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Design and Analysis of Terminal Guidance Law for Kinetic Interceptors based on Pulse Engine

Journal of Electronic Research and Application 2024年第5期8卷 95-108页

作者： Shixin Li Jia Ma Shuai Yue School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210094China Aerospace System Engineering Shanghai Shanghai 201100China Shanghai Key Laboratory of Spacecraft Mechanism Shanghai 201108China National Key Laboratory of Space Intelligent Control Beijing 100048China

A new terminal guidance law is proposed based on a solid propellant pulse engine and an improved proportional navigation method to address the terminal guidance issue for kinetic *** this basis,the start-stop curve of the pulse motor during the terminal guidance process is designed,along with its start-up *** effectiveness of the proposed guidance strategy is verified through simulation.

关键词： Pulse engine Terminal guidance law Kinetic interceptor Proportional navigation method

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Towards Finite Blocklength Covert Communications via A Jammer Mounted on A UAV

Towards Finite Blocklength Covert Communications via A Jamme...

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IEEE International Conference on Communications in China (ICCC)

作者： Xinyu Guo Yida Wang Yong Luo Changbiao Lei Leizhen Xie Tianyu Jia School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu China Academy of Military Science of PLA Institute of System Engineering Beijing China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China PLA Troop of 32027 Kaifeng China

ISBN: (数字)9798350378412

ISBN: (纸本)9798350378429

In this work, we focus on covert communications via a jammer mounted on an unmanned aerial vehicle (UAV) under the supervision of a warden with finite blocklength, i.e., with the short delay constraint. Specifically, we analytically derive the Kullback-Leibler (KL) divergence to obtain a tight lower bound of the sum of the warden’s detection error probabilities, which can be used to characterize the covertness constraint. Then, we derive the communication outage probability to evaluate the communication quality. From the perspective of the aerial jammer, we jointly optimize its transmit power and hovering height to minimize the communication outage probability under the covertness constraint. The optimal aerial jammer’s hovering height is affected by the relation of the distances between the receiver/warden and the aerial jammer, and the optimal aerial jammer’s transmit power is forced to increase when facing stricter covertness requirement, larger blocklength or larger information transmit power.

关键词： Error probability Autonomous aerial vehicles Power system reliability Delays Security Jamming Optimization

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Analysis of a Data Set to Determine the Dependence of Airline Passenger Satisfaction 7th

Analysis of a Data Set to Determine the Dependence of Airlin...

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7th Computational Methods in systems and Software, CoMeSySo 2023

作者： Tynchenko, V.S. Borodulin Kleshko, I.I. Nelyub, V.A. Rukosueva Artificial Intelligence Technology Scientific and Education Center Bauman Moscow State Technical University Moscow105005 Russia Peter the Great St. Petersburg Polytechnic University Saint Petersburg Russia Department of Information Economic System Institute of Engineering and Economics Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia Department of Systems Analysis and Operations Research Institute of Informatics and Telecommunications Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia Information-Control Systems Department Institute of Computer Science and Telecommunications Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia Department of Technological Machines and Equipment of Oil and Gas Complex School of Petroleum and Natural Gas Engineering Siberian Federal University Krasnoyarsk660041 Russia

ISBN: (纸本)9783031535512

This paper presents an analysis of a data set to determine the factors influencing airline passenger satisfaction. The study examines various criteria such as gender, customer type, age, travel type, class, and range to assess their impact on passenger satisfaction. The dataset consists of 25 columns, including attributes like Wi-Fi availability, convenience of online booking, seat comfort, in-flight entertainment, baggage handling, and overall satisfaction. The sample is relatively balanced, with equal representation of men and women, predominantly repeat customers, and a majority flying for business purposes. Key findings include a strong correlation between departure and arrival delays, higher satisfaction among passengers in business class, and positive ratings for Wi-Fi service correlating with overall satisfaction. Correlation analysis reveals interdependencies between different attributes, such as the influence of cleanliness on seat comfort and food and beverage ratings. In addition, a neural network forecasting model is used to estimate the average ratings of passengers, although with low accuracy, which was later excluded. Finally, a decision tree algorithm is utilized to identify the most significant attributes affecting passenger satisfaction words. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Baggage handling

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Aircraft Autonomous Positioning Based on a Coarse to Fine Multi-modal Image Registration Scheme

Aircraft Autonomous Positioning Based on a Coarse to Fine Mu...

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2021 IEEE International Conference on Power Electronics, Computer Applications, ICPECA 2021

作者： Sun, Fangde Fu, Wenxing Lu, Xiaohui Dong, Jing Han, Songlai Central South University School of Aeronautics and Astronautics Changsha China Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratory Beijing China People's Liberation Army 91039th Unit Beijing China National University of Defense Technology Aerospace Science and Engineering Changsha China

ISBN: (纸本)9781728190037

In this paper, an autonomous positioning method based on coarse-to-fine multi-modal image matching is proposed for UAV navigation in GPS denied environment. Coarse image matching refers to roughly determining the approximate position of the real-time image in the reference image. Fine image matching refers to iterative matching around the position obtained by coarse image matching to achieve more accurate matching results. Besides, RANSAC is adopted to eliminate the outliers of image matching. After getting the result of image matching, we use PNP to estimate the position of the aircraft. The proposed position method has the advantages of high accuracy and reliability. The experimental results show that the average error of the position of the proposed method is 59%. © 2021 IEEE.

关键词： Image matching

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0.75 Gbit/s high-speed classical key distribution with mode-shift keying chaos synchronization of Fabry–Perot lasers

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Light(science & Applications) 2021年第9期10卷 1780-1788页

作者： Hua Gao Anbang Wang Longsheng Wang Zhiwei Jia Yuanyuan Guo Zhensen Gao Lianshan Yan Yuwen Qin Yuncai Wang Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceTaiyuanChina College of Physics and Optoelectronics Taiyuan University of TechnologyTaiyuanChina School of Information Engineering Guangdong University of TechnologyGuangzhouChina Guangdong Provincial Key Laboratory of Photonics Information Technology GuangzhouChina Center for Information Photonics and Communications School of Information Science and TechnologySouthwest Jiaotong UniversityChengduChina

High-speed physical key distribution is diligently pursued for secure *** this paper,we propose and experimentally demonstrate a scheme of high-speed key distribution using mode-shift keying chaos synchronization between two multi-longitudinal-mode Fabry–Perot lasers commonly driven by a super-luminescent *** users dynamically select one of the longitudinal modes according to private control codes to achieve mode-shift keying chaos *** two remote chaotic light waveforms are quantized to generate two raw random bit streams,and then those bits corresponding to chaos synchronization are sifted as shared keys by comparing the control *** this method,the transition time,i.e.,the chaos synchronization recovery time is determined by the rising time of the control codes rather than the laser transition response time,so the key distribution rate is improved *** experiment achieved a 0.75-Gbit/s key distribution rate with a bit error rate of 3.8×10^(−3)over 160-km fiber transmission with dispersion *** entropy rate of the laser chaos is evaluated as 16 Gbit/s,which determines the ultimate final key rate together with the key generation *** is therefore believed that the method pays a way for Gbit/s physical key distribution.

关键词： Gbit/s synchronization chaos

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MUP-LIO: Mapping Uncertainty-aware Point-wise Lidar Inertial Odometry

MUP-LIO: Mapping Uncertainty-aware Point-wise Lidar Inertial...

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IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Hekai Yao Xuetao Zhang Gang Sun Yisha Liu Xuebo Zhang Yan Zhuang Intelligent Robotic Laboratory School of Artificial Intelligence School of Control Science and Engineering Dalian University of Technology Dalian China School of Information Science and Technology Dalian Maritime University Dalian China College of Artificial Intelligence The Institute of Robotics and Automatic Information System (IRAIS) Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This paper proposes a mapping uncertainty-aware point-wise Lidar Inertial Odometry (LIO), which synthesizes the point-wise point-to-plane match and map refreshment into a probabilistic model. As a result, it can address the issue of mismatching during point registration and remove in-frame motion distortion of Lidar sensors. Specifically, the uncertainty-aware map is designed to embody the uncertainty of map geometric features (points and planes), which comes from the Lidar point measurement and pose estimation. Then the map can be modeled in a probabilistic form. In addition, the proposed framework refreshes map at each Lidar point measurement to timely revise geometric features and provide non-delayed map. On the basis, the probabilistic point-to-plane match method is designed to seek a corresponding plane for each Lidar point in point registration, which can enhance the effectiveness of match and provide adaptive observation noises for more accurate state estimation. Comparative experiments on various public datasets are conducted to demonstrate the superior performance of the proposed framework in terms of higher accuracy and better robustness.

关键词： Laser radar Accuracy Uncertainty Probabilistic logic Distortion Robustness Sensors Odometry Distortion measurement State estimation

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SeqEnhance: A Lightweight Image Processing PipeLine for Low-Light Image Enhancement

SeqEnhance: A Lightweight Image Processing PipeLine for Low-...

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Artificial Intelligence technology (ACAIT), Asian Conference on

作者： Runlin Zhou Peiliang Huang Dingwen Zhang Jun Ren AHU-IAI AI Joint Laboratory Anhui University Hefei China Hefei Comprehensive National Science Center Institute of Artificial Intelligence Hefei China School of Automation Northwestern Polytechnical University Xi’an China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9798350359145

ISBN: (纸本)9798350359152

Low-light image enhancement (LLIE) is an important task in computer vision, aiming to improve the visual perception or interpretability of images captured in poorly illuminated environments. Recently, deep learning based methods have been extensively explored to address this issue. While many of these methods have achieved significant advancements in various evaluation metrics for LLIE, only a few have made progress in improving inference speed for the resulting images. As a result, achieving both high-quality enhancements and efficient inference speed remains a challenge. To tackle this challenge, we propose SeqEnhance, a fast LLIE method based on a predefined parameterized image processing pipeline. Our approach combines the inference capabilities of deep neural networks for parameter estimation and the efficient processing capabilities of image processing pipelines to generate enhanced images in an end-to-end manner. The experimental results demonstrate that the proposed method achieves competitive performance on image quality evaluation metrics such as PSNR and SSIM with a fast inference speed.

关键词： Measurement Image quality Deep learning Computer vision Parameter estimation Pipelines Artificial neural networks

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Interpretable analysis of feature importance and implicit correlation based on sEMG grayscale. images

Interpretable analysis of feature importance and implicit co...

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Industrial Cyber-Physical systems (ICPS)

作者： Xiaohu AO Feng Wang Juan Zhao Jinhua She School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan

For patients requiring upper limb rehabilitation, the hand rehabilitation robot assists the patient in completing movements within a certain training trajectory to achieve therapeutic results. There have been studies based on deep learning to convert surface electromyography (sEMG) signals into sEMG images for motion intention analysis. Although good recognition accuracy has been achieved, the working principle of neural networks and the processing of image features by the networks are not well explained. The interpretability of deep neural networks determines human confidence in neural network decisions. In this paper, we design a method based on feature importance and implicit correlation for hand motion intention recognition, experimentally explored that convolutional neural networks have implicit definitions for sEMG grayscale images of the same hand gesture action, and verified the effectiveness of the designed method.

关键词： Deep learning Analytical models Correlation Image recognition Neural networks Thumb Gray-scale

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Correlation Analysis and Predictive Factors for Building a Mathematical Model 1

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7th Computational Methods in systems and Software, CoMeSySo 2023

作者： Nelyub, V.A. Tynchenko, V.S. Gantimurov, A.P. Degtyareva, K.V. Kukartseva, O.I. Artificial Intelligence Technology Scientific and Education Center Bauman Moscow State Technical University Moscow105005 Russia Peter the Great St. Petersburg Polytechnic University Saint Petersburg Russia Information-Control Systems Department Institute of Computer Science and Telecommunications Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia Department of Technological Machines and Equipment of Oil and Gas Complex School of Petroleum and Natural Gas Engineering Siberian Federal University Krasnoyarsk660041 Russia Department of Information Economic System Institute of Engineering and Economics Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia Department of Systems Analysis and Operations Research Institute of Informatics and Telecommunications Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia

ISBN: (数字)9783031535499

ISBN: (纸本)9783031535482

The study, published in the journal Nature Medicine, looked at data on 1,000 people from China who were tracked over an average period of six years. The participants were divided into two groups: those who lived in areas with high levels of air pollution and those who lived in areas with low levels of air pollution. The study analyzed data on patients with lung cancer, including their age, gender, exposure to air pollution, alcohol consumption, dust allergy, occupational hazards, genetic risk, chronic lung disease, balanced diet, obesity, smoking, passive smoking, chest pain, cough, hemoptysis, fatigue, weight loss, shortness of breath, wheezing, difficulty swallowing, nail thickening and snoring. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Air pollution

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Prediction of piRNA-mRNA interactions based on an interactive inference network

Prediction of piRNA-mRNA interactions based on an interactiv...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yajun Liu Ru Li Aimin Li Rong Fei Xie Guo Fang-Xiang Wu Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an University of Technology Xi'an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China Department of Computer Science Department of Mechanical Engineering Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada

As the largest class of small non-coding RNAs, piRNAs primarily present in the reproductive cells of mammals, which influence post-transcriptional processes of mRNAs in multiple ways. Effective methods for predicting piRNA and mRNA target relationships can help identify piRNA functions, investigate the possibility of piRNAs as biomarkers and therapeutic targets. In this study, we propose a computational approach for classifying the relationships of piRNA-mRNA pairs based on an interactive inference network (IIN). First, we gather piRNA-mRNA target data, collect sequence data by position alignment, and construct a benchmark dataset. Furthermore, a reliable negative set is constructed by positive-unlabeled learning. Finally, we view a piRNA and a mRNA sequence as a premise and hypothesis sentence, respectively, and IIN model is used to predict the relationship between them. The experiments demonstrate that our method effectively characterizes piRNA-mRNA interaction and could be beneficial for researchers to investigate piRNA functions.

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