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12th International Scientific Conference on computer Science, COMSCI 2024

作者： Harbaliev, Georgi Vasilev, Velyo Budakova, Dilyana Technical University of Sofia Faculty of Electronics and Automation Department of Computer Systems and Technologies Plovdiv4000 Bulgaria

ISBN: (纸本)9798350392166

This paper presents an approach to model and study the behavior of a firefighting drone. Unity ML-Agents Toolkit and two advanced Deep Reinforcement Learning algorithms are used. They are respectively Soft Actor-Critic (SAC) and Proximal Policy Optimization (PPO) which are supported. Their effectiveness in training a virtual agent drone to put out a fire is being studied. For the experiment, a fire is realized at different places randomly in the training virtual environment. The results show that the agents can detect and extinguish many of the fires and achieve adaptive behavior. From this, it can be concluded that these algorithms can be used for real purposes and the Unity ML Agent toolkit is suitable for conducting experiments. © 2024 IEEE.

关键词： Drones

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Application of Artificial Intelligence in Hardware Description Languages Education 33

Application of Artificial Intelligence in Hardware Descripti...

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33rd International Scientific Conference Electronics, ET 2024

作者： Kostadinov, Atanas N. Technical University of Sofia Plovdiv branch Faculty of Electronics and Automation Department of Computer Systems and Technologies 25 Tsanko Diustabanov Str Plovdiv4000 Bulgaria

ISBN: (纸本)9798350376449

The paper presents the use of artificial intelligence (AI) in teaching students hardware description languages (HDLs). These HDLs find applications in various academic disciplines. Different descriptions of basic electronic modules and corresponding testbenches are presented, using multiple implementations of AI. The text (prompt) is given when obtaining the description and testbench, and their simulation shows the correct operation. © 2024 IEEE.

关键词： computer hardware description languages

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New Skills and Knowledge for Digital Entrepreneurs in the age of Artificial Intelligence 19

New Skills and Knowledge for Digital Entrepreneurs in the ag...

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19th European Conference on Innovation and Entrepreneurship, ECIE 2024

作者： Orozova, Daniela Angelova, Nadezhda Zlatev, Zlatin Department of Informatics and Mathematics Faculty of Economics Trakia University Stara Zagora Bulgaria Department of Electrical Engineering Automation Computer Systems and Communications Faculty of Technics and Technologies Trakia University Yambol Bulgaria

ISBN: (纸本)9781917204149

Digital technologies are becoming increasingly complex and integrated, leading to significant transformations in society and the economy. The article aims to explore and summarize the new opportunities and potential risks of the widespread use of artificial intelligence (AI) in all aspects of life, to define the new skills and necessary knowledge of digital entrepreneurs and to highlight the need for transformation in modern education. Recognizing that the relationship between technology and business is two-way and becoming stronger, revealing that well-prepared employees are a guarantee of success and prosperity of companies in various fields, we try to focus on the main groups of qualities, skills and basic knowledge of students in the age of artificial intelligence. The development of the Internet, expansion of connectivity through social networks, the advent of AI, 3D printing, and immersive technologies like Augmented Reality, and Virtual Reality, require new knowledge and skills, leading to new challenges in education. Qualified personnel in this modern world must have solid professional training and systemic thinking (knowledge, skills, accumulated information), developed cognitive abilities, and personal skills based on collecting and analyzing large amounts of diverse information from heterogeneous sources. Questions arise: how can multiple information sources be combined effectively, and how can the fusion of multiple sources provide additional information to support decision-making processes? Combining information obtained from the real world makes the results heterogeneous and more informative. It follows the need to develop machine learning methods to extract relevant information from increasingly complex data sets. The goal is to improve the accuracy of the applied classification algorithms by combining predictions from multiple models, as well as obtaining a more stable final classification evaluation, effective handling of noisy data, adaptation to c

关键词： Adversarial machine learning

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Two Different Approaches of Applying ANFIS Based MPPT for a PV Water Pumping System with a SEPIC Converter

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Applied Solar Energy (English translation of Geliotekhnika) 2024年第3期60卷 383-399页

作者： Miqoi, S. Tidhaf, B. El Ougli, A. Team of Embedded Systems Renewable Energy and Artificial Intelligence National School of Applied Sciences Mohammed First University Oujda Oujda Morocco Computer Science Signal Automation and Cognitivism Laboratory Faculty of Sciences Dhar El Mahraz Fez Fez30050 Morocco

Abstract: The main objective of this work is to enhance the performance of the Photovoltaic water pumping system to cover the water requirement in rural areas. To do so, it is important to make sure that the PV array produces its maximum power at all times, which can be influenced by external condition (mainly the temperature and irradiation). Hence, we are employing the Adaptive Neuro-Fuzzy Inference System based MPPT in two ways. The ANFIS controller is considered more accurate and efficient as it uses an artificial neural network to learn from training data and generate fuzzy rules based on that data. Both approaches of ANFIS are used to control the duty cycle of the SEPIC converter, which connects the PV panel to the DC motor feeding the water pump. The system combining the PV panel, the SEPIC converter, the controller and the DC motor, is designed and simulated under MATLAB/Simulink. The performance of the proposed methods is tested under various meteorological conditions. © Allerton Press, Inc. 2024. ISSN 0003-701X, Applied Solar Energy, 2024, Vol. 60, No. 3, pp. 383–399. Allerton Press, Inc., 2024. ISSN 0003-701X, Applied Solar Energy, 2024. Allerton Press, Inc., 2024.

关键词： DC motors

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Use of Software Simulators in Digital Logic Design Education 32

Use of Software Simulators in Digital Logic Design Education

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32nd International Scientific Conference Electronics, ET 2023

作者： Kostadinov, Atanas N. Technical University of Sofia Faculty of Electronics and Automation Department of Computer Systems and Technologies 25 Tsanko Diustabanov Str. Plovdiv4000 Bulgaria

ISBN: (纸本)9798350302004

This paper presents the use of software simulators throughout the whole digital logic design learning process. Specific examples of the application of these software products in the lecture material, the laboratory exercises, the course project in the discipline, and exam preparation are given. Free simulators are used, and of course, there are also paid ones. The use of such programs enhances student learning. © 2023 IEEE.

关键词： Application programs

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Automatic Generation of a Microservice Data Structure from ReLEL 14

Automatic Generation of a Microservice Data Structure from R...

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14th International Conference on Emerging Ubiquitous systems and Pervasive Networks / 13th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare, EUSPN/ICTH 2023

作者： Léa, Fanomezana Mihajasoa Andrianjaka, Rapatsalahy Miary Raft, Razafindrakoto Nicolas Badica, Costin Laboratory for Mathematical and Computer Applied to the Development Systems University of Fianarantsoa Madagascar Laboratory of Multidisciplinary Applied Research University of Antananarivo Madagascar Faculty of Automation Computers and Electronic University of Craiova Romania

The popularity of microservice architecture abbreviated MSA has attracted researchers and practitioners in recent years. MSA aims to divide the complex monolithic system from the service to the database into several autonomous blocks called microservices. In this way, updates and deployment of each service can be managed independently. The dissociation of data storage for each microservice is one of the particularities of this architecture. However, the manual implementation of certain tasks in the design and development of the MSA is time-consuming particularly with regard to data management. The objective of this article is therefore to automatically generate the data structure of a microservice from ReLEL in order to systematically derive the MSA databases. Our approach is based on the Praxeme methodology. It is realized in two stages. First, the semantic aspect is derived. Then, we develop ATL derivation rules to design the data structure. © 2024 Elsevier B.V.. All rights reserved.

关键词： Data structures

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Advanced Analysis of Electro-Oculographic Signal using Deep Neural Networks for Safety Purposes in automation and Production systems 15

Advanced Analysis of Electro-Oculographic Signal using Deep ...

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15th International Conference on computer and automation Engineering, ICCAE 2023

作者： Kuric, Ivan Stenchlak, Vladimir Zajacko, Ivan Bohusik, Martin Wiecek, Dorota University of Žilina Department of Automation and Production Systems Žilina Slovakia University of Bielsko-Biala Faculty of Mechanical Engineering and Computer Science Bielsko-Biala Poland

ISBN: (纸本)9798350396225

This article deals with the problematics of obtaining and processing the EOG signals. This research describes the ways in which it is possible to measure and evaluate the measured bio-electrical signals of brain and muscle activity in more detail. The work also describes the analysis of the current state of this problematics and individual models of artificial intelligence are also described in the work - artificial neural networks that can be used for such advanced analysis. The experimental part of this work is performed in the MATLAB environment using the Deep Neural Network Toolbox. The experimental part of the work is focused on the analysis and processing of bio-electrical activity eye-motor muscles in the area of eye-tracking with the help of the OLIMEX EEG-SMT device. The information provided in this research can be used for improving safety and reliability and elimination of potential risks connected to an epilepsy disease and epilepsy seizures in automated production systems. © 2023 IEEE.

关键词： Deep neural networks

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Air parameters monitoring in urban area based on LoRaWAN: Data collection for environmental assessment 32

Air parameters monitoring in urban area based on LoRaWAN: Da...

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32nd International Scientific Conference Electronics, ET 2023

作者： Lishev, Stefan N. Spasov, Grisha V. Petrova, Galidiya I. Pavlova, Petya E. Technical University of Sofia Faculty of Electronics and Automation Department of Computer Systems 25 Tsanko Djustabanov Str Plovdiv4000 Bulgaria Technical University of Sofia Faculty of Electronics and Automation Department of Elecronics 25 Tsanko Djustabanov Str Plovdiv4000 Bulgaria

ISBN: (纸本)9798350302004

Advances in Internet of Things (IoT) technologies have given a strong progress in environmental monitoring, particularly in air quality assessment. Various technologies are being considered to realize IoT devices, of which LoRaWAN is one of the most promising. This paper presents a prototype of LoRaWAN End device for real-time environmental assessment that stores the measured data in the cloud. The user interface consists of a mobile application that connects to the cloud server to retrieve data and set connection settings. © 2023 IEEE.

关键词： User interfaces

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Comparative Analysis of SVM and CNN Classifiers for EEG Signal Classification in Response to Different Auditory Stimuli

Comparative Analysis of SVM and CNN Classifiers for EEG Sign...

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2024 International Conference on Telecommunications and Intelligent systems, ICTIS 2024

作者： Tibermacine, Ahmed Akrour, Djouher Khamar, Rofeida Tibermacine, Imad Eddine Rabehi, Abdelaziz University of Biskra Department of Computer Science Biskra Algeria Sapienza University of Rome Department of Computer Automation and Management Engineering Rome Italy Zian Achour University of Djelfa Laboratory of Telecommunications and Smart Systems Faculty of Sciences and Technology Djelfa17000 Algeria

ISBN: (纸本)9798331527396

This study aims to classify brainwave patterns using electroencephalogram (EEG) signals in response to various auditory stimuli, specifically Quran recitation, participants' favorite music, and Interstellar's main theme. By analyzing the unique EEG responses elicited by these stimuli, the study explores cognitive and emotional processing differences. Two prominent classifiers, Support Vector Machine (SVM) and Convolutional Neural Networks (CNN), were utilized. SVM, combined with Power Spectral Density (PSD) features, achieved the highest accuracy of 95% when distinguishing Quran recitation from rest. CNN, particularly with Kernel Density Estimation (KDE) features, exhibited strong performance in distinguishing between different auditory stimuli, with an average accuracy exceeding 90%. These results highlight the critical role of feature extraction techniques, such as PSD and KDE, in improving classification performance and deepening our understanding of EEG-based emotional and cognitive responses to auditory stimuli. © 2024 IEEE.

关键词： Convolutional neural networks

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An Approach to Modeling and Studying the Behavior of Firefighting Drones Using Unity ML-Agents

An Approach to Modeling and Studying the Behavior of Firefig...

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computer Science (COMSCI), International Scientific Conference on

作者： Georgi Harbaliev Velyo Vasilev Dilyana Budakova Department of Computer Systems and Technologies Faculty of Electronics and Automation Technical University of Sofia Plovdiv Bulgaria

ISBN: (数字)9798350392166

ISBN: (纸本)9798350392173

关键词： Training computer science Adaptation models Virtual environments Deep reinforcement learning Optimization Drones

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