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Innovative Research in Applied Science, Engineering and Technology (IRASET),Conference on

作者： Abdeljabar Aboulkassim Said Kririm Naoual Armi Bensalem Boukili El Hanafi Arjdal Materials Signals Systems and Physical Modeling Laboratory Faculty of Sciences Ibnou Zohr University Agadir Morocco Department of Physics Faculty of Sciences Dhar El Mahraz Computer Science Signal Automation and Cognitivism Laboratory Sidi Mohamed Ben Abdellah University Fez Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

This paper presents a novel approach to develop a fuzzy maximum power point tracking (MPPT) controller that performs well in variable weather photovoltaic (PV) systems. The photovoltaic output voltage can be adjusted using a DC-DC boost converter. The last step is controlled by the duty cycle, which is essentially bounded between 0 and 1 . Using the Lyapunov approach and Descriptor Takagi-Sugeno (DT-S) fuzzy modelling, we establish the stabilisation conditions with H∞ performance represented as linear matrix inequalities (LMIs). Finally, we apply the proposed control to a solar system and the results of our simulation validate the efficiency of the presented methods.

关键词： Maximum power point trackers Photovoltaic systems Simulation Stability criteria Takagi-Sugeno model Solar system Linear matrix inequalities Meteorology Lyapunov methods Fuzzy systems

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Modelling aircraft noise map around an airport using machine learning

Modelling aircraft noise map around an airport using machine...

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IEEE International Symposium on Innovations in Intelligent systems and Applications (INISTA)

作者： Valohery Clermont Rafanambinantsoa Ionut Dorinel Muraretu William Germain Dimbisoa Thomas Mahatody Costin Bãdicã Raft Razafindrakoto Laboratory for Mathematical and Computer Applied to the Development Systems University of Fianarantsoa Fianarantsoa Madagascar Faculty of Automation Computers and Electronics University of Craiova Craiova Romania Laboratory of Multidisciplinary Applied Research University of Antananarivo Antananarivo Madagascar

ISBN: (数字)9798350368130

ISBN: (纸本)9798350368147

The measurement of aircraft noise is very important for the industry of air transportation, for residents and for the *** the United States of America, the Federal Aviation Authority (FAA) has a managing tool for aircraft noise map called Aeronautical Environmental Design Tool (AEDT) (Boeker Fleming, 2008); in French Bruitparif is the tool which satisfies the European directive for noise map elaboration strategy. The noise map enables city authorities, residents, and the airport manager to control the noise produced by aeronautical activities in order to master, for instance, the building of infrastructures surrounding the airport zone - a dataset built with a relational data base management system obtained from secondary radar detection. These data, after having gone through a data cleaning process, will be brought and tested with functions such as Naive Bayes, decision tree and random forest. Based on confusion matrix as a metric, we assessed the provided result by the decision tree with metrics as “ 98% for precision, 97% for recall and 97% for f1-score”. This article emphasizes that on the one hand, the data used for machine learning have the same quality in terms of integrity and precision of the radar itself and on the other hand the performance resides on the confusion matrix.

关键词： Technological innovation Noise Urban areas Radar detection Radar Airports Bayes methods

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Best Selection of Generative Adversarial Networks Hyper-Parameters Using Genetic Algorithm

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SN computer Science 2021年第4期2卷 283页

作者： Alarsan, Fajr Ibrahem Younes, Mamoon Informatics and Decision Supporting Systems Higher Institute for Applied Sciences and Technology Damascus Syrian Arab Republic Faculty of Computer and Automation Engineering Damascus University Damascus Syrian Arab Republic

Generative adversarial networks (GANs) are most popular generative frameworks that have achieved compelling performance. They follow an adversarial approach where two deep models generator and discriminator compete with each other. In this paper, we propose a Generative Adversarial Network with best hyper-parameters selection to generate fake images for digit numbers 1–9 with generator and train discriminator to decide whereas the generated images are fake or true. Genetic algorithm (GA) technique was used to adapt GAN hyper-parameters, the resulted algorithm is named GANGA: generative adversarial network with genetic algorithm. The resulted algorithm has achieved high performance;it was able to get zero value of loss function for the generator and discriminator separately. Anaconda environment with tensorflow library facilitates was used;python as programming language was adapted with needed libraries. The implementation was done using MNIST dataset to validate the work. The proposed method is to let genetic algorithm choose best values of hyper-parameters depending on minimizing a cost function such as a loss function or maximizing accuracy function used to find best values of learning rate, batch normalization, number of neurons and a parameter of dropout layer. © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Discriminator Generative adversarial networks (GAN) Generator Genetic algorithm Image synthesis MNIST dataset

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Smart room for patient monitoring based on IoT technologies 23

Smart room for patient monitoring based on IoT technologies

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Proceedings of the 2023 6th Artificial Intelligence and Cloud Computing Conference

作者： Nataly Zhukova Anna Motienko Dmitriy Levonevskiy Alexey Subbotin Pham Tuan Anh Laboratory of big data technologies in socio-cyberphysical systems St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS) Russia Faculty of Computer Technologies and Informatics St. Petersburg State Electrotechnical University Russia Faculty of Software Engineering and Computer Systems ITMO University Russia

ISBN: (纸本)9798400716225

This article presents a method for building a hospital room with extended intelligent features based on Internet of Things (IoT) technologies. We begin by reviewing existing vision-based health care systems and identifying important and useful functions that they should have. We then present a method for building a smart room that allows increase the level of the intelligence of the existing hospital rooms due to extensive use of the up-to-date machine learning methods. The proposed solution assumes using readily available hardware devices to reduce the cost of smart room building. Compared to commercially available assistive technologies, the proposed smart room turn out to have high level of intelligence and to be very cost effective. The system's non-intrusive nature makes it easy to use it both in hospitals and at home for patient care.

关键词： Internet of Things IoT automation in medicine intellectual room machine learning smart room smart ward

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Possibilities of Implementing Pre-Trained Feed-forward Neural Networks in Mobile Robotics

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Transportation Research Procedia 2023年 74卷 418-425页

作者： Vladimír Stenchlák Vladimír Tlach Ivan Kuric Martin Bohušík Zuzana Ságová Dorota Wiecek Department of Automation and Production Systems Faculty of Mechanical Engineering University of Zilina Univerzitná 8215/1 010 26 Zilina Slovakia Department of Production Engineering Faculty of Mechanical Engineering and Computer Sciences University of Bielsko-Biała Willowa 2 43-309 Bielsko-Biała Poland

This paper is describing how artificial intelligence algorithms can be implemented in controlling development boards like Arduino, ST32, or Raspberry for mobile crawler robots. Especially in the classification of decisions based on the input variables. The artificial intelligence algorithms specifically used in this paper and this example are called feed-forward artificial neural networks. In this paper, there is described how a relatively small neural network that is pre-trained in MATLAB platform can be implemented to the Arduino control board for controlling crawler mobile robot. In this article, there is described the mechanical construction and electrical connections of the mobile robot for a better understanding of this application. The designed crawler mobile robot in this article was primarily used for educational purposes.

关键词： Artificial intelligence Mobile Robotics Neural Networks Classification

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Comparison of risk assessment approaches and analyzes used in technical transport systems

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Transportation Research Procedia 2023年 74卷 516-521页

作者： Milan Sága Ivan Kuric Ivana Klačková Dorota Więcek Department of Automation and Production Systems Faculty of Mechanical Engineering University of Zilina Univerzitná 8215/1 010 26 Žilina Slovakia Department of Production Engineering Faculty of Mechanical Engineering and Computer Sciences University of Bielsko-Biała Willowa 2 43-309 Bielsko-Biała Poland

On the basis of current normative and legal bases, such as standards, directives, and laws that control interoperability and safety of systems, the paper's goal is to compare methods for risk assessment of transportation and engineering equipment and protection systems. The initial system definition defined at a high level of abstraction and a few methods used in the development of safety requirements' initial phase are taken into consideration. Eliminating the risk or lowering either of the two criteria that determine the relevant risk, such as the severity of the damage caused by the risk in question and the likelihood that the harm will occur, either independently or concurrently, can accomplish the objective of risk reduction.

关键词： transport safety risk

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Prediction of Temperature Behavior in Hydraulic Circuits

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Transportation Research Procedia 2023年 74卷 500-507页

作者： Daria Fedorova Vladimír Stenchlák Vladimír Tlach Ivan Kuric Dariusz Wiecek Department of Automation and Production Systems Faculty of Mechanical Engineering University of Zilina Univerzitná 8215/1 010 26 Žilina Slovakia Department of Production Engineering Faculty of Mechanical Engineering and Computer Sciences University of Bielsko-Biała Willowa 2 43-309 Bielsko-Biała Poland

The increasing complexity of products and systems in modern engineering production requires higher demands on the operation and maintenance of systems. For this reason, the role of maintenance can hardly be underestimated, as the maintenance of machinery and equipment is an integral part of any manufacturing process. Maintenance is closely related to the precision of the parts produced and the quality of the manufacturing process. A current trend in Industry 4.0 is predictive maintenance, which enables real-time detection of faulty equipment conditions based on condition monitoring. Utilizing artificial intelligence for predictive analytics can considerably contribute to the prediction of potential failures. Consequently, maintenance costs related to production downtime and equipment repair will be decreased. In this paper, a non-linear autoregressive neural network for real-time prediction of working fluid temperature parameters in a hydraulic circuit is presented. A testing device is also developed to collect experimental data, optimize, and test the proposed prediction model.

关键词： Neural network NAR predictive maintenance

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Development of Software for Automated Marking of Vertebral Bodies

Development of Software for Automated Marking of Vertebral B...

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2022 IEEE International Multi-Conference on Engineering, computer and Information Sciences, SIBIRCON 2022

作者： Piletskii, D. Gladkov, A. Yakimenko, A. Novosibirsk State Technical University Faculty of Automation and Computer Engineering Novosibirsk Russia Novosibirsk State Technical University Department of Data Acquisition and Processing Systems Novosibirsk Russia Institute of Computational Mathematics and Mathematical Geophysics SB RAS Laboratory of Geophysical Informatics Novosibirsk Russia

ISBN: (纸本)9781665464802

in order to create a digital twin of the spine to simulate the behavior of the spine after various interventions, the task of automating the marking of the vertebral bodies on radiographs was formulated. The presented work describes the developed approaches to solving the problem of marking the vertebral bodies on radiographs, and also describes algorithms for extracting images of the spine and images of individual vertebrae. For the detection of images of each individual vertebra, the YOLOv5 model was used, and an ensemble of regression models was created to solve the problem of marking the image of each individual vertebra. After a series of experiments, marking errors were estimated at 4.6% using the ratio of coordinates obtained using trained models and correctly marked data. Theories were also put forward about the possible improvement of the created software by dividing the vertebrae into two subclasses in order to reduce the markup error to the desired 0.8%. © 2022 IEEE.

关键词： computer vision

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Features of the Computational Process Organization of Initial Parameters Determination for Shading 12

Features of the Computational Process Organization of Initia...

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12th International Conference on Advanced computer Information Technologies, ACIT 2022

作者： Romanyuk, Olexandr Romanyuk, Oksana Mykhaylov, Pavlo Chekhmestruk, Roman Korobeinikova, Tetiana Romanyuk, Sergey Vinnytsia National Technical University Faculty of Information Technologies and Computer Engineering Vinnytsia Ukraine 3D Generation Ua Vinnytsia Ukraine Institute of Computer Technologies Automation and Metrology Lviv Polytechnic National University Lviv Ukraine Ceo 3D Gneration GmbH Dortmund Germany Institute of Computer Systems Odessa Polytechnic State University Odessa Ukraine

ISBN: (数字)9781665410502

ISBN: (纸本)9781665466479

The property of constancy of color intensity increment for the whole triangle is proved, which allows to significantly reduce the amount of calculations when implementing shading, since the increment of color intensity is determined for the whole triangle and not for each rasterization line. This allows to perform these calculations in the preparation cycle and exclude 'long' operations directly from the shading cycle. Based on the proven property, a number of parallelization methods are proposed, which have a simple hardware implementation. Structural diagrams of devices for shading tasks are given. Methods for reducing the complexity of vector normalization are proposed. © 2022 IEEE.

关键词： Rasterization

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Energy-based Control of Three-Link Planar Robot with Last Active Link

Energy-based Control of Three-Link Planar Robot with Last Ac...

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Chinese automation Congress (CAC)

作者： Yongjia Wang Xin Xin Yannian Liu School of Automation Southeast University Nanjing China Faculty of Computer Science and Systems Engineering Okayama Prefectural University Okayama Japan

This paper studies the energy-based control for a 3-link planar robot with last active link, for which the angle between the last link and the vertical is actuated. The swing-up and stabilizing task around the robot’s upright equilibrium point (UEP) is investigated. An energy-based controller is derived to control both its overall energy and actuated variable. By presenting a property of the robot that holds under arbitrary physical parameters, this paper proves that almost all initial states converge to an invariant set where the last link is upright and the robot’s overall energy equals its value at the UEP, providing certain requirements on control gains are satisfied. This paper provides simulation verification for the obtained theoretical results, in which a local stabilizing controller is utilized to accomplish stabilization at the UEP.

关键词： Analytical models automation Switches Control systems Trajectory Task analysis Robots

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