experimental validation is performed on a re-manufactured 6-kV 1600-kW induction motor in a thermal power plant in China. The results show that the presented design structure can eliminate the local thermal spot in rotor side and the measured thermal distribution in the surface of stator cooler can also be reduced by 18°C. The achievement of this paper can provide the technical support for countermeasure of broken bar fault in large-power and high-voltage induction motors. © 2020 IEEE.

关键词： Finite element method

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The Design of the Intelligent Car Based on the Arduino UNO and Lab VIEW 5

The Design of the Intelligent Car Based on the Arduino UNO a...

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5th Annual International Conference on Network and Information systems for computers, ICNISC 2019

作者： Tang, Lili Huang, Wei You, Jie Department of Computer and Information Engineering Zhixing College of Hubei University Wuhan430011 China Fourth Laboratory System Design Institute of Hubei Aerospace Technology Academy Wuhan430011 China

The design of wireless remote control intelligent car uses PC-side LabVIEW host computer control software responsible for the interaction interface with the car, uses serial communication module APC220-43, one is connected to the PC to send commands from the host computer, the other is connected to the Arduino UNO to receive instructions from the host computer, and uses open source MCU controller Arduino UNO lower computer is responsible for receiving, parsing and executing instructions sent by LabVIEW. The upper computer and the lower computer carry out long-distance transmission of instructions through APC220-43 wireless serial communication module to realize the remote control of the car and the measurement of temperature, humidity and distance data. This design scheme provides certain reference value for the design fields of smart home, smart transportation, remote assistance, etc. © Published under licence by IOP Publishing Ltd.

关键词： Automation

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An Automated Feature engineering Method for Online Payment Fraud Detection

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Jisuanji Xuebao/Chinese Journal of computers 2020年第10期43卷 1983-2001页

作者： Wang, Cheng Wang, Chang-Qi Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai201804 China The Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai201804 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China

Internet finance fraud is an increasingly serious social and economic problem. Online payment services (OPSs) are the typical models of Internet finance, and the fraudulent transaction in OPSs is also a typical fraud pattern. The method of identifying fraudulent transactions by constructing a fraud detection model based on machine learning has become a promising idea for online payment anti-fraud. In the process of constructing fraud detection models, the feature engineering is the most critical step. It is also one of the most time-consuming and specialized steps in the relevant area. In the study of feature engineering, the existing online payment fraud detection models are mainly carried out by experts in the form of manual construction based on business knowledge. However, there are many fraud scenarios in OPSs where the process of feature construction is so different. Artificial feature construction methods can no longer meet the increasing demand of anti-fraud. An important way to solve this problem is to automate feature engineering. In the field of Internet financial anti-fraud, the expressibility and interpretability of features play a pivotal role. It is helpful to understand the original source fields and their construction process of important features. This is useful for mining and analyzing the characteristics of fraud methods and follow-up improvement rules engines. These are of great significance for fraud detection models. Therefore, the interpretability of the model method is particularly important. Usually, the optimization of detection accuracy is carried out under the premise of ensuring interpretability. This paper proposed a lightweight, tree-structure, high efficiency and scalable automatic feature engineering method for fraud detection of online payment. The method is as follows: (1) The method has low requirements on the calculation conditions and little dependence on the dataset samples. To realize this advantage, it used the tree structur

关键词： Feature extraction

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Univariate Forecasting of time series data Based on Seq2Seq Model 20

Univariate Forecasting of time series data Based on Seq2Seq ...

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Proceedings of the 2020 4th International Conference on Electronic Information Technology and computer engineering

作者： Yanwen Guo Tao Wu Yanbing Liu Yixin Jiang Department of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China School of Cybersecurity and Information Law Chongqing University of Posts and Telecommunications Chongqing China Chongqing Engineering Laboratory of Internet and Information Sccurity Chongqing University of Posts and Telecommunications Chongqing China Electric Power Research Institute CSG Guangdong Provincial Key Laboratory of Power System Network Security Guangzhou China

ISBN: (纸本)9781450387811

With the release of country's 2020 new infrastructure projects, the increasing demand for electricity in various projects has further promoted the intelligent upgrade of the power grid. The processing of grid data at the edge has become one of the future trends of next generation grid. In the field of power grid edge time series data prediction, the inability to obtain the variable characteristics of other systems and the uncertainty of the length of various edge input data, this paper proposes a Seq2seq prediction model based on a Bi-directional Long Short Term Memory (Bi-LSTM). Bi-LSTM can make full use of contextual information to achieve a more accurate prediction effect. The Seq2Seq model can process variable-length sequence data. In this paper, Seq2Seq model and BI-LSTM model are combined to solve the problem of uncertain edge length and univariate prediction. At the same time, in order to solve the information loss caused by Seq2Seq in the encoding stage, the Attention mechanism is introduced, it can compute the allocation of resources to more important tasks while addressing the problem of information overload. Through experimental research, it is found that the proposed ABSeq2Seq model is superior to other classic models in univariate prediction, and it has the better generalization for various types of data. We have proved its effectiveness in the single variable power prediction.

关键词： Time Series Bi-LSTM Seq2Seq Prediction Attention Mechanism Univariate

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Temporal Correlation Meets Embedding: Towards a 2nd Generation of JDE-based Real-Time Multi-Object Tracking

arXiv

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arXiv 2024年

作者： Zhang, Yunfei Liang, Chao Gao, Jin Zhang, Zhipeng Hu, Weiming Maybank, Stephen Zhou, Xue Li, Liang School of Information Science and Technology Shanghaitech University Shanghai201210 China State Key Laboratory of Multimodal Artificial Intelligence System Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing101408 China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen518110 China KargoBot China Department of Computer Science and Information Systems Birkbeck College LondonWC1E 7HX United Kingdom School of Automation Engineering University of Electronic Science and Technology of China Chengdu611731 China Beijing Institute of Basic Medical Sciences Beijing100850 China

Joint Detection and Embedding (JDE) trackers have demonstrated excellent performance in Multi-Object Tracking (MOT) tasks by incorporating the extraction of appearance features as auxiliary tasks through embedding Re-Identification task (ReID) into the detector, achieving a balance between inference speed and tracking performance. However, solving the competition between the detector and the feature extractor has always been a challenge. Meanwhile, the issue of directly embedding the ReID task into MOT has remained unresolved. The lack of high discriminability in appearance features results in their limited utility. In this paper, a new learning approach using cross-correlation to capture temporal information of objects is proposed. The feature extraction network is no longer trained solely on appearance features from each frame but learns richer motion features by utilizing feature heatmaps from consecutive frames, which addresses the challenge of inter-class feature similarity. Furthermore, our learning approach is applied to a more lightweight feature extraction network, and treat the feature matching scores as strong cues rather than auxiliary cues, with an appropriate weight calculation to reflect the compatibility between our obtained features and the MOT task. Our tracker, named TCBTrack, achieves state-of-the-art performance on multiple public benchmarks, i.e., MOT17, MOT20, and DanceTrack datasets. Specifically, on the DanceTrack test set, we achieve 56.8 HOTA, 58.1 IDF1 and 92.5 MOTA, making it the best online tracker capable of achieving real-time performance. Comparative evaluations with other trackers prove that our tracker achieves the best balance between speed, robustness and accuracy. Code is available at https://***/yfzhang1214/TCBTrack. Copyright © 2024, The Authors. All rights reserved.

关键词： HTTP

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On-edge multi-task transfer learning: Model and practice with data-driven task allocation

arXiv

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arXiv 2021年

作者： Zheng, Zimu Chen, Qiong Hu, Chuang Wang, Dan Liu, Fangming The National Engineering Research Center for Big Data Technology and System Key Laboratory of Services Computing Technology and System Ministry of Education School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China The Edge Cloud Innovation Lab. Technical Innovation Department Cloud BU Huawei Technologies Co. Ltd. Shenzhen China The Department of Computing Hong Kong Polytechnic University Kowloon Hong Kong Hong Kong

On edge devices, data scarcity occurs as a common problem where transfer learning serves as a widely-suggested remedy. Nevertheless, transfer learning imposes heavy computation burden to the resource-constrained edge devices. Existing task allocation works usually assume all submitted tasks are equally important, leading to inefficient resource allocation at a task level when directly applied in Multi-task Transfer Learning (MTL). To address these issues, we first reveal that it is crucial to measure the impact of tasks on overall decision performance improvement and quantify task importance. We then show that task allocation with task importance for MTL (TATIM) is a variant of NP-complete Knapsack problem, where the complicated computation to solve this problem needs to be conducted repeatedly under varying contexts. To solve TATIM with high computational efficiency, we propose a Data-driven Cooperative Task Allocation (DCTA) approach. Finally, we evaluate the performance of DCTA by not only a trace-driven simulation, but also a new comprehensive real-world AIOps case study which bridges model and practice via a new architecture and main components design within AIOps system. Extensive experiments show that our DCTA reduces 3.24 times of processing time, and saves 48.4% energy consumption compared with the state-of-the-art when solving TATIM. Copyright © 2021, The Authors. All rights reserved.

关键词： Energy utilization

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