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A Green Paradigm for Internet of Things: Ambient Backscatter Communications

China Communications 2019年第7期16卷 109-119页

作者： Wei Zhang Yao Qin Wenjing Zhao Minzheng Jia Qiang Liu Ruisi He Bo Ai Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology and also with Institute of Telecommunication Satellites China Academy of Space Technology (CAST) Beijing Key Lab of Transportation Data Analysis and Mining Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications School of Computer and Information Technology Beijing Jiaotong University Beijing 100044 China Department of Information Engineering Beijing Polytechnic College Beijing 100042 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 100044 China

Internet of Things (IoT) has attracted extensive interest from both academia and industries, and is recognized as an ultimate infrastructure to connect everything at anytime and anywhere. The implementation of IoT generally faces the challenges from energy constraint and implementation cost. In this paper, we will introduce a new green communication paradigm, the ambient backscatter (AmBC), that could utilize the environmental wireless signals for both powering a tiny-cost device and backscattering the information symbols. Specifically, we will present the basic principles of AmBC, analyze its features and advantages, suggest its open problems, and predict its potential applications for our future IoT.

关键词： ambient backscatter (AmBC) RF-powered device Internet of Things (IoT) battery-free tag wire-less sensor

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Research on Network Traffic Anomaly Detection of Source-Network-Load Industrial control System Based on GRU-OCSVM 3

Research on Network Traffic Anomaly Detection of Source-Netw...

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3rd International Symposium on Resource Exploration and Environmental Science, REES 2019

作者： Huo, Xuesong Wu, Kehe Miao, Weiwei Wang, Liming He, Hui Su, Dawei State Grid Jiangsu Electric Power Co. Ltd. Power Dispatching Control Center Nanjing210000 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China Information and Communication Branch of State Grid Jiangsu Electric Power Co. Ltd. Nanjing210019 China

With the large number of distributed generators and diverse loads connected to industrial control systems, there are more and more interactions among power supply, power grid and load. Any network link attack in the source network will affect the security of the industrial control system, resulting in economic loss of the industrial control system. Therefore, it is very important to study the network attacks against the source-network-load industrial control system. Aiming at the current insufficient situation of network traffic anomaly detection in the source-network-load industrial control system, this paper analysed the composition and flow characteristics of the source-network-load system, studied the scheme of network traffic anomaly detection of the source-network-load system, and proposed a network traffic anomaly detection algorithm based on GRU-OCSVM. The time characteristics of the traffic sequence were extracted by the GRU and input into OCSVM for traffic anomaly detection. Finally, the original network traffic of the source-network-load system was collected to construct anomaly detection data set for simulation experiment. The experimental results showed that the proposed method had high detection rate and low false positive rate, which can meet the needs of network traffic anomaly detection in the source-network-load system. © Published under licence by IOP Publishing Ltd.

关键词： Anomaly detection

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A Markov Traffic Model for Signalized Traffic Networks Based on Bayesian Estimation

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IFAC-PapersOnLine 2020年第2期53卷 15029-15034页

作者： S.Y. Liu S. Lin Y.B. Wang B. De Schutter W.H.K. Lam School of Computer Science and Technology University of Chinese Academy of Sciences Beijing 100089 China Key Lab of Big Data Mining and Knowledge Management Chinese Academy of Sciences College of Civil Engineering and Architecture Zhejiang University PR China Delft Center for Systems and Control Delft University of Technology The Netherlands Department of Civil and Structural Engineering The Hong Kong Polytechnic University Hong Kong SAR China

In order to better understand the stochastic dynamic features of signalized traffic networks, we propose a Markov traffic model to simulate the dynamics of traffic link flow density for signalized urban traffic networks with demand uncertainty. In this model, we have four different state modes for the link according to different congestion levels of the link. Each link can only be in one of the four link state modes at any time, and the transition probability from one state to the other state is estimated by Bayesian estimation based on the distributions of the dynamic traffic flow densities, and the posterior probabilities. Therefore, we use a first-order Markov Chain Model to describe the dynamics of the traffic flow evolution process. We illustrate our approach for a small traffic network. Compared with the data from the microscopic traffic simulator SUMO, the proposed model can estimate the link traffic densities accurately and can give a reliable estimation of the uncertainties in the dynamic process of signalized traffic networks.

关键词： Markov traffic model Traffic signals Bayesian Urban traffic network

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Application of the Dynamic Iterative Learning control to the Heteroplanar Active Magnetic Bearing

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IFAC-PapersOnLine 2020年第2期53卷 1511-1516页

作者： Lukasz Hladowski Arkadiusz Mystkowski Krzysztof Galkowski Eric Rogers Bing Chu Institute of Control and Computation Engineering University of Zielona Góra ul. Podgórna 50 65-246 Zielona Góra Poland Faculty of Electrical Engineering Bialystok University of Technology ul.Wiejska 45c 15-351 Bialystok Poland School of Electronics and Computer Science University of Southampton Southampton SO17 1BJ UK

Heteroplanar active magnetic bearings have numerous applications, where one example is a high-temperature gas-cooled reactors. Rotor imbalance, however, may cause problems for critical parts of the system in the form of repetitive periodic vibrations. This is known problem and periodic component extraction is widely used in active magnetic bearing unbalance control laws. More recently, iterative learning control has been considered as an alternative and this paper gives new results on this approach. In particular, a new control law in the 2D systems setting is developed and the results of a simulation based study using the model of a test rig are given, where such a study is an essential step prior to experimental validation.

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Stabilizing Frequency of Microgrid Integrated With Electric Vehicles by Droop control

Stabilizing Frequency of Microgrid Integrated With Electric ...

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

作者： Mishkat Ullah Jan Ai Xina Shahzad Ali Haseeb Ur Rehmana Sheeraz Iqbala Arsalan Masooda Salman Salmana Muhammad Aurangzeba School of Electrical & Electronics Engineering North China Electric Power University Beijing China School of Computer & Control Engineering North China Electric Power University Beijing China

ISBN: (数字)9781728131375

ISBN: (纸本)9781728131382

Emergence of Microgrid (MG) has changed the structure of power system. On one hand, it opened opportunities to integrate renewable energy sources in islanding mode; on the other hand, the power and frequency have become the main hurdles during its islanding operation. In this paper, the droop control technique is used to counter the effect of frequency fluctuation at MG. Wind energy and Photovoltaics are the two renewable energy sources (RES) studied in work. Diesel generator is used to cater the frequency deviations due to intermittent nature of these RES. Microgrid Operator (MGO) is used as a centralized controller to look after all generating units and loads. The MGO sends a reference signal based upon the frequency deviation, which is calculated by the droop controller. This reference signal is sent to all generating units as well Electric Vehicles Operator (EVsO). All the generators and EVsO respond to that reference signal and adjust their generating power accordingly. Electric Vehicles (EV), operated by EVsO, remains in continuous contact with the MGO through communication link. In this work, a centralized approach for the operation of EVsO is employed. There are two main tasks of the EVsO. One is to calculate the cumulative power of all the EVs connected with the MG, by calculating their initial state of charge; and another is, to change the charging and discharging rate of EVs by stratifying the energy needs of both MG and EVs.

关键词： Frequency control Generators Wind turbines Microgrids Electric vehicles Batteries

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Review of renewable energy curtailment in China: Current situation and solutions

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AIP Conference Proceedings 2022年第1期2681卷

作者： Yingai Jin Yiwen Zhang Nan Jiang Mingjie Lv Hang Yin Wenyuan Sun Liang Li 1State Key Laboratory of Automotive Simulation and Control Jilin University Changchun 130025 China 2College of Automotive Engineering Jilin University Changchun 130025 China 3School of Physics Engineering and Computer Science University of Hertfordshire Hatfield AL10 9AB UK

In recent decades, China's renewable power generation has developed quickly. However, the randomness of output power causes wind and photovoltaic power curtailment. With the rapid development of renewable energy, renewable energy consumption has gradually become the focus of research. This article comprehensively reviews the current situation and practices of reducing the curtailment of renewable energy in China. From the perspective of methods used to stabilize the fluctuation characteristics of generation output, two modes are outlined: based on energy storage devices and complementary wind-solar system. Then, an Advanced Adiabatic Compressed Air Energy Storage (AA-CAES) system simulation model is proposed as a crucial solution to reduce renewable energy waste. Finally, the application and development trend of renewable energy and energy storage technology has prospected.

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Weighted Linear Multiple Kernel Learning for Saliency Detection 2nd

Weighted Linear Multiple Kernel Learning for Saliency Detect...

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2nd EAI International Conference on Robotic Sensor Networks, ROSENET 2018

作者： Zhou, Quan Wu, Jinwen Fan, Yawen Zhang, Suofei Wu, Xiaofu Zheng, Baoyu Jin, Xin Lu, Huimin Latecki, Longin Jan National Engineering Research Center of Communications and Networking Nanjing University of Posts and Telecommunications Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China College of Information Engineering China University of Geosciences Wuhan China School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing China National Engineering Research Center of Communications and Networking Nanjing University of Posts and Telecommunications Nanjing China Department of Cyber Security Beijing Electronic Science and Technology Institute Beijing China CETC Big Data Research Institute Co. Ltd. Guizhou Guiyang China Department of Mechanical and Control Engineering Kyushu Institute of Technology Kitakyushu Japan Department of Computer and Information Sciences Temple University PhiladelphiaPA United States

ISBN: (纸本)9783030177621

This paper presents a novel saliency detection method based on weighted linear multiple kernel learning (WLMKL), which is able to adaptively combine different contrast measurements in a supervised manner. Three commonly used bottom-up visual saliency operations are first introduced, including corner-surround contrast (CSC), center-surround contrast (CESC), and global contrast (GC). Then these contrast measures are fed into our WLMKL framework to produce the final saliency map. We show that the assigned weights for each contrast feature maps are always normalized in our WLMKL formulation. In addition, the proposed approach benefits from the advantages of the contribution of each individual contrast operation, and thus produces more robust and accurate saliency maps. The extensive experimental results show the effectiveness of the proposed model, and demonstrate the combination is superior to individual subcomponent. © 2020, Springer Science and Business Media Deutschland GmbH. All rights reserved.

关键词： Center-surround contrast Corner-surround contrast Global contrast Multiple kernel learning Saliency detection

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Molecular Diagnostic and Using Deep Learning Techniques for Predict Functional Recovery of Patients Treated of Cardiovascular Disease

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IEEE Access 2019年 7卷 120315-120325页

作者： Ar Junejo Yin Shen Asif Ali Laghari Xiaobo Zhang Hao Luo School of Control Science and Engineering Harbin Institute of Technology Harbin China Department of Computer Science Sindh Madressatul Islam University Karachi Pakistan School of Automation Guandong University of Technology Guangzhou China

Today, with the development of industry and mechanized life style, the prevalence of the disease is rising steadily as well. Observing at the trend and lifecycle style, its predict that after ten years around 23.6 million people die because of Cardiovascular Disease (CVD). For that reason, aim to use Deep Learning Techniques (DLTs), to analysis stable CVD that would give valuable awareness to decrease misdiagnosis in the Robust Healthcare Industry (RHI). An objective of this paper is first, Molecular diagnosis (MD), and second using Deep Learning Techniques DLTs, to synthesis and characterize to accumulate (raw information) from CVD patients, those who admitted the emergency section between January (2018 to December 2019). We are using Artificial Neural Network (ANN), model characterize to predict CVD patients and configuration, Feature selection (FS), Mean Square Error (MSE), accuracy, sensitivity. The ANN accuracy is 98.4, K-nearest neighbor (KNN) accuracy is 98.01%, Naïve Bayes (NB), accuracy is 96.99%. Decision tree (DT), accuracy is 87.81%. Our robust data driven model explore the efficient accuracy rate to predict CVD patients. The ANN model in term of their efficient in disease analysis, and prognosis of the RHI.

关键词： Heart Blood Diseases Arteries Mathematical model Artificial neural networks

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Findings from the Tushirikiane-4-MH (Supporting Each Other for Mental Health) Mobile Health-Supported Virtual Reality Randomized controlled Trial Among Urban Refugee Youth in Kampala, Uganda

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Global Mental Health 2025年 12卷 e12-e12页

作者： Logie, Carmen H. Okumu, Moses Admassu, Zerihun MacKenzie, Frannie Gittings, Lesley Kortenaar, Jean-Luc Khan, Naimul Hakiza, Robert Musoke, Daniel Kibuuka Nakitende, Aidah Katisi, Brenda Kyambadde, Peter Lester, Richard Mbuagbaw, Lawrence Factor-Inwentash Faculty of Social Work University of Toronto Toronto ON Canada Women's College Research Institute Women's College Hospital Toronto ON Canada United Nations University Institute for Water Environment & Health Hamilton ON Canada Centre for Gender and Sexuality Health Equity Vancouver BC Canada School of Social Work University of Illinois Urbana-Champaign United States Uganda Christian University Mukono Uganda School of Health Studies Western University London ON Canada Centre for Social Science Research University of Cape Town South Africa Dalla Lana School of Public Health University of Toronto Toronto ON Canada Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto ON Canada Young African Refugees for Integral Development (YARID) Kampala Uganda International Research Consortium Kampala Uganda National AIDS and STI Control Programme Ministry of Health Kampala Uganda Most At Risk Population Initiative Mulago Hospital Kampala Uganda Department of Medicine University of British Columbia Vancouver BC Canada Department of Health Research Methods Evidence and Impact McMaster University Hamilton ON Canada Department of Anesthesia McMaster University Hamilton ON Canada

Background: Virtual reality (VR) for mental health promotion remains understudied in low income humanitarian settings. We examined the effectiveness of VR in reducing depression with urban refugee youth in Kampala, Uganda. Methods: This randomized controlled trial assessed VR alone (Arm 1), VR followed by group problem management plus (GPM+) (Arm 2), and a control group (Arm 3), with a peer-driven and convenience sample of refugee youth aged 16-25 in Kampala. The primary outcome, depression, was measured with the Patient Health Questionnaire-9. Secondary outcomes included: mental health literacy, mental health stigma, self-compassion, mental wellbeing, and adaptive coping. Analyses were conducted at three timepoints (baseline, 8-weeks, 16-weeks) using generalized estimating equations (GEE). Results: Among participants (n=335, mean age: 20.77, standard deviation: 3.01;cisgender women: n=158, cisgender men: n=173, transgender women: n=4) we found no depression reductions for Arms 1 or 2 at 16-weeks compared with Arm 3. At 16-weeks, mental health literacy was significantly higher for Arm 2 compared with Arm 3, and self compassion was significantly higher in Arms 1 and Arm 2 compared with Arm 3. Discussion: VR alongside GPM+ may benefit self-compassion and MHL among urban refugee youth in Kampala, but these interventions were not effective in reducing depression. © The Author(s), 2025. Published by Cambridge University Press.

关键词： depression refugees self-compassion Uganda virtual reality youth

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Detecting Glaucoma in the Ocular Hypertension Study Using Deep Learning

TechRxiv

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TechRxiv 2021年

作者： Fan, Rui Bowd, Christopher Christopher, Mark Brye, Nicole Proudfoot, James A. Rezapour, Jasmin Belghith, Akram Goldbaum, Michael H. Chuter, Benton Girkin, Christopher A. Fazio, Massimo A. Liebmann, Jeffrey M. Weinreb, Robert N. Gordon, Mae O. Kass, Michael A. Kriegman, David Zangwill, Linda M. Hamilton Glaucoma Center Viterbi Family Department of Ophthalmology Shiley Eye Institute University of California La Jolla San DiegoCA United States Department of Computer Science and Engineering University of California La Jolla San DiegoCA United States Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201804 China Department of Ophthalmology Universitätsmedizin der Johannes Gutenberg-Universität Mainz Rheinland-Pfalz Mainz Germany Department of Ophthalmology School of Medicine The University of Alabama at Birmingham BirminghamAL United States Department of Biomedical Engineering School of Engineering The University of Alabama at Birmingham BirminghamAL United States Bernard and Shirlee Brown Glaucoma Research Laboratory Edward S. Harkness Eye Institute Columbia University Medical Center New YorkNY United States Department of Ophthalmology and Visual Sciences Washington University School of Medicine Washington University St. LouisMO United States

Importance: Automated deep learning (DL) analyses of fundus photographs potentially can reduce the cost and improve the efficiency of reading center assessment of endpoints in clinical trials. Objective: To investigate the diagnostic accuracy of DL algorithms trained on fundus photographs from the Ocular Hypertension Treatment Study (OHTS) to detect primary open-angle glaucoma (POAG). Study Design: Diagnostic/prognostic Study Setting and Participants: 1,636 OHTS participants from 22 sites with a mean follow-up (range) of 10.7 (0.0, 14.3) years. 66,715 photographs from 3,272 eyes were used to train and test a ResNet-50 model to detect the OHTS Endpoint Committee POAG determination based on optic disc (n=287 eyes, 3,502 photographs) and/or visual field (n=198 eyes, 2,300 visual fields) changes. Three independent test sets were used to evaluate the generalizability of the model. Main Outcome and Measures: Areas under the receiver operating characteristic curve (AUROC) and sensitivities at fixed specificities were calculated to compare model performance. Evaluation of false-positive rates was used to determine whether the DL model detected POAG before the Endpoint Committee POAG determination. Results: The DL model achieved an AUROC (95% CI) of 0.88 (0.82, 0.92) for the overall OHTS POAG endpoint. For the OHTS endpoints based on optic disc changes or visual field changes, AUROCs were 0.91 (0.88, 0.94) and 0.86 (0.76, 0.93), respectively. False-positive rates (at 90% specificity) were higher in photographs of eyes that later developed POAG by disc or visual field (19.1%) compared to eyes that did not develop POAG (7.3%) during their follow-up. The diagnostic accuracy of the DL model developed on the optic disc endpoint applied to 3 independent datasets was lower with AUROC ranging from 0.74 to 0.79. Conclusion and Relevance: The model’s high diagnostic accuracy using OHTS photographs suggests that DL has the potential to standardize and automate POAG determination for cl

关键词： Ophthalmology

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