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Active Fault Tolerant Nonsingular Terminal Sliding Mode Control for Electromechanical System Based on Support Vector Machine

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Chinese Journal of Mechanical Engineering 2024年第3期37卷 189-203页

作者： Jian hu zhengyin Yang Jianyong Yao School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210094China

Effective fault diagnosis and fault-tolerant control method for aeronautics electromechanical actuator is concerned in this *** borrowing the advantages of model-driven and data-driven methods,a fault tolerant nonsingular terminal sliding mode control method based on support vector machine(SVM)is proposed.A SVM is designed to estimate the fault by off-line learning from small sample data with solving convex quadratic programming method and is introduced into a high-gain observer,so as to improve the state estimation and fault detection accuracy when the fault *** state estimation value of the observer is used for state reconfiguration.A novel nonsingular terminal sliding mode surface is designed,and Lyapunov theorem is used to derive a parameter adaptation law and a control *** is guaranteed that the proposed controller can achieve asymptotical stability which is superior to many advanced fault-tolerant *** addition,the parameter estimation also can help to diagnose the system faults because the faults can be reflected by the parameters *** comparative simulation and experimental results illustrate the effectiveness and advancement of the proposed controller compared with several other main-stream controllers.

关键词： Aeronautics electromechanical actuator Fault tolerant control Support vector machine State observer Parametric uncertainty

Building potential patent portfolios: An integrated approach based on topic identification and correlation analysis

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Chinese Journal of Library and Information Science 2015年第2期 39-51页

作者： Xian ZHANG Haiyun XU Shu FANG zhengyin hu Shuying LI Chengdu Library Chinese Academy of Sciences University of Chinese Academy of Sciences

Purpose： This paper suggests a framework to identify important patents for building potential patent portfolios based on patents owned by different assignees so as to highlight the value of individual patents in technology transfer and identify potential collaborators for patent assignees. Design/methodology/approach： The analysis framework includes the following steps： l） co-classification analysis based on the International Patent Classification （IPC） codes and Derwent Manual Codes （DMC） to detect sub-tech fields, 2） keyword co-occurrence analysis aiming to understand the core technology information in each patent, and 3） social network analysis used for identifying important technologies and partnerships of key assignees. A case study was conducted with 27,401 chemistry patents filed by a Chinese national research institute. Findings： The results show that this framework is effective in building potential technological patent portfolios based on patents owned by different assignees and identifying future collaborators for the assignees. This integrated approach based on topic identification and correlation analysis that combines network-based analysis with keyword-based analysis can reveal important patented technologies and their connections and help understand detailed technological information mentioned in patents. Research limitations： In keywords analysis, only titles and abstracts of patent documents were used and weights of keywords in different parts of the documents were not *** implications： The analysis framework provides valuable information for decision- makers of large institutions which have many patents with broad application prospects. Originality/value： Different from previous patent portfolio studies based on the use of a combination of patent analysis indicators, this study provides insights into a method of building patent portfolios to discover the potential of individual patents in technology transfer and promote cooperatio

关键词： Patent portfolio Patent cooperation Topic identification Correlation analysis Social network analysis (SNA)

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基于文献的知识发现新近研究综述

数据分析与知识发现 2021年第4期5卷 1-12页

作者：代冰胡正银中国科学院成都文献情报中心成都610041 中国科学院大学经济与管理学院图书情报与档案管理系北京100190

【目的】对基于文献的知识发现(Literature-Based Discovery,LBD)近十年的文献进行综述,了解该主题的最新研究进展、发展趋势与面临的挑战。【文献范围】在Web of Science、CNKI和百度学术中使用"literature based discovery"、"literat... 详细信息

【目的】对基于文献的知识发现(Literature-Based Discovery,LBD)近十年的文献进行综述,了解该主题的最新研究进展、发展趋势与面临的挑战。【文献范围】在Web of Science、CNKI和百度学术中使用"literature based discovery"、"literature AND knowledge discovery"、"文献知识发现"、"文献AND知识挖掘"进行检索,限定文献发表时间为2010年-2020年,共筛选出72篇代表性文献进行述评。【方法】从研究对象、方法技术、结果评估与典型应用4个方面对文献进行归纳梳理,并总结LBD的发展趋势与面临的挑战。【结果】LBD发展呈现出研究对象复杂化、分析方法智能化、发现结果丰富化与应用服务实践化的趋势;LBD在多源异构数据融合、知识发现可解释性、结果有效性评估、多领域专家协同方面面临重大挑战。【局限】主要基于文献对LBD新近进展进行综述,对LBD工具系统及产业界应用覆盖不够。【结论】作为情报学、信息学、数据科学的交叉研究领域,LBD对挖掘跨学科领域隐性知识与提供高质量学科化知识服务具有重要意义,但真正实现支持潜在的科学新发现还存在诸多挑战。

关键词：文献挖掘知识发现知识图谱文本挖掘情报研究

An SAO-based approach to technology evolution analysis using patent information: Case study—graphene sensors

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Chinese Journal of Library and Information Science 2015年第3期 62-75页

作者： zhengyin hu Shu FANG Ling WEI Yi WEN Xian ZHANG Min WANG Chengdu Documentation and Information Center Chinese Academy of Sciences University of the Chinese Academy of Sciences Department of Information Management Shanxi University of Finance & Economics Institute of Electronics Chinese Academy of Sciences

Purpose: This paper introduces an approach to technology evolution analysis using patent information based on Subject-Action-Object(SAO) ***/methodology/approach: First, SAO structures were extracted from patent documents and were cleaned. Second, several dimension-reduction techniques were used to generate technology topics. Then, the hierarchical relationships between technology topics were calculated based on patent clustering. Finally, technology evolution maps were drawn by adding a ***: This approach can reveal technology evolution processes from multiple perspectives than other *** limitations: The semantic annotation of an SAO type is not very accurate and the semantic types of technology topics need to be *** implications: The approach can be applied to draw technology evolution maps using different types of technology topics such as problem or ***/value: This approach offers an analytical dimension and more details than existing techniques, and it helps identify fundamental and emerging technologies more accurately and comprehensively.

关键词： Technology evolution Patent analysis SAO Feature d

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专利文本技术挖掘研究进展综述

现代图书情报技术 2014年第6期 62-70页

作者：胡正银方曙中国科学院成都文献情报中心成都610041 中国科学院大学北京100049

【目的】归纳基于文本专利技术挖掘通用流程,提炼其中关键技术,并对典型挖掘场景进行分析。【文献范围】以"专利挖掘、专利分析"等关键词在Elsevier、Springer、CNKI数据库进行检索,并参考全球技术挖掘相关会议,共阅读相关文献105篇,实... 详细信息

【目的】归纳基于文本专利技术挖掘通用流程,提炼其中关键技术,并对典型挖掘场景进行分析。【文献范围】以"专利挖掘、专利分析"等关键词在Elsevier、Springer、CNKI数据库进行检索,并参考全球技术挖掘相关会议,共阅读相关文献105篇,实际参考文献66篇。【方法】梳理其关键技术专利知识表示的研究现状与发展趋势,选取三类典型技术挖掘场景进行分析,通过归纳总结、提炼出专利技术挖掘未来发展趋势与研究热点。【结果】专利知识表示的粒度与结构决定了专利技术挖掘的深度、广度与维度。基于SAO基础语义单元,面向技术难题与解决方案的专利技术挖掘有望成为未来发展趋势与研究热点。【局限】本研究仅探讨现有文本挖掘、统计分析、自然语言处理技术在专利技术挖掘中的应用情况,对这些技术本身的发展趋势关注不足。【结论】本研究有助于全面了解专利技术挖掘的概貌、涉及的关键技术及主要应用场景。

关键词：专利技术挖掘语义知识表示主题聚类专利分类技术演化

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面向趋势预测的热点主题演化分析方法研究

数据分析与知识发现 2020年第6期4卷 22-34页

作者：岳丽欣刘自强胡正银中国人民大学信息资源管理学院北京100872 中国科学院成都文献情报中心成都610041 中国科学院大学经济与管理学院图书情报与档案管理系北京100190

【目的】从外部数量特征和内部文本特征两个层面,构建科学的数理模型和内容预测模型,进而对热点研究主题演化趋势进行预测分析。【方法】基于LDA模型进行主题识别并构建主题时间序列,结合均值与线性回归拟合确定热点主题;利用ARIMA模型... 详细信息

【目的】从外部数量特征和内部文本特征两个层面,构建科学的数理模型和内容预测模型,进而对热点研究主题演化趋势进行预测分析。【方法】基于LDA模型进行主题识别并构建主题时间序列,结合均值与线性回归拟合确定热点主题;利用ARIMA模型和Word2Vec模型从主题强度和主题内容两个层面预测分析热点主题趋势。【结果】对美国干细胞领域进行实证研究,筛选出造血干细胞移植技术、癌症干细胞和干细胞抑制作用、干细胞诱导分化、衍生配子技术、造血干细胞5个热点主题并预测其发展趋势。【局限】基于Word2Vec模型对主题内容趋势进行分析主要以单个词汇为基础,解读过程中可能存在歧义。【结论】与人工解读为主的主题趋势预测分析方法相比,本研究所提方法能在一定程度上提高预测分析的效率与科学性。

关键词：趋势预测热点主题 ARIMA模型 Word2Vec模型主题演化

Amino acids industry knowledge service platform

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Chinese Journal of Library and Information Science 2015年第4期 78-89页

作者： Yi WEN Hongguang FU Shu FANG Qinggang LI zhengyin hu Chunjiang LIU Ning YANG Xian ZHANG Yuan XU Chenjun Ding Yuexian Zhu Chengdu Documentation and Information Center Chinese Academy of Sciences School of Computer Science and Engineering University of Electronic Science and Technology of China Tianjin Institute of Industrial Biotechnology Chinese Academy of Sciences University of Chinese Academy of Sciences

Purpose： This paper introduces an amino acids industry knowledge service platform, which integrates industry data, science literature, and technology knowledge from patents.Design/methodology/approach： From the perspective of knowledge organization, the amino acids industry knowledge service platform comprises a basic data layer, a knowledge representation layer, and a knowledge service layer. The platform integrates heterogeneous information sources by means of a multi-dimensional integration index. It enables users to find technology knowledge from patents by employing the semantic Theory of Inventive Problem Solving （TRIZ）.Findings： This paper constructs an integrated amino acids industry database, which offers a general service oriented to the public, and a technical innovation knowledge base, which offers a value-added service oriented to enterprises.Research limitations： The technical innovation knowledge base only includes parts of amino acids technology knowledge, making it suitable to meet certain specific needs.Practical implications： Semantic annotation of technical innovation knowledge from patents requires manual work by domain experts.Originality/value： The amino acids industry knowledge service platform offers not only an integrated search service for amino acids industry information, but also a deep tech mining service for technical innovation knowledge of amino acids. It will offer a more personalized knowledge service in the future.

关键词： Knowledge service Amino acids industry information Multi-dimensionalintegration index Semantic TRIZ

基于领域知识图谱的生命医学学科知识发现探析

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数据分析与知识发现 2020年第11期4卷 1-14页

作者：胡正银刘蕾蕾代冰覃筱楚中国科学院成都文献情报中心成都610041 中国科学院大学经济与管理学院图书情报与档案管理系北京100190 广州市再生医学与健康广东省实验室广州510700 中国科学院广州生物医药与健康研究院广州510530

【目的】探讨融合多源数据,开展深层次学科知识发现研究与服务的方法。【方法】通过构建科技文献SPO语义网络形成领域知识图谱的核心;通过"实体对齐、概念层次融合与关系融合"实现多源异构数据融合,生成完整领域知识图谱;基于领域知识... 详细信息

【目的】探讨融合多源数据,开展深层次学科知识发现研究与服务的方法。【方法】通过构建科技文献SPO语义网络形成领域知识图谱的核心;通过"实体对齐、概念层次融合与关系融合"实现多源异构数据融合,生成完整领域知识图谱;基于领域知识图谱开展深层次学科知识发现;选择造血干细胞癌症治疗进行实证研究。【结果】提出一套基于知识图谱的学科知识发现方法框架KGSKD,可多维度、细粒度融合多源异构数据,定义数据间复杂语义关系,原生支持知识推理、路径发现、链路预测等知识发现应用。【局限】KGSKD存在容易出现数据过饱和、知识发现过程可解释性较差、与领域专家沟通难度较高等局限。【结论】KGSKD具有数据类型更丰富、知识关联更全面、挖掘方法更先进、发现结果更深入等优势,可更有效地支持生命医学学科深层次知识发现研究与服务。

关键词：学科知识发现知识图谱 SPO三元组数据融合实体对齐

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面向学科知识服务的微信小程序研究与实践

图书情报工作 2020年第14期64卷 54-62页

作者：徐源胡正银宋亦兵吴璇中国科学院成都文献情报中心成都610041 中国科学院大学经济与管理学院图书情报与档案管理系北京100190 中国科学院广州生物医药与健康研究院信息情报中心广州510530

[目的/意义]通过相关研究与实践,为运用微信小程序助力学科知识服务提供思路与参考。[方法/过程]分析微信小程序的特性与服务现状,提出以用户为中心的"大环境、深发现、小前端、富生态"的学科知识服务框架与模式,并从信息服务、知识服... 详细信息

[目的/意义]通过相关研究与实践,为运用微信小程序助力学科知识服务提供思路与参考。[方法/过程]分析微信小程序的特性与服务现状,提出以用户为中心的"大环境、深发现、小前端、富生态"的学科知识服务框架与模式,并从信息服务、知识服务、个性化服务等视角进行服务内容研究。以"干细胞助手"微信小程序为例进行案例实践,证明该方法的可行性。[结果/结论]只要合理规划、科学布局,小程序生态也能承载丰富的学科知识服务应用,从移动端支持用户的科研创新活动。

关键词：学科知识服务微信小程序知识发现科技大数据知识图谱