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3rd International Conference on Big Data Technologies, ICBDT 2020

作者： Li, Da Lei, Yingke Chen, Qianlin Zhang, Huan Science and Technology on Communication Information Security Control Laboratory College of Electronic Engineering National University of Defense Technology 230037 China 77526 Troop of the People's Liberation Army China 63768 Troop of the People's Liberation Army China

ISBN: (纸本)9781450387859

Precise positioning of outdoor user equipment (UE) is a hot spot for mobile communication. Satellite navigation and positioning technology has low positioning accuracy in complicated scenarios. In this paper, we propose a Cell-ID (CID) based positioning method via Long-Time-Evolution (LTE) network using reference signal received power (RSRP). By using the generalized regression neural network (GRNN) algorithm, precise positioning of UE is realized with a small amount of data. The performance of the proposed method is acquired by the means of cumulative distribution function (CDF). The experiment compares the effects of data preprocessing, CID information and training methods on positioning accuracy. And the experimental results prove the feasibility and effectiveness of the positioning method in complicated environments, with the positioning accuracy of 12.7m. © 2020 ACM.

关键词： Neural networks

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Polynomial-SHAP analysis of liver disease markers for capturing of complex feature interactions in machine learning models

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Computers in Biology and Medicine 2024年 182卷 109168-109168页

作者： Ejiyi, Chukwuebuka Joseph Cai, Dongsheng Ejiyi, Makuachukwu B. Chikwendu, Ijeoma A. Coker, Kenneth Oluwasanmi, Ariyo Bamisile, Oluwatoyosi F. Ejiyi, Thomas U. Qin, Zhen College of Nuclear Technology and Automation Engineering Sichuan Industrial Internet Intelligent Monitoring and Application Engineering Research Center Chengdu University of Technology Sichuan Chengdu China Pharmacy Department University of Nigeria Nsukka Enugu State Nsukka Nigeria School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China Department of Electrical and Electronic Engineering Ho Technical University Ghana Ghana Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Sichuan Chengdu China Department of Pure and Industrial Chemistry University of Nigeria Nsukka Enugu State Nsukka Nigeria

Liver disease diagnosis is pivotal for effective patient management, and machine learning techniques have shown promise in this domain. In this study, we investigate the impact of Polynomial-SHapley Additive exPlanations analysis on enhancing the performance and interpretability of machine learning models for liver disease classification. Our results demonstrate significant improvements in accuracy, precision, recall, F1_score, and Matthews correlation coefficient across various algorithms when polynomial- SHapley Additive exPlanations analysis is applied. Specifically, the Light Gradient Boosting Machine model achieves exceptional performance with 100 % accuracy in both scenarios. Furthermore, by comparing the results obtained with and without the approach, we observe substantial differences in the performance, highlighting the importance of incorporating Polynomial-SHapley Additive exPlanations analysis for improved model performance. The Polynomial features and SHapley Additive exPlanations values also enhance the interpretability of machine learning models by capturing complex feature interactions, enabling users to gain deeper insights into the underlying mechanisms driving the diagnosis. Moreover, data rebalancing using Synthetic Minority Over-sampling Technique and parameter tuning were employed to optimize the performance of the models. These findings underscore the significance of employing this analytical approach in machine-learning-based diagnostic systems for liver diseases, offering superior performance and enhanced interpretability for informed decision-making in clinical practice. © 2024 Elsevier Ltd

关键词： Adversarial machine learning

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Learning Hierarchical Color Guidance for Depth Map Super-Resolution

arXiv

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arXiv 2024年

作者： Cong, Runmin Sheng, Ronghui Wu, Hao Guo, Yulan Wei, Yunchao Zuo, Wangmeng Zhao, Yao Kwong, Sam Institute of Information Science Beijing Jiaotong University Beijing100044 China School of Control Science and Engineering Shandong University Jinan250061 China Key Laboratory of Machine Intelligence and System Control Ministry of Education Shandong Jinan250061 China Artificial Intelligence Institute Beijing Normal University Beijing100875 China Changsha410073 China School of Electronics and Communication Engineering Sun Yat-sen University Guangzhou510275 China School of Computer Science and Technology Harbin Institute of Technology Harbin150001 China Lingnan University Hong Kong

Color information is the most commonly used prior knowledge for depth map super-resolution (DSR), which can provide high-frequency boundary guidance for detail restoration. However, its role and functionality in DSR have not been fully developed. In this paper, we rethink the utilization of color information and propose a hierarchical color guidance network to achieve DSR. On the one hand, the low-level detail embedding module is designed to supplement high-frequency color information of depth features in a residual mask manner at the low-level stages. On the other hand, the high-level abstract guidance module is proposed to maintain semantic consistency in the reconstruction process by using a semantic mask that encodes the global guidance information. The color information of these two dimensions plays a role in the front and back ends of the attention-based feature projection (AFP) module in a more comprehensive form. Simultaneously, the AFP module integrates the multi-scale content enhancement block and adaptive attention projection block to make full use of multi-scale information and adaptively project critical restoration information in an attention manner for DSR. Compared with the state-of-the-art methods on four benchmark datasets, our method achieves more competitive performance both qualitatively and quantitatively. The code and results can be found from the link of https://***/HCGNet_TIM2024. © 2024, CC BY-NC-SA.

关键词： Restoration

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Real-time and ultrafast optical pulse quantization based on slicing the supercontinuum

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Chinese Optics Letters 2021年第8期19卷 69-74页

作者： Ya Guo Qiang Cai Zhiwei Jia Bingjie Xu Zhensen Gao Qianwu Zhang Ruonan Zhang Adonis Bogris K.Alan Shore Yuncai Wang Pu Li Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China School of Information Engineering Guangdong University of TechnologyGuangzhou 510006China Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai UniversityShanghai 200444China School of Electronics and Information Northwestern Polytechnical UniversityXi’an 710072China Science and Technology on Communication Security Laboratory Institute of Southwestern CommunicationChengdu 610041China Department of Informatics and Computer Engineering University of West AtticaAthens 12243Greece School of Electronic Engineering Bangor UniversityWales LL571UTUnited Kingdom

All-optical analog-to-digital conversion is a paramount issue in modern science. How to implement real-time and ultrafast quantization to optical pulses with different intensities in an all-optical domain is a central problem. Here, we report a realtime demonstration of an all-optical quantization scheme based on slicing the supercontinuum in a nonlinear fiber. In comparison with previous schemes through off-line analysis of the power of different optical spectral components in the supercontinuum, this, to the best of our knowledge, is the first demonstration of such functionality online in the time ***, the extinction ratio among the quantized outputs can exceed 10 d B, which further confirms the feasibility of the proposed quantization scheme. The current 3 bit resolution in the proof-of-principle experiment is limited by the current experimental condition, but it can be expected to be greatly enhanced through improving both the spectral width of the generated supercontinuum and the number of filtering channels used.

关键词： all-optical analog-to-digital conversion photonic quantization all-optical signal processing supercontinuum generation

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Personalized Video Recommendation with Attentive Multi-View Learning and Long-Term and Short-Term Interest Modeling

SSRN

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SSRN 2022年

作者： Wang, Chuangjian Zhang, Yuelin Yuan, Youwei Jiang, Peng Zhou, Qi Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China School of Management Huazhong University of Science and Technology Wuhan430081 China School of Journalism and Information Communication Huazhong University of Science and Technology Wuhan430081 China

Personalized video recommendations can be a good solution to the problem of massive video overload. However, most of the existing recommendation algorithms use ID as the core for feature design, which is far from enough. This paper proposes a new recommendation algorithm. This approach can use the features of multiple views to learn the representation of features in videos and users. In video encoder, this paper proposes an attentive multi-view learning model that can learn a uniform video representation for video type, title, content, and starring stars as different views. In the user encoder, this paper learns the long-term and short-term interests of users from multiple views. Firstly, the long-term interest of users is learned from two perspectives: the global behavior of users themselves and the neighbor behavior. Then, this paper designs an attentive Bi-LSTM model to learn users' short-term interests using recent users' viewing history behaviors. Extensive experiments are conducted on a large real dataset, and the experiments show that our approach can improve the effectiveness of video recommendation. © 2022, The Authors. All rights reserved.

关键词： Large dataset

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An Improved Lmmse Channel Estimation Algorithm for Mimo-Ofdm System

SSRN

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SSRN 2022年

作者： Tang, Wanwei Wang, Lixia Wang, Zedai Wei, Mingzhe Zhao, Jinlong Yue, Xinwei The Key Laboratory of Intelligent Data Information Processing and Control of Hebei Province Tangshan University Tangshan063000 China The School of Engineering Hong Kong University of Science and Technology 999077 Hong Kong The School of Electronic and Information Engineering Beihang University Beijing100191 China The School of Information and Communication Engineering Beijing Information Science and Technology University Beijing100101 China

This paper studies channel estimation techniques to recover the received signal more accurately and quickly. The classical Least Squares (LS) and Linear Minimum Mean-squared Error (LMMSE) estimation have the problems of poor estimation performance and high complexity. An Fast-LMMSE channel estimation algorithm is proposed to balance the performance and complexity. In order to apply it to the actual system, the corresponding pilot is also designed. Simulation results are provided and the comparison shows the performance gains achieved by the proposed technique over LS and MMSE estimation in SISO and MIMO communication systems. © 2022, The Authors. All rights reserved.

关键词： Channel estimation

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Interference Resource Scheduling Algorithm Based on Potential Game for UAV Cooperative Combat

Interference Resource Scheduling Algorithm Based on Potentia...

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International Conference on communication technology (ICCT)

作者： Min Deng Zhigao Wu Yongqi Chen School of Automatic and Electronic Information Xiangtan University Hunan National Center for Applied Mathematics Xiangtan China School of Automatic and Electronic Information Xiangtan University Xiangtan China Science and Technology on Communication Information Security Control Laboratory JiaxingChina

ISBN: (纸本)9781665432078

Interference resource scheduling is crucial in UAV (unmanned aerial vehicle) cooperative combats of all scales. In view of the simple constraints of the existing scheduling models and their small-scale application situations, a resource scheduling model with constraint of the minimum number of jammed targets is proposed to maximize the benefit of interference and minimize the cost. The analytic hierarchy process is used to weight the indicators of benefit and cost. And the interference resource scheduling model is constructed by the game theory. Besides, the feasibility and existence of the Nash equilibrium are proved. Then, a potential game theory algorithm combined with the tabu algorithm was proposed to solve the interference resource allocation problem. The simulation results show that the designed interference resource scheduling algorithm can achieve higher integration benefit than the other compared algorithms with less iterations.

关键词： Costs Scheduling algorithms Heuristic algorithms Simulation Interference Dynamic scheduling Autonomous aerial vehicles

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Impacts of Hardware Impairments on Mutualistic Cooperative Ambient Backscatter communications

arXiv

引用

arXiv 2022年

作者： Ye, Yinghui Shi, Liqin Chu, Xiaoli Lu, Guangyue Sun, Sumei Shaanxi Key Laboratory of Information Communication Network and Security Xi’an University of Posts & Telecommunications China Department of Electronic and Electrical Engineering The University of Sheffield United Kingdom Institute of Infocomm Research Agency for Science Technology and Research Singapore Singapore

In mutualistic cooperative ambient backscatter communications (AmBC), Internet-of-Things (IoT) device sends its information to a desired receiver by modulating and backscattering the primary signal, while providing beneficial multipath diversity to the primary receiver in return, thus forming a mutualism relationship between the AmBC and primary links. We note that the hardware impairments (HIs), which are unavoidable in practical systems and may significantly affect the transmission rates of the primary and AmBC links and their mutualism relationships, have been largely ignored in the study of mutualistic cooperative AmBC networks. In this paper, we consider a mutualistic cooperative AmBC network under HIs, and study the impacts of HIs on the achievable rates of the primary link and the AmBC link. In particular, we theoretically prove that although HIs degrades the rate of each link, the mutualism relationship between the AmBC and primary links is maintained, i.e., the rate of the primary link in the mutualistic cooperative AmBC network is still higher than that without the AmBC link. The closed-form rate expressions of both the AmBC and primary links are derived. Computer simulations are provided to validate our theoretical analysis. Copyright © 2022, The Authors. All rights reserved.

关键词： Backscattering

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Knowledge-aided covariance matrix estimation algorithm based on geometric mean in STAP for airborne radar

Knowledge-aided covariance matrix estimation algorithm based...

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IET International Radar Conference (IRC 2023)

作者： Yang Jing Xiaolin Du Guolong Cui Jibin Zheng Jianbo Li School of Computer and Control Engineering Yantai University Yantai People's Republic of China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu People's Republic of China National Key Laboratory of Radar Signal Processing Xidian University Xi’an People's Republic of China School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing People's Republic of China

ISBN: (数字)9781837240982

The problem of knowledge-aided (KA) covariance matrix estimation in airborne radar space-time adaptive processing (STAP) is studied in this paper. In the traditional KA covariance matrix estimation methods, the insufficient number of available samples and inaccurate prior knowledge can cause serious deterioration of STAP performance. To tackle this problem, a new KA covariance matrix estimation algorithm based on geometric mean is proposed. Specifically, by utilizing the persymmetric structure information as well as the geometric mean in the space of positive definite matrices, a geometric mean estimator is constructed, which is then linearly combined with the prior covariance matrix to obtain a new type of CCM estimators. Simulation results illustrate that the proposed algorithm has good STAP performance with small samples and inaccurate prior knowledge.

关键词：

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Fast Fourier single-pixel imaging based on Sierra–Lite dithering algorithm

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Chinese Physics B 2019年第6期28卷 189-194页

作者： Zhen-Yu Liang Zheng-Dong Cheng Yan-Yan Liu Kuai-Kuai Yu Yang-Di Hu National University of Defense Technology State Key Laboratory of Pulsed Power Laser TechnologyHefei 230037China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin 300000China

The single-pixel imaging(SPI) technique is able to capture two-dimensional(2 D) images without conventional array sensors by using a photodiode. As a novel scheme, Fourier single-pixel imaging(FSI) has been proven capable of reconstructing high-quality images. Due to the fact that the Fourier basis patterns(also known as grayscale sinusoidal patterns)cannot be well displayed on the digital micromirror device(DMD), a fast FSI system is proposed to solve this problem by binarizing Fourier pattern through a dithering algorithm. However, the traditional dithering algorithm leads to low quality as the extra noise is inevitably induced in the reconstructed images. In this paper, we report a better dithering algorithm to binarize Fourier pattern, which utilizes the Sierra–Lite kernel function by a serpentine scanning method. Numerical simulation and experiment demonstrate that the proposed algorithm is able to achieve higher quality under different sampling ratios.

关键词： single-pixel imaging binary Fourier basis pattern the dithering algorithm

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