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Hyperspectral imagery quality assessment and band reconstruction using the prophet model

CAAI Transactions on Intelligence technology 2025年第1期10卷 47-61页

作者： Ping Ma Jinchang Ren Zhi Gao Yinhe Li Rongjun Chen National Subsea Centre School of ComputingEngineering and TechnologyRobert Gordon UniversityAberdeenUK School of Computer Science Guangdong Polytechnic Normal UniversityGuangzhouChina School of Remote Sensing and Information Engineering Wuhan UniversityWuhanChina

In Hyperspectral Imaging(HSI),the detrimental influence of noise and distortions on data quality is profound,which has severely affected the following-on analytics and decisionmaking such as land *** study presents an innovative framework for assessing HSI band quality and reconstructing the low-quality bands,based on the Prophet *** introducing a comprehensive quality metric to start,the authors approach factors in both spatial and spectral characteristics across local and global *** metric effectively captures the intricate noise and distortions inherent in the HSI ***,the authors employ the Prophet model to forecast information within the low-quality bands,leveraging insights from neighbouring high-quality *** validate the effectiveness of the authors’proposed model,extensive experiments on three publicly available uncorrected datasets are *** a head-to-head comparison,the framework against six state-ofthe-art band reconstruction algorithms including three spectral methods,two spatialspectral methods and one deep learning method is *** authors’experiments also delve into strategies for band selection based on quality metrics and the quality evaluation of the reconstructed *** addition,the authors assess the classification accuracy utilising these reconstructed *** various experiments,the results consistently affirm the efficacy of the authors’method in HSI quality assessment and band ***,the authors’approach obviates the need for manually prefiltering of noisy *** comprehensive framework holds promise in addressing HSI data quality concerns whilst enhancing the overall utility of HSI.

关键词： band reconstruction band quality hyperspectral image(HSI) prophet model

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Journal of Shanghai Jiaotong university(science) 2024年第3期29卷 480-491页

作者：王丽张旭毅姚亚兵尉雪龙 Library Northwest Normal UniversityLanzhou 730070China Department of Criminal Science and Technology Henan Police CollegeZhengzhou 450046China School of Computer and Communication Lanzhou University of TechnologyLanzhou 730050China School of Computer Science and Engineering Northeastern UniversityShenyang 110169China

This study mainly focused on the dynamic self-similar k_(c)-center network as a result of information distribution through social *** attraction with various preferences was characterized in the model as a result of reciprocal attraction among individuals and human ***,the model incorporated the community network structure and network evolution mechanism,and a dynamic self-similar k_(c)-center network generation model was *** with the classical scale-free network generation algorithm,the generated network embodied not only the characteristics of the small-world and scale-free,but also the characteristics of dynamic self-similar k_(c)-center *** experimental results were verified by comparing the real data with the experimental *** results showed that there are dynamic self-similar k_(c)-center networks and their internal network relationship dynamics in the micro scale,meso scale and global perspective based on information dissemination.

关键词： edge state evolutionary network self-similarity ke-center network

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Learning-based joint UAV trajectory and power allocation optimization for secure IoT networks

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Digital Communications and Networks 2022年第4期8卷 415-421页

作者： Dan Deng Xingwang Li Varun Menon Md Jalil Piran Hui Chen Mian Ahmad Jan School of Information Engineering Guangzhou Panyu PolytechnicGuangzhou410630China School of Physics and Electronic Information Engineering Henan Polytechnic UniversityJiaozuo454150China Department of Computer Science and Engineering SCMS School of Engineering and TechnologyIndia Department of Computer Science and Engineering Sejong UniversitySouth Korea Department of Computer Science Abdul Wali Khan University MardanPakistan

Non-Orthogonal Multiplex Access(NOMA)can be deployed in Unmanned Aerial Vehicle(UAV)networks to improve spectrum *** to the broadcasting feature of NOMA-UAV networks,it is essential to focus on the security of the wireless *** paper focuses on maximizing the secrecy sum rate under the constraint of the achievable rate of the legitimate *** tackle the non-convexity optimization problem,a reinforcement learning-based alternative optimization algorithm is ***,with the help of successive convex approximations,the optimal power allocation scheme with a given UAV trajectory is obtained by using convex optimization ***,through plenty of explorations of the wireless environment,the Q-learning networks approach the optimal location transition strategy of the UAV,even without the wireless channel state information.

关键词： Unmanned aerial vehicle(UAV) NOMA Reinforcement learning Secure communications Deep Q-learning

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Improved HHO algorithm based on good point set and nonlinear convergence formula

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The Journal of China Universities of Posts and Telecommunications 2021年第2期28卷 48-67页

作者： Guo Hairu Meng Xueyao Liu Yongli Liu Shen School of Computer Science and Technology Henan Polytechnic UniversityJiaozuo 454000China

Harris hawks optimization(HHO)algorithm is an efficient method of solving function optimization ***,it is still confronted with some limitations in terms of low precision,low convergence speed and stagnation to local *** this end,an improved HHO(IHHO)algorithm based on good point set and nonlinear convergence formula is ***,a good point set is used to initialize the positions of the population uniformly and randomly in the whole search ***,a nonlinear exponential convergence formula is designed to balance exploration stage and exploitation stage of IHHO algorithm,aiming to find all the areas containing the solutions more comprehensively and *** proposed IHHO algorithm tests 17 functions and uses Wilcoxon test to verify the *** results indicate that IHHO algorithm not only has faster convergence speed than other comparative algorithms,but also improves the accuracy of solution effectively and enhances its robustness under low dimensional and high dimensional conditions.

关键词： HHO algorithm local optimum good point set nonlinear formula multi-dimension

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Nanoimprint lithography-assisted block copolymer self-assembly for hyperfine fabrication of magnetic patterns based on L10-FePt nanoparticles

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science China Chemistry 2025年第5期68卷 2027-2034页

作者： Jie Zhang Yi Chen Guijun Li Zelin Sun Zhengong Meng Wai-Yeung Wong Department of Applied Biology and Chemical Technology and Research Institute for Smart Energy The Hong Kong Polytechnic University The Hong Kong Polytechnic University Shenzhen Research Institute Division of Integrative Systems and Design and Department of Electronic and Computer EngineeringThe Hong Kong University of Science and Technology School of Flexible Electronics (Future Technology) and Institute of Advanced Materials (IAM) Nanjing Tech University

L10-FePt-type bit-patterned media has provided a promising alternative for ultrahigh-density magnetic recording systems in the current digital era, but rapid fabrication of magnetic patterns with hyperfine bit islands is still challenging, especially with the target for miniaturization and scalable production simultaneously. Herein, Fe,Pt-containing block copolymers were utilized as single-source precursors for solution-processable patterning and subsequent generation of the demanding magnetic FePt dots by in situ pyrolysis. High-throughput nanoimprint lithography was initially employed to fabricate the predefined bit cells precisely,and then the intrinsic self-assembly of phase-separated block copolymers further drove the formation of accurate bit *** from the synergistic effect of top-down lithographic approach and bottom-up self-assembly, the customizable patterns could be achieved for large-scale mass production in targeted areas, but high-density isolated dots could also be accurately aligned along the patterned features after subsequent self-assembly. This reliable strategy would provide a good avenue to precisely construct ultrahigh-density magnetic data storage devices.

关键词： organometallic precursor magnetic nanoparticles block copolymer self-assembly nanoimprint lithography

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BraDect: A Novel Brain Tumor Image Classification Algorithm 11

BraDect: A Novel Brain Tumor Image Classification Algorithm

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11th International Conference on Networks, Communication and Computing, ICNCC 2022

作者： Tang, Chaosheng Li, Bin Sun, Junding School of Computer Science and Technology Henan Polytechnic University Henan Jiaozuo454000 China

ISBN: (纸本)9781450398039

Brain tumor is one of the common diseases of the central nervous system, and the incidence and death of brain tumors are among the highest in the world. Although the incidence of brain tumors is lower than that of other systemic tumors, due to the wide range of types and pathological types, the same pathological type is divided into different sub-grades, and has complex imaging manifestations, which makes clinical diagnosis and treatment difficult. In this paper, a new CAD model named BraDect is proposed based on the inducible bias of convolution and the high capacity of Transformer, and the fully connected layer and attention mechanism are improved, which effectively solves the problem of large amount of parameters and low efficiency in the current model. The proposed method had performed SOTA as specificity=99.83%, precision=99.84%, Recall=99.83%, F1 score=99.84%, area under the ROC curve=99%, accuracy=99.28%. © 2022 ACM.

关键词： Tumors

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Catalytic effects of V-and O-species derived from PrF_(3)/V_(2)C for efficient hydrogen storage in MgH_(2)

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Nano Research 2024年第8期17卷 7117-7125页

作者： Zhenluo Yuan Yuhang Wang Xiuxiu Zhang Shuyan Guan Xiaojiao Wang Liqiang Ji Qiuming Peng Shumin Han Yanping Fan Baozhong Liu College of Chemistry and Chemical Engineering Henan Polytechnic UniversityJiaozuo 454000China Henan Famous Diamond Co. Ltd.Mengzhou 454763China School of Chemical Engineering Zhengzhou UniversityZhengzhou 450001China Collaborative Innovation Center of Steel Technology University of Science and Technology BeijingBeijing 100083China State Key Laboratory of Metastable Materials Science and Technology Yanshan UniversityQinhuangdao 066004China

Magnesium hydride(MgH_(2))is considered as an ideal hydrogen storage material with excellent hydrogen capacity,but the slow kinetics impedes its ***,an efficient additive of V2C MXene-anchored PrF_(3) nanoparticles(PrF_(3)/V_(2)C)was synthesized,which presents excellent catalytic effect in improving the reversibility and stability of hydrogen storage in MgH_(2).The initial dehydrogenation temperature of the 5 wt.% PrF_(3)/V_(2)C-containing MgH_(2)(182℃) is 105℃ lower than that of pure MgH_(2),and 6.5 wt.%hydrogen is rapidly released from 5 wt.%PrF_(3)/V_(2)C-added MgH_(2)sample in 6 min at 240℃.In addition,5 wt.%PrF_(3)/V_(2)C-containing MgH_(2) sample possesses outstanding reversible hydrogen storage capability of 6.5 wt.% after 10 cycles of dehydrogenation and *** analysis shows that the introduction of Pr improves the stability of V-species(V^(0)and V^(2+))and O-species(lattice oxygen(OL)and vacancy oxygen(OV))formed during ball milling,promotes the interaction between V-species and O-species,and enhances their reversibility,which contributes to the significant improvement in re/dehydrogenation reversibility and cycling stability of MgH_(2).This study provides effective ideas and strategies for the purpose of designing and fabricating high-efficient catalysts for solid-state hydrogen storage materials.

关键词： hydrogen storage materials MgH_(2) dehydrogenation reversibility cyclic stability

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HybridCANet:UNet-like network Bridging CNN and Attention for Multimodal Brain Image Segmentation 11

HybridCANet:UNet-like network Bridging CNN and Attention for...

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11th International Conference on Networks, Communication and Computing, ICNCC 2022

作者： Tang, Chaosheng Dai, Chendi Sun, Junding School of Computer Science and Technology Henan Polytechnic University Henan Jiaozuo454000 China

ISBN: (纸本)9781450398039

Brain tumor is one of the diseases that seriously threaten human life and health. Accurate segmentation of tumor lesion region is an important step in image-guided radiotherapy, and also a key part in planning effective treatment strategies and preventing other diseases. In order to solve the problems of low contrast and high Imaging redundancy between adjacent organs in Magnetic Resonance Imaging images (MRI) segmentation of brain tumor. In this paper, we propose a hybrid efficient segmentation network based on a deep learning approach to extract MRI brain tumor volume feature maps using 2D convolution at the encoder, and design an Efficient Self-Attention Module (ESAM) to focus on robust feature map parameters while narrowing the parameter weights of irrelevant features. The Hybrid Cross-Attention Module (HCAM) explicitly models the correlation between the two stage feature maps in the decoder stage, and dynamically recalibrates the feature maps according to the input context features. We introduce spatial information of 3D images by fusing multi-view fusion training model. The accurate segmentation and lightweight design of MRI segmentation network will provide a powerful reference for clinicians in the diagnosis and treatment of brain tumors. © 2022 ACM.

关键词： Image segmentation

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Hydraulic fracture propagation in soft coal composite reservoirs:Mechanical responses and energy dissipation mechanisms

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International Journal of Mining science and technology 2025年第4期35卷 573-588页

作者： Aitao Zhou Yizheng He Kai Wang Bo Li Yida Wang Yuexin Yang School of Emergency Management and Safety Engineering China University of Mining and Technology-BeijingBeijing 100083China Beijing Key Laboratory for Precise Mining of Intergrown Energy and Resources China University of Mining and Technology-BeijingBeijing 100083China School of Safety Science and Engineering Henan Polytechnic UniversityJiaozuo 454003China State Key Laboratory Cultivation Base for Gas Geology and Gas Control Henan Polytechnic UniversityJiaozuo 454003China

The hydraulic fractures induced in soft coal composite reservoirs have complex extension and energy evolution *** this study,the mechanism whereby gas outbursts can be eliminated by hydraulic fracturing was *** combined fracturing process of a coal seam and its roof under different in situ stress and fracture spacing conditions was analysed through true triaxial physical tests and numerical *** results showed that the pre-fracturing of the roof had a pressure relief effect on the coal seam,and the secondary pressure relief of the coal seam could be completed at a lower fracture initiation *** ensure the continued presence of the stress shadow effect in actual projects,the fracture spacing should be maintained within the critical range influencing the fracture *** the vertical stress is high,a call on increasing the fracture spacing can be taken;otherwise,it must be *** the early phase of fracturing,energy is mostly concentrated at the tip and surface of the fracture;however,the proportion of surface energy for subsequent fracturing is gradually reduced,and the energy is mostly used to open the formation and work on the surrounding *** fracturing creates new fractures to interconnect originally heterogeneously distributed gas zones,enabling the entire coal seam to first establish interconnected pressure equilibration,then undergo gradientcontrolled *** fracturing can homogenize the stress field and gas pressure field in the original coal seam via communication pressure equalization and reduction decompression,reduce the elastic and extension energies,increase the minimum failure energy required for instability;and realize the elimination of gas *** findings provide some theoretical support for the efficient development of coalbed methane and the prevention and control of dynamic gas disasters in coal mines.

关键词： Coal-rock complex Soft coal seams Hydraulic fracturing Energy evolution Eliminating gas outburst

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Knowledge Graph Embedding of Fusion Adversarial Network and Entity-Level Information Negative Sampling Link Prediction Model 3rd

Knowledge Graph Embedding of Fusion Adversarial Network and ...

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3rd International Conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Jin, Baohua Li, Zhanpeng Li, Hongchan Zhu, Haodong The School of Computer Science and Technology Zhengzhou University of Light Industry Henan Zhengzhou450000 China

ISBN: (纸本)9789819624676

Most existing negative sampling methods for knowledge graph embedding models involve randomly selecting entities to replace the head or tail entities of factual triples to generate negative triples, resulting in lower-quality negative triples that affect the feature learning capability of entities and relationships. In order to solve this problem, after studying the factors affecting the quality of negative sampling, a knowledge graph connection prediction method based on the negative sampling of adversarial network and entity-level information is proposed. First, after inputting triple samples, model the semantic hierarchy of triples to increase hierarchical constraints. Then, based on the features of entities that are similar within the same hierarchy, select similar entities and relationships in a polar coordinate system and provide them to the generator in the adversarial network. This is used to generate high-quality negative triples for the discriminator, ultimately obtaining an ideal discriminator model, thus improving the performance of knowledge graph embedding models. Results from comparative and ablation experiments demonstrate significant improvements achieved by the proposed method in the link prediction task, thereby confirming its effectiveness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Generative adversarial networks

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