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On tuning of ADRC with competing design indices:a quantitative study

Control Theory and Technology 2023年第1期21卷 16-33页

作者： Yutao Zhao Yi Huang Zhiqiang Gao Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China Department of Electrical Engineering and Computer Science Center for Advanced Control TechnologiesCleveland State UniversityClevelandOH 44115USA

Controller optimization has mostly been done by minimizing a certain single cost *** practice,however,engineers must contend with multiple and conflicting considerations,denoted as design indices(DIs)in this *** to account for such complexity and nuances is detrimental to the applications of any advanced control *** paper addresses this challenge heads on,in the context of active disturbance rejection controller(ADRC)and with four competing DIs:stability margins,tracking,disturbance rejection,and noise *** this end,the lower bound for the bandwidth of the extended state observer is first established for guaranteed closed-loop ***,one by one,the mathematical formula is meticulously derived,connecting each DI to the set of controller *** our best knowledge,this has not been done in the context of *** formulas allow engineers to see quantitatively how the change of each tuning parameter would impact all of the DIs,thus making the guesswork *** example is given to show how such analytical methods can help engineers quickly determine controller parameters in a practical scenario.

关键词： Uncertain systems Active disturbance rejection control(ADRC) Design indices(DIs) Extended state observer(ESO)

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Domain knowledge discovery from abstracts of scientific literature on Nickel-based single crystal superalloys

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Science China(Technological Sciences) 2023年第6期66卷 1815-1830页

作者： LIU Yue DING Lin YANG ZhengWei GE XianYuan LIU DaHui LIU Wei YU Tao AVDEEV Maxim SHI SiQi School of Computer Engineering and Science Shanghai UniversityShanghai 200444China Shanghai Engineering Research Center of Intelligent Computing System Shanghai 200444China State Key Laboratory of Advanced Special Steel&Shanghai Key Laboratory of Advanced Ferrometallurgy&School of Materials Science and Engineering Shanghai UniversityShanghai 200444China Materials Genome Institute Shanghai UniversityShanghai 200444China Institute of Functional Materials Central Iron&Steel Research InstituteBeijing 100081China Australian Nuclear Science and Technology Organisation Locked Bag 2001Kirrawee DC NSW 2232Australia School of Chemistry The University of SydneySydney 2006Australia Zhejiang Laboratory Hangzhou 311100China

Despite the huge accumulation of scientific literature,it is inefficient and laborious to manually search it for useful information to investigate structure-activity ***,we propose an efficient text-mining framework for the discovery of credible and valuable domain knowledge from abstracts of scientific literature focusing on Nickel-based single crystal ***,the credibility of abstracts is quantified in terms of source timeliness,publication authority and author’s academic ***,eight entity types and domain dictionaries describing Nickel-based single crystal superalloys are predefined to realize the named entity recognition from the abstracts,achieving an accuracy of 85.10%.Thirdly,by formulating 12 naming rules for the alloy brands derived from the recognized entities,we extract the target entities and refine them as domain knowledge through the credibility *** this,we also map out the academic cooperative“Author-Literature-Institute”network,characterize the generations of Nickel-based single crystal superalloys,as well as obtain the fractions of the most important chemical elements in *** extracted rich and diverse knowledge of Nickel-based single crystal superalloys provides important insights toward understanding the structure-activity relationships for Nickel-based single crystal superalloys and is expected to accelerate the design and discovery of novel superalloys.

关键词： Nickel-based single crystal superalloys text mining named entity recognition credibility analysis domain knowledge

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Path planning of UAV base station based on deep reinforcement learning 12

Path planning of UAV base station based on deep reinforcemen...

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12th International Conference on Identification, Information and Knowledge in the internet of Things, IIKI 2021

作者： Yang, Siming Shan, Zheng Cao, Jiang Gao, Yuan Guo, Yang Wang, Ping Wang, Xiaonan Wang, Jing Zhang, Tingting Guo, Jiayu State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Zhengzhou450001 China Academy of Military Science of the PLA Beijing100091 China Network Technology Research Center of the PLA Beijing100090 China

UAV base station platform has become the current research hotspot of assisting ground base station for wireless *** present, the most important issue is how to make path planning to provide the stable communication guarantee for multiple mobile users. In this article, we model the air-to-ground channel to describe the path loss between the UAV platform and the user and build a simulation environment for training based on the OpenAI-GYM architecture. In addition, this paper proposes a reinforcement learning algorithm based on intrinsic rewards, which uses the mean square error of the state prediction results to quantify the novelty of the state. Algorithms enable agents to efficiently carry out strategy iterations. Experiments results showed that our algorithm has a higher score and takes less time. © 2022 The Authors. Published by Elsevier B.V.

关键词： Deep learning Deep reinforcement learning UAV path planning Wireless communication coverage

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Distributed Deep Learning System for Efficient Face Recognition in Surveillance System 3

Distributed Deep Learning System for Efficient Face Recognit...

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3rd International Conference on advanced Information Science and System, AISS 2021

作者： Liu, Jinjin Chen, Zhifeng Li, Xiaonan Wei, Tongxin School of Computer Science Zhongyuan University of Technology China and State Key Laboratory of Mathematical Engineering and Advanced Computing China State Key Laboratory of Mathematical Engineering and Advanced Computing China School of Computer Science Zhongyuan University of Technology China School of Cyberspace Security Zhengzhou University China

ISBN: (纸本)9781450385862

In view of the bandwidth consumption caused by data stream transmission in video analysis system and the demand for accurate online real-time analysis of massive data, this paper proposes a deep learning model framework for face recognition employed in the embedded system. Through data collaboration, the cloud could build a more complex data set with a small amount of uploaded data gathered by the end devices. And the framework collaboration makes sure that the fully-trained cloud model directly download or distillate knowledge to the end devices. Experiments show that the deep model not only realizes the real-time response and the accurate response of the cloud system, but also greatly reduces the bandwidth consumption caused by sample data transmission in the model training process. © 2021 ACM.

关键词： Distillation

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Distributed Truss Computation in Dynamic Graphs

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Tsinghua Science and Technology 2023年第5期28卷 873-887页

作者： Ziwei Mo Qi Luo Dongxiao Yu Hao Sheng Jiguo Yu Xiuzhen Cheng School of Computer Science and Technology Shandong UniversityQingdao 266200China State Key Laboratory of Software Development Environment School of Computer Science and Engineering and the Beijing Advanced Innovation Center for Big Data and Brain ComputingBeihang UniversityBeijing 100191China Big Data Institute Qilu University of Technology(Shandong Academy of Sciences)Jinan 250353China

Large-scale graphs usually exhibit global sparsity with local cohesiveness,and mining the representative cohesive subgraphs is a fundamental problem in graph *** k-truss is one of the most commonly studied cohesive subgraphs,in which each edge is formed in at least k 2 triangles.A critical issue in mining a k-truss lies in the computation of the trussness of each edge,which is the maximum value of k that an edge can be in a *** works mostly focus on truss computation in static graphs by sequential ***,the graphs are constantly changing dynamically in the real *** study distributed truss computation in dynamic graphs in this *** particular,we compute the trussness of edges based on the local nature of the k-truss in a synchronized node-centric distributed *** decomposing the trussness of edges by relying only on local topological information is possible with the proposed distributed decomposition ***,the distributed maintenance algorithm only needs to update a small amount of dynamic information to complete the *** experiments have been conducted to show the scalability and efficiency of the proposed algorithm.

关键词： distributed algorithm dynamic graph graph mining cohesive subgraph k-truss

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Code Clone Detection Based on Code Semantic Enhancement Model

Code Clone Detection Based on Code Semantic Enhancement Mode...

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Intelligent Communication and Computer engineering (ICICCE), International Conference on

作者： Zhang Chunyan Shen Ziang Liang Chen State Key of Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Department of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing China

Code clones are code fragments that are similar in composition or semantics of code statements, which can significantly improve software development efficiency and reduce costs by improving the quality of reusable code. However, existing code clone detection methods ignore the source code structure information and sequence information seriously. In this paper, we launched our research on the harder-to-break Type IV code clone detection, and propose a new method, namely Aug_Clone, to complete code clone detection task. Firstly, we utilize our published code semantic enhancement model to obtain the code semantic vector. Secondly, we perform code clone detection by calculating the similarity between these semantic vectors. At last, we evaluate our method on a large public data set, and experimental results show improvement over the state-of-the-art benchmarks, which demonstrates the effectiveness and efficiency of our method.

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A Cross-Platform Instant Messaging User Association Method Based on Supervised Learning 4th

A Cross-Platform Instant Messaging User Association Method B...

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4th International Conference on Big Data and Security, ICBDS 2022

作者： Zhou, Pei Luo, Xiangyang Du, Shaoyong Shi, Wenqi Guo, Jiashan School of Cyber Science and Engineering Zhengzhou University Zhengzhou450000 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450000 China

ISBN: (纸本)9789819932993

To solve the multi-platform user association problem of complex trajectory matching process and high time cost in cross-platform association positioning of instant messaging users, and at the same time make full use of the information in user trajectories, this paper proposes a supervised learning-based cross-platform instant messaging user association positioning method. The algorithm firstly places probes in the area where the target may appear to obtain user information;then gets user trajectories through the obtained user distance information and time information;selects user features through the classification algorithm of supervised learning, and designs a cross-platform instant messaging user association localization method based on supervised learning, so as to increase the association efficiency and accuracy of cross-platform instant messaging user association. The method conducts specific experiments for the most commonly used instant messaging tools in China, WeChat and Stranger users, and the results show that the method can achieve efficient and reliable association for these two types of instant messaging users. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Trajectories

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A Review of Field Text Analysis

A Review of Field Text Analysis

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2021 IEEE Conference on Telecommunications, Optics and Computer Science, TOCS 2021

作者： Li, Zhuolun Kang, Fei Yu, Pu Shu, Hui Zhengzhou University School of Software Zhengzhou China Meac State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665424981

Field text analysis is the process of using natural language processing technology to understand the Text and extract information from unstructured text data. In recent years, due to the increasing maturity of machine learning technology, higher requirements have been put forward for field text analysis. This review first introduces the process of Text preprocessing and the development of text representation. Secondly, it summarizes the four typical techniques of text analysis, including named entity recognition, relation extraction, extractive text summarization, and text classification. Finally, for each typical technology, it introduces the commonly used methods and part of the researcher's exploration of this technology. © 2021 IEEE.

关键词： Text processing

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A Graph Reasoning Model Based on Multiple Types of Nodes 7

A Graph Reasoning Model Based on Multiple Types of Nodes

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7th International Conference on Big Data and Information Analytics, BigDIA 2021

作者： Liu, Yibing Huo, Lijun Zhou, Gang Information Engineering University State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China National University of Defense Technology Key Laboratory of Information System Engineering Changsha China

ISBN: (纸本)9781665424660

Multi-hop machine reading comprehension (MRC) depends on the model to answer a semantically related question based on the given supporting text. In this study, inspired by previous research about Graph Neural Network(GNN), we develop a new graph covering three kinds of nodes: Sentence, Entity, Candidate. A corresponding MRC method based on graph inference is proposed, called SEC reasoner. The advantage of SECr is that it adopts different granular information as graph nodes, which can execute a more comprehensive reasoning. Our proposed model first initialize the node representations by co-Attention, multi-head attention and self-Attention based on context embedding. SECr then employs GNN based information transfer algorithms to collect evidences from the node encoding, and calculates a score for choosing the answer. In experiments, we evaluate the model on two popular benchmark datasets-WikiHop and MedHop. SECr reachs accuracy rates of 71.6%, 63.1% respectively, which is a competitive result. In addition, a comprehensive analysis proves the effectiveness and interpretability of the SECr. © 2021 IEEE.

关键词： Semantics

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A Review on IoT Botnet 2021

A Review on IoT Botnet

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2nd International Conference on computing and Data Science, CONF-CDS 2021

作者： Zhao, Hao Shu, Hui Xing, Ying State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Software College Zhongyuan University of Technology Zhengzhou China

ISBN: (纸本)9781450389570

The rapid development of the Internet of Things (IoT) also generates security threats that cannot be ignored. This paper lists the development history of botnets, introduces representative IoT botnets, and reveals their new characteristics. The botnet mechanism and characteristics of IoT botnets are analyzed in depth from three aspects: composition structure, life cycle, and attack behavior, and are compared with traditional botnets. Networks for comparison. The analysis discusses the details of IoT botnet technologies such as scanning discovery, covert communication and survival residency. Summarizes the research status of IoT botnet detection technologies and gives future directions. Finally, the importance of preventing IoT botnets and solving IoT security problems is discussed. © 2021 ACM.

关键词： Internet of things

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