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IEEE International Conference on Web Services (ICWS)

作者： Xiaodong Fu Li Liu Lijun Liu Yong Feng Kun Yue Yunnan Provincial Key Laboratory of Computer Technology Application Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China School of Information Science and Engineering Yunnan University Kunming China

ISBN: (数字)9781728187860

ISBN: (纸本)9781728187877

A core source of raw information used as inputs to the reputation systems of online services is the feedback ratings provided by users. However, it is impossible that all users rate services with the same criteria and so ratings of different users are incommensurable. Meanwhile, users are not necessarily willing to provide honest feedbacks. Thus, aggregating dishonest cardinal ratings into reputation will potentially lead to unreliable and misleading reputation. In this paper, we propose a reputation model that aggregates ordinal user preferences rather than cardinal ratings for online services with user incentive. A distance metric is defined to measure the discrepancy between ordinal preferences. Then an optimal reputation model with the attributes of incentive compatible and individually rational is proposed. We design a B&B algorithm to solve the optimization problem so that a reputation vector that maximizes the total value of all users can be found efficiently. A comprehensive experimental study and performance analysis are conducted to evaluate the effectiveness and efficiency of the proposed method.

关键词： Measurement Web services Conferences Aggregates Performance analysis Optimization

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Management of services of a hyperconverged infrastructure using the coordinator 1st

Management of services of a hyperconverged infrastructure us...

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1st International Conference on computer Science, engineering and Education Applications, ICCSEEA2018

作者： Rolik, Oleksandr Telenyk, Sergii Zharikov, Eduard Department of Automation and Control in Technical Systems National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" Kyiv Ukraine Department of Theoretical Electrical Engineering and Computer Science Faculty of Electrical and Computer Engineering Cracow University of Technology Cracow Poland

ISBN: (纸本)9783319910079

Modern data centers’ providers are gradually moving away from traditional and multi-vendor IT infrastructures to open, standardized and interchangeable solutions that are based on a software defined approach to managing data center resources. The authors analyze the architectural features, requirements, limitations, hardware and software of hyperconverged infrastructures and their advantages in comparison with traditional and converged architectures deployed in data centers. The authors propose to employ two-level coordination schema to manage compute, storage, network and virtualization subsystems of hyperconverged infrastructure along with the self-management algorithms inside these subsystems. © Springer International Publishing AG, part of Springer Nature 2019.

关键词： Digital storage

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Nonlinear Swing down Control of the Acrobot ⁎

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IFAC-PapersOnLine 2020年第2期53卷 5813-5818页

作者： Xin Xin Maki Sakurai Shinsaku Izumi Taiga Yamasaki Jinhua She Yannian Liu Faculty of Computer Science and Systems Engineering Okayama Prefectural University 111 Kuboki Soja Okayama 719-1197 Japan School of Engineering Tokyo University of Technology Hachioji 192-0982 Japan School of Automation Southeast University 2 Sipailou Nanjing 210018 China

In this paper, we concern swing down control of the Acrobot which is a 2-link planar robot with a single actuator driving the second joint, whose control objective is to stabilize the Acrobot to the downward equilibrium point with the two links in the downward position for all initial states of the Acrobot with the exception of a set of Lebesgue measure zero. To achieve this control objective, we design a nonlinear controller by using nonnegative linear feedback of the sine function of the angle of the second joint in addition to the negative linear feedback of its angular velocity. By analyzing globally the solution of the closed-loop system consisting of the Acrobot and the presented controller and focusing on the equilibrium points of the closed-loop system and their stability, we prove that the control objective is achieved provided that some conditions on two control gains are satisfied. We design the two control gains such that the real parts of the dominant poles of the linearized model of the closed-loop system around the downward equilibrium point are minimized. We provide simulation results for two Acrobots to show the effectiveness of the presented controller.

关键词： Underactuated mechanical systems Acrobot swing down control robot control nonlinear control passivity Lyapunov stability motion analysis

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Stochastic Control for DC–DC Power Converters: A Generalized Minimum Variance Control Approach

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IFAC-PapersOnLine 2020年第2期53卷 13410-13417页

作者： Kevin E. Lucas Daniel J. Pagano Douglas A. Plaza David Alejandro Vaca—Benavides Sara J. Ríos Federal University of Santa Catarina (UFSC) Department of Automation and Systems Florianópolis 88040-900 Brazil ESPOL Polytechnic University Faculty of Electrical and Computer Engineering Campus Gustavo Galindo Guayaquil 09-01-5863 Ecuador

This paper proposes a Generalized Minimum Variance (GMV) controller to regulate the output of the DC-DC power converters in order to decrease the impact of the noise in the system performance. The Dual Active Bridge and the Buck converters are used to illustrate the proposed methodology. The proposed controller is designed using the stochastic augmentation methodology that provides a Proportional-Integral-Derivative (PID) controller, in the Reference Signal Tracking (RST) structure, the ability to adequately treat noise of a stochastic nature. The GMV control reduces the variance of the control signal and in turn leads to a better output characteristic. The simulation results show that the GMV controller achieve better performance in the sense of minimum variance and energy consumption in comparison with a robust PID controller.

关键词： minimum variance control stochastic control stochastic Augmentation dc-dc converter parametric uncertain robust control

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Robust Feedback Linearization Control for DAB Converter feeding a CPL

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IFAC-PapersOnLine 2020年第2期53卷 13402-13409页

作者： Kevin E. Lucas Daniel J. Pagano Douglas A. Plaza David Alejandro Vaca—Benavides Sara J. Ríos Federal University of Santa Catarina (UFSC) Department of Automation and Systems Florianóplis 88040-900 Brazil ESPOL Polytechnic University Faculty of Electrical and Computer Engineering Campus Gustavo Galindo Guayaquil 09-01-5863 Ecuador

Cascaded converters are used to satisfy the different voltage levels that loads need. Instability problems in cascaded systems may occur due to the interaction of Point-of-Load (POL) converters. POL converters exhibit the important characteristic of almost-perfect regulation at the output terminals independent of the input perturbations. However, such characteristic reflects at the input terminal as a constant power load (CPL). CPL exhibits incremental negative resistance behavior causing undesired oscillations and a high risk of instability in interconnected converters. In this paper, the cascaded converter system consists of a Dual Active Bridge (DAB) DC-DC converter that maintains a regulated DC voltage on the intermediate bus and a POL DC-DC Buck converter that acts as a CPL. Aiming to ensure system stability and effectively mitigate oscillations effects in a cascaded system, this paper proposes a Robust Feedback Linearization Control to regulate the intermediate DC bus voltage. Simulation tests are performed by using a MATLAB/Simulink simulator to show the robustness and effectiveness of the proposed controller. The simulation results show that the proposed control approach ensures robust control performance and stability with a minor performance degradation compared to a Robust Control approach, Feedback Linearization Control approach, and Classical Control approach.

关键词： cascaded system constant power load dc-dc converter dual active bridge converter feedback linearization control robust control

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CEBRA Method: Decoding Brain Activity for Advanced Brain-computer Interface Technology

CEBRA Method: Decoding Brain Activity for Advanced Brain-Com...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Jingcheng Yang Frank Kulwa Xuanwei Liu Yiqing Lu Yufa Fu Guanglin Li Yaping Huai Xin Zhang Yongcheng Li CAS Key Laboratory of Human-Machine Intelligence Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences (CAS) Shenzhen China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Shenzhen Dapeng New District Nanao People’s Hospital Shenzhen China Department of Rehabilitation Medicine Shenzhen Longhua District Central Hospital Shenzhen China Brain Cognition and Brain-Computer Intelligence Integration Group Kunming University of Science and Technology Kunming China Shandong Zhongke Advanced Technology Co. Ltd. Jinan China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

The emerging neurorehabilitation technology, Brain-computer Interface (BCI), provides a novel prospect for stroke recovery. However, decoding brain activity during the movement present substantial challenges, and feature extraction is crutial to build a better decoder. In this study the CEBRA method were employed to extract features first based on electroencephalogram(EEG) data during Motor Execution(ME) and Motor lmagery (Ml) tasks for 20 participants (including 10 stroke patients). The results revealed that, in MI tasks, CEBRA-RF (Random Forests) achieved an average classification accuracy of 91.33%, with an average F1-score of 91.19%, and CEBRA-SVM (Support Vector Machine) achieved an average classification accuracy of 91.32%, with an average F1-score of 90.83%. Compared to other conventional feature extraction methods, CEBRA shows significantly higher accuracy (t-test, p<0.01). However, in ME tasks, CEBRA-RF achieved an average classification accuracy of 75.67%, with an average F1-score of 75.39%, and CEBRA-SVM achieved an average classification accuracy of 76.13%, with an average F1-score of 75.80%. Nevertheless, no significant differences were observed compared to other feature extraction methods. These findings demonstrate the potential of CEBRA in decoding patients’ brain activity. The results of this study hold promise in addressing the current challenges of low decoding accuracy in BCI systems, offering a new approach for designing BCI-assisted rehabilitation systems for stroke patients.

关键词： Support vector machines Brain Accuracy Stroke (medical condition) Feature extraction Motors Brain-computer interfaces Neurorehabilitation Decoding Paralysis

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Evaluation of metrological characteristics of a computerized conductivity meter of irrigation solution based on the uncertainty theory

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Journal Europeen des Systemes Automatises 2019年第4期52卷 333-340页

作者： Vovna, Oleksandr V. Laktionov, Ivan S. Dobrovolska, Liudmyla O. Kabanets, Maryna M. Lebediev, Vladyslav A. Department of Electronic Engineering Faculty of Computer-Integrated Technologies Automatization Electrical Engineering and Radioelectronics SHEE 'Donetsk National Technical University' of the Ministry of Education and Science of Ukraine Shybankova sq. 2 Pokrovsk Ukraine Department of Automation and Computer Technologies Faculty of information technologies SHEE 'Priazovskyi State Technical University' under Ministry of Education and Science of Ukraine Universytets’ka str. 7 Mariupol Ukraine Language Training Department Faculty of Computer-Integrated Technologies Automatization Electrical Engineering and Radioelectronics SHEE 'Donetsk National Technical University' of the Ministry of Education and Science of Ukraine Shybankova sq. 2 Pokrovsk Ukraine

There is a gap in the research on the metrological characteristics of computerized conductivity meters of industrial greenhouses. To make up for this gap, this paper explores these characteristics of modern computerized conductivity meters for irrigation solution, based on uncertainty theory, instrumental analysis of liquid media, theory of probability and mathematical statistics, etc. The author designed a conductivity meter for irrigation solution based on an analog conductivity sensor for Arduino, and measured output voltage and solution temperature. Based on the measured results, both the basic uncertainties (noise properties of electronic components) and additional uncertainties (solution temperature dynamics) of the computerized tool were evaluated. The results show that the designed conductivity meter has a basic relative uncertainty within ±0.61 %;the relative additional uncertainty could be improved from 10.5 to 3.21 % through piecewise linear approximation of the measured conductivity;the total relative critical uncertainty of conductivity measurement was not more than ±3.82 %. The research findings lay the basis for high-quality online monitoring of irrigation solution when growing greenhouse flora. © 2019 Lavoisier. All rights reserved.

关键词： Uncertainty analysis

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MODELING AND FUZZY CONTROL OF PERMANENT MAGNET SYNCHRONOUS MOTORS

MODELING AND FUZZY CONTROL OF PERMANENT MAGNET SYNCHRONOUS M...

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The 10th International Conference on Power Electronics, Machines and Drives (PEMD 2020)

作者： D.-K. Jukić T. Varga T. Benšić V. J. Štil M. Barukčić Automation and Control Institute TU Wien Vienna Austria Faculty of Electrical Engineering Computer Science and Information Technology Osijek Josip Juraj Strossmayer University of Osijek Osijek Croatia

This paper deals with Permanent Magnet Synchronous Motor modeling and control. The derived nonlinear dq model is a combination of Finite Element Method simulation data with the classical dq model. The so derived model keeps the precision of the Finite Element Method simulations and also the fast execution times of the dq model. The Finite Element Method data is included in the dq model using Artificial Neural Networks. The derived model is also used for controller design. The chosen controller is a PI like Fuzzy Logic Controller, which is tuned using Genetic Algorithm optimization. The Permanent Magnet Synchronous Motor with Fuzzy Logic Controller operation is tested using Real-Time (Model-in-the-Loop) simulations.

关键词： fuzzy control finite element analysis genetic algorithms neural nets permanent magnet motors machine control synchronous motors nonlinear control systems PI control electric machine analysis computing

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Sensitivity analysis of neural network models: Applying methods of analysis of finite fluctuations

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2019年第4期63卷 306-311页

作者： Sysoev, Anton Ciurlia, Alessandro Sheglevatych, Roman Blyumin, Semen Department of Applied Mathematics Faculty of Automation and Computer Science Lipetsk State Technical University 30 Moskovskaya str. LipetskRU-398055 Russia Department of Information Engineering Faculty of Engineering Marche Polytechnic University IT-60131 Ancona 12 Via Brecce Bianche Italy Lipetsk Region Health Department RU-398050 Lipetsk 6 Ulitsa Zegelya str Russia

As an initial stage prior to Mathematical Modeling, the information processing should provide qualitative data preparation for the construction of consistent models of technical, economic, social systems and technological processes. The question, concerning choosing the most significant input factors affecting the function of the system, is a very actual and important. This problem could be solved with the application of methods of Sensitivity Analysis. The presented paper has the purpose to show a possible approach to this problem through the method of the Analysis of Finite Fluctuations, based on Lagrange mean value theorem, to study the sensitivity of the model under consideration. The numerical example of comparing the results obtained by Sobol sensitivity coefficients, Garson algorithm and proposed approach showed the sustainability of the introduced method. There is shown, that the proposed approach is stable in the sense of applying different input datasets. In particular, the proposed approach has been applied to the construction of a neural network model identifying any anomalies present in certain medical insurances, in order to define the most significant input factors in the anomaly's detecting, discard the others and get a slim and efficient model. © 2019 Budapest University of Technology and Economics. All rights reserved.

关键词： Sensitivity analysis

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Analysis of Automatic Code Generation Tools based on Machine Learning

Analysis of Automatic Code Generation Tools based on Machine...

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2019 IEEE International Conference on computer Science and Educational Informatization, CSEI 2019

作者： Zhang, Xiaojiang Jiang, Ying Wang, Zhijun Yunnan Key Lab of Computer Technology Application Kunming University of Science and Technology Kunming China Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming China

ISBN: (纸本)9781728123080

At present, there are many researches on automatic code generation methods based on machine learning. However, there is no analysis on automatic code generation tools based on machine learning. According to the role of existing code generation tools based on machine learning in practical development, this paper proposes the content and the method of analysis of automatic code generation tools based on machine learning. Based on the presented method, the corresponding analysis plug-ins API4ACGT are implemented. Finally, three existing automatic code generation tools based on machine learning are used to generate specific codes in two programming environments. The experimental results show that the proposed method and analysis plug-ins API4ACGT are effective. © 2019 IEEE.

关键词： Machine learning

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