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Robust stabilization for a class of nonlinear networked control systems

控制理论与应用（英文版） 2008年第3期6卷 300-304页

作者： Jinfeng GAO Hongye SU Xiaofu JI Jian CHU State Key Laboratory of Industrial Control Technology Institute of Advanced Process Control Zhejiang University Hangzhou Zhejiang 310027 China School of Electrical and Information Engineering Jiangsu University Zhenjiang Jiangsu 212013 China

The problem of robust stabilization for a class of uncertain networked control systems （NCSs） with nonlinearities satisfying a given sector condition is investigated in this paper. By introducing a new model of NCSs with parameter uncertainty, network-induced delay, nonlinearity and data packet dropout in the transmission, a strict linear matrix inequality （LMI） criterion is proposed for robust stabilization of the uncertain nonlinear NCSs based on the Lyapunov stability theory. The maximum allowable transfer interval （MATI） can be derived by solving the feasibility problem of the corresponding LMI. Some numerical examples are provided to demonstrate the applicability of the proposed algorithm.

关键词： Networked control systems （NCSs） Robust control Nonlinearity Linear matrix inequality （LMI）

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Tolerance-based multigranulation rough sets in incomplete systems

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Frontiers of computer Science 2014年第5期8卷 753-762页

作者： Zaiyue ZHANG Xibei YANG School of Computer Science and Engineering Jiangsu University of Science and Technology Zhenjiang 212003 China Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information (Nanjing University of Science and Technology) Ministry of Education Nanjing 210094 China Artificial Intelligence Key Laboratory of Sichuan Province Zigong 643000 China

Presently, the notion of multigranulation has been brought to our attention. In this paper, the multigranulation technique is introduced into incomplete information systems. Both tolerance relations and maximal consistent blocks are used to construct multigranulation rough sets. Not only are the basic properties about these models studied, but also the relationships between different multigranulation rough sets are explored. It is shown that by using maximal consistent blocks, the greater lower approximation and the same upper approximation as from tolerance relations can be obtained. Such a result is consistent with that of a single-granulation framework.

关键词： incomplete information system maximal con-sistent block multigranulation rough sets tolerance relation

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A fuzzy grey cognitive maps-based decision support system for maintaining water quality

A fuzzy grey cognitive maps-based decision support system fo...

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第25届中国控制与决策会议

作者： Bingyi Kang Yong Deng Jiangsu Key Laboratory of Resources and Environmental Information Engineering China University of Mining and Technology School of Computer and Information Science Southwest University

ISBN: (纸本)9781467355339

Maintaining water quality is of great importance for consumer's health. How to evaluate and predict the aging water quality is an open issue. In this paper, a framework based on fuzzy grey cognitive maps (FGCMs) is proposed to quantify overall potential for water quality failures. A new method of aggregating different experts based on interval number is presented in the process of constructing FGCM. At last, a case study is utilized to illustrate the efficiency of the proposed method.

关键词： Water Quality Management, Fuzzy Grey Cognitive Maps, Interval number

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Tag Correspondence Model for User Tag Suggestion

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Journal of computer Science & technology 2015年第5期30卷 1063-1072页

作者：涂存超刘知远孙茂松 Department of Computer Science and Technology Tsinghua University Beijing 100084 China State Key Laboratory on Intelligent Technology and Systems Tsinghua University Beijing 100084 China National Laboratory for Information Science and Technology Tsinghua University Beijing 100084 China Jiangsu Collaborative Innovation Center for Language Ability Jiangsu Normal University Xuzhou 221009 China

Some microblog services encourage users to annotate themselves with multiple tags, indicating their attributes and interests. User tags play an important role for personalized recommendation and information retrieval. In order to better understand the semantics of user tags, we propose Tag Correspondence Model （TCM） to identify complex correspondences of tags from the rich context of microblog users. The correspondence of a tag is referred to as a unique element in the context which is semantically correlated with this tag. In TCM, we divide the context of a microblog user into various sources （such as short messages, user profile, and neighbors）. With a collection of users with annotated tags, TCM can automatically learn the correspondences of user tags from multiple sources. With the learned correspondences, we are able to interpret implicit semantics of tags. Moreover, for the users who have not annotated any tags, TCM can suggest tags according to users＇ context information. Extensive experiments on a real-world dataset demonstrate that our method can efficiently identify correspondences of tags, which may eventually represent semantic meanings of tags.

关键词： microblog user tag suggestion tag correspondence model probabilistic graphical model context

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Recent Advances on Neural Headline Generation

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Journal of computer Science & technology 2017年第4期32卷 768-784页

作者： Ayana Shi-Qi Shen Yan-Kai Lin Cun-Chao Tu Yu Zhao Zhi-Yuan Liu Mao-Song Sun Department of Computer Science and Technology Tsinghua University Beijing 100084 China State Key Laboratory of Intelligent Technology and Systems Tsinqhua University Beijinq 100084 China Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing 100083 China Department of Computer Information Management Inner Mongolia University of Finance and Economics Hohhot 010000 China Jiangsu Collaborative Innovation Center for Language Ability Jiangsu Normal University Xuzhou 221009 China

Recently, neural models have been proposed for headline generation by learning to map documents to headlines with recurrent neural network. In this work, we give a detailed introduction and comparison of existing work and recent improvements in neural headline generation, with particular attention on how encoders, decoders and neural model training strategies alter the overall performance of the headline generation system. Furthermore, we perform quantitative analysis of most existing neural headline generation systems and summarize several key factors that impact the performance of headline generation systems. Meanwhile, we carry on detailed error analysis to typical neural headline generation systems in order to gain more comprehension. Our results and conclusions are hoped to benefit future research studies.

关键词： neural network headline generation data analysis

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Optimizing Non-Decomposable Evaluation Metrics for NeuralMachine Translation

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Journal of computer Science & technology 2017年第4期32卷 796-804页

作者： Shi-Qi Shen Yang Liu Mao-Song Sun Department of Computer Science and Technology Tsinghua University Beijing 100084 China State Key Laboratory of Intelligent Technology and Systems Tsinghua University Beijing 100084 China Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing 100084 China Jiangsu Collaborative Innovation Center for Language Ability Jiangsu Normal University Xuzhou 221009 China

While optimizing model parameters with respect to evaluation metrics has recently proven to benefit end to-end neural machine translation (NMT), the evaluation metrics used in the training are restricted to be defined at the sentence level to facilitate online learning algorithms. This is undesirable because the final evaluation metrics used in the testing phase are usually non-decomposable (i.e., they are defined at the corpus level and cannot be expressed as the sum of sentence-level metrics). To minimize the discrepancy between the training and the testing, we propose to extend the minimum risk training (MRT) algorithm to take non-decomposable corpus-level evaluation metrics into consideration while still keeping the advantages of online training. This can be done by calculating corpus-level evaluation metrics on a subset of training data at each step in online training. Experiments on Chinese-English and English-French translation show that our approach improves the correlation between training and testing and significantly outperforms the MRT algorithm using decomposable evaluation metrics.

关键词： neural machine translation training criterion non-decomposable evaluation metric

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Spectroscopic techniques combined with DD-SIMCA model and explainable artificial intelligence for rapidly and accurately identifying the quality of Astragali Radix

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Industrial Crops and Products 2025年 231卷

作者： Bai, Lei Zhang, Zhi-Tong Yuan, Dongping Hu, Ziliang Qi, Yali Liu, Wenjian Guan, Huanhuan Chen, Li Shi, Zhiqi Hu, Chenjun Xue, Mei Li, Jindong Yan, Guojun State Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture Nanjing University of Chinese Medicine Nanjing210023 China Taizhou School of Clinical Medicine The Affiliated Taizhou People's Hospital of Nanjing Medical University Taizhou225300 China Wuxi TCM Hospital Affiliated to Nanjing University of Chinese Medicine Wuxi214071 China School of Artificial Intelligence and Information Technology Nanjing University of Chinese Medicine Jiangsu Province Engineering Research Center of TCM Intelligence Health Service Nanjing210023 China

Astragali Radix (AR) is a traditional Chinese medicine (TCM) widely used worldwide for its nutritional and medicinal benefits, but it is facing increasing quality issues. This article developed a novel method for quickly and accurately identifying AR's quality. In this study, spectroscopic techniques combined with data-driven soft independent modelling of class analogy (DD-SIMCA) and explainable artificial intelligence (XAI) were used to determine AR's geographic origins and predict its antioxidant activity. The results showed that preprocessed near-infrared (NIR) or raw visible (VIS) spectra with DD-SIMCA could accurately identify AR's authentic regions, with 100 % sensitivity, specificity, and accuracy. Additionally, XAI identified 80 features from NIR spectra and 33 from VIS spectra, both strongly correlated with AR's antioxidant activity. Fusing these features and integrating them with support vector machine led to significantly better model performance, with Rp2 of 0.9760, RPDP of 6.7447, RMSEP of 1.3824, and MAEP of 1.1088. Overall, this study provided valuable insights for the quality assessment of TCMs and other medicinal plants. © 2025 The Authors

关键词： Damage detection

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Target vehicle detection and tracking in surveillance videos based on exponential forgetting and perceptual hash algorithm

Advances in Transportation Studies

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Advances in Transportation Studies 2018年第Special issue期2卷 97-106页

作者： Fan, H.H. Zhu, H.J. School of Computer Engineering Jiangsu University of Technology Changzhou213001 China Key Laboratory of Cloud Computing and Intelligent Information Processing of Changzhou City Changzhou213001 China

In order to obtain the stable background of a traffic surveillance video, the application scenarios, computational complexity, and results of the Gaussian background model were analyzed. In the background modeling process, many artifacts were generated, making it difficult to reconstruct a highly stable background image. In order to solve this problem, we proposed a background model based on exponential forgetting algorithm. This method satisfies the background reconstruction of complex environment, the computation is small and the background result is pure. To further improve the accuracy of the test, shadows of the vehicle were detected to reduce the error caused on vehicle detection. The perceptual hash algorithm was used to track the target vehicle. The proposed algorithm is verified by different video data. The experimental results show that a good vehicle tracking effect is achieved in a variety of weather conditions. © 2018, Gioacchino Onorati Editore. All rights reserved.

关键词： Vehicles

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Qoe-Aware Edge Server Placement in Mobile Edge Computing Using an Enhanced Genetic Algorithm

SSRN

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SSRN 2025年

作者： Sha, Jinxiang Wu, Jintao Wang, Mingliang Pu, Yonglin Lu, Sheng Bilal, Muhammad School of Computer Science and Technology Nanjing University of Information Science and Technology Jiangsu Nanjing210044 China Yunnan Key Laboratory of Service Computing Yunnan University of Finance and Economics Yunnan Kunming650221 China State Key Laboratory for Novel Software Technology Nanjing University Jiangsu Nanjing210023 China School of Computing and Communications Lancaster University LancasterLA1 4WA United Kingdom

Mobile Edge Computing (MEC) enhances service quality by decentralizing computational resources to network edges, thereby reducing latency and improving Quality of Service (QoS). However, the spatial distribution of edge servers critically impacts network transmission efficiency, while heterogeneous user perceptions of QoS metrics frequently lead to suboptimal Quality of Experience (QoE). Current research on Edge Server Placement (ESP) predominantly focuses on localized optimization of QoS metrics, yet fails to adequately incorporate systematic QoE modeling and coordinated optimization frameworks, leading to significant discrepancies between actual user experience and satisfaction with resource allocation. To address this gap, this study establishes a formalized QoE-aware Edge Server Placement (EESP) framework by rigorously characterizing the interdependence between QoE and QoS. We first prove the NP-completeness of the EESP problem through computational complexity analysis. Subsequently, we develop an Integer Linear Programming-based exact solver (EESP-O) for small-scale scenarios and propose an Enhanced Genetic Algorithm (EESP-EGA) for large-scale deployments. The EESP-EGA integrates adaptive crossover probability mechanisms and elite retention strategies to achieve near-optimal solutions for complex real-world configurations. Experimental evaluations conducted on a broad range of real-world datasets demonstrate that the proposed method outperforms several existing representative approaches in terms of QoE. © 2025, The Authors. All rights reserved.

关键词： Genetic algorithms

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Sharing of Encrypted Lock keys in the Blockchain-Based Renting House System from Time- and Identity-Based Proxy Reencryption

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China Communications 2022年第5期19卷 164-177页

作者： Zhiwei Wang Liping Qian Danwei Chen Guozi sun School of Computer Nanjing University of Posts and TelecommunicationsNanjing 210023China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing 210023China Guangxi Key Laboratory of Cryptography and Information Security Department of Computer SciencesGuilin University of Electronic TechnologyGuilin 541004China

To design an efficient protocol for sharing the encrypted lock keys in the renting house system,we introduce a new notion called time-and identitybased proxy reencryption(TIPRE)and the blockchain *** CPA secure TIPRE scheme is constructed from Green et al.’s identity-based proxy reencryption scheme by adding the time *** every time period,a time stamp authority generates a public key embedded with the current time stamp for each *** our protocol for the renting house system,the TIPRE scheme is the primary building block,and the blockchain platform serves instead of a trusted third party,such as a real estate agency between landlords and *** TIPRE scheme allows the landlord to change the lock key at each time period for *** blockchain platform allows the landlords and tenants to directly interact,and all of the interactions are recorded in the blockchain database to provide the desired security requirements,such as nonrepudiation and ***,we provide the secure analysis of our protocol and test its performance by implementing it in the MacBook Pro and the Intel Edison development platforms.

关键词： identity-based proxy reencryption time stamp renting houses system blockchain

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