检索结果-内蒙古大学图书馆

SSRN 2024年

作者： Zhang, Chi Han, Xu Zhang, Min Cui, Ruirui Deng, Chaoyong Yan, Jingjing Hang, Yuan Ji, Miaoxin Dong, Zhe You, Xianglong College of Electrical Engineering Henan University of Technology Zhengzhou450001 China Key Laboratory of Functional Composite Materials of Guizhou Province College of Big Data and Information Engineering Guizhou University Guiyang550025 China State Key Laboratory of Public Big Data Guizhou University Guiyang550025 China College of Mechanical and Vehicle Engineering Chongqing University Chongqing400044 China Guiyang University China

Solid state reaction method is most commonly used to synthesize Sr2MgSi2O7: Eu2+, Dy3+ phosphors. In order to avoid the energy waste caused by high sintering temperature, we systematically studied and optimized the preparation process of Sr2MgSi2O7: Eu2+, Dy3+ long afterglow phosphors by increasing the Si/Sr ratio in the raw materials. The appropriate addition of silica not only facilitates the preparation of single phase Sr2MgSi2O7: Eu2+, Dy3+ phosphor but also enhances the rate of solid state reaction, so as to achieve the purpose of reducing the sintering temperature. The photoluminescence property of Si/Sr=1.3 sample sintered at 1300℃ exhibits a similarity to that of Si/Sr=1 sample sintered at 1400℃, while in terms of the afterglow property, the former demonstrates an enhancement by a factor of 3.5 compared to the latter. Thus, the sintering temperature can be reduced by at least 100℃. Additionally, the electronic structures of the Sr2MgSi2O7 host, the doped luminescence center Eu, the oxygen vacancies and the co-doped activator Dy have been methodically investigated through first-principles calculations. By integrating the findings on the distribution of the dopants and defects levels, we predict and propose the photoluminescence and afterglow mechanisms of Sr2MgSi2O7: Eu2+, Dy3+. The afterglow performance primarily depends on the concentration of electron traps. The calculation results demonstrate that the trap levels that can effectively capture electrons include both oxygen vacancies (VO and VO2+ shallow traps) and Dy 4f levels (deep traps). The increase of Si/Sr ratio can enhance the number of oxygen vacancies and the effective density of Dy3+ ions in the host, thus increasing the number of captured electrons and improving the afterglow performance. These studies suggest an efficient, cheap and energy-saving strategy for the preparation of Sr2MgSi2O7: Eu2+, Dy3+ long afterglow phosphor, and reveal the roles of oxygen vacancies and co-doped Dy in the aftergl

关键词： Magnesium compounds

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Angular distribution measurement for ^12C fragmentation via ^12C ＋ ^12C scattering at 100 MeV/u

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Chinese Physics C 2018年第7期42卷 30-36页

作者： Wei-Wei Qu Gao-Long Zhang Guo-Yu Tian Zhi-Qiang Chen Shou-Ping Xu Royichi Wada State Key Laboratory of Radiation Medicine and Protection School of Radiation Medicine and ProtectionSoochow UniversitySuzhou 215123China Collaborative Innovation Center of Radiological Medicine of Jiangsu Higher Education Institutions Suzhou 215123China School of Physics and Nuclear Energy Engineering Beihang UniversityBeijing 100191China Beijing Advanced Innovation Center for Big Data-based Precision Medicine Beihang UniversityBeijing100083China Institute of Modern Physics Chinese Academy of SciencesLanzhou 730000China Department of Radiation Oncology PLA General HospitalBeijing 100853China Cyclotron Institute Texas A&M UniversityCollege StationTexas 77843USA

The angular distributions and energy spectra of 11B, 10B, and 9Be fragments of 12C in the angular range from 1.0° to 7.5° at 100 MeV/u were obtained via 12C ＋ 12C scattering. Detailed comparisons are presented between the experimental data and the modified antisymmetrized molecular dynamics （AMD-FM）, binary intranuclear cascade model （BIC） and Liège intranuclear cascade model （INCL＋＋）. The experimental angular distributions and energy spectra are well reproduced by the AMD-FM calculations but fail to be reproduced by the physical models installed in the Geant4 program, including the BIC and INCL＋＋ models.

关键词： breakup angular distribution AMD Geant4 simulation

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Privacy-Preserved Neural Graph Similarity Learning

arXiv

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arXiv 2022年

作者： Hou, Yupeng Zhao, Wayne Xin Li, Yaliang Wen, Ji-Rong Gaoling School of Artificial Intelligence Renmin University of China China Alibaba Group China Beijing Key Laboratory of Big Data Management and Analysis Methods China Engineering Research Center of Next-Generation Intelligent Search and Recommendation Ministry of Education

To develop effective and efficient graph similarity learning (GSL) models, a series of data-driven neural algorithms have been proposed in recent years. Although GSL models are frequently deployed in privacy-sensitive scenarios, the user privacy protection of neural GSL models has not drawn much attention. To comprehensively understand the privacy protection issues, we first introduce the concept of attackable representation to systematically characterize the privacy attacks that each model can face. Inspired by the qualitative results, we propose a novel Privacy-Preserving neural Graph Matching network model, named PPGM, for graph similarity learning. To prevent reconstruction attacks, the proposed model does not communicate node-level representations between devices. Instead, we learn multi-perspective graph representations based on learnable context vectors. To alleviate the attacks to graph properties, the obfuscated features that contain information from both graphs are communicated. In this way, the private properties of each graph can be difficult to infer. Based on the node-graph matching techniques while calculating the obfuscated features, PPGM can also be effective in similarity measuring. To quantitatively evaluate the privacy-preserving ability of neural GSL models, we further propose an evaluation protocol via training supervised black-box attack models. Extensive experiments on widely-used benchmarks show the effectiveness and strong privacy-protection ability of the proposed model PPGM. The code is available at: https://***/RUCAIBox/PPGM. © 2022, CC BY.

关键词： Graph neural networks

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Generative Aspect Based Sentiment Analysis for Online Health Community with data Augmentation

SSRN

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SSRN 2023年

作者： Han, Pu Ye, Dongyu Gu, Liang Chen, Wenqi Wei, Hongchen Li, Xiaoyan School of Management Nanjing University of Posts & Telecommunications Nanjing210003 China Jiangsu Provincial Key Laboratory of Data Engineering and Knowledge Service Nanjing210023 China School of Basic Medical Sciences Nanjing Medical University Nanjing210029 China

Accurate analysis of patients' feedback on various medical aspects is of great importance for improving the quality of healthcare services. In this paper, we address the task of extracting aspects and opinions by adopting a generative end-to-end deep learning model. And we address the challenge of limited high-quality labeled data in aspect-based sentiment analysis by introducing a data augmentation method. To evaluate the effectiveness of our proposed generative model and data augmentation technique in the healthcare domain, we collected reviews related to diagnosis and treatment from online health communities(OHC) and verified the effectiveness of the proposed model. The experimental results demonstrate the superiority of generative models in complex aspect-based sentiment analysis tasks, showing a noteworthy nearly 13% increase in F1 score. Furthermore, we find that our data augmentation method is effective in enhancing the experimental outcomes. Our work contributes to the advancement of natural language processing techniques in the healthcare domain, and it has the potential to improve the quality of healthcare services through more fine-grained analysis of patients' feedback. Our code and dataset are available at https://***/woloc/OHC_*** now. © 2023, The Authors. All rights reserved.

关键词： Sentiment analysis

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Dual Prompt-Based Few-Shot Learning for Automated Vulnerability Patch Localization

Dual Prompt-Based Few-Shot Learning for Automated Vulnerabil...

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IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Junwei Zhang Xing Hu Lingfeng Bao Xin Xia Shanping Li The State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou China Software Engineering Application Technology Lab Huawei China

ISBN: (数字)9798350330663

ISBN: (纸本)9798350330670

Vulnerabilities are disclosed with corresponding patches so that users can remediate them in time. However, there are instances where patches are not released with the disclosed vulnerabilities, causing hidden dangers, especially if dependent software remains uninformed about the affected code repository. Hence, it is crucial to automatically locate security patches for disclosed vulnerabilities among a multitude of commits. Despite the promising performance of existing learning-based localization approaches, they still suffer from the following limitations: (1) They cannot perform well in data scarcity scenarios. Most neural models require extensive datasets to capture the semantic correlations between the vulnerability description and code commits, while the number of disclosed vulnerabilities with patches is limited. (2) They struggle to capture the deep semantic correlations between the vulnerability description and code commits due to inherent differences in semantics and characters between code changes and commit messages. It is difficult to use one model to capture the semantic correlations between vulnerability descriptions and code commits. To mitigate these two limitations, in this paper, we propose a novel security patch localization approach named Prom VPat, which utilizes the dual prompt tuning channel to capture the semantic correlation between vulnerability descriptions and commits, especially in data scarcity (i.e., few-shot) scenarios. We first input the commit message and code changes with the vulnerability description into the prompt generator to generate two new inputs with prompt templates. Then, we adopt a pre-trained language model (i.e., PLM) as the encoder, utilize the prompt tuning method to fine-tune the encoder, and generate two correlation probabilities as the semantic features. In addition, we extract 26 handcrafted features from the vulnerability descriptions and the code commits. Finally, we utilize the attention mechanism to fuse the

关键词： Location awareness Codes Correlation Semantics PROM Feature extraction Software

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Preconditioned deconvolution method for high-resolution ghost imaging

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Photonics Research 2021年第6期9卷 1069-1077页

作者： ZHISHEN TONG ZHENTAO LIU CHENYU HU JIAN WANG SHENSHENG HAN Key Laboratory of Quantum Optics of CAS Shanghai Institute of Optics and Fine MechanicsChinese Academy of SciencesShanghai 201800China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China School of Data Science Fudan UniversityShanghai 200433China ZJLab Shanghai Key Laboratory of Intelligent Information ProcessingShanghai 200433China Hangzhou Institute for Advanced Study University of Chinese Academy of SciencesHangzhou 310024China

Ghost imaging(GI)can nonlocally image objects by exploiting the fluctuation characteristics of light fields,where the spatial resolution is determined by the normalized second-order correlation function g^(2) .However,the spatial shift-invariant property of g^(2) is distorted when the number of samples is limited,which hinders the deconvolution methods from improving the spatial resolution of *** this paper,based on prior imaging systems,we propose a preconditioned deconvolution method to improve the imaging resolution of GI by refining the mutual coherence of a sampling matrix in *** theoretical analysis shows that the preconditioned deconvolution method actually extends the deconvolution technique to GI and regresses into the classical deconvolution technique for the conventional imaging *** imaging resolution of GI after preconditioning is restricted to the detection *** simulation and experimental results show that the spatial resolution of the reconstructed image is obviously enhanced by using the preconditioned deconvolution *** the experiment,1.4-fold resolution enhancement over Rayleigh criterion is achieved via the preconditioned *** results extend the deconvolution technique that is only applicable to spatial shift-invariant imaging systems to all linear imaging systems,and will promote their applications in biological imaging and remote sensing for high-resolution imaging demands.

关键词： ghost Ghost resolution

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Densely packed object detection with transformer-based head and EM-merger

Densely packed object detection with transformer-based head ...

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作者： Zhong, Xiaojing Zhang, Ni Hu, Hao Li, Li Cen, Junhua Wu, Qingyao School of Software Engineering South China University of Technology Guangzhou China Key Laboratory of Big Data and Intelligent Robot Ministry of Education Guangzhou China Pazhou Lab Guangzhou China Peng Cheng Laboratory Guangzhou China Zhongnan Building Materials Group Co. Ltd. Guangdong GW Guangzhou China Internet Technology Co. Ltd. Guangdong GW Guangzhou China

Due to the high density of objects and their varying sizes, detecting them accurately and without repetition in such scenarios is more challenging than traditional object detection methods. In this paper, we propose a YOLOv5-based object detection approach equipped with a Transformer-based Head and EM-Merger unit specifically designed for densely packed scenes. We incorporate the transformer architecture into the prediction heads to enable a self-attention mechanism that captures long-term dependencies between the densely packed objects. Additionally, we introduce an EM-Merger unit to resolve redundant object detections. Experimental results on the RebarDSC and SKU110K datasets demonstrate that our method significantly outperforms the baseline approach, achieving new state-of-the-art detection performance. © 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.

关键词： Object detection

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Takeover Performance and Workload under Varying Automation Levels, Time Budget and Road Curvature

Takeover Performance and Workload under Varying Automation L...

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2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2022

作者： Xu, Chengliang Li, Penghui Li, Yibing Merat, Natasha Lu, Ziwang Guo, Xing Tsinghua University State Key Laboratory of Automotive Safety and Energy School of Vehicle and Mobility Beijing China Beijing Jiaotong University Key Lab. of Transport Industry of Big Data Application Technologies for Comprehensive Transport School of Traffic and Transportation Beijing China University of Leeds Institute for Transport Studies Leeds United Kingdom Beijing Information Science and Technology University School of Mechanical and Electrical Engineering Beijing China

ISBN: (纸本)9781665409025

In SAE Level 2 (L2) and Level 3 (L3) automated driving, drivers are required to take over control from automation when reaching system boundaries. The length of time budget is the vital parameter that needs to be determined to ensure a safe takeover manner. Existing literature on this issue rarely considers potential interactions between time budget and other factors, and a variable time budget seemed to be paradoxical in critical unplanned transitions. To this end, this study investigated drivers' takeover performance and workload under varying automation levels, time budget and road curvature. We employed the operational design domain (ODD) exiting event as the transition scenario where the ego car was about to leave the highway. Results showed that drivers in L3 takeovers performed worse and elicited higher workload than L2 when entering a curved ramp with a limited time budget. Takeovers when entering a curved ramp yielded worse performance and higher workload, as compared to entering a straight ramp. Such detrimental effects caused by loss of situation awareness (SA) and change of road curvature can be mitigated by increasing the length of time budget. All these findings suggest that even in simplified ODD exiting scenarios, the length of time budget should vary according to the state of the driver and the environment. © 2022 IEEE.

关键词： Automation

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New Markov model used for path prediction over WLAN

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Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin university (engineering and Technology Edition) 2006年第SUPPL. 1期36卷 24-28页

作者： Yu, Xue-Gang Liu, Yan-Heng Wei, Da Tian, Ming Wang, Pin College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Changchun 130012 China Department of Mathematics Ocean University of China Qingdao 266003 China

In order to reduce the complexity of the state space in Order-k Markov predictor, a new Step-2 Markov predictor is proposed to make path prediction over WLAN. The feasibility of the Step-2 Markov predictor is proved by calculating and comparing conditional entropy of Step-2 and Order-k Markov predictors. And the paper also analyzes and compares the prediction accuracy of the two kinds of Markov predictors using actual Wi-Fi trace data. The work shows that the Step-2 Markov predictor is more stable than Order-1 Markov predictor for different length trace files and it also reduces the complexity of the Markov state space dramatically and gets approximately the same prediction accuracy with Order-2 Markov predictor and higher accuracy than Order-k (k≠2) Markov predictors.

关键词： Local area networks

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Technical Function-effect Based Patent Multi-to-One Negation Game Model 25

Technical Function-effect Based Patent Multi-to-One Negation...

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25th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022

作者： Du, Lu Liu, Weidong Xiao, Kaiyang Gao, Shixuan Han, Yong College of Computer Science Inner Mongolia University Hohhot China Institute of Scientific and Technical Information of China Beijing China Natl. and Loc. Jt. Eng. Res. Center of Intelligent Information Processing Technology for Mongolian Hohhot China Inner Mongolia Key Laboratory of Social Computing and Data Processing Hohhot China Inner Mongolia Engineering Laboratory for Big Data Analysis Technology Hohhot China Inner Mongolia Intellectual Property Service Center Hohhot China

ISBN: (纸本)9781665405270

As the number of patent applications increases yearly, the negation relation between patents has become intertwined, which makes it difficult for constructing negation relation in patent examination manually. Therefore, how to automatically construct negation relation between patents has become the hot research. Constructing negation relation is the process of comparing technical features between patents, which depends on the technical features in the patent claims and the technical function-effect. Although there are many researches on patent one-to-one negation, few researches on patent multi-to-one negation. The research on negation relation of multi-to-one patents, has the following challenges: (1) the definition of patent features is ambiguous in comparison of negation relation;(2) the role of patent function-effect is often ignored in judgement of negation relation. To solve the above issues, we propose a technical function-effect based patent multi-to-one negation game model. In the model, we decompose patent technical features into technical utility and technical function-effect. Patent technical utility is mainly realized by using the valence theory in linguistics. After obtaining technical utility, we choose to have the same technical effect, express the technical features of different technical functions, and obtain the patent technical function-effect. Finally, we combine the technical utility and function-effect to construct a technical utility/function-effect game tree to judge the patent negation relation. According to the two-tailed test in the A/B-test, our model outperforms the baseline model in the evaluation measurement. This model can subsequently be used to calculate the portfolio value and the strategic value of the patents. © 2022 IEEE.

关键词： Patents and inventions

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