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International Conference on Computer Supported Cooperative Work in Design

作者： Yiyun Xing Kaili Zhou Jianqiang Zhang Gongpeng Song Qin Lu Key Laboratory of Computing Power Network and Information Security Ministry of EducationShandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Faculty of Computer Science and Technology Shandong Engineering Research Center of Big Data Applied Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China Shandong Branch of China Mobile Communication Group Design Institute Co. Jinan China

ISBN: (数字)9798331513054

ISBN: (纸本)9798331513061

Hierarchical Text Classification, as a critical task in natural language processing, has broad applications in scenarios with complex label structures and limited samples. However, existing methods still face challenges in capturing hierarchical label information and text interactions, resulting in suboptimal classification performance. This study proposes a few-shot hierarchical text classification method based on prompt embeddings and dynamically fused hierarchical features. Building on pre-trained language models, the method encodes hierarchical structure information as prompts through an adaptive prompt embedding model and dynamically fuses hierarchical features to generate more expressive text representations. Additionally, a positive sample generation strategy based on contrastive learning is introduced, enabling the model to effectively distinguish hierarchical features across different categories, further enhancing classification performance. Experimental results demonstrate that this method significantly improves classification accuracy on multiple public datasets, exhibiting stronger generalization ability and robustness compared to mainstream methods. This approach offers a novel and effective solution for hierarchical text classification tasks.

关键词： Adaptation models Accuracy Federated learning Computational modeling Text categorization Buildings Contrastive learning Robustness Natural language processing Faces

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Near-Field Spatial Correlation for Multi-Path XL-Array communications with Partial Visibility

Near-Field Spatial Correlation for Multi-Path XL-Array Commu...

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IEEE Conference on Global communications (GLOBECOM)

作者： Zhenjun Dong Xinrui Li Yong Zeng Shi Jin Tao Jiang National Mobile Communications Research Laboratory and Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing China Purple Mountain Laboratories Nanjing China School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan China

For extremely large-scale array (XL-array) communications, the scatterers and/or user equipments (UEs) may be located in the near-field region and only visible to some portions of the XL-array. This paper studies the near-field spatial correlation function (S-CF) of multi-path XL-array communications with mixed line-of-sight (LoS) and non-LoS (NLoS) links. The generic near-field non-uniform spherical wave (NUSW) characteristic and the partial visibility property are considered. For the LoS link, a novel near-field S-CF is derived, which is in terms of the correlation of UE's visibility and location. It is found that the near-field S-CF depends on the UE's angle of arrival (AoA) and distance, which differs from the far-field result that only depends on the UE's AoA. For the NLoS links, we derive a novel integral expression for the near-field S-CF in terms of the correlation of the scatterers' visibility and location distribution. The near-field result is shown to depend on the scatterers' partial visibility and the power location spectrum (PLS) characterized by the AoAs and distances of scatterers, in contrast to the far-field model, which relies on the power angular spectrum (PAS). The result demonstrates that the near-field S-CF of the LoS/NLoS component no longer exhibits spatial wide-sense stationarity (SWSS) and is more generic than the far-field model. To gain further insights, we consider a specific scatterer's location distribution, namely the multi-ring scatterer model. Numerical results show the necessity of modeling near-field S-CF for XL-array communications with partial visibility.

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A Kirchhoff-approximation numerical model for three-dimensional acoustic scattering from rough under-ice surfaces

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Chinese Journal of Acoustics 2021年第4期40卷 511-524页

作者： CHEN Wenjian LI Fubing YIN Jingwei ZHOU Shunbo SUN Hui LANG Pengyuan Acoustic Science and Technology Laboratory Harbin Engineering UniversityHarbin 150001 Key Laboratory of Marine Information Acquisition and Security(Harbin Engineering University) Ministry of Industry and Information TechnologyHarbin 150001 College of Underwater Acoustic Engineering Harbin Engineering UniversityHarbin 150001 School of Information and Communication Engineering Beijing Information Science and Technology UniversityBeijing 100101

A KirchhofF-approximation numerical method of three-dimensional acoustic scattering from a rough under-ice surface is *** triangulation is used to triangulate a Gaussian rough under-ice surface,the Z-bufFer algorithm is used to remove the surface elements in the shadowed areas and obtain those in the bright areas,and the scattering intensity is calculated by the planar element method of Gordon's *** the numerical calculation model,the ice surface is regarded as one of local impedance,thereby incorporating it directly into the local reflection coefficient of the rough under-ice surface to calculate the scattering sound field and avoiding the approximation of the reflection coefficient in the analytical calculation *** scattering intensities of the numerical and analytical models are compared for under-ice surfaces with large and small roughness at different incident angles and *** the two types of results,those of the numerical calculation model are more consistent with measurements.

关键词： approximation numerical surfaces

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Dynamic Unmanned Aerial Vehicle Selection via Evolutionary Game

Dynamic Unmanned Aerial Vehicle Selection via Evolutionary G...

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IEEE International Conference on communications in China (ICCC)

作者： Anqi Meng Tianshi Ren Mei Yang Xiaozheng Gao Xianchao Zhang Jinbo Zhang Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China School of Information and Electronics Beijing Institute of Technology Beijing China School of Arts and Sciences Beijing Institute of Fashion Technology Beijing China Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province Jiaxing University Jiaxing China Science and Technology on Communication Networks Laboratory The 54th Research Institute of CETC Shijiazhuang China

Unmanned aerial vehicle assisted (UAV-assisted) wireless communication network is a promising paradigm of wireless communication network. In this paper, we apply the evolutionary game to the UAV selection process of ground user equipment (UE). Specifically, we first establish a UAV-assisted uplink wireless communication model, and then we use replicator dynamics to describe the process of evolution game. Finally, we propose a dynamic UAV selection algorithm based on evolutionary game with low computation complexity. The numerical results prove the effectiveness of our developed algorithm in UAV-assisted wireless communication network.

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Short-term traffic flow prediction based on BAS-VMD-CEEMDAN and IWOA-RF

Short-term traffic flow prediction based on BAS-VMD-CEEMDAN ...

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information Systems and Computing technology (ISCTech), International Conference on

作者： Jia Tian Deyong Wang Yanyun Fn Xueyi Zhao Jian Fang Wenxi Shi School of Information Science and Engineering Xinjiang University Urumqi China Key Laboratory of Big Data of Xinjiang Social Security Risk Prevention and Control Xinjiang Lianhaichuangzhi Information Technology Co. Ltd Urumqi China Beijing Academy of Science and Technology Beijing China

Short-term traffic flow forecasting is crucial for intelligent traffic management. In view of the non-linear and random nature of short-term traffic flow, a prediction model based on BAS-VMD-CEEMDAN and IWOA-RF is proposed. Firstly, the parameters of the VMD, namely the modal number (K) and the value of the quadratic penalty term (α), are optimized using the BAS algorithm, and then the traffic flow is decomposed to obtain several VMF components and one RES component, which extracts the smooth information of the traffic flow. Subsequently, the RES component is decomposed using the decomposition completeness of CEEMDAN to obtain several IMF components, refining the complex information of the RES component. Then, the RF model is constructed according to the characteristics of each component, and then the parameters of RF models are optimized using IWOA. Finally, overlay the predictions of each component superimposed to obtain the final predictions. Experimental results show that the short-term traffic flow forecasting model basedon BAS-VMD-CEEMDAN-IWOA-RF has a high accuracy compared to other decomposition models.

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Modulation Signal Recognition Based on Feature Fusion and Residual CNN in Fractal Noise Background 6

Modulation Signal Recognition Based on Feature Fusion and Re...

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6th International Conference on Signal and Image Processing, ICSIP 2021

作者： Chen, Di Xiong, Gang Huang, Baigang Wang, Lijun No.36 Research Institute of Cetc Science and Technology On Communication Information Security Control Laboratory Jiaxing China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Institute of Navigation and Sensing Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9780738133737

In this paper, a modulated signal recognition method based on feature fusion and ResCNN (FF-ResCNN) under generalized fractal noise background is proposed. Firstly, in the feature extraction and fusion part, considering the robustness, anti-noise and interpretability of the features, the fusion feature vectors of generalized fractal spectrum, instantaneous feature and high-order cumulant feature are constructed. Secondly, in order to suppress the possible gradient and degradation problems, the ResCNN model is used to train and classify the fusion features when the CNN model is used to further collect the deep-level abstract features. Finally, feature extraction, feature fusion and classification experiments are carried out for nine modulated signals under two noise types (GWN and fractal noise). Experimental results show that in the case of generalized fractal noise, when SNR=0dB, the recognition accuracy of signal modulation type reaches 95.42%, which verifies the superiority of the proposed method. At the same time, the simulation analysis is carried out for different feature fusion schemes, which provides a valuable reference for feature combination optimization under different noise environment. © 2021 IEEE.

关键词： Feature extraction

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Experimental Study on Target Localization for DTMB-Based Passive Bistatic Radar 1

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3rd EAI International Conference on Artificial Intelligence for communications and Networks, AICON 2021

作者： Qian, Jiachuan Li, Haijie Zhu, Huijie Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China The 36th Research Institute of China Electronics Technology Group Corporation Jiaxing314033 China Huaxin Consulting and Designing Institute Co. Ltd. Hangzhou China

ISBN: (数字)9783030901967

ISBN: (纸本)9783030901950

This paper introduces the target localization experiment using the digital television terrestrial broadcasting (DTMB) signal. Firstly, the feasibility and advantages of DTMB signal as an external illumination source signal are analyzed. Then the ambiguity function of DTMB signal is analyzed, as well as its distance and Doppler resolution. ECA algorithm is introduced to suppress direct wave and multipath clutter. In order to obtain the positioning results of target, the array antenna is used as the direction-finding antenna to measure the azimuth angle of target. Finally, the target localization experiment based on DTMB signal is designed, and the localization information of target is determined by combining the actual position of TV Tower and receiver in two dimensions. © 2021, ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Clutter (information theory)

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Double-RIS Enabled Physical Layer security for Wireless-Powered communication Systems Over Rayleigh Fading Channels

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IEEE Transactions on communications 2025年

作者： Chen, Jingyu Cao, Kunrui Ding, Haiyang Lv, Lu Ye, Yinghui Chi, Haolian Wang, Tao Yang, Liang National University of Defense Technology School of Information and Communications Wuhan430035 China Xidian University School of Telecommunications Engineering Xi'an710071 China Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security Xi'an710121 China Hunan University College of Computer Science and Electronic Engineering Changsha410082 China

This paper investigates the physical layer security for a double-reconfigurable intelligent surface (DRIS) aided wireless-powered communication (WPC) system in the presence of an eavesdropper, where one RIS (termed as RIS-1) is deployed between power station (PS) and information user (U) while the other RIS (termed as RIS-2) is deployed between U and access point (AP). Moreover, an idle user acts as a cooperative jamming user (J) to emit the artificial noise to improve the transmission security of U. According to different types in energy harvesting (EH) and information transmission (IT)/noise transmission (NT) of U/J, we propose four DRIS enabled wireless-powered cooperative jamming transmission schemes based on jointly enhancing EH and IT of U (namely DRIS-1), jointly enhancing EH of U and NT of J (namely DRIS-2), jointly enhancing EH of J and IT of U (namely DRIS-3), and jointly enhancing EH and NT of J (namely DRIS-4), respectively. We analyze connection outage probability (COP), secrecy outage probability (SOP), and effective secrecy throughput (EST) of the proposed four schemes, respectively. The results show that DRIS-1 scheme has the highest diversity gain among the four schemes. Besides, the gain of the number of reflecting elements at RIS-1 has the same order as that at RIS-2 in DRIS-1 scheme and DRIS-4 scheme. In DRIS-2 scheme, the gains of the number of reflecting elements at RIS-1 and RIS-2 are two powers and one power, respectively, while the opposite is true in DRIS-3 scheme. In addition, DRIS-1 scheme achieves the best COP, while DRIS-4 scheme achieves the best SOP. DRIS-1 scheme, DRIS-3 scheme, and DRIS-4 scheme respectively achieve the best EST in the low, middle, and high region of transmission power or number of RIS elements. © 1972-2012 IEEE.

关键词： Inductive power transmission

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Secure Computation Offloading via Cooperative Jamming in Marine IoT Networks

Secure Computation Offloading via Cooperative Jamming in Mar...

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GLOBECOM 2022 - 2022 IEEE Global communications Conference

作者： Li Ping Qian Mingqing Li Xinyu Dong Yuan Wu Xiaoniu Yang College of Information Engineering Zhejiang University of Technology Hangzhou Zhejiang China Department of Computer and Information Science University of Macau Macao SAR China State Key Laboratory of Internet of Things for Smart City University of Macau Macao SAR China Science and Technology on Communication Information Security Control Laboratory Jiaxing China Institute of Cyberspace Security Zhejiang University of Technology Hangzhou China

ISBN: (纸本)9781665435413

Edge computing has been envisioned as a promising approach to enable the computation-intensive yet latencysensitive marine mobile services in the fifth generation and beyond wireless networks. In this paper, we investigate the edge computing in Marine Internet of Things (M-IoT) via the assistance of unmanned surface vehicles (USVs) subject to the eavesdropping attack. In particular, we consider a scenario in which USVs are exploited to provide cooperative jamming for the communication security at the physical layer when the high altitude platform (HAP) is performing task offloading transmission. We jointly optimize the workload offloaded by HAP, the HAP's transmission power as well as each USV's interfering signal power with the objective of minimizing the total energy consumption for completing the total workloads under the latency constraint. The bisection search method is first adopted to obtain the optimal solutions to the offloaded workload and each USV's interfering signal power. Further, by exploiting the monotonicity, the polyblock outer approximation based algorithm (POA-Algorithm) is designed to obtain the HAP's optimal transmission power. Finally, numerical results validate the optimality and effectiveness of our proposed algorithm by comparing it with the results of LINGO and different jamming schemes.

关键词： Energy consumption Wireless networks Search methods Physical layer Approximation algorithms security Jamming

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An Efficient Medical Image Deep Fusion Model Based on Convolutional Neural Networks

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Computers, Materials & Continua 2023年第2期74卷 2905-2925页

作者： Walid El-Shafai Noha A.El-Hag Ahmed Sedik Ghada Elbanby Fathi E.Abd El-Samie Naglaa F.Soliman Hussah Nasser AlEisa Mohammed E.Abdel Samea Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafr El-SheikhEgypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Medical Imaging and Interventional Radiology National Liver InstituteMenoufia UniversityEgypt

Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and *** learning provides a high performance for several medical image analysis *** paper proposes a deep learning model for the medical image fusion *** model depends on Convolutional Neural Network(CNN).The basic idea of the proposed model is to extract features from both CT and MR ***,an additional process is executed on the extracted *** that,the fused feature map is reconstructed to obtain the resulting fused ***,the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching(HM),Histogram Equalization(HE),fuzzy technique,fuzzy type,and Contrast Limited Histogram Equalization(CLAHE).The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement *** realistic datasets of different modalities and diseases are tested and ***,real datasets are tested in the simulation analysis.

关键词： Image fusion CNN deep learning feature extraction evaluation metrics medical diagnosis

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