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2nd International Conference on Green Communication, Network, and Internet of Things, CNIoT 2022

作者： Ren, Jiyuan Liu, Fuyang Song, Yang Wang, Zhe Yin, Lu Wang, Jing Dispatching and Control Center Northeast Branch of State Grid Corporation of China Shenyang China School of Computer Science and Engineering Northeastern University Shenyang China

ISBN: (纸本)9781510662940

The risk of data leakage and security vulnerabilities exist in digital grid mobile application platforms such as "i State Grid". To address this problem, an application security plug-in for digital grid smart terminals is designed. A lightweight mobile application security protection system architecture is proposed to prevent user data from being damaged and leaked. The system architecture mainly contains three aspects: static environment assessment of mobile applications, dynamic detection of malicious applications, and mobile application risk assessment. That also reduces the security risk from external factors such as the Internet, and effectively ensures the safe and stable operation of the "i State Grid" system. © 2023 SPIE.

关键词： Risk assessment

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Recent Developments in Event-Triggered control of Nonlinear Systems:An Overview

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无人系统（英文） 2023年第1期11卷 27-56页

作者： Pengpeng Zhang Tengfei Liu Jie Chen Zhong-Ping Jiang Department of Control Science & Engineering Frontiers Science Center for Intelligent Autonomous SystemsTongji UniversityShanghai 201804P.R.China State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819P.R.China Department of Electrical and Computer Engineering New York University370 Jay StreetBrooklynNY 11201USA

Event-triggered control is a most popular paradigm for transferring feedback information in an economical"as needed"*** study of event-triggered control can be traced back to the *** significant advances on the topic of control over networks and the topic of nonlinear control systems over the last two decades,event-triggered control has quickly emerged as a major theoretical subject in control *** of event-triggered control are wide-spread ranging from embedded control systems and industrial control processes to unmanned systems and cyber-physical transportation *** this paper,we first review developments in the synthesis of event-triggered sampling *** event triggering mechanisms,such as static event trigger,dynamic event trigger,time-regularized event trigger,and event trigger with positive threshold offsets,are systematically ***,we study how to design a stabilizing controller that is robust with respect to the sampling ***,we review some recent results in the directions of self-triggered control,event-triggered tracking control and cooperative control,and event-triggered control of stochastic systems and partial differential equation *** applications of event-triggered control are also discussed.

关键词： Event-triggered control event-triggered sampling mechanism event-triggered controller

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Personalized Federated Learning for Heterogeneous Residential Load Forecasting

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Big Data Mining and Analytics 2023年第4期6卷 421-432页

作者： Xiaodong Qu Chengcheng Guan Gang Xie Zhiyi Tian Keshav Sood Chaoli Sun Lei Cui the Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Taiyuan University of Science and TechnologyTaiyuan 030024China the Faculty of Engineering and Information Technology University of Technology SydneyUltimo 2007Australia the Centre for Cyber Security Research and Innovation Deakin UniversityMelbourne 3125Australia the School of Computer Science and Technology Taiyuan University of Science and TechnologyTaiyuan 030024China

Accurate load forecasting is critical for electricity production,transmission,and *** learning(DL)model has replaced other classical models as the most popular prediction ***,the deep prediction model requires users to provide a large amount of private electricity consumption data,which has potential privacy *** nodes can federally train a global model through aggregation using federated learning(FL).As a novel distributed machine learning(ML)technique,it only exchanges model parameters without sharing raw ***,existing forecasting methods based on FL still face challenges from data heterogeneity and privacy ***,we propose a user-level load forecasting system based on personalized federated learning(PFL)to address these *** obtained personalized model outperforms the global model on local ***,we introduce a novel differential privacy(DP)algorithm in the proposed system to provide an additional privacy *** on the principle of generative adversarial network(GAN),the algorithm achieves the balance between privacy and prediction accuracy throughout the *** perform simulation experiments on the real-world dataset and the experimental results show that the proposed system can comply with the requirement for accuracy and privacy in real load forecasting scenarios.

关键词： load forecasting personalized federated learning differential privacy

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Document-level Event Extraction combined with Writing Style and Argument Role RelationA Document-level Event Extraction model DEEWR 4

Document-level Event Extraction combined with Writing Style ...

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4th International Conference on Artificial Intelligence and computer engineering, ICAICE 2023

作者： Zhao, Jingsheng Yan, Shuai Ni, Qihui Wang, Yongzheng Zhu, Qiaoming School of Information and Control Engineering Qingdao University of Technology Qingdao266520 China School of Computer Science and Technology Soochow University Suzhou215006 China

ISBN: (纸本)9798400708831

Document-level event extraction is an important task in natural language processing, which faces the challenges of arguments-scattering and multi-events. The current mainstream method is to decompose document-level event extraction into three subtasks: entity extraction, event type recognition, and argument-filling. However, existing methods flew consider the impact of writing style on event extraction, and have complex models with high training costs. To address these problems, this paper proposes a document-level event extraction model that incorporates both writing style and argument role relation. First, Roberta is used to encode the document sentences to obtain semantic features, and BiLSTM-CRF is used to identify candidate entities. Second, the writing style is modeled as the relative distribution of argument roles in the document and is used to supervise the event type recognition results. Third, argument-filling is simplified to the relation judgment between the argument roles. This method effectively addresses the problem of scattered arguments by constructing event clusters based on the relation of argument roles. It also deals with the multi-event problem through event cluster division. Compared with previous path expansion-based methods, experimental results show that the model has lower training costs and performs better in low training epochs. © 2023 ACM.

关键词： Filling

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Cluster-Refined Optimal Transport for Unsupervised Action Segmentation

Cluster-Refined Optimal Transport for Unsupervised Action Se...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Wang, Shijie Zhang, Jinrong Liu, Yule Li, Shiyao Feng, Lin School of Computer Science and Technology Dalian University of Technology Dalian China School of Control Science and Engineering Dalian University of Technology Dalian China School of Innovation and Entrepreneurship Dalian University of Technology Dalian China

ISBN: (纸本)9798350368741

Action segmentation in untrimmed videos is essential for comprehensive video understanding. Despite significant progress in unsupervised methods, capturing both long-range dependencies and short-duration actions simultaneously remains a challenging task. To address this challenge, this paper introduces the Cluster-Refined Optimal Transport (CROT) method, combining hierarchical clustering and optimal transport for unsupervised action segmentation. We first hierarchically cluster video frame representations to capture long-range dependencies and generate pseudo-boundaries. Initial pseudo-labels are then obtained via optimal transport, ensuring short-duration actions are recognized. Finally, these pseudo-labels are refined using the pseudo-boundaries, resulting in the final segmentation output. Extensive experiments on three public datasets, i.e., YouTube Instructions, Breakfast, and 50Salads, demonstrate that our method performs on par with or better than previous approaches. © 2025 IEEE.

关键词： action segmentation hierarchical clustering optimal transport unsupervised learning

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Learning Communities from Equilibria of Nonlinear Opinion Dynamics 63

Learning Communities from Equilibria of Nonlinear Opinion Dy...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Xing, Yu Bizyaeva, Anastasia Johansson, Karl H. Kth Royal Institute of Technology and with Digital Futures Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm Sweden Cornell University Sibley School of Mechanical and Aerospace Engineering IthacaNY United States

ISBN: (纸本)9798350316339

This paper studies community detection for a nonlinear opinion dynamics model from its equilibria. It is assumed that the underlying network is generated from a stochastic block model with two communities, where agents are assigned with community labels and edges are added independently based on these labels. Agents update their opinions following a nonlinear rule that incorporates saturation effects on interactions. It is shown that clustering based on a single equilibrium can detect most community labels (i.e., achieving almost exact recovery), if the two communities differ in size and link probabilities. When the two communities are identical in size and link probabilities, and the intercommunity connections are denser than intra-community ones, the algorithm can achieve almost exact recovery under negative influence weights but fails under positive influence weights. Utilizing fixed point equations and spectral methods, we also propose a detection algorithm based on multiple equilibria, which can detect communities with positive influence weights. Numerical experiments demonstrate the performance of the proposed algorithms. © 2024 IEEE.

关键词： Nash equilibrium

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Remotely controllable Data Self-Destruction for Privacy-Preserving Sensitive Data Services 25

Remotely Controllable Data Self-Destruction for Privacy-Pres...

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25th IEEE International Conferences on High Performance Computing and Communications, 9th International Conference on Data science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Zhou, Chengxin Xue, Xianbin Riad, Khaled Zhu, Yan Chu, William Cheng-Chung School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China North Navigation Control Technology Co. Ltd. Beijing China College of Computer Science and Information Technology King Faisal University Saudi Arabia Tunghai University Department of Computer Science Taichung Taiwan

ISBN: (纸本)9798350330014

This paper address a comprehensive solution to address data privacy and security challenges in data science, providing secure self-destruction of sensitive data, confidentiality through encryption, and flexible control over message destruction. Based on outsourcing cloud data services, we introduce a cloud retrograde storage (CRS) system for privacy-preserving self-destruction of sensitive data. The CRS is based on a frequently colliding hash table and recycle pool, and supports remote time, count, and range control. Hereby, we provide a remotely controllable mechanism for the prompt destruction of inactive messages against digital forensics without reducing the availability of services. The method used in the CRS involves storing messages in a recycle pool, where they are automatically erased at the end of their validity period or after being viewed by all recipients. The system also incorporates encryption and decryption processes to ensure confidentiality. The result of performance evaluation shows that the CRS effectively handles the destruction of messages and provides secure data removal from storage pools. The experiments demonstrate the efficiency and practicality of the CRS for large-scale data services. © 2023 IEEE.

关键词： Sensitive data

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Accelerated Iterative Learning control for a Class of Discrete Linear Systems with Uncertain Dynamics

Accelerated Iterative Learning Control for a Class of Dis...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Chen, Yunjun Sun, Likun Xiong, Hui Zhao, Zhanshan School of Control Science and Engineering Tiangong University Tianjin China School of Artificial Intelligence Tiangong University Tianjin China School of Computer Science and Technology Tiangong University Tianjin China

ISBN: (纸本)9789811966125

An improved iterative learning control approach is proposed for a class of discrete linear systems with uncertain dynamics. It is well known that the gain in iterative learning control is prudently chosen to ensure robustness when the system exists uncertainty. Based on the sliding mode reaching law, a novel error term with power is designed to enable error to decrease faster in iteration, which is useful for systems with significant uncertainty. The convergence condition and stability for the proposed scheme are also analyzed. Finally, numerical simulation results illustrate that faster convergence is obtained compared with the pre-existing control methods. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Iterative methods

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Multi-layer network modelling of genomic and transcriptomic data to investigate the response to checkpoint inhibitors in NSCLC

Multi-layer network modelling of genomic and transcriptomic ...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Mascolo, Davide Farina, Lorenzo Petti, Manuela Sapienza University of Rome Program in Data Science Rome Italy Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy

ISBN: (纸本)9798350337488

Recent innovations and developments in molecular biology and biotechnology have made it possible to acquire and store large omics datasets. In particular genomics, transcriptomics and the study of their relationship represent the key elements to understand how genotype influences phenotype. In this work we investigate the potential of multi-layer network modeling in integrating genomic and transcriptomic data of 152 advanced non-small cell lung cancer (NSCLC) patients treated with anti-PD-(L)1 therapy. For the transcriptomic layer, we performed differential expression and differential co-expression analyses in order to identify a subset of key genes in differentiating responder patients from non-responders. Adding to the genomic-transcriptomic model other three layers related to immune, myeloid and curated immunotherapy-based literature signatures we obtained a 5-layer Patient Similarity Network. The application of Similarity Network Fusion algorithm revealed a statistically significant stratification of patients (p-value ≤ 0.05) which allows the identification of two clusters characterized by patients responding and not responding to immunotherapy. © 2023 IEEE.

关键词： immunotherapy multi-layer network Network-based omics integration non-small cell lung cancer patient Stratification

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An improved longitude correction algorithm for fisheye image edge distortion 3

An improved longitude correction algorithm for fisheye image...

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3rd International Conference on Artificial Intelligence and computer engineering, ICAICE 2022

作者： Ji, Xiu Yang, Huamin Han, Cheng Wang, Hexin Lang, Chaoyue School of Computer Science and Technology Changchun University of Science and Technology Jilin Changchun130022 China School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132022 China

ISBN: (纸本)9781510663473

The fisheye camera is widely used in computer vision because of its large field of view. However, in optical theory, the large field of view is at the cost of distortion. It is impossible to obtain effective information directly from the fisheye image, so the original image needs to be distorted first to become a linear image without distortion. Aiming at the existence of traditional longitude correction in the image center, edge correction effect is different and edge distortion, introducing the repositioning center algorithm and stretch factor. Firstly, the effective area of fisheye image is obtained by row-by-row column scanning method. And then uses the repositioning center algorithm to obtain the new center and radius, according to the distortion principle to calculate the distortion principle. The mapping relationship between the target image and the original image is obtained, and finally modified by the bilinear interpolation method. Compared with the traditional longitude correction, the proposed algorithm can correct the fisheye image accurately and effectively, and improve the quality of correction. © 2023 SPIE.

关键词： Image enhancement

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