检索结果-内蒙古大学图书馆

2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Liu, Zinan Niu, Shengren Qiu, Xiaolan Peng, Lingxiao Zhong, Lihua Ding, Chibiao Chinese Academy of Sciences The National Key Laboratory of Microwave Imaging Technology Aerospace Information Research Institute Beijing China Chinese Academy of Sciences Suzhou Key Laboratory of Microwave Imaging Processing and Application Technology Aerospace Information Research Institute Suzhou China Chinese Academy of Sciences Key Laboratory of Technology in Geospatial Information Processing and Application Systems Aerospace Information Research Institute Beijing China

ISBN: (纸本)9798331515669

Image-based synthetic aperture radar (SAR) target three-dimensional (3D) reconstruction is an important application for extracting target information from high-resolution two-dimensional (2D) SAR images. However, due to the complex mechanism of SAR imaging, developing a data-driven, fully automated 3D reconstruction framework with explicit physical constraints is very difficult. Thus, this paper proposes a differentiable framework for image-based SAR target reconstruction with 3D Gaussian Splatting, which can automatically realize the 3D target reconstruction from multi-view SAR images. Specifically, the proposed differentiable framework accumulates and generates simulated SAR images according to the SAR imaging geometry and projection during the forward simulation stage. By calculating the loss between the simulated and ground truth SAR images and backpropagating, the spatial positions of the 3D Gaussians are continuously adjusted until convergence, generating the 3D point cloud model of the target. The experiment is conducted on the constructed T72 SAR image dataset and the reconstruction results demonstrate the effectiveness of the proposed framework. © 2024 IEEE.

关键词： 3D reconstruction

来源：评论

学校读者我要写书评

暂无评论

Adaptive Time Slot Resource Allocation in SWIPT IoT Networks

引用

Computer Modeling in Engineering & Sciences 2023年第9期136卷 2787-2813页

作者： Yunong Yang Yuexia Zhang Zhihai Zhuo Key Laboratory of Information and Communication Systems Ministry of Information IndustryBeijing Information Science and Technology UniversityBeijing100101China Key Laboratory of ModernMeasurement&Control Technology Ministry of EducationBeijing Information Science&Technology UniversityBeijing100101China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beijing100101China

The rapid advancement of Internet of Things(IoT)technology has brought convenience to people’s lives;however further development of IoT faces serious challenges,such as limited energy and shortage of network spectrum *** address the above challenges,this study proposes a simultaneous wireless information and power transfer IoT adaptive time slot resource allocation(SIATS)***,an adaptive time slot consisting of periods for sensing,information transmission,and energy harvesting is designed to ensure that the minimum energy harvesting requirement ismet while the maximumuplink and downlink throughputs are ***,the optimal transmit power and channel assignment of the system are obtained using the Lagrangian dual and gradient descent methods,and the optimal time slot assignment is determined for each IoT device such that the sum of the throughput of all devices is *** results show that the SIATS algorithm performs satisfactorily and provides an increase in the throughput by up to 14.4%compared with that of the fixed time slot allocation(FTS)*** the case of a large noise variance,the SIATS algorithm has good noise immunity,and the total throughput of the IoT devices obtained using the SIATS algorithm can be improved by up to 34.7%compared with that obtained using the FTS algorithm.

关键词： Internet of Things simultaneous wireless information and power transfer adaptive time slot resource allocation

来源：评论

学校读者我要写书评

暂无评论

Ultraviolet photodetectors based on ferroelectric depolarization field

引用

Journal of Energy Chemistry 2023年第2期77卷 487-498,I0013页

作者： Xiaoyu Zhou Qingqing Ke Silin Tang Jilong Luo Zihan Lu School of Microelectronics Science and Technology Sun Yat-sen UniversityZhuhai 519082GuangdongChina Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Sun Yat-sen UniversityZhuhai 519082GuangdongChina

Ultraviolet(UV)photodetectors are extensively adopted in the fields of the Internet of Things,optical communications and ***,with broadening the application scope of UV photodetectors,developing integrated devices with more functionalities rather than basic photo-detecting ability are highly required and have been triggered ever-growing interest in scientific and industrial *** thin films have become a potential candidate in the field of UV detection due to their wide bandgap and unique photovoltaic ***,ferroelectric thin films perform excellent dielectric,piezoelectric,pyroelectric,acousto-optic effects,etc.,which can satisfy the demand for the diversified development of UV *** this review,according to the different roles of ferroelectric thin films in the device,the UV photodetectors based on ferroelectric films are classified into ferroelectric depolarization field driven type,ferroelectric depolarization field and built-in electric field co-driven type,and ferroelectric field enhanced *** three types of ferroelectric UV photodetectors have great potential and are expected to promote the development of a new generation of UV detection *** the end of the paper,the advantages and challenges of three types of ferroelectric UV photodetectors are summarized,and the possible development direction in the future is proposed.

关键词： UV photodetector Ferroelectric Thin film Depolarization field Built-in electric field

来源：评论

学校读者我要写书评

暂无评论

Data secure transmission intelligent prediction algorithm for mobile industrial IoT networks

引用

Digital Communications and Networks 2023年第2期9卷 400-410页

作者： Lingwei Xu Hao Yin Hong Jia Wenzhong Lin Xinpeng Zhou Yong Fu Xu Yu Department of Information Science and Technology Qingdao University of Science and TechnologyQingdao266061China Fujian Key Laboratory of Sensing and Computing for Smart Cities Xiamen UniversityXiamen361005China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control(Minjiang University) Fuzhou350121China Faculty of Information Science and Engineering Ocean University of ChinaQingdao266100China Shandong Provincial Key Laboratory of Computer Networks Shandong Computer Science Center(National Supercomputer Center in Jinan)JinanChina

Mobile Industrial Internet of Things(IIoT)applications have achieved the explosive growth in recent *** mobile IIoT has flourished and become the backbone of the industry,laying a solid foundation for the interconnection of all *** variety of application scenarios has brought serious challenges to mobile IIoT networks,which face complex and changeable communication *** data secure transmission is critical for mobile IIoT *** paper investigates the data secure transmission performance prediction of mobile IIoT *** cut down computational complexity,we propose a data secure transmission scheme employing Transmit Antenna Selection(TAS).The novel secrecy performance expressions are first ***,to realize real-time secrecy analysis,we design an improved Convolutional Neural Network(CNN)model,and propose an intelligent data secure transmission performance prediction *** mobile signals,the important features may be removed by the pooling *** will lead to negative effects on the secrecy performance prediction.A novel nine-layer improved CNN model is *** of the input and output layers,it removes the pooling layer and contains six convolution ***,Back-Propagation(BP)and LeNet methods are employed to compare with the proposed *** simulation analysis,good prediction accuracy is achieved by the CNN *** prediction accuracy obtains a 59%increase.

关键词： Mobile IIoT networks Data secure transmission Performance analysis Intelligent prediction Improved CNN

来源：评论

学校读者我要写书评

暂无评论

Re-HGNM: a repeat aware hypergraph neural machine for session-based recommendation

引用

Neural Computing and Applications 2024年第17期36卷 9661-9674页

作者： Peng, Yuze Xu, Shengjun Huang, Yihua School of Electronics and Information Technology Sun Yat-Sen University Guangdong Guangzhou510006 China The Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems School of Electronics and Information Technology Sun Yat-Sen University Guangdong Guangzhou510006 China Southern Marine Science and Engineering Guangdong Laboratory Guangdong Zhuhai519080 China

Hypergraph neural network (HGNN) for session-based recommendation (SBR) is quite rare but has been rewarded with promising performance. However, under the hypergraph framework, no works have emphasized the importance of repeat consumption, which is an important consumption pattern in SBR (e.g., people watch movies or listen to music repeatedly over time) and limits the performance of SBR in a beyond graph topology manner. For filling this gap and better recommendation performance, this paper incorporates repeat consumption into HGNNs and proposes a new recommendation machine, named Re-HGNM, which leverages the powerful expressiveness of HGNNs in representation learning and takes repeat consumption into account by considering the relationship between repeat behaviors and modeling repeat recommendations. Specially, in the encoder of Re-HGNM, we process sessions as hyperedges, in which the repeated behaviors are merged, to constitute hypergraph that conveys not only the complex relations between unique items but the relationships between repeat behaviors. After learning item representation by hypergraph convolution, a repeat-explore module is employed to determine whether to make repeat recommendation. In repeat mode, the next click must be in old items;thereby, the shrunk prediction space makes it easier to find the target item. Therefore, in the decoding stage, two decoders correspondingly work under two separate modes. Finally, compared with the current best baseline, Re-HGNM relatively improved P@20 by 58.37%, 8.70%, 1.28%, and 1.16% and MRR@20 by 25.52%, 10.31%, 10.76%, and 2.76% on the Tmall, RetailRocket, Nowplaying, and Diginetica, to be the current state-of-the-art model for SBR. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2023.

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

Towards Privacy-Aware Causal Structure Learning in Federated Setting

引用

IEEE Transactions on Big Data 2023年第6期9卷 1525-1535页

作者： Huang, Jianli Guo, Xianjie Yu, Kui Cao, Fuyuan Liang, Jiye Intelligent Interconnected Systems Laboratory of Anhui Province School of Computer Science and Information Engineering Hefei University of Technology Hefei230601 China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education School of Computer and Information Technology Shanxi University Taiyuan030006 China

Causal structure learning has been extensively studied and widely used in machine learning and various applications. To achieve an ideal performance, existing causal structure learning algorithms often need to centralize a large amount of data from multiple data sources. However, in the privacy-preserving setting, it is impossible to centralize data from all sources and put them together as a single dataset. To preserve data privacy, federated learning as a new learning paradigm has attached much attention in machine learning in recent years. In this paper, we study a privacy-aware causal structure learning problem in the federated setting and propose a novel federated PC (FedPC) algorithm with two new strategies for preserving data privacy without centralizing data. Specifically, we first propose a novel layer-wise aggregation strategy for a seamless adaptation of the PC algorithm into the federated learning paradigm for federated skeleton learning, then we design an effective strategy for learning consistent separation sets for federated edge orientation. The extensive experiments validate that FedPC is effective for causal structure learning in federated learning setting. © 2023 IEEE.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

A hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction

引用

Energy and AI 2024年第4期18卷 368-379页

作者： Weipeng Li Yuting Chong Xin Guo Jun Liu School of Automation and Information Engineering Xi’an University of TechnologyNo.5 Jinhua South RoadXi’an710048ShaanxiChina Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing No.5 Jinhua South RoadXi’an710048ShaanxiChina

Efficient and accurate wind power prediction is crucial for enhancing the reliability and safety of power *** data-driven forecasting methods are regarded as an effective ***,the inherent randomness and nonlinearity of wind power systems,along with the abundance of redundant information in measurement data,present challenges to forecasting *** integration of precise and efficient techniques for data feature decomposition and extraction is essential in conjunction with advanced driven data-forecasting *** on the seasonal variation characteristics of wind energy,a hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction is *** effectiveness and superiority of the proposed method in predictive accuracy are demonstrated through comprehensive multi-model experiment comparisons.

关键词： Wind power prediction Data-driven Hybrid model Seasonal feature decomposition Gated recurrent networks Attention mechanism

来源：评论

学校读者我要写书评

暂无评论

Synthesis of Failure-Robust Plans for Multi-Robot systems Under Temporal Logic Specifications 19

Synthesis of Failure-Robust Plans for Multi-Robot Systems Un...

引用

19th IEEE International Conference on Automation Science and Engineering, CASE 2023

作者： Huang, Feifei Li, Shaoyuan Yin, Xiang Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Department of Automation Shanghai200240 China

ISBN: (纸本)9798350320695

In this study, we address the multi-robot path planning problem for tasks specified by linear temporal logic (LTL) formulae. Unlike existing studies, we take into account the possibility of robot failures, where a failed robot can no longer contribute to the completion of the LTL task. Our objective is to find a failure-robust path, which ensures that the LTL task can always be fulfilled, even if a maximum number of robots fail at any point during execution. To achieve this, we extend the mixed-integer linear programming (MILP) approach to the failure-robust setting. To overcome the computational complexity, we identify a fragment of LTL formulae called the free-union-closed LTL, which allows for more scalable synthesis without considering the global combinatorial issue. We present case studies to demonstrate our findings. Our approach provides a novel solution to the problem of multi-robot path planning under robot failures, offering a practical and efficient way to achieve robustness in the face of unforeseen events. © 2023 IEEE.

关键词： Multipurpose robots

来源：评论

学校读者我要写书评

暂无评论

Development of Hardware Module for Collecting Parameters of Microhydroelectric Power Plant Operation in Mountainous Conditions

Development of Hardware Module for Collecting Parameters of ...

引用

2024 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2024

作者： Onishchenko, Stefan V. Mamiy, Aliy R. Yurkaev, Konstantin A. Adyghe State University Laboratory Of Renewable Energy Sources Maykop Russia Adyghe State University Department Of Automated Systems Of Processing Information And Control Maykop Russia

ISBN: (纸本)9798350395013

Hydropower plants play a major role in the global energy sector, generating up to 17% of all energy generated. Despite this, the spread of small hydropower is not as extensive, although it has an extremely large potential and is a competitive renewable energy source, as small hydropower plants have high efficiencies of up to 80%. The implementation of such energy complexes requires a preliminary assessment of their efficiency, for which atlases and data from existing GIS systems are most often used, but they may not have information on the potential of small rivers and streams, and do not allow for seasonal changes in the water landscape, which is particularly pronounced in mountainous terrain. Therefore, this paper proposes to examine the process of developing a small generating station suitable for use on small streams in mountainous terrain, which can be used as a means to collect data on the energy production profile of small mountain streams, which will help to establish seasonal dependencies and balance the energy system, achieving sustainable energy production through the involvement of other generation sources. © 2024 IEEE.

关键词： Rivers

来源：评论

学校读者我要写书评

暂无评论

Fault Detection Unknown Input Observer for Local Nonlinear Fuzzy Autonomous Ground Vehicles System Based on a Joint Peak-to-Peak Analysis and Zonotopic Analysis Threshold

引用

IEEE Transactions on Vehicular Technology 2025年第5期74卷 7226-7236页

作者： Li, Yi Dong, Jiuxiang Northeastern University State Key Laboratory of Synthetical Automation of Process Industries Shenyang110819 China Northeastern University College of Information Science and Engineering Shenyang110819 China Northeastern University Key Laboratory of Vibration and Control of Aero-Propulsion Systems Ministry of Education of China Liaoning Shenyang China

This paper focuses on the fault detection problem of local nonlinear fuzzy autonomous ground vehicles systems with disturbances by developing set membership estimation. The intractable influence of disturbances and local nonlinear part on the design of fault detection thresholds is the principal difficulty in fault detection using the existing set membership estimation methods. To this end, a fault detection unknown input observer via a novel joint peak-to-peak analysis and zonotopic analysis threshold is proposed. Firstly, the disturbances are divided into decouplable and non-decouplable parts. An unknown input observer, designed with peak-to-peak performance criteria, is employed to achieve the decoupling of the decouplable disturbance part. Subsequently, based on the dynamic structure of the observer, the local non-linear part is represented as polyhedra through peak-to-peak analysis and zonotopic analysis, thereby providing an interval estimation for the system output. his method utilizes zonotopic analysis to mitigate the over-estimation issue in the initial stage inherent in traditional peak-to-peak performance-based interval estimation techniques. Furthermore, it retains the necessary degrees of freedom during the decoupling process of certain disturbances to optimize the observer's performance. Consequently, this approach significantly enhances the accuracy of the interval estimation as compared to existing methods. Moreover, the peak-to-peak performance of fault detection unknown input observer is analysed using the fuzzy basis-dependent Lyapunov function to decrease the conservatism. Lastly, simulations are analysed in order to validate the accuracy of the proposed thresholds. © 1967-2012 IEEE.

关键词： Lyapunov functions

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：