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Journal of medical Internet research 2020年第3期22卷 e18362页

作者： Deborah L Johanson Ho Seok Ahn Bruce A MacDonald Byeong Kyu Ahn JongYoon Lim Euijun Hwang Craig J Sutherland Elizabeth Broadbent Department of Psychological Medicine Faculty of Medical and Health Sciences The University of Auckland Auckland New Zealand. Centre for Automation and Robotic Engineering Science The University of Auckland Auckland New Zealand. Department of Electrical Computer and Software Engineering Faculty of Engineering The University of Auckland Auckland New Zealand.

[This corrects the article DOI: 10.2196/13667.].

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Energy management of a single grid-connected home microgrid for determining optimal supply/demand bids 5

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Energy management of a single grid-connected home microgrid ...

5th International Symposium on Environment-Friendly Energies and Applications, EFEA 2018

作者： Fouladfar, Mohammad Hossein Sumaiti, Ameena Al Fenik, Mohammed Seddik Marzband, Mousa Busawon, Krishna Pouresmaeil, Edris Science and Research of Bushehr Branch Islamic Azad University Bushehr Iran Electrical and Computer Engineering Khalifa University of Science and Technology Masdar Institute Abu Dhabi United Arab Emirates Faculty of Engineering and Environment Dep. of Maths Physics and Electrical Engineering Northumbria University Newcastle Newcastle United Kingdom Department of Electrical Engineering and Automation Aalto University Espoo Finland

ISBN: (纸本)9781538655177

As a result of socio-economic growth and paying attention to environmental aspects requirement in order to improve the reliability and achieve higher service, better power quality and increasing energy efficiency are taken more into consideration. Thus, home micro-grids (H-MG) with non-dispatchable Source and interruptible loads can be used as the primary tool to achieve the stated objectives. In order to implement the energy management system (EMS) an algorithm is presented in this paper. EMS which is based on harmony search method for multi-purpose extrapolation of a sample H-MG with renewable energy sources (RES) as well as compound resources of backup power such as micro-turbine and battery for levelling the mismatch of power or for additional power saving in case of necessary. In this paper, the harmony search (HS) for an algorithm to minimize the costs associated with sources, RLD and reduce the price of the electricity (i.e. market clearing price) with respect to the proposed price of production and supply, the price of non-interruptible loads, the optimal production of each of the existing resources in the micro grid is determined. For reliability enhancement the uncertainty is considered in using wind turbines (WT), photovoltaic (PV), load demand and market clearing price in the algorithm. The recommended algorithm system is tested on a H-MG sample. These results show the capability of the HS approach in supplying the load requested. © 2018 IEEE.

关键词： Energy management systems

The learning of fuzzy cognitive maps with noisy data: A rapid and robust learning method with maximum entropy

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arXiv 2019年

作者： Feng, Guoliang Lu, Wei Pedrycz, Witold Yang, Jianhua Liu, Xiaodong School of Control Science and Engineering Dalian University of Technology Dalian116023 China School of Automation Engineering Northeast Electric Power University Jilin132012 China School of Control Science and Engineering Dalian University of Technology Dalian116023 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia

Numerous learning methods for fuzzy cognitive maps (FCMs), such as the Hebbian-based and the population-based learning methods, have been developed for modeling and simulating dynamic systems. However, these methods are faced with several obvious limitations. Most of these models are extremely time consuming when learning the large-scale FCMs with hundreds of nodes. Furthermore, the FCMs learned by those algorithms lack robustness when the experimental data contain noise. In addition, reasonable distribution of the weights is rarely considered in these algorithms, which could result in the reduction of the performance of the resulting FCM. In this article, a straightforward, rapid, and robust learning method is proposed to learn FCMs from noisy data, especially, to learn large-scale FCMs. The crux of the proposed algorithm is to equivalently transform the learning problem of FCMs to a classic-constrained convex optimization problem in which the least-squares term ensures the robustness of the well-learned FCM and the maximum entropy term regularizes the distribution of the weights of the well-learned FCM. A series of experiments covering two frequently used activation functions (the sigmoid and hyperbolic tangent functions) are performed on both synthetic datasets with noise and real-world datasets. The experimental results show that the proposed method is rapid and robust against data containing noise and that the well-learned weights have better distribution. In addition, the FCMs learned by the proposed method also exhibit superior performance in comparison with the existing methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Fuzzy rules

Analysis of the quality of uninterruptible power supply using a UPS

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Analysis of the quality of uninterruptible power supply usin...

Applications of Electromagnetics in Modern Techniques and Medicine (Conference)

作者： Krzysztof Przystupa Joanna Koziel Lublin University of Technology Faculty of Mechanical Engineering Department of Automation Lublin University of Technology Department of Electrical Engineering and Computer Science Faculty Institute of Electrical Engineering and Electrotechnologies

ISBN: (纸本)9781538669372

The paper discusses the problem or the quality of electric current, indicating its disadvantages. Based on them, using the FTA method, a power failure tree diagram was developed. The simplest methods of hardware prevention of low power quality occurrence are shown. In this case, a power failure tree was also developed using the same method. The obtained results were compared and discussed.

关键词： Uninterruptible power supply Power quality Supply voltage parameters

Recording Eye-tracking Parameters during a Program Source-code Debugging Example

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Recording Eye-tracking Parameters during a Program Source-co...

International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Jozsef Katona Attila Kovari Ilona Heldal Carsten Helgesen Cristina Costescu Adrian Rosan Andrea Hathazi Serge Thill Robert Demeter CogInfoCom Based LearnAbility Research Team Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Engineering University of Dunaujvaros Dunaujvaros Hungary Department of Computing Mathematics and Physics Western Norway University of Applied Sciences Bergen Norway Special Education Department Faculty of Psychology and Educational Sciences Babes- Bolyai University Cluj-Napoca Romania Cognition and Behaviour Radboud University Nijmegen Netherland Department of Automation and Information Technology Faculty of Electrical Engineering and Computer Science Transilvania University of Brasov Brasov Romania

ISBN: (数字)9781728147932

ISBN: (纸本)9781728147949

Recently, researches based on eye-tracking have more often appeared on the field of cognitive studies, education support systems and virtual reality. Eye-tracking based analysis may be useful in IT, particular in algorithm thinking, program code debugging. The purpose of this paper is to introduce the conditions of Gazepoint GP3 device and OGAMA used to record eye-motion parameters and demonstrate the recording process and steps.

关键词： Conferences Testing Software Debugging Education Cognition Three-dimensional displays

Short term electric load forecast with artificial neural networks

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arXiv 2018年

作者： Cristian, Vasar Iosif, Szeidert Ioan, Filip Gabriela, Prostean Department of Control System Engineering Politehnica' University from Timisoara Faculty of Automation and Computer Science Timisoara300223 Romania

This paper presents issues regarding short term electric load forecasting using feedforward and Elman recurrent neural networks. The study cases were developed using measured data representing electrical energy consume from Banat area. There were considered 35 different types of structure for both feedforward and recurrent network cases. For each type of neural network structure were performed many trainings and best solution was selected. The issue of forecasting the load on short term is essential in the effective energetic consume management in an open market environment. Copyright © 2007 IFAC Copyright © 2018, The Authors. All rights reserved.

关键词： Electric load forecasting

Advances in Intelligent Systems and Computing

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Preface

Advances in Intelligent Systems and Computing 2019年 837卷 v-vi页

作者： Matoušek, Radek Department of Applied Computer Science Institute of Automation and Computer Science Faculty of Mechanical Engineering Brno University of Technology Brno Czech Republic

Design of stable and new polysaccharide nanoparticles composite and their interaction with solid cellulose surfaces

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Nano-Structures and Nano-Objects 2020年 24卷

作者： Czabany, Ivana Hribernik, Silvo Bračič, Matej Kurečič, Manja Thomas, Sabu Stana Kleinschek, Karin Mohan, Tamilselvan Institute of Chemistry University of Graz Heinrichstrasse 28 Graz 8010 Austria Institute of Automation Faculty of Electrical Engineering and Computer Science University of Maribor Koroska cesta 46 Maribor 2000 Slovenia Laboratory for Characterisation and Processing of Polymers Faculty of Mechanical Engineering University of Maribor Smetanova 17 Maribor 2000 Slovenia School of Energy Materials International and Inter University Centre for Nanoscience and Nanotechnology School of Chemical Sciences Mahatma Gandhi University Priyadarshini Hills P.O. Kottayam 686560 Kerala India Institute for Chemistry and Technology of Biobased Systems (IBioSys) Graz University of Technology Stremayrgasse 9 Graz 8010 Austria

This study presents a simple and straightforward method for the preparation of aqueous-based stable polysaccharide-metal oxide nanoparticles composites — composed of carboxymethyl cellulose (CMC) and titanium dioxide nanoparticles (TiO₂ NPs), and their interaction with the cellulose surface, is presented. Using a combination of anionic polysaccharide CMC as a stabilizer agent and ultrasound probe sonication technique as an agitation tool, a highly stable dispersion of CMC/TiO₂ NPs composites is prepared in water, with and without the presence of calcium chloride electrolyte, at various pH values. The results of the dynamic light scattering and the zeta-potential measurements showed that the quality, the stability of the dispersions and the hydrodynamic radius of the particles (ca, 200–300 nm) remain well-preserved for several weeks under normal storage conditions. The transmission electron microscope revealed that the morphology and size of the dry particles size (ca. 25–50 nm) remain unchanged and are not influenced by the addition of the stabilizer CMC, the electrolyte or the pH value of the solution. The presence of electrolyte and the low pH of the dispersions strongly favored an irreversible and enhanced deposition of CMC/TiO₂ NPs on cellulose surface as showed by a quartz crystal microbalance with dissipation. A linear correlation between the concentration of CMC and the adsorbed mass of polymer and NPs, and the water content of the adsorbed layers is observed. X-ray photoelectron spectroscopy and atomic force microscopy are combined to prove the successful immobilization of polymer and NPs on the cellulose surface. The knowledge gained from this study can be extended not only for the stabilization of various metal oxide nanoparticles but also for the development of green polymer/NPs composites, that may have the potential to be used as functional coatings in biomedical (e.g. wound dressing) applications. © 2020

关键词： Adsorption Carboxmethyl cellulose QCM-D Thin films Titanium dioxide nanoparticles Water content Zeta potential

RF chain reduction for MIMO systems: A hardware prototype

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arXiv 2019年

作者： Gong, Tierui Shlezinger, Nir Ioushua, Shahar Stein Namer, Moshe Yang, Zhijia Eldar, Yonina C. State Key Lab of Robotics Key Lab of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel School of Electrical Engineering Tel Aviv University Tel Aviv Israel Faculty of Electrical Engineering Technion Haifa Israel

RF chain circuits play a major role in digital receiver architectures, allowing passband communication signals to be processed in baseband. When operating at high frequencies, these circuits tend to be costly. This increased cost imposes a major limitation on future multiple-input multiple-output (MIMO) communication technologies. A common approach to mitigate the increased cost is to utilize hybrid architectures, in which the received signal is combined in analog into a lower dimension, thus reducing the number of RF chains. In this work we present a hardware prototype implementing analog combining for RF chain reduction. The prototype consists of a specially designed configurable combining board as well as a dedicated experimental setup. Our hardware prototype allows to evaluate the effect of analog combining in MIMO systems using actual communication signals. The experimental study, which focuses on channel estimation accuracy in MIMO channels, demonstrates that using the proposed prototype, the achievable channel estimation performance is within a small gap in a statistical sense from that obtained using a costly receiver in which each antenna is connected to a dedicated RF chain. Furthermore, in the considered scenarios, this gap becomes negligible when the reduction rate, i.e., the ratio of the number of RF chains to the number of antennas, is above 62.5%. Copyright © 2019, The Authors. All rights reserved.

关键词： Channel estimation

Forecasting time series for power consumption data in different buildings using the fractional Brownian motion

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arXiv 2019年

作者： Bondarenko, Valeria Filipova-Petrakieva, Simona Taralova, Ina Andreev, Desislav University of Beira Covilha Portugal Bulgarian Section Technical University of Sofia Bulgaria Department "Theory of Electrical Engineering" Faculty of Automation Sofia Bulgaria Laboratoire des Sciences du Numerique de Nantes Ecole Centrale de Nantes Nantes France Technical University of Sofia Bulgaria Department "Computer Science" Faculty of Computer Systems and Technologies "Advance Driver Assistance Systems" Company Visteon Electronics Bulgaria Sofia Bulgaria

In the present paper will be discussed the problem related to the individual household electric power consumption of objects in different areas - industry, farmers, banks, hospitals, theaters, hostels, supermarkets, universities. The main goal of the directed research is to estimate the active P and full S power consumptions for all studied buildings. The defined goal is achieved by solving of the following three problems. The first problem studies which buildings increase their power consumption. The second one finds which objects have the greatest increase of power consumption. And the third problem regards if it is possible to make a short-term forecast, based on the solutions of previous two problems. The present research and solving of the aforementioned problems is conducted using fractional Brownian motion theory. The applicability of this approach is illustrated on the example with 20 real objects in different areas. The paper ends with conclusion notes about possibilities to make short-term forecasts about power consumption of the considered buildings. Copyright © 2019, The Authors. All rights reserved.

关键词： Electric power utilization