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The distributed co-simulation protocol for the integration of real-time systems and simulation environments 50

The distributed co-simulation protocol for the integration o...

50th Summer Computer simulation Conference, SCSC 2018, Part of the 2018 Summer simulation Multi-Conference, SummerSim 2018

作者： Krammer, Martin Msc, Martin Benedikt Blochwitz, Torsten Alekeish, Khaled Amringer, Nicolas Kater, Christian Materne, Stefan Ruvalcaba, Roberto Schuch, Klaus Zehetner, Josef Damm-Norwig, Micha Schreiber, Viktor Nagarajan, Natarajan Corral, Isidro Sparber, Tommy Klein, Serge Andert, Jakob VIRTUAL VEHICLE Research Center Graz Austria Centre of Excellence for System Simulation ESI-ITI GmbH Dresden Germany dSPACE GmbH Paderborn Germany Leibniz Universität Hannover Hannover Germany Electrics and Electronics Department TWT GmbH Stuttgart Germany Advanced Simulation Technologies Department AVL List GmbH Graz Austria AVL List GmbH Graz Austria Ks.MicroNova GmbH Kassel Germany Automotive Engineering Group University of Ilmenau Ilmenau Germany ETAS GmbH Stuttgart Germany Robert Bosch GmbH Stuttgart Germany Spath Micro Electronic Design GmbH Graz Austria Institute of Mechatronic Systems for Combustion Engines RWTH Aachen University Aachen Germany

ISBN: (纸本)9781510860209

Virtual system development gets more and more important in many industrial domains. It is considered to reduce development times, lower computing costs, and shorten time-to-market. Co-simulation is a particularly promising approach for modular and interoperable development. In practice the integration and coupling of heterogeneous systems still require enormous efforts. The configuration and operation of distributed hardware-in-the-loop systems and simulations contribute to efficiency of testing. Currently no standardized interface or protocol specification is available, which allows the interaction of real-time and non-real-time systems of different vendors. This paper for the first time presents the Distributed Co-simulation Proto-col (DCP) which is subject to proposal as a standard for real-time and non-real-time system integration and simulation. The DCP consists of a data model, a finite state machine, and a communication protocol including a set of protocol data units. It is designed as a tool independent standard. It was developed in context of the ACOSAR project and is subject to standardization as a Modelica Association Project (MAP). It enables the definition, configuration and execution of a wide range of different simulations and test scenarios. It supports a master-slave architecture for simulation setup and control. The specification defines the design of a slave only, the design of a master is not in scope of the *** highlight the industrial applicability of the DCP, three examples from the automotive domain are shown. © 2018 Society for Modeling & simulation International (SCS).

关键词： Real time systems

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Sensing metric-based hybrid underlay/overlay transmission framework for CR-IoT networks for smart city applications

Sensing metric-based hybrid underlay/overlay transmission fr...

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7th IET Smart Cities Symposium (SCS 2023)

作者： Indu Bala Maad M. Mijwil Mostafa Abotaleb El-Sayed M. El-kenawy Abdelhameed Ibrahim School of Electrical and Electronics Engineering Lovely Professional University Punjab India Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

With the increasing number of IoT devices, there is a growing need for bandwidth to support their communication. Unfortunately, there is a shortage of available bandwidth due to preallocated bands for various services. To address this issue, Cognitive Internet of Things (CR-IoT) enables devices to optimize their efficiency and enhance their communication capabilities by intelligently accessing available bandwidth. This is achieved through the use of soft sensing metrics, where devices continuously monitor the RF environment and transmit data opportunistically in overlay mode if a free channel is detected, or in underlay mode if not. In this paper, a soft sensing metric based hybrid transmission framework is proposed for CR-IoT devices to meet the data rate requirement for the smart city applications. The efficacy of this approach is demonstrated through simulation results.

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Bibliometric and social network analysis of the SoS field

Bibliometric and social network analysis of the SoS field

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IEEE International Conference on system of systems Engineering (SoSE)

作者： Guang-rong You Xiao Sun Min Sun Ji-min Wang Ying-wu Chen Key Lab on Complex Systems Simulation Beijing Institute of System Engineering Beijing R. P. of China Department of Information Science Peking University Beijing Beijing R. P. of China National University of Defence Technology Changsha R. P. of China

This exploratory work combines bibliometric methods and social network analysis to provide a knowledge map on the development of system of systems research field. For this purpose, the study mined the published articles related to system of systems until 2012 indexed by Web of Knowledge platform including SCI-EXPANDED, SSCI, CPCI-S, and other scientific literature databases. The auctorial, institutional, national patterns in system of systems research are revealed using bibliometric methods. Social network analysis is used to discover relationships between authors and key terms in the research field. Based on this quantitative analysis, the study found the influential journals, key researchers, leading institutions and countries, and major research areas in system of systems research field. Last, suggestions are made on the future development of system of systems field.

关键词： Educational institutions Conferences Modeling Bibliometrics Social network services Collaboration

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Optimizing machine learning algorithms to enhance blood donation for liver patients: a case study

Optimizing machine learning algorithms to enhance blood dona...

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7th IET Smart Cities Symposium (SCS 2023)

作者： Maad M. Mijwil El-Sayed M. El-kenawy Indu Bala Mohammad Aljanabi Mostafa Abotaleb Abdelhameed Ibrahim Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt School of Electrical and Electronics Engineering Lovely Professional University Punjab India Department of Computer Aliraqia University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

Blood is vital for transporting oxygen, nutrients, and hormones to all body parts as it circulates through arteries and veins. It removes carbon dioxide, regulates body temperature, and maintains the body's immune system. Individuals constantly need blood and its derivatives to save their lives and improve their health through medical treatments and surgical operations. Liver diseases are one of the diseases that affects the health of individuals and requires blood to continue living. These diseases cause significant damage to people's health, and early diagnosis plays a crucial role in saving lives. In this paper, machine learning algorithms (support vector machine and random forest) are involved in detecting liver diseases and determining whether donors are suitable to donate blood from blood values. This paper is applied research that found that the performance measures of the random forest algorithm achieved excellent performance in identifying suitable people to donate blood.

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Preface

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CEUR Workshop Proceedings 2017年 1989卷 5-7页

作者： Pozin, Boris A. Cavalli, Ana Rosa Petrenko, Alexander K. Department of Information and Analytical Systems EC-leasing Co. Russia Department of Network Software TELECOM and Management SudParis France Department of System Engineering Institute of System Programming of RAS Russia

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Cloud identification model for sky images based on Otsu

Cloud identification model for sky images based on Otsu

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International Conference on Renewable Power Generation (RPG 2015)

作者： Hongping Li Fei Wang Hui Ren Hongbin Sun Chun Liu Bo Wang Jing Lu Zhao Zhen Xiaoli Liu State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources (North China Electric Power University) Baoding 071003 Hebei Province China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment (Department of Electrical Engineering Tsinghua University) Haidian District Beijing 100084 China China ElectricPowerResearch Institute HaidianDistrict Beijing 100192 China

Irradiance changes caused by clouds movement are the main factors, which lead to mutation of photovoltaic power. In order to increase the accuracy of the ultra-short-term photovoltaic power prediction, based on of clouds images, the cloud identification for sky images is one of the primary aspects for improving photovoltaic power accuracy. A cloud identification model for sky images is established based on Otsu. Firstly, a series of sky images are collected by Total Sky Imager (TSI) with the regions of clouds and sky are distinguished. Secondly, the color features (based on RGB values) of pixels in sample images and the spectral and texture features of the whole image are extracted; Finally, we established a cloud identification model for sky images based on Otsu according to the clouds' and sky areas' division and the general characteristics featured by pixels and images. The simulated results show that the model in this paper can identify the clouds in a sky images effectively.

关键词： Otsu cloud identification texture threshold Clouds sky images texture textures pixel

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Data poisoning: issues, challenges, and needs

Data poisoning: issues, challenges, and needs

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7th IET Smart Cities Symposium (SCS 2023)

作者： Mohammad Aljanabi Alaa Hamza Omran Maad M Mijwil Mostafa Abotaleb El-Sayed M. El-kenawy Sahar Yousif Mohammed Abdelhameed Ibrahim Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Science Department Computer Science & Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence.

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Photovoltaic plant operating statuses identification model based on support vector machine using loss quantity of electricity feature parameters

Photovoltaic plant operating statuses identification model b...

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International Conference on Renewable Power Generation (RPG 2015)

作者： Kangping Li Fei Wang Zhao Zhen Yujing Sun Zengqiang Mi Hongbin Sun Chun Liu Bo Wang Jing Lu State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources (North China Electric Power University) Baoding 071003 Hebei Province China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment (Department of Electrical Engineering Tsinghua University) Haidian District Beijing 100084 China China Electric Power Research Institute Haidian District Beijing 100192 China)

ISBN: (纸本)9781510821415

Operating Statuses Identification (OSI) can help operators to find fault timely and minimize the loss. So it is of great significance for optimal operation of photovoltaic (PV) plants. The loss quantity of electricity (LQOE) is defined as that should have been generated but actually not, which is caused by inverter fault, PV modules fault, dust stratification or combinations of them. Firstly, mathematical models of PV cells are proposed to figure out the LQOE of each PV module. Secondly, after analysing the relation between LQOE and operating statuses, an index set of LQOE describing the distinction of different operating statuses are defined including four statistical feature parameters and a user-defined index. Thirdly, Support Vector Classification models for OSI (OSI-SVC) are built with input features extracted from the index set. Lastly, simulations are carried out to verify the effectiveness and evaluate the performance of the OSI-SVC models. The results indicated that the operating statuses can be effectively recognized by the proposed model.

关键词： Feature Extraction Loss quantity of electricity Operating Statuses Identification Support Vector Machine

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Spring festival points the way to cleaner air in China

arXiv

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arXiv 2020年

作者： Wang, Siwen Su, Hang Streets, David G. Zhang, Qiang Lu, Zifeng He, Kebin Andreae, Meinrat O. Pöschl, Ulrich Cheng, Yafang Max Planck Institute for Chemistry Mainz55128 Germany Energy Systems Division Argonne National Laboratory LemontIL60439 United States Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System Science Tsinghua University Beijing100084 China State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China Scripps Institution of Oceanography University of California San Diego San DiegoCA92093 United States

Human migration during the Chinese Spring Festival (SF) is the largest collective human activity of its kind in the modern era-involving about one-tenth of the world population and over six percent of the earth's land surface area. The festival results in a drop of air pollutant emissions that causes dramatic changes of atmospheric composition over China's most polluted regions. Based on satellite and in-situ measurements for the years 2005-2019 over 50 cities in eastern China, we find that the atmospheric NO2 pollution dropped by ~40% during the SF week, and fine particulate matter (PM2.5) decreased by ~30% in the following week, reflecting the effectiveness of precursor emission controls on the mitigation of secondary PM2.5 formation. However, although human activity and emissions are at the lowest level, air pollution over eastern China during the SF still far exceeds that over other worldwide pollution hotspots. Our analyses suggest that measures based solely on end-of-pipe controls and industry upgrades may not suffice to meet air quality goals. Further cleaning of the air in China depends fundamentally on sustainable advances in both heavy industry upgrades and clean energy transition. Copyright © 2020, The Authors. All rights reserved.

关键词： Air cleaners

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Space Charge Transport of $\boldsymbol{\text{Al}_2 \mathrm{O}_3}$ /Silicone Rubber Composites Under Thermal Aging

Space Charge Transport of $\boldsymbol{\text{Al}_2 \mathrm{O...

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International Conference on High Voltage Engineering and Application, ICHVE

作者： Yunxiao Zhang Chenning Yan Kai Wu Yuanxiang Zhou Tianfeng Zhang College of Electrical Engineering and Automation Fuzhou University Fuzhou Fujian China Department of Electrical Engineering State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Tsinghua University Beijing China The Wind Solar Storage Division of State Key Laboratory of Power System and Generation Equipment School of Electrical Engineering Xinjiang University Urumqi China Electric Power Research Institute Anhui Electric Power Company of State Grid Hefei China

ISBN: (数字)9781665407502

ISBN: (纸本)9781665407519

Silicone rubber (SIR) has been widely used in the insulation of cable accessories due to its excellent performance. In this paper, pure SIR and nano $\boldsymbol{\text{Al}_2 \mathrm{O}_3 / \text{SIR}}$ composites are thermally aged for 0–80 days at $\boldsymbol{200^{\circ} \mathrm{C}}$ . The effects of long-term thermal aging on the space charge transport are analyzed. The results show that with the increase of thermal aging time, the accumulation of heteropolar charge of pure SIR and nano $\boldsymbol{\text{Al}_{2}\mathrm{O}_{3}/\text{SIR}}$ composites gradually decreases and changes to the accumulation of homopolar charge. Compared with pure SIR, the space charge accumulation of $\boldsymbol{\text{Al}_{2}\mathrm{O}_{3}/\text{SIR}}$ composites decreases significantly and changes little with the increase of thermal aging time. It is believed that when doped nano $\boldsymbol{\text{Al}_{2}\mathrm{O}_{3}}$ in SIR, the increase of carrier mobility and the introduction of metal oxides reacting with fallen free radicals to form stable compounds both lead to less space charge accumulation of $\boldsymbol{\text{Al}_{2}\mathrm{O}_{3}/\text{SIR}}$ composites.

关键词： Nanocomposites Impurities Metals High-voltage techniques Aging Space charge Thermal analysis

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