检索结果-内蒙古大学图书馆

Spatiotemporal nonlinear dynamics in multimode fiber laser based on carbon nanotubes

Frontiers of physics 2024年第5期19卷 179-184页

作者： Jingxuan Sun Yachen Wang Congyu Zhang Lijun Xu Bo Fu Key Laboratory of Precision Opto-Mechatronics Technology School of Instrumentation and Optoelectronic EngineeringBeihang UniversityBeijing 100191China Key Laboratory of Big Data-Based Precision Medicine Ministry of Industry and Information TechnologySchool of Engineering MedicineBeihang UniversityBeijing 100191China

We investigated 1-μm multimode fiber laser based on carbon nanotubes,where multiple typical pulse states were observed,including Q-switched,Q-switched mode-locked,and spatiotemporal mode-locked ***,stable spatiotemporal mode-locking was realized with a low threshold,where the pulse duration was 37 ps and the wavelength was centred at 1060.5 ***,both the high signal to noise and long-term operation stability proved the reliability of the mode-locked ***,the evolution of the spatiotemporal mode-locked pulses in the cavity was also simulated and *** work exhibits the flexible outputs of spatiotemporal phenomena in multimode lasers based on nanomaterials,providing more possibilities for the development of high-dimensional nonlinear dynamics.

关键词： spatiotemporal mode-locking multimode fiber saturable absorber ultrafast laser

来源：评论

学校读者我要写书评

暂无评论

Hadamard Encoding Based Frequent Itemset Mining under Local Differential Privacy

引用

Journal of Computer Science & Technology 2023年第6期38卷 1403-1422页

作者：赵丹赵素云陈红刘睿瑄李翠平张晓莹 Institute of Scientific and Technical Information of China Beijing 100038China Key Laboratory of Data Engineering and Knowledge Engineering(Ministry of Education) School of InformationRenmin University of ChinaBeijing 100872China

Local differential privacy(LDP)approaches to collecting sensitive information for frequent itemset mining(FIM)can reliably guarantee *** current approaches to FIM under LDP add"padding and sampling"steps to obtain frequent itemsets and their frequencies because each user transaction represents a set of *** current state-of-the-art approach,namely set-value itemset mining(SVSM),must balance variance and bias to achieve accurate ***,an unbiased FIM approach with lower variance is highly *** narrow this gap,we propose an Item-Level LDP frequency oracle approach,named the Integrated-with-Hadamard-Transform-Based Frequency Oracle(IHFO).For the first time,Hadamard encoding is introduced to a set of values to encode all items into a fixed vector,and perturbation can be subsequently applied to the *** FIM approach,called optimized united itemset mining(O-UISM),is pro-posed to combine the padding-and-sampling-based frequency oracle(PSFO)and the IHFO into a framework for acquiring accurate frequent itemsets with their ***,we theoretically and experimentally demonstrate that O-UISM significantly outperforms the extant approaches in finding frequent itemsets and estimating their frequencies under the same privacy guarantee.

关键词： local differential privacy frequent itemset mining frequency oracle

来源：评论

学校读者我要写书评

暂无评论

A DDoS Identification Method for Unbalanced data CVWGG

引用

Computers, Materials & Continua 2024年第12期81卷 3825-3851页

作者： Haizhen Wang Na Jia Yang He Pan Tan College of Computer and Control Engineering Qiqihar UniversityQiqihar161006China Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis Qiqihar UniversityQiqihar161006China

As the popularity and dependence on the Internet increase,DDoS(distributed denial of service)attacks seriously threaten network *** accurately distinguishing between different types of DDoS attacks,targeted defense strategies can be formulated,significantly improving network protection *** attacks usually manifest as an abnormal increase in network traffic,and their diverse types of attacks,along with a severe data imbalance,make it difficult for traditional classification methods to effectively identify a small number of attack *** solve this problem,this paper proposes a DDoS recognition method CVWGG(Conditional Variational Autoencoder-Wasserstein Generative Adversarial Network-gradient penalty-Gated Recurrent Unit)for unbalanced data,which generates less noisy data and high data quality compared with existing *** mainly includes unbalanced data processing for CVWG,feature extraction,and *** uses the CVAE(Conditional Variational Autoencoder)to improve the WGAN(Wasserstein Generative Adversarial Network)and introduces a GP(gradient penalty)term to design the loss function to generate balanced data,which enhances the learning ability and stability of the ***,the GRU(Gated Recurrent Units)are used to capture the temporal features and patterns of the ***,the logsoftmax function is used to differentiate DDoS attack *** PyCharm and Python 3.10 for programming and evaluating performance with metrics such as accuracy and precision,the results show that the method achieved accuracy rates of 96.0%and 97.3%on two datasets,***,comparison and ablation experiment results demonstrate that CVWGG effectively mitigates the imbalance between DDoS attack categories,significantly improves the classification accuracy of different types of attacks and provides a valuable reference for network security defense.

关键词： Conditional variational autoencoder generating adversarial networks DDoS attack

来源：评论

学校读者我要写书评

暂无评论

A Frequency and Polarization Reconfigurable Transparent Water Antenna

引用

Progress in Electromagnetics Research C 2025年 152卷 177-186页

作者： Li, Lei Gao, Jing Nan, Jingchang School of Electronics and Information Engineering Liaoning Technical University Huludao125105 China Liaoning Key Laboratory of Radio Frequency and Big Data for Intelligent Applications Huludao125105 China

A novel frequency and polarization reconfigurable water patch antenna is proposed for radio communication in the UHF band. Based on theoretical analysis and simulation results, water is an ideal material for designing transparent liquid ground. Water enhances outstanding transparency, excellent aesthetics, and high optical stealth performance for a wider range of application scenarios. The entire structure is made with polyvinyl chloride material and distilled water, except for the feed structure. By filling different cavities with liquid water, five different operating states are obtained in 1.924–2.5 GHz (26.1%), 1.67–2.33 GHz (33%), 0.644–2.288 GHz (112.1%), 1.975–2.54 GHz (25%), and 1.748–2.108 GHz (18.7%), achieving frequency reconfigurability. The antenna can be flexibly switched between linear polarization (LP) and two right-handed circular polarization (RHCP) states. The results show that the 3 dB axial ratio (AR) bandwidth covers 1.93–2.08 GHz (7.5%) and 2.06–2.132 GHz (3.5%). The antenna achieves high optical transparency of 100% and a peak gain of 7.97 dBi. © 2025, Electromagnetics Academy. All rights reserved.

关键词： Circular polarization

来源：评论

学校读者我要写书评

暂无评论

data-driven unsupervised anomaly detection and recovery of unmanned aerial vehicle flight data based on spatiotemporal correlation

引用

Science China(Technological Sciences) 2023年第5期66卷 1304-1316页

作者： YANG Lei LI ShaoBo LI ChuanJiang ZHU CaiChao ZHANG AnSi LIANG GuoQiang School of Mechanical Engineering Guizhou UniversityGuiyang550025China State Key Laboratory of Public Big Data Guizhou UniversityGuiyang550025China State Key Laboratory of Mechanical Transmission Chongqing UniversityChongqing400044China

Anomaly detection is crucial to the flight safety and maintenance of unmanned aerial vehicles(UAVs)and has attracted extensive attention from ***-based approaches rely on prior knowledge,while model-based approaches are challenging for constructing accurate and complex physical models of unmanned aerial systems(UASs).Although data-driven methods do not require extensive prior knowledge and accurate physical UAS models,they often lack parameter selection and are limited by the cost of labeling anomalous ***,flight data with random noise pose a significant challenge for anomaly *** work proposes a spatiotemporal correlation based on long short-term memory and autoencoder(STCLSTM-AE)neural network data-driven method for unsupervised anomaly detection and recovery of UAV flight ***,UAV flight data are preprocessed by combining the Savitzky-Golay filter data processing technique to mitigate the effect of noise in the original historical flight data on the ***-based feature subset selection is subsequently performed to reduce the reliance on expert ***,the extracted features are used as the input of the designed LSTM-AE model to achieve the anomaly detection and recovery of UAV flight data in an unsupervised ***,the method's effectiveness is validated on real UAV flight data.

关键词： unmanned aerial vehicle(UAV) anomaly detection spatiotemporal correlation based on long short-term memory and autoencoder(STC-LSTM-AE) Savitzky-Golay feature selection

来源：评论

学校读者我要写书评

暂无评论

Multicomponent Similarity Graphs for Cross-Network Node Classification

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第3期5卷 1411-1424页

作者： Zhang, Yuhong Shi, Congmei Li, Xinzheng Zhang, Zan Hu, Xuegang School of Computer Science and Information Engineering Hefei University of Technology Hefei230601 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230088 China Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education Hefei230009 China

Cross-network node classification aims to train a classifier for an unlabeled target network using a source network with rich labels. In applications, the degree of nodes mostly conforms to the long-tail distribution, i.e., most nodes in the network are tail nodes with sparse neighborhoods. The established methods focus on either the discrepancy cross network or the long tail in a single network. As for the cross-network node classification under long tail, the coexistence of sparsity of tail nodes and the discrepancy cross-network challenges existing methods for long tail or methods for the cross-network node classification. To this end, a multicomponent similarity graphs for cross-network node classification (MS-CNC) is proposed in this article. Specifically, in order to address the sparsity of the tail nodes, multiple component similarity graphs, including attribute and structure similarity graphs, are constructed for each network to enrich the neighborhoods of the tail nodes and alleviate the long-tail phenomenon. Then, multiple representations are learned from the multiple similarity graphs separately. Based on the multicomponent representations, a two-level adversarial model is designed to address the distribution difference across networks. One level is used to learn the invariant representations cross network in view of structure and attribute components separately, and the other level is used to learn the invariant representations in view of the fused structure and attribute graphs. Extensive experimental results show that the MS-CNC outperforms the state-of-the-art methods. Impact Statement-Node classification is an important task in graph mining. With the unavailability of labels, some researchers propose cross-network node classification, using one labeled network to assist the node classification of another unlabeled network. However, the long-tail of nodes leads to unsatisfactory performance and challenges the recent cross-network node classification m

关键词： Graphic methods

来源：评论

学校读者我要写书评

暂无评论

Discovering Reliable Information Extraction Patterns with Pre-Trained Model for Text with Writing Style

Discovering Reliable Information Extraction Patterns with Pr...

引用

2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Bu, Chenyang Liu, Jiacheng Liu, Jiaxuan Ji, Shengwei Yang, Hongbin School of Computer Science and Information Engineering Ministry of Education Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Anhui Hefei230027 China School of Artificial Intelligence and Big Data Hefei University China

ISBN: (纸本)9798350337020

Large-scale pre-trained models such as GPT and BERT have demonstrated remarkable performance in information extraction tasks. However, their black-box nature poses challenges for reliability and interpretability. In contrast, rule- based extraction methods have better interpretability, but typically require domain experts to manually establish rules, limiting their generalization ability. In industry, there is often a demand for reliable knowledge extraction to reduce the time spent on manual verification of each piece of knowledge. In this paper, we explore the idea of combining GPT and symbolic-based methods to automatically discover reliable extraction patterns in text with a particular writing style. This method leverages the characteristics of high information density and similar writing patterns in text with a specific writing style to generate verifiable and reliable patterns. We conduct experiments on two datasets with a specific writing style to demonstrate its effectiveness, validating the idea of combining large models for reliable information extraction pattern discovery in the tested datasets. © 2023 IEEE.

关键词： Information extraction Reliable pattern Writing style data

来源：评论

学校读者我要写书评

暂无评论

Joint user profiling with hierarchical attention networks

引用

Frontiers of Computer Science 2023年第3期17卷 133-143页

作者： Xiaojian LIU Yi ZHU Xindong WU Key Laboratory of Knowledge Engineering with Big Data(Hefei University of Technology) Ministry of EducationHefei 230009China School of Computer Science and Information Engineering Hefei University of TechnologyHefei 230009China School of Information Engineering Yangzhou UniversityYangzhou 225009China Mininglamp Academy of Sciences MininglampBeijing 100193China

User profiling by inferring user personality traits,such as age and gender,plays an increasingly important role in many real-world *** existing methods for user profiling either use only one type of data or ignore handling the noisy information of ***,they usually consider this problem from only one *** this paper,we propose a joint user profiling model with hierarchical attention networks(JUHA)to learn informative user representations for user *** JUHA method does user profiling based on both inner-user and inter-user *** explore inner-user features from user behaviors(e.g.,purchased items and posted blogs),and inter-user features from a user-user graph(where similar users could be connected to each other).JUHA learns basic sentence and bag representations from multiple separate sources of data(user behaviors)as the first round of data *** this module,convolutional neural networks(CNNs)are introduced to capture word and sentence features of age and gender while the self-attention mechanism is exploited to weaken the noisy *** this,we build another bag which contains a user-user ***-user features are learned from this bag using propagation information between linked users in the *** acquire more robust data,inter-user features and other inner-user bag representations are joined into each sentence in the current bag to learn the final bag ***,all of the bag representations are integrated to lean comprehensive user representation by the self-attention *** experimental results demonstrate that our approach outperforms several state-of-the-art methods and improves prediction performance.

关键词： user profiling hierarchical attention joint learning inner-user feature inter-user feature

来源：评论

学校读者我要写书评

暂无评论

Preparation and characterization of a new orange-red phosphor Ba_(2)LaTaO_(6):Eu^(3+)with abnormal thermal quenching

引用

Journal of Rare Earths 2023年第11期41卷 1678-1688,I0002页

作者： Fadong Li Ruirui Cui Gaofeng Yuan Xin Zhang Min Zhang Chaoyong Deng School of Electronics and Information Engineering Guiyang UniversityGuiyang550005China Key Laboratory of Functional Composite Materials of Guizhou Province College of Big Data and Information EngineeringGuizhou UniversityGuiyang550025China

Herein,double-perovskite Ba_(2)LaTaO_(6) Eu-doped orange-red phosphors were successfully synthesized using a high-temperature solid-phase *** phosphor phase purity was investigated using X-ray diffraction and microscopic morphology *** luminescence properties were investigated using absorption,emission,excitation,and temperature-dependent *** transition mechanism mainly involves a magnetic-dipole transition with an energy transfer mode featuring multipole-multipole interactions,and concentration quenching is achieved via dipole-dipole *** addition,the intensity of the temperature-dependent spectrum increases abnormally between 298 and 373 K,with the luminous intensity at 373 K increasing to 110%of that observed at room *** phenomenon can be attributed to lattice defects in Ba_(2)LaTaO_(6):Eu^(3+),and the phosphor luminous intensity at473 K remains at 80.62%of that at room *** addition,white-light-emitting diode devices based on this novel Ba_(2)LaTaO_(6):0.35Eu^(3+)phosphor were fabricated to evaluate the potential applications of the as-prepared phosphor.

关键词： Photoluminescence Orange-red phosphor Abnormal thermal quenching High thermal stability Rare earths

来源：评论

学校读者我要写书评

暂无评论

Transverse Velocity Field Measurement of Solar High-resolution Images Based on Unsupervised Deep Learning

引用

Research in Astronomy and Astrophysics 2025年第3期25卷 236-248页

作者： Zhen-Hong Shang Long Chen Zhen-Ping Qiang Yi Bi Run-Xin Li Faculty of Information Engineering and Automation Kunming University of Science and Technology Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology College of Big Data and Intelligent Engineering Southwest Forestry University Yunnan Observatories Chinese Academy of Sciences

Measuring the transverse velocity field in high-resolution solar images is essential for understanding solar *** paper introduces an innovative unsupervised deep learning optical flow model designed to calculate the transverse velocity field,addressing the challenges of missing optical flow labels and the limited accuracy of velocity field measurements in high-resolution solar *** proposed method converts the transverse velocity field computation problem into an optical flow computation problem,using two forward propagations of features to get rid of the reliance on optical flow ***,it reduces the impact of the“Brightness Consistency”constraint on optical flow accuracy by identifying and handling optical flow *** apply this method to compute the transverse velocity fields of high-resolution solar image sequences from the Hαand TiO bands,observed by the New Vacuum Solar *** experiments with several wellestablished optical flow methods,including those based on supervised deep learning models,show that our approach outperforms the comparison methods according to key evaluation metrics such as Residual Map Mean,Residual Map Variance,Cross Correlation,and Structural Similarity Index ***,since optical flow captures the fundamental motion information in image sequences,the proposed method can be applied to a variety of research areas,including solar image registration,sequence alignment,image super-resolution,magnetic field calibration,and solar activity *** code is available at https://***/jackie-willianm/Transverse-Velocity-Field-Measurement-of-Solar-High-Resolution-Images.

关键词： methods: data analysis Sun: fundamental parameters techniques: image processing

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：