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arXiv 2021年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Chai, Tianyou Johansson, Karl H. The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden The Digital Futures Stockholm10044 Sweden The Department of Control Science and Engineering College of Electronics and Information Engineering The Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore

This paper considers the distributed online convex optimization problem with time-varying constraints over a network of agents. This is a sequential decision making problem with two sequences of arbitrarily varying convex loss and constraint functions. At each round, each agent selects a decision from the decision set, and then only a portion of the loss function and a coordinate block of the constraint function at this round are privately revealed to this agent. The goal of the network is to minimize the network-wide loss accumulated over time. Two distributed online algorithms with full-information and bandit feedback are proposed. Both dynamic and static network regret bounds are analyzed for the proposed algorithms, and network cumulative constraint violation is used to measure constraint violation, which excludes the situation that strictly feasible constraints can compensate the effects of violated constraints. In particular, we show that the proposed algorithms achieve O(T max{κ,1-κ}) static network regret and O(T 1-κ/2) network cumulative constraint violation, where T is the time horizon and κ ∈ (0, 1) is a user-defined trade-off parameter. Moreover, if the loss functions are strongly convex, then the static network regret bound can be reduced to O(T κ). Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Economic and social effects

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Complexity at Mesoscales:A Common Challenge in Developing Artificial Intelligence

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Engineering 2019年第5期5卷 924-929页

作者： Li Guo Jun Wu Jinghai Li State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing 100049China School of Computer and Information Technology Beijing Jiaotong UniversityBeijing 100044China

Exploring the physical mechanisms of complex systems and making effective use of them are the keys to dealing with the complexity of the *** emergence of big data and the enhancement of computing power,in conjunction with the improvement of optimization algorithms,are leading to the development of artificial intelligence(AI)driven by deep ***,deep learning fails to reveal the underlying logic and physical connotations of the problems being *** provides a concept to understand the mechanism of the spatiotemporal multiscale structure of complex systems,and its capability for analyzing complex problems has been validated in different *** paper proposes a research paradigm for AI,which introduces the analytical principles of mesoscience into the design of deep learning *** is done to address the fundamental problem of deep learning models detaching the physical prototype from the problem being solved;the purpose is to promote the sustainable development of AI.

关键词： Artificial intelligence Deep learning Mesoscience Mesoscale Complex system

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Simulation Optimization of AOA Estimation Algorithm Based on MIMO UWB Communication System 2019

Simulation Optimization of AOA Estimation Algorithm Based on...

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Proceedings of the 2nd International Conference on information Technologies and Electrical Engineering

作者： Kun Zhang Chong Shen Bhatti Uzair Aslam Keliu Long Xiaoyan Chen Nan Li Education Center of MTA Hainan Tropical Ocean University Sanya Hainan China State Key Laboratory of Marine Resources Utilization in South China Sea Hainan University Haikou Hainan China State Key Laboratory of Marine Resources Utilization in South China Sea Hainan University Haikou Hainan China College of Computer Science and Information Technology Nanjing Normal University Nanjing Jiangsu China State Key Laboratory of Marine Resources Utilization in South China Sea Hainan University Haikou Hainan China College of Computer Science and Technology Hainan Tropical Ocean University Sanya Hainan China

ISBN: (纸本)9781450372930

The application of UWB technology is mainly used for positioning systems both at home and abroad. Compared with conventional wireless communication technologies, UWB also has outstanding advantages such as large capacity, high speed, and low power [1]. UWB signals also have great advantages in data transmission performance. This paper proposes a method of combining AOA estimation in UWB MIMO system. Firstly, the tag position is located, and then the position information is packaged and sent to the base station along with other detection data, which is beneficial to the data transmission process. Position for real-time precise positioning. The adoption of MIMO technology can improve the spectrum efficiency and improve the system performance for the system. The AOA estimation can achieve accurate positioning accuracy by using multiple antennas.

关键词： MIMO technology UWB Data transmission AOA estimation

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Hopf algebra of multi-decorated rooted forests, free matching Rota-Baxter algebras and Gröbner-Shirshov bases

arXiv

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arXiv 2020年

作者： Gao, Xing Guo, Li Zhang, Yi School of Mathematics and Statistics Key Laboratory of Applied Mathematics and Complex Systems Lanzhou University Gansu Lanzhou730000 China Department of Mathematics and Computer Science Rutgers University NewarkNJ07102 United States School of Mathematics and Statistics Nanjing University of Information Science & Technology Jiangsu Nanjing210044 China

Recent advances in stochastic PDEs, Hopf algebras of typed trees and integral equations have inspired the study of algebraic structures with replicating operations. To understand their algebraic and combinatorial nature, we first use rooted forests with multiple decoration sets to construct free Hopf algebras with multiple Hochschild 1-cocycle conditions. Applying the universal property of the underlying operated algebras and the method of Gröbner-Shirshov bases, we then construct free objects in the category of matching Rota-Baxter algebras which is a generalization of Rota-Baxter algebras to allow multiple Rota-Baxter operators. Finally the free matching Rota-Baxter algebras are equipped with a cocycle Hopf algebra *** Codes 16T30, 17B38, 05E16, 16Z10, 05C05, 16W99, 16S10, 05A05 Copyright © 2020, The Authors. All rights reserved.

关键词： Algebra

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Preface

Lecture Notes in Electrical Engineering

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Lecture Notes in Electrical Engineering 2022年 808 LNEE卷 v页

作者： Liu, Qi Liu, Xiaodong Chen, Bo Zhang, Yiming Peng, Jiansheng School of Computer and Software Nanjing University of Information Science and Technology Nanjing Jiangsu China School of Computing Edinburgh Napier University Edinburgh United Kingdom State Key Laboratory of Radar Signal Processing Xidian University Xi’an Shaanxi China School of Civil Engineering and Transportation Hebei University of Technology Tianjin Tianjin China Hechi Universtiy Guangxi Hechi China

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Node Scheduling Algorithm Based on Grid for Wireless Sensor Networks 19

Node Scheduling Algorithm Based on Grid for Wireless Sensor ...

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19th IEEE International Conference on Communication technology, ICCT 2019

作者： Zhang, Kun Chen, Jing Shen, Chong Chen, Yu Long, Keliu Aslam, Bhatti Uzair Education Center of MTA Hainan Tropical Ocean University Sanya Hainan572022 China State Key Laboratory of Marine Resources Utilization in South China Sea Hainan University Haikou Hainan570228 China College of Computer Science and Technology Hainan Tropical Ocean University Sanya Hainan572022 China College of Computer Science and Information Technology Nanjing Normal University Nanjing Jiangsu210023 China

ISBN: (纸本)9781728105352

How to reduce the energy consumption of the network and extend the life cycle of the wireless sensor network is one of the hotspots in the research of wireless sensor network. In the premise of ensuring the coverage of network, the node scheduling algorithm that let redundant nodes turn into the sleep state is a very effective energy-saving measure. In this paper, a node scheduling mechanism based on grid is proposed. The mechanism calculates the weight of each node in each grid, and then determine whether the node is a redundant coverage node. The result of Matlab simulation shows that the mechanism can effectively prolong the survival time of network. © 2019 IEEE.

关键词： Scheduling algorithms

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STR: Secure computation on additive shares using the share-transform-reveal strategy

arXiv

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arXiv 2020年

作者： Xia, Zhihua Gu, Qi Zhou, Wenhao Xiong, Lizhi Weng, Jian Xiong, Naixue N. College of Cyber Security Jinan University Guangzhou510632 China Engineering Research Center of Digital Forensics Ministry of Education School of Computer and Software Jiangsu Engineering Center of Network Monitoring Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology Nanjing University of Information Science & Technology Nanjing210044 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin541004 China The College of Intelligence and Computing Tianjin University Tianjin300350 China

The rapid development of cloud computing probably benefits many of us while the privacy risks brought by semi-honest cloud servers have aroused the attention of more and more people and legislatures. In the last two decades, plenty of works seek to outsource various specific tasks to servers while ensuring the security of private data. The tasks to be outsourced are countless;however, the computations involved are similar. In this paper, we construct a series of novel protocols that support the secure computation of various functions on numbers (e.g., the basic elementary functions) and matrices (e.g., the calculation of eigenvectors and eigenvalues) on arbitrary n ≥ 2 servers. All protocols only require constant rounds of interactions and achieve low computation complexity. Moreover, the proposed n-party protocols ensure the security of private data even though n − 1 servers collude. The convolutional neural network models are utilized as the case studies to verify the protocols. The theoretical analysis and experimental results demonstrate the correctness, efficiency, and security of the proposed protocols. Copyright © 2020, The Authors. All rights reserved.

关键词： Additives

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Unsupervised ensemble learning based on graph embedding for image clustering 25th

Unsupervised ensemble learning based on graph embedding for ...

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25th International Conference on Neural information processing, ICONIP 2018

作者： Luo, Xiaohui Zhang, Li Li, Fanzhang Hu, Chengxiang School of Computer Science and Technology and Joint International Research Laboratory of Machine Learning and Neuromorphic Computing Provincial Key Laboratory for Computer Information Processing Technology Soochow University SuzhouJiangsu215006 China

ISBN: (纸本)9783030041816

Manifold learning has attracted more and more attention in machine learning for past decades. Unsupervised Large Graph Embedding (ULGE), which performs well on the large-scale data, has been proposed for manifold learning. To improve the clustering performance, a novel Unsupervised Ensemble Learning based on Graph Embedding (UEL-GE) is explored, which takes ULGE to get low-dimensional embeddings of the given data and uses the K-means method to obtain the clustering results. Furthermore, the multiple clusterings are corrected by using the bestMap method. Finally, the corrected clusterings are combined to generate the final clustering. Extensive experiments on several data sets are conducted to show the efficiency and effectiveness of the proposed ensemble learning method. © Springer Nature Switzerland AG 2018.

关键词： K-means clustering

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An Integrated and Intelligent Dental Healthcare System with Mobile Services 15th

An Integrated and Intelligent Dental Healthcare System with ...

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15th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2019

作者： Xu, Yueshen Lu, Yi Li, Rui Niu, Lin Du, Wenzhi An, Ni Liu, Yaning Liu, Xinyi Jiang, Yan Li, Zhenhua Guo, Jin Wang, Xiangdong School of Computer Science and Technology Xidian University Xi’an710071 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University SuzhouJiangsu215006 China Stomatological Hospital Xi’an Jiaotong University Xi’an710004 China Clinical Research Center of Shaanxi Province for Dental and Maxillofacial Diseases College of Stomatology Xi’an Jiaotong University Xi’an China Shaanxi Lishengruihui Technology Co. Ltd. Xi’an710075 China

ISBN: (纸本)9783030301453

Medical informatization takes a key role in medical and healthcare industries, which is a necessary way of improving service quality and treatment experience in a hospital. In this paper, we design and implement an integrated and intelligent healthcare system with mobile services, specific to dental healthcare. The developed system contains four components, including WeChat official account, intelligent question and answering (Q&A) system, mobile follow-up care mini program and AI speech assistant. The developed WeChat official account and intelligent Q&A system provide a large amount of professional knowledge on dental health, which can help narrow the knowledge gap between doctors and patients. The two components facilitate patients to follow up our applications without downloading any extra softwares, as the developed functions (e.g., voice service) are provided through mobile services. These two components also facilitate follow-up management, decreasing manpower and resource usage in hospital. Our system is developed to serve patients as well as dentists, and provides a group of interactive healthcare services in a low cost. In this paper, we elaborate the whole system architecture and implementation detail of each component. We also report the performance test result and training process of the classifier. © 2019, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Hospitals

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Positive-Unlabeled Learning for Sentiment Analysis with Adversarial Training 15th

Positive-Unlabeled Learning for Sentiment Analysis with Adve...

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15th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2019

作者： Xu, Yueshen Li, Lei Huang, Jianbin Yin, Yuyu Shao, Wei Mai, Zhida Hei, Lei School of Computer Science and Technology Xidian University Xi’an710071 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University SuzhouJiangsu215006 China School of Computer Hangzhou Dianzi University Hangzhou310018 China School of Science RMIT University MelbourneVIC3001 Australia Xanten Guangdong Development Co. Ltd. Foshan528200 China Center of Journal Publication Xidian University Xi’anShaanxi710071 China

ISBN: (纸本)9783030301453

Sentiment classification is a critical task in sentiment analysis and other text mining applications. As a sub-problem of sentiment classification, positive and unlabeled learning or positive-unlabeled learning (PU learning) problem widely exists in real-world cases, but it has not been given enough attention. In this paper, we aim to solve PU learning problem under the framework of adversarial training and neural network. We propose a novel model for PU learning problem, which is based on adversarial training and attention-based long short-term memory (LSTM) network. In our model, we design a new adversarial training technique. We conducted extensive experiments on two real-world datasets. The experimental results demonstrate that our proposed model outperforms the compared methods, including the well-known traditional methods and state-of-the-art methods. We also report the training time, and discuss the sensitivity of our model to parameters. © 2019, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Long short-term memory

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