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arXiv 2018年

作者： Chen, Mingzhe Semiari, Omid Saad, Walid Liu, Xuanlin Yin, Changchuan Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China Chinese University of Hong Kong Shenzhen518172 China Department of Electrical Engineering Princeton University PrincetonNJ08544 United States Department of Electrical and Computer Engineering University of Colorado Colorado Springs Colorado SpringsCO80918 United States Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24060 United States

In this paper, the problem of enhancing the virtual reality (VR) experience for wireless users is investigated by minimizing the occurrence of breaks in presence (BIP) that can detach the users from their virtual world. To measure the BIP for wireless VR users, a novel model that jointly considers the VR application type, transmission delay, VR video quality, and users’ awareness of the virtual environment is proposed. In the developed model, the base stations (BSs) transmit VR videos to the wireless VR users using directional transmission links so as to provide high data rates for the VR users, thus, reducing the number of BIP for each user. Since the body movements of a VR user may result in a blockage of its wireless link, the location and orientation of VR users must also be considered when minimizing BIP. The BIP minimization problem is formulated as an optimization problem which jointly considers the predictions of users’ locations, orientations, and their BS association. To predict the orientation and locations of VR users, a distributed learning algorithm based on the machine learning framework of deep (ESNs) is proposed. The proposed algorithm uses concept from federated learning to enable multiple BSs to locally train their deep ESNs using their collected data and cooperatively build a learning model to predict the entire users’ locations and orientations. Using these predictions, the user association policy that minimizes BIP is derived. Simulation results demonstrate that the developed algorithm reduces the users’ BIP by up to 16% and 26%, respectively, compared to centralized ESN and deep learning algorithms. Copyright © 2018, The Authors. All rights reserved.

关键词： Virtual reality

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Study on Urban Water Landscape Planning Paradigm

Study on Urban Water Landscape Planning Paradigm

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2017 4th PMSS International Conference on Environmental Studies, Health Services and Social Sciences (EHS 2017)

作者： Jing He Hongxia Zhu Department of Architecture School of Civil Engineering and ArchitectureUniversity of Jinan Computer System Shandong College of Electronic Technology

In this paper,the research on the urban water landscape planning paradigm is *** space expansion will inevitably lead to the evolution of landscape pattern,this aspect at home and abroad have carried out a lot of research,and the city landscape and city spatial expansion model combined,according to city expansion and the road for construction and the adjacent relationship of the city can be extended into three kind of development model of filling type and extension type and *** water system is the blood of urban life is an important basis for urban landscape *** improve the quality of urban water system construction,the river management to better integrated into the city *** this background,this paper proposes the novel idea on the paradigm which will promote the further development.

关键词： Urban water Landscape planning Paradigm

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Analysis on the Development Trend of Urban Green Space Planning from the Perspective of Urban Agglomeration Planning

Analysis on the Development Trend of Urban Green Space Plann...

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2017 4th PMSS International Conference on Environmental Studies, Health Services and Social Sciences (EHS 2017)

作者： Jing He Hongxia Zhu Department of Architecture School of Civil Engineering and ArchitectureUniversity of Jinan Computer System Shandong College of Electronic Technology

In this paper,we conduct analysis on the development trend of urban green space planning from the perspective of urban agglomeration *** evaluation system of urban green space ecosystem function comprehensively evaluates and synthesizes some research that results from many angles and *** evaluation system relies on the objective statistical data and the subjective investigation and analysis as *** involves forestry,ecology,biology,statistics,environmental protection,urban planning and other aspects and the indicators cover the traditional evaluation of the contents of the general quantitative indicators,quality indicators,structural indicators and functional *** on the theory of organic evolution,the urban green space system is planned,constructed and managed,and the positive evolution of the urban green space system is completed through the coordination of the structural mechanism of the six internal mechanisms and coordination of the internal and external *** paper proposes the novel perspective on the analysis of the challenge which will promote the further development.

关键词： Urban green Space planning Urban agglomeration

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Construction of Urban Green Space Planning Evaluation system Based on SVM-AHP

Construction of Urban Green Space Planning Evaluation System...

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2017 4th ICMIBI International Conference on Training, Education, and Management (ICMIBI-TEM 2017)

作者： Jing He Hongxia Zhu Department of Architecture School of Civil Engineering and Architecture University of Jinan Computer system Shandong College of Electronic Technology

This paper presents the construction of the modern urban green space planning evaluation system based on SVM-AHP. At present, the research of urban green space is more concerned with the evaluation of ecological functions and ecosystem services of urban green space, and there are more mature methods and practice cases. With increase of environmental pressures brought about by urbanization, various environmental stresses pose a potential risk to the health of urban green space, directly reduce the green space ecosystem services, urban green space's health evaluation and risk assessment are increasingly brought to the attention of the people. With the integration of the SVM and AHP, this paper presents the novel idea on the issues that will promote the further development.

关键词： SVM-AHP Green space Planning evaluation system

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Multi-operating Modes Based Energy Management Strategy of Virtual Power Plant

Multi-operating Modes Based Energy Management Strategy of Vi...

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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Muhammad Hanan Waseem Yousaf Xin Ai Ehtisham Asghar Muhammad Yaqoob Javed Salman Salman Power System With Renewable Energy Sources North China Electric Power University Beijing China School of Control &Computer Engineering North China Electric Power University Beijing China North China Electric Power University Beijing Beijing CN Department of Electrical Computer Engineering COMSATS University Islamabad Lahore Punjab Pakistan Department of Electrical University Islamabad Lahore Punjab Pakistan

In this paper, a Virtual Power Plant (VPP) consists of a solar photovoltaic (PV) system, a wind turbine (WT) power generation system and an energy storage system (ESS) that is proposed in order to extenuate the utilization of fossil fuels on account of global warming and to cope with the increasing demand of electrical energy. These inexhaustible energy sources and the ESS are integrated to a common AC bus via double stage interfacing power converters. Multi-operating modes are generated by an Energy Management Strategy (EMS) that contingent on solar, wind and load power to control the scheduling operation of loads during dynamic weather and load conditions in order to avoid from blackout which is a primary focus of this paper. The PV and WT power generation systems are contemplated as the main sources of energy that satisfy the load demand in a regular manner whereas the battery is used only as a backup for the exigency. The modelling and the simulation of the presented VPP system are carried out under MATLAB/SIMULINK software. Simulation outcomes are shown and discussed that unveils the effectiveness and performance of the designed EMS.

关键词： Batteries Energy management Wind turbines State of charge Mathematical model

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Reliable Code Generation and Test Environment demonstrated on a PI-controller Design

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IFAC-PapersOnLine 2016年第3期49卷 465-470页

作者： Schwarz, M.H. Sheng, H. Üstoglu, I. Chabaan, W. Börcsök, J. Safety Computer Technology University of Kassel Germany Control and Automation Engineering Department Yildiz Technical University Istanbul Turkey Computer Architecture and System Programming University of Kassel Germany

This paper focuses on the latest version of a tool developed within the department to guide developer through the various steps of requirements, test-procedures and documentations to finally download the derived algorithm on a safety programmable logic controller (PLC). Requirements on how to develop and how to test software are steadily increasing due to international standards, which have to be obeyed in industries in general, and in the process- and automation industries in particular. A simple model is derived to be used to develop a PI controller that has to pass several steps to be qualified for execution on a PLC. The paper explains the different steps and describes the various problems that might occur. © 2016

关键词： controllers Accident prevention Reliability Software testing Automated code generation Automation industry International standards P i controller designs PI control Programmable Logic controller (PLC) Simple modeling Test Environment

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Stability and Performance Analysis of Saturated systems Using an Enhanced Max Quadratic Lyapunov Function

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IFAC-PapersOnLine 2017年第1期50卷 11847-11852页

作者： Li Y. Lin Z. Li N. Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA 22904-4743 United States

This paper revisits the problem of estimating the domain of attraction and the nonlinear L2 gain of a saturated system with an algebraic loop. A max quadratic Lyapunov function, the maximum function of a group of quadratic Lyapunov functions, is proposed for use in the stability and performance analysis for a saturated system. The max quadratic Lyapunov function involves a partitioning of the state space. Exploiting the special properties of regions of the state space, we propose in this paper an enhanced max quadratic Lyapunov function, which results from adding a term that characterizes the regions of the state space to the max quadratic Lyapunov function. The matrix associated with the enhanced max quadratic Lyapunov function is not required to be positive definite, and thus a set of less conservative stability and performance conditions are established, from which a larger estimate of the domain of attraction and a tighter estimate of the nonlinear L2 gain can be obtained. Simulation results indicate the effectiveness and superiority of the proposed method. © 2017

关键词： Domain of attraction enhanced max quadratic Lyapunov functions input saturation L2 gain

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Self-Awareness for Autonomous systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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Breast Cancer Diagnosis Using an Unsupervised Feature Extraction Algorithm Based on Deep Learning

Breast Cancer Diagnosis Using an Unsupervised Feature Extrac...

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Chinese control Conference

作者： Yawen Xiao Jun Wu Zongli Lin Xiaodong Zhao Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai China The Center for Bioinformatics and Computational Biology East China Normal University Shanghai China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA U.S.A School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China

Breast cancer is the most often detected cancer in women. At the same time, it is one of the most curable types of cancer if diagnosed early. With the development of the detection technology, a growing amount of clinical data and high-dimensional features can be used for breast cancer diagnosis. The high-dimensional data contributes to advances in the diagnostic technology, but also incurs a large amount of computational redundancy. Thus, extracting important information and reducing the feature dimension is critical to effective prediction and an accurate treatment decision. However, the previous works for breast cancer diagnosis are mainly based on labeled data that is difficult to obtain. To address this issue, in this paper, we demonstrate a new scheme, which integrates a deep learning based unsupervised feature extraction algorithm, the stacked auto-encoders, with a support vector machine model (SAE-SVM), for breast cancer diagnosis. The stacked auto-encoders with the greedy layer-wise pre-training and an improved momentum update algorithm is applied to capture essential information and extract necessary features of the original data. Then, a support vector machine model is employed to classify the samples with new features into malignant or benign tumors. The proposed method was tested on the Wisconsin Diagnostic Breast Cancer data set. The performance is evaluated using various measures and compared with the previously published results. The comparison results show that the proposed SAE-SVM method improves the accuracy to 98.25% and outperforms the other methods. The deep learning based unsupervised feature extraction significantly improves the performance of classification and provides a promising approach to breast cancer diagnosis.

关键词： Breast cancer Feature extraction Machine learning Support vector machines Electronic mail Principal component analysis

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Data Stream Online Clustering Based on Fuzzy Expectation-Maximization Approach

Data Stream Online Clustering Based on Fuzzy Expectation-Max...

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IEEE International Conference on Data Stream Mining & Processing (DSMP)

作者： Anastasiia O. Deineko Polina Ye. Zhernova Boris Gordon Oleksandr O. Zayika Iryna Pliss Nelya Pabyrivska Artificial Intelligence Department Kharkiv National University of Radio Electronics Kharkiv Ukraine System Engineering Department Kharkiv National University of Radio Electronics Kharkiv Ukraine Computer Systems Department Tallinn University of Technology Tallinn Estonia Control Systems Research Laboratory Kharkiv National University of Radio Electronics Kharkiv Ukraine Department of Mathematics Lviv Polytechnic National University Lviv Ukraine

ISBN: (纸本)9781538628751

In the paper the online fuzzy clustering recurrent procedure has been introduced that allows the forming of hyperellipsoidal clusters with an arbitrary orientation of the axes is proposed. Such clustering system is the generalization of a number of known algorithms, it is intended to solve tasks within the general problems of Data Stream Mining (DSM) and Dynamic Data Mining (DDM), when information is sequentially fed to processing in online mode.

关键词： Data mining Clustering algorithms Task analysis Linear programming Probabilistic logic Minimization Neural networks

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