检索结果-内蒙古大学图书馆

A Novel Consecutive Artificial Noise Secrecy Enhancing Scheme for RIS Aided MIMO system With Imperfect CSI

IEEE Transactions on Vehicular technology 2025年

作者： Shang, Pingping Tao, Zhuofan Xie, Zhonghui Huang, Min Sui, He Li, Jun Hai, Han Hubei University of Technology School of Electrical and Electronic Engineering Wuhan430068 China Hubei University of Technology Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Wuhan430068 China Civil Aviation University of China College of Aeronautical Engineering Tianjin300399 China Guangzhou University School of Electronics and Communication Engineering Guangzhou510006 China Donghua University College of Information Science and Technology Shanghai201620 China

Reconfigurable intelligent surface (RIS) is a technology with great promise, which is widely used in wireless networks to improve the coverage and enhance the performance. However, security concerns pose a major challenge for wireless networks, especially given inevitable errors in channel estimation. This paper proposes a high spectrum efficiency security scheme using generalized spatial modulation (GSM) and space-time block coding (STBC) for scenarios with imperfect channel state information (CSI). In this scheme, GSM uses RIS block indices as unique identifiers, ideal for secure scenarios. It operates by activating different RIS blocks over two time slots to reflect unmodulated carrier signals, while STBC is designed based on the phase shifts of the RIS. To ensure secure communication, a low-complexity continuous artificial noise (CAN) is transmitted with STBC signals to interfere with eavesdroppers and prevent them from decoding the signals. The ergodic secrecy rate is deduced, and the bit error rate (BER) is validated through experiments. The simulation results indicate that the proposed solution can remarkably improves the security performance of the RIS-assisted wireless communication systems. © 1967-2012 IEEE.

关键词： Space-time block coding (STBC)

来源：评论

学校读者我要写书评

暂无评论

Artificial intelligence for geoscience:Progress,challenges,and perspectives

引用

The Innovation 2024年第5期5卷 136-160,135页

作者： Tianjie Zhao Sheng Wang Chaojun Ouyang Min Chen Chenying Liu Jin Zhang Long Yu Fei Wang Yong Xie Jun Li Fang Wang Sabine Grunwald Bryan MWong Fan Zhang Zhen Qian Yongjun Xu Chengqing Yu Wei Han Tao Sun Zezhi Shao Tangwen Qian Zhao Chen Jiangyuan Zeng Huai Zhang Husi Letu Bing Zhang Li Wang Lei Luo Chong Shi Hongjun Su Hongsheng Zhang Shuai Yin Ni Huang Wei Zhao Nan Li Chaolei Zheng Yang Zhou Changping Huang Defeng Feng Qingsong Xu Yan Wu Danfeng Hong Zhenyu Wang Yinyi Lin Tangtang Zhang Prashant Kumar Antonio Plaza Jocelyn Chanussot Jiabao Zhang Jiancheng Shi Lizhe Wang Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China School of Computer Science China University of GeosciencesWuhan 430078China State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China Key Laboratory of Virtual Geographic Environment(Ministry of Education of PRC) Nanjing Normal UniversityNanjing 210023China Data Science in Earth Observation Technical University of Munich80333 MunichGermany The National Key Laboratory of Water Disaster Prevention Yangtze Institute for Conservation and DevelopmentHohai UniversityNanjing 210098China Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China School of Geographical Sciences Nanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008China Soil Water and Ecosystem Sciences DepartmentUniversity of FloridaPO Box 110290GainesvilleFLUSA Materials Science Engineering Program Cooperating Faculty Member in the Department of Chemistry and Department of Physics Astronomy University of CaliforniaCaliforniaRiversideCA 92521USA Institute of Remote Sensing and Geographical Information System School of Earth and Space SciencesPeking UniversityBeijing 100871China Key Laboratory of Computational Geodynamics University of Chinese Academy of SciencesBeijing 100049China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China College of Geography and Remote Sensing Hohai UniversityNanjing 211100China Department of Geography The University of Hong KongHong Kong 999077SARChina Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Nanjing 210044China School of Environmental Science and Engineering Nanjing University of Information Science&TechnologyNanjing 210044China Collaborative Inno

This paper explores the evolution of geoscientific inquiry,tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence(AI)and data collection *** models,which are grounded in physical and numerical frameworks,provide robust explanations by explicitly reconstructing underlying physical ***,their limitations in comprehensively capturing Earth’s complexities and uncertainties pose challenges in optimization and real-world *** contrast,contemporary data-driven models,particularly those utilizing machine learning(ML)and deep learning(DL),leverage extensive geoscience data to glean insights without requiring exhaustive theoretical *** techniques have shown promise in addressing Earth science-related ***,challenges such as data scarcity,computational demands,data privacy concerns,and the“black-box”nature of AI models hinder their seamless integration into *** integration of physics-based and data-driven methodologies into hybrid models presents an alternative *** models,which incorporate domain knowledge to guide AI methodologies,demonstrate enhanced efficiency and performance with reduced training data *** review provides a comprehensive overview of geoscientific research paradigms,emphasizing untapped opportunities at the intersection of advanced AI techniques and *** examines major methodologies,showcases advances in large-scale models,and discusses the challenges and prospects that will shape the future landscape of AI in *** paper outlines a dynamic field ripe with possibilities,poised to unlock new understandings of Earth’s complexities and further advance geoscience exploration.

关键词： Earth utilizing landscape

来源：评论

学校读者我要写书评

暂无评论

An adaptive fault detection strategy for Cz crystal growth process

引用

IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Mu, Lingxia Feng, Nan Zhang, Zhenhua Zhang, Youmin Zhang, Jian Xian University of Technology Crystal Growth Equipment and Systems Integration National Engineering Research Center Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian710048 China University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Concordia University Department of Mechanical Industrial and Aerospace Engineering MontrealQCH3G 1M8 Canada

The monitoring and fault detection for the Czochralski (Cz) crystal growth process is important to ensure the quality of the produced mono-crystalline silicon. The Cz process is a typical multi-modes industrial process, which makes the detection difficult in distinguish the change caused by the fault or mode switching. In this paper, an adaptive fault detection strategy for Cz crystal growth process is proposed. Firstly, quality-related variables are selected from numerous process variables, based on which the training dataset is constructed. Then, a fault detection model is built based on slowly-varying feature and statics indicator. A model switching strategy and updating algorithm are designed to handle the abnormal situation caused by the mode switching or fault occurrence. Three representative experiments are conducted to verify the performance of the proposed strategy, including numerical cases, a publicly available dataset, and Cz crystal growth process from our laboratory. © 1963-2012 IEEE.

关键词： Crystal growth from melt

来源：评论

学校读者我要写书评

暂无评论

ECLIPSE: Expunging Clean-label Indiscriminate Poisons via Sparse Diffusion Purification

arXiv

引用

arXiv 2024年

作者： Wang, Xianlong Hu, Shengshan Zhang, Yechao Zhou, Ziqi Zhang, Leo Yu Xu, Peng Wan, Wei Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China School of Information and Communication Technology Griffith University SouthportQLD4215 Australia

Clean-label indiscriminate poisoning attacks add invisible perturbations to correctly labeled training images, thus dramatically reducing the generalization capability of the victim models. Recently, defense mechanisms such as adversarial training, image transformation techniques, and image purification have been proposed. However, these schemes are either susceptible to adaptive attacks, built on unrealistic assumptions, or only effective against specific poison types, limiting their universal applicability. In this research, we propose a more universally effective, practical, and robust defense scheme called ECLIPSE. We first investigate the impact of Gaussian noise on the poisons and theoretically prove that any kind of poison will be largely assimilated when imposing sufficient random noise. In light of this, we assume the victim has access to an extremely limited number of clean images (a more practical scene) and subsequently enlarge this sparse set for training a denoising probabilistic model (a universal denoising tool). We then introduce Gaussian noise to absorb the poisons and apply the model for denoising, resulting in a roughly purified dataset. Finally, to address the trade-off of the inconsistency in the assimilation sensitivity of different poisons by Gaussian noise, we propose a lightweight corruption compensation module to effectively eliminate residual poisons, providing a more universal defense approach. Extensive experiments demonstrate that our defense approach outperforms 10 state-of-the-art defenses. We also propose an adaptive attack against ECLIPSE and verify the robustness of our defense scheme. Our code is available at https://***/CGCL-codes/ECLIPSE. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Impacts of Flight Altitude and UAV Posture on the UAV-to-Ground Channel Gain

Impacts of Flight Altitude and UAV Posture on the UAV-to-Gro...

引用

IEEE Conference on Wireless communications and Networking

作者： Haoran Ni Boyu Hua Qiuming Zhu Xin Liu Junwei Bao Tongtong Zhou Weizhi Zhong Farman Ali The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Nanjing University of Aeronautics and Astronautics Nanjing China National Mobile Communications Research Laboratory Southeast University Nanjing China School of Information and Communication Engineering Dalian University of Technology Dalian China College of Physics Nanjing University of Aeronautics and Astronautics Nanjing China Qurtuba University of Science and Information Technology

This paper proposes a general unmanned aerial vehicle (UAV)-to-ground (U2G) channel model. The proposed model is consistent with real scenarios by considering the impacts of flight altitude and UAV posture on channel gain. Machine learning and ray tracing (RT) techniques are employed to improve the generation method of altitude-dependent parameters, i.e., path loss (PL) and shadow fading (SF). In addition, posture-related fuselage shadowing coefficient (FSC) is introduced to modify the channel gain, and three-dimensional (3D) geometry modeling of the fuselage is conducted to calculate the FSC. Numerical simulation results show that the flight altitude and UAV posture have obvious effects on channel gain. The proposed model with modified channel gain can effectively describe the PL, SF, and received power under fuselage shadowing. The validity and advantage of the improved channel gain are verified by comparing the simulation results with the measured ones.

关键词： Geometry Three-dimensional displays Simulation Machine learning Gain measurement Autonomous aerial vehicles Power capacitors

来源：评论

学校读者我要写书评

暂无评论

Global Spatial-Temporal information-based Residual ConvLSTM for Video Space-Time Super-Resolution

引用

IEEE Transactions on Multimedia 2025年

作者： Fu, Congrui Yuan, Hui Jiang, Shiqi Zhang, Guanghui Shen, Liquan Hamzaoui, Raouf Center of Experimental Teaching China Shandong University School of Control Science and Engineering China Ministry of Education Key Laboratory of Machine Intelligence and System Control China Shandong University School of software Shandong Jinan China Shandong University School of Computer Science and Technology China Shanghai University School of Communication and Information Engineering Shanghai China De Montfort University School of Engineering and Sustainable Development LeicesterLE1 9BH United Kingdom

By converting low-frame-rate, low-resolution videos into high-frame-rate, high-resolution ones, space-time video super-resolution techniques can enhance visual experiences and facilitate more efficient information dissemination. We propose a convolutional neural network (CNN) for space-time video super-resolution, namely GIRNet. Our method combines long-term global information and short-term local information from the video to better extract complete and accurate spatial-temporal information. To generate highly accurate features and thus improve performance, the proposed network integrates a feature-level temporal interpolation module with deformable convolutions and a global spatial-temporal information-based residual convolutional long short-term memory (convLSTM) module. In the feature-level temporal interpolation module, we leverage deformable convolution, which adapts to deformations and scale variations of objects across different scene locations. This provides a more efficient solution than conventional convolution for extracting features from moving objects. Our network effectively uses forward and backward feature information to determine inter-frame offsets, leading to the direct generation of interpolated frame features. In the global spatial-temporal information-based residual convLSTM module, the first convLSTM is used to derive global spatial-temporal information from the input features, and the second convLSTM uses the previously computed global spatial-temporal information feature as its initial cell state. This second convLSTM adopts residual connections to preserve spatial information, thereby enhancing the output features. Experiments on the Vimeo90K dataset show that the proposed method outperforms open source state-of-the-art techniques in peak signal-to-noise-ratio (by 1.45 dB, 1.14 dB, and 0.2 dB over STARnet, TMNet, and 3DAttGAN, respectively), structural similarity index(by 0.027, 0.023, and 0.006 over STARnet, TMNet, and 3DAttGAN, respectiv

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

A Multi-Point Two-Hop Neighbor Relay Based OLSR Routing Protocol Design Method for Self-organized Multi-agent communication*

A Multi-Point Two-Hop Neighbor Relay Based OLSR Routing Prot...

引用

control Conference (ANZCC), Australian and New Zealand

作者： Zhenlei Wang Chunfeng Li Xiongjun Wu The 54th Research Institute of China Electronics Technology Group Corporation (CETC54) Hebei Province China The 802 Institute of Shanghai Academy of Space Flight Technology The Eighth Academy of China Aerospace Science and Technology Corporation National Defense Key Laboratory of Science and Technology on Electromagnetic Scattering Shanghai Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

The OLSR routing protocol is a proactive Linkstate routing protocol in Ad hoc networks. It uses MPR nodes to spread TC messages across the network, reducing the flooding of protocol control messages in the network. However, all MPR nodes used to propagate a TC message in the whole network are not optimal, and there are a lot of redundancy, which results in unnecessary forwarding of TC messages and increases the overhead of control protocol. To overcome this limitation, the concepts of multi-point one hop neighbor relay (MPOHNR) and multi-point two hop neighbor relay (MPTHNR) are proposed, and the node selection algorithms of MPOHNR and MPTHNR are given. By using MPOHNR and MPTHNR to forward TC messages alternately, the number of forwarding nodes is reduced, the control protocol overhead is reduced, the effective bandwidth of the link is greatly increased, and the end-to-end average delay is reduced. Numerical simulations by using the EXATA software verifies that, the improved OLSR routing protocol is a potential design method for optimizing OLSR routing protocol.

关键词：

来源：评论

学校读者我要写书评

暂无评论

RainGaugeNet: CSI-Based Sub-6 GHz Rainfall Attenuation Measurement and Classification for ISAC Applications

arXiv

引用

arXiv 2025年

作者： Li, Yan Yang, Jie Huang, Yixuan Yang, Tao Wen, Chao-Kai Jin, Shi The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Frontiers Science Center for Mobile Information Communication and Security Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China The National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety Institute of Water Science and Technology Hohai University Nanjing210098 China The Institute of Communications Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan The National Mobile Communications Research Laboratory Southeast University Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China

Rainfall impacts daily activities and can lead to severe hazards such as flooding. Traditional rainfall measurement systems often lack granularity or require extensive infrastructure. While the attenuation of electromagnetic waves due to rainfall is well-documented for frequencies above 10 GHz, sub-6 GHz bands are typically assumed to experience negligible effects. However, recent studies suggest measurable attenuation even at these lower frequencies. This study presents the first channel state information (CSI)-based measurement and analysis of rainfall attenuation at 2.8 GHz. The results confirm the presence of rain-induced attenuation at this frequency, although classification remains challenging. The attenuation follows a power-law decay model, with the rate of attenuation decreasing as rainfall intensity increases. Additionally, rainfall onset significantly increases the delay spread. Building on these insights, we propose RainGaugeNet, the first CSI-based rainfall classification model that leverages multipath and temporal features. Using only 20 seconds of CSI data, RainGaugeNet achieved over 90% classification accuracy in line-of-sight scenarios and over 85% in non-line-of-sight scenarios, significantly outperforming state-of-the-art methods. Copyright © 2025, The Authors. All rights reserved.

关键词： Channel state information

来源：评论

学校读者我要写书评

暂无评论

Research on Emotion Classification of Film and Television Scene Images Based on Different Salient Region

Research on Emotion Classification of Film and Television Sc...

引用

2020 International Conference on Culture-Oriented Science and technology, ICCST 2020

作者： Su, Zhi-Bin Liu, Bing Zhang, Li-Jing Ren, Hui Communication University of China School of Information and Communication Engineering China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China

ISBN: (纸本)9781728181387

With the rapid development of intelligent image processing and computer vision, interpreting and extracting emotion information from images have become a hot research topic, especially the studies on film and television scene images with rich expressions and certain feelings from the aspect of audience. To investigate the distribution of emotions and its affect on the result of machine learning, this paper established the emotion classification models with different salient and non-salient regions based on self-built dataset from film and television works. Three salient extraction algorithms were used to the regional segmentation, and the color and texture features of each region were extracted. Emotion classification models were established based on SVM and RF algorithms respectively. Since features of the salient region could not cover all the information of the original image, the prediction accuracy of the unprocessed image was the highest. Nevertheless, when models made an error in the emotion prediction of the original image, the experimental results of salient region could get the correct answer under the certain circumstances. Through the analysis, the areas of interest can be used for emotion prediction to reduce the redundancy;however, to make it more accurate, the appropriate salient region extraction algorithm should be selected for different types of images and features. Our study provides data and theoretical guidance for image understanding and retrieval, and it has practical significance for more detailed classification based on the affective sensation. © 2020 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Research on Multimodal Algorithms for Multi-routes Planning Based on Niche Technique

Research on Multimodal Algorithms for Multi-routes Planning ...

引用

2020 International Conference on Culture-Oriented Science and technology, ICCST 2020

作者： Ren, Hui Shen, Xiaochen Jia, Xiaojun Communication University of China Ministry of Culture and Tourism Beijing Key Laboratory of Modern Entertainment Technology Communication University of China School of Information and Communication Engineering State Key Laboratory of Media Convergence of Communication Communication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Beijing100024 China

ISBN: (纸本)9781728181387

Multiple routes strategy, classified as a typical multimodal optimization, is an effective method for AGV to tackle the real-world problem. This article majorly explores the traditional optimization algorithm and the evolutionary algorithm for the routes planning problem. Compared with the traditional path planning method, the evolutionary algorithm based on niche technique can successfully avoid the particle interference in the multimodal condition, thereby ensuring the solution diversity. However, various restrictions may be produced when the niche technique cooperates with the evolutionary algorithm. Hence, this paper summarizes some niche techniques with evolutionary algorithms to analyze their merits for solving the multimodal problem. Also, several benchmark functions are involved for further discussing the effectiveness of the niche technology on the multimodal problem and some improvements are conducted for the algorithm to achieve a more effective work. © 2020 IEEE.

关键词： Evolutionary algorithms

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：