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2017 IEEE 6th Data Driven control and Learning Systems Conference (DDCLS’17)

作者： Xia Wu Zengqiang Chen Mingwei Sun Qinglin Sun College of Computer and Control Engineering Nankai University Key Lab of Intelligent Robotics of Tianjin College of Science Civil Aviation University of China

ISBN: (纸本)9781509054626

An improved algorithm called active disturbance rejection generalized predictive control which combines advantages of active disturbance rejection control and generalized predictive control is proposed for time-delay systems in this paper to reduce the limitations of active disturbance rejection control(ADRC) in plants with large time-delay and improve the imperfections of generalized predictive control method such as huge computation and strong dependence on mathematical model. The method proposed in this paper can deduce the general solution to the Diophantine equations off-line without the system parameter identification because of the extended state observer. Hence, the online computation burden of this improved method is reduced typically and its application is enlarged. Simulation results show that this proposed design turns out to be a new solution for the large time-delay systems.

关键词： Active Disturbance Rejection control(ADRC) Generalized Predictive control(GPC) Active Disturbance Rejection Generalized Predictive control(ADRC-GPC) Diophantine Equation Large Time-delay Systems

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Distributed control of DC grids: Integrating prosumers motives

arXiv

引用

arXiv 2019年

作者： Cucuzzella, Michele Bouman, Thijs Kosaraju, Krishna Chaitanya Schuitema, Geertje Lemmen, N.H. Johnson-Zawadzki, Steph Fischione, Carlo Steg, Linda Scherpen, Jacquelien M.A. Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia27100 Italy Jan C. Willems Center for Systems and Control ENTEG University of Groningen Nijenborgh 4 Groningen9747 AG Netherlands University of Groningen Grote Kruisstraat 2/1 Groningen9712 TS Netherlands Department of Electrical Engineering University of Notre Dame Notre DameIN46556 United States University College Dublin College of Business Carysfort Avenue Blackrock Dublin Ireland The School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm114 28 Sweden

In this paper, a novel distributed control strategy addressing a (feasible) psycho-social-physical welfare problem in islanded Direct Current (DC) smart grids is proposed. Firstly, we formulate a (convex) optimization problem that allows prosumers to share current with each other, taking into account the technical and physical aspects and constraints of the grid (e.g., stability, safety), as well as psycho-social factors (i.e., prosumers’ personal values). Secondly, we design a controller whose (unforced) dynamics represent the continuous time primal-dual dynamics of the considered optimization problem. Thirdly, a passive interconnection between the physical grid and the controller is presented. Global asymptotic convergence of the closed-loop system to the desired steady-state is proved and simulations based on collected data on psycho-social aspects illustrate and confirm the theoretical results. Copyright © 2019, The Authors. All rights reserved.

关键词： controllers

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Global, regional, and national burden of asthma and atopic dermatitis, 1990–2021, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021

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The Lancet Respiratory Medicine 2025年第5期13卷 425-446页

作者： Oh, Jiyeon Kim, Soeun Kim, Min Seo Abate, Yohannes Habtegiorgis Abd ElHafeez, Samar Abdelkader, Atef Abdi, Parsa Abdulah, Deldar Morad Aboagye, Richard Gyan Abolhassani, Hassan Abtahi, Dariush Abualruz, Hasan Abu-Gharbieh, Eman Aburuz, Salahdein Adane, Mesafint Molla Addo, Isaac Yeboah Adeleke, Olumide Thomas Aden, Bashir Adnani, Qorinah Estiningtyas Sakilah Adra, Saryia Afzal, Muhammad Sohail Ahmad, Sajjad Ahmad, Tauseef Ahmadi, Ali Ahmed, Syed Anees Al Awaidy, Salah Al Bakour, Mohamad Anas Alam, Khurshid Albashtawy, Mohammed Al-Eyadhy, Ayman Al-Gheethi, Adel Ali Saeed Alhalaiqa, Fadwa Naji Ali, Syed Shujait Ali, Waad Alif, Sheikh Mohammad Al-Jabi, Samah W. Alqahtani, Jaber S. AlQudah, Mohammad Alrawashdeh, Ahmad Alshahrani, Najim Z. Altaany, Zaid Altaf, Awais Al-Tammemi, Alaa B. Altirkawi, Khalid A. Alvis-Guzman, Nelson Alwafi, Hassan Al-Wardat, Mohammad Al-Worafi, Yaser Mohammed Aly, Hany Alyahya, Mohammad Sharif Ibrahim Alzoubi, Karem H. Amusa, Ganiyu Adeniyi Ansar, Adnan Anuoluwa, Boluwatife Stephen Anuoluwa, Iyadunni Adesola Anyasodor, Anayochukwu Edward Arabloo, Jalal Aravkin, Aleksandr Y. Areda, Demelash Asghari-Jafarabadi, Mohammad Ashraf, Tahira Athari, Seyyed Shamsadin Aujayeb, Avinash Ayana, Lemessa Assefa A. Aziz, Shahkaar Azzam, Ahmed Y. Barqawi, Hiba Jawdat Barrow, Amadou Bastan, Mohammad-Mahdi Batra, Kavita Behera, Priyamadhaba Behzadi, Payam Bell, Michelle L. Beneke, Alice A. Berhie, Alemshet Yirga Beyene, Kebede A. Bhattacharjee, Priyadarshini Bhatti, Jasvinder Singh Bolarinwa, Obasanjo Afolabi Bouaoud, Souad Bustanji, Yasser Butt, Nadeem Shafique Camargos, Paulo Cámera, Luis Alberto Carugno, Andrea Cenderadewi, Muthia Cerrai, Sonia Chakraborty, Sandip Chan, Jeffrey Shi Kai Chandika, Rama Mohan Chattu, Vijay Kumar Chaudhary, Anis Ahmad Cheng, Esther T. W. Chichagi, Fatemeh Chimoriya, Ritesh Ching, Patrick R. Chirinos-Caceres, Jesus Lorenzo Chong, Yuen Yu Chopra, Hitesh Chu, Dinh-Toi Corlateanu, Alexandru Cruz-Martins, Natalia da Silva, Alanna Gomes Dababo, Nour Dadras, Omid Dai, Xiaochen Damiani Department of Medicine Kyung Hee University College of Medicine Seoul South Korea Center for Digital Health Kyung Hee University College of Medicine Seoul South Korea Broad Institute of MIT and Harvard Cambridge MA United States Massachusetts General Hospital Boston MA United States Department of Clinical Governance and Quality Improvement Aleta Wondo General Hospital Aleta Wondo Ethiopia Department of Epidemiology Alexandria University Alexandria Egypt Department of Mathematics and Sciences Ajman University Ajman United Arab Emirates Department of Medicine Memorial University St John's NL Canada Community and Maternity Nursing Unit University of Duhok Duhok Iraq Department of Family and Community Health University of Health and Allied Sciences Ho Ghana Research Center for Immunodeficiencies Tehran Iran Department of Medical Biochemistry and Biophysics Karolinska Institute Stockholm Sweden Department of Anesthesiology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Nursing Al Zaytoonah University of Jordan Amman Jordan Department of Clinical Sciences Sharjah United Arab Emirates Department of Biopharmaceutics and Clinical Pharmacy University of Jordan Amman Jordan College of Pharmacy University of Jordan Amman Jordan Department of Pharmacology and Therapeutics Al Ain United Arab Emirates College of Medicine and Health Sciences Bahir Dar University Bahir Dar Ethiopia School of Medicine University of Sydney Sydney NSW Australia Centre for Social Research in Health University of New South Wales Sydney NSW Australia Department of Family Medicine Bowen University Iwo Nigeria Bowen University Teaching Hospital Ogbomoso Nigeria United Arab Emirates University Al Ain United Arab Emirates Institute of Public Health Walden University Al Ain United Arab Emirates Department of Public Health Padjadjaran University (Universitas Padjadjaran) Bandung Indonesia Clinical Sciences Department Sharjah United Arab Emirates Department

Background: Asthma and atopic dermatitis are common allergic conditions that contribute to substantial health loss, economic burden, and pain across individuals of all ages worldwide. Therefore, as a component of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021, we present updated estimates of the prevalence, disability-adjusted life-years (DALYs), incidence, and deaths due to asthma and atopic dermatitis and the burden attributable to modifiable risk factors, with forecasted prevalence up to 2050. Methods: Asthma and atopic dermatitis prevalence, incidence, DALYs, and mortality, with corresponding 95% uncertainty intervals (UIs), were estimated for 204 countries and territories from 1990 to 2021. A systematic review identified data from 389 sources for asthma and 316 for atopic dermatitis, which were further pooled using the Bayesian meta-regression tool. We also described the age-standardised DALY rates of asthma attributable to four modifiable risk factors: high BMI, occupational asthmagens, smoking, and nitrogen dioxide pollution. Furthermore, as a secondary analysis, prevalence was forecasted to 2050 using the Socio-demographic Index (SDI), air pollution, and smoking as predictors for asthma and atopic dermatitis. To assess trends in the burden of asthma and atopic dermatitis before (2010–19) and during (2019–21) the COVID-19 pandemic, we compared their average annual percentage changes (AAPCs). Findings: In 2021, there were an estimated 260 million (95% UI 227–298) individuals with asthma and 129 million (124–134) individuals with atopic dermatitis worldwide. Asthma cases declined from 287 million (250–331) in 1990 to 238 million (209–272) in 2005 but increased to 260 million in 2021. Atopic dermatitis cases consistently rose from 107 million (103–112) in 1990 to 129 million (124–134) in 2021. However, age-standardised prevalence rates decreased—by 40·0% (from 5568·3 per 100 000 to 3340·1 per 100 000) for asthma and 8·3% (from 1885·4

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Steady-state analysis of a neural-cognition based human-social behavior model

arXiv

引用

arXiv 2018年

作者： Wei, Jieqiang Nekouei, Ehsan Wu, Junfeng Cvetkovic, Vladimir Johansson, Karl H. Department of Automatic Control School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden College of Control Science and Engineering Zhejiang University Hangzhou China School of Architecture and the Built Environment

We consider an extension of the Rescorla-Wagner model which bridges the gap between conditioning and learning on a neural-cognitive, individual psychological level, and the social population level. In this model, the interaction among individuals is captured by a Markov process. The resulting human-social behavior model is a recurrent iterated function systems which behaves differently from the classical Rescorla- Wagner model due to randomness. Convergence and ergodicity properties of the internal states of agents in the proposed model are studied. Copyright © 2018, The Authors. All rights reserved.

关键词： Decision making

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JOINT CONVOLUTIONAL NEURAL NETWORK FOR SMALL-SCALE SHIP CLASSIFICATION IN SAR IMAGES

JOINT CONVOLUTIONAL NEURAL NETWORK FOR SMALL-SCALE SHIP CLAS...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Yanxia Wu Ye Yuan Jian Guan Libo Yin Jinyong Chen Ge Zhang Pengming Feng College of Computer Science and Technology Harbin Engineering University Harbin China China Industrial Control Systems Cyber Emergency Response Team Beijing China The 54th Research Institute of China Electronics Technology Group Corporation Shijiazhuang China State Key Laboratory of Space-Ground Integrated Information Technology Beijing China

Ship classification using synthetic aperture radar (SAR) imagery is a challenge problem in maritime surveillance. Because of the scale limitation of ship targets in SAR image, convolutional neural networks (CNNs) can not achieve similar performance as for natural image classification. In this paper, we propose a joint CNNs framework for small-scale ship targets classification in SAR image, where a generator and a classifier are jointly connected. The generator can reconstruct the small-scale low-resolution (LR) images to large-scale super-resolution (SR) images, and the classifier is used for ship classification. A novel joint loss optimization strategy is introduced to solve the problem, where an MSE-based content loss is employed to generate high quality SR images, and a classification loss is applied to enable the generator and the classifier to be trained in a joint way. Experiments are conducted to demonstrate the superior performance of our proposed method, as compared with the state-of-the-art methods.

关键词： Marine vehicles Generators Synthetic aperture radar Containers Radar polarimetry Convolutional neural networks Training

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Emergence of the First Strains of SARS-CoV-2 Lineage B.1.1.7 in Romania: Genomic Analysis

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JMIRx med 2021年第3期2卷 e28049页

作者： Andrei Lobiuc Mihai Dimian Olga Sturdza Roxana Filip Mihai Covasa Department of Human Health and Development College of Physical Exercise and Sport Stefan cel Mare University of Suceava Suceava Romania. Department of Computers Electronics and Automation College of Electrical Engineering and Computer Science Stefan cel Mare University of Suceava Suceava Romania. Integrated Center for Research Development and Innovation in Advanced Materials Nanotechnologies and Distributed Systems for Fabrication and Control Stefan cel Mare University of Suceava Suceava Romania. Suceava County Emergency Hospital Suceava Romania.

BACKGROUND:The United Kingdom reported the emergence of a new and highly transmissible SARS-CoV-2 variant (B.1.1.7) that rapidly spread to other countries. The impact of this new mutation-which occurs in the S protein-on infectivity, virulence, and current vaccine effectiveness is still under evaluation. OBJECTIVE:The aim of this study is to sequence SARS-CoV-2 samples of cases in Romania to detect the B.1.1.7 variant and compare these samples with sequences submitted to GISAID. METHODS:SARS-CoV-2 samples were sequenced and amino acid substitution analysis was performed using the CoV-GLUE platform. RESULTS:We have identified the first cases of the B.1.1.7 variant in samples collected from Romanian patients, of which one was traced to the region of the United Kingdom where the new variant was originally sequenced. Mutations in nonstructural protein 3 (Nsp3; N844S and D455N) and ORF3a (L15F) were also detected, indicating common ancestry with UK strains as well as remote connections with strains from Nagasaki, Japan. CONCLUSIONS:These results indicate, for the first time, the presence and characteristics of the new variant B.1.1.7 in Romania and underscore the need for increased genomic sequencing in patients with confirmed COVID-19.

关键词： COVID-19 Romania case study epidemiology genetics genome impact infectious disease lineage mutation sequencing spread strain transmission variant virology virus

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Fuzzy Clustering based Anomaly Detection for Distributed Multi-view Data

Fuzzy Clustering based Anomaly Detection for Distributed Mul...

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IEEE International Conference on Fuzzy Systems

作者： Hongmei Wang Tianhua Chen Hongtao Wang Xuqiang Shao Pan Su Science and Technology College North China Electric Power University China Department of Computer Science University of Huddersfield UK School of Control and Computer Engineering North China Electric Power University China

Anomaly detection aims to identify the abnormal instances, whose behavior deviates significantly from the others. Nowadays owing to the existence of diverse data generation sources, different attributes of the same instances may be located on distributed parties forming a multi-view dataset. Thus multiview anomaly detection has become a key task to discover outliers across various views. Traditionally, to perform multiview anomaly detection, one needs to centralize data instances from all views into a single machine. However, in many real-world scenarios, it is impractical to send data from diverse views to a master machine due to the privacy issues. Inspired by this, we propose a fuzzy clustering based distributed approach for multiview anomaly detection that simultaneously learns a membership degree matrix for each view and then detects anomalies for all parties. Specifically, we first introduce a combined fuzzy c-means clustering method for multi-view data and then design an anomaly measurement criterion to quantify the abnormal score from membership degree matrix. To solve the proposed model, a protocol is provided to unify all parties performing a well-designed optimization in an iterative way. Experiments on three datasets with different anomaly settings demonstrate the effectiveness of our approach.

关键词： Anomaly detection Distributed databases Optimization Protocols Data privacy Privacy Entropy

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Shell analysis and optimisation of a pure electric vehicle power train based on multiple software

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World Electric Vehicle Journal 2018年第4期9卷 49页

作者： Guo, Shaocui Tong, Xiangrong Yang, Xu Yantai Vocational College Shandong Yantai264005 China School of computer and control engineering Yantai University Shandong Yantai264005 China Department of Computer Science and Technology Tongji University Shanghai201804 China

Motor end cover mounting fracture is a problem recently encountered by novel pure electric vehicles. Regarding the study of the traditional vehicle engine mount bracket and on the basis of the methods of design and optimisation available, we have analysed and optimised the pure electric vehicle end cover mount system. Multi-body dynamic software and finite element software have been combined. First, we highlight the motor end cover mount bracket fracture engineering problems, analyse the factors that may produce fracture, and propose solutions. By using CATIA software to establish a 3D model of the power train mount system, we imported it into ADAMS multi-body dynamic software, conducted 26 condition analysis, obtained five ultimate load conditions, and laid the foundations for subsequent analysis. Next, a mount and shell system was established by the ANSYS finite element method, and modal, strength, and fatigue analyses were performed on the end cover mount. We found that the reason for fracture lies in the intensity of the end cover mount joint, which leads to the safety factor too small and the fatigue life not being up to standard. The main goal was to increase the strength of the cover mount junction, stiffness, safety coefficient, and fatigue life. With this aim, a topology optimisation was conducted to improve the motor end cover. A 3D prototype was designed accordingly. Finally, stiffness, strength, modal, and fatigue were simulated. Our simulation results were as follows. The motor end cover suspension stiffness increases by 20%, the modal frequency increases by 2.3%, the quality increases by 3%, the biggest deformation decreases by 52%, the maximum stress decreases by 28%, the minimum safety factor increases by 40%, and life expectancy increases 50-fold. The results from sample and vehicle tests highlight that the component fracture problem has been successfully solved and the fatigue life dramatically improved. © 2018 by the authors.

关键词： Fracture

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Optimization of software rejuvenation policy based on state-control-limit

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International Journal of Performability engineering 2018年第2期14卷 210-222页

作者： Dang, Weichao Zeng, Jianchao College of Electrical and Information Engineering Lanzhou University of Technology Lanzhou730050 China Division of Industrial and System Engineering Taiyuan University of Science and Technology Taiyuan030024 China School of Computer Science and Control Engineering North University of China Taiyuan030051 China

Software Rejuvenation is a proactive software control technique used to improve computing system performance when a system suffers from software aging. In this paper, a state-control-limit-based rejuvenation policy with periodical inspection has been proposed. The steady-state system availability model has been constructed based on the semi-renewal process. The steady-state probability density of degradation system stated as a function of the inspection interval and the rejuvenation threshold have been derived. The average unavailable time of when a soft failure occurs within an inspection cycle has been taken into account to calculate the steady-state system availability. Finally, the system availability with corresponding optimal inspection time interval and rejuvenation threshold have been obtained numerically. © 2018 Totem Publisher, Inc. All rights reserved.

关键词： Availability

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State-control-limit-based rejuvenation modeling of virtualized cloud server

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International Journal of Performability engineering 2018年第3期14卷 473-482页

Software rejuvenation modeling of the virtualized Cloud Server has been studied. A software rejuvenation policy on the virtual machines and the virtual machine monitor has been proposed in order to ensure high availability of the virtualized Cloud Server. The multi-component system, composed of the virtual machines and the virtual machine monitor, which are structurally dependent, has been reduced to the multiple two-component systems. The state-control-limit-based rejuvenation policy has been proposed and the stationary probability density of the two component system state has been derived. Furthermore, the stationary unavailability of the virtualized Cloud Server has been modeled. Numerical experiments have verified the correctness of the probability density function and the feasibility of the rejuvenation policy. The state-control-limit-based rejuvenation policy leads to lower unavailability of the virtualized Cloud Server in comparison with the lifetime-based rejuvenation policy. © 2018 Totem Publisher, Inc. All rights reserved.

关键词： Virtual machine

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