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32nd International Conference on Software, Telecommunications and computer Networks, SoftCOM 2024

作者： Alrjoob, Ayat M. Ababnah, Ahmad A. Al-Mistarihi, Mamoun F. Darabkh, Khalid A. German-Jordanian University School of Electrical Engineering and Information Technology Electrical and Communication Engineering Department Amman11180 Jordan Jordan University of Science and Technology Faculty of Engineering Electrical Engineering Department P.o.Box 3030 Irbid22110 Jordan The University of Jordan School of Engineering Computer Engineering Department Amman11942 Jordan

ISBN: (纸本)9789532901382

The Internet of Things (IoT) has transformed device communication, necessitating reliable information security, especially physical layer security (PLS). Protecting data confidentiality in wireless transfers is critical in IoT environments. Cognitive Radio Networks (CRNs) optimize spectrum utilization, enhancing network efficiency. This study investigates PLS in CRNs, featuring a primary source-destination pair and a secondary user (SU) that performs cooperative jamming to secure the primary user's (PU) communication. The SU generates artificial interference, with transmit power determined by the primary network's interference tolerance. We develop mathematical formulas to assess outage probabilities, aiming to enhance security and efficiency in IoT and spectrum management. © 2024 University of Split, FESB.

关键词： Risk assessment

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Autonomous Vehicle Control in CARLA Simulator Using Reinforcement Learning 66

Autonomous Vehicle Control in CARLA Simulator Using Reinforc...

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66th International Symposium ELMAR, ELMAR 2024

作者： Cincurak, Dorian Grbic, Ratko Vranjcs, Mario Vranjes, Denis TTTech Auto Central and Eastern Europe OsijekHR-31000 Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering OsijekHR-31000 Croatia

ISBN: (纸本)9798350375411

Autonomous vehicles (AVs) have emerged as a transformative technology that promises safer and more efficient transportation systems. Central to the development of autonomous driving is the ability to make real-time decisions in complex and dynamic environments. Reinforcement learning (RL) has gained considerable attention as a promising approach that enables AVs to learn control policies directly from interaction with their environment. In this paper, two RL algorithms for autonomous driving were developed in the CARLA autonomous driving simulator: one based on the Deep Q-Learning (DQN) algorithm and the other based on the Deep Deterministic Policy Gradient (DDPG) algorithm. The evaluation of the developed algorithms was carried out using the user-defined metrics and shows promising results in learning from interaction. © 2024 IEEE.

关键词： Deep reinforcement learning

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The 5S Method and Its Strategic Determinants Within the Organization of Production Plants 32nd

The 5S Method and Its Strategic Determinants Within the Orga...

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32nd International Conference on Organization and Technology of Maintenance, OTO 2023

作者： Crnjac Milić, Dominika Faculty of Electrical Engineering Computer Science and Information Technology in Osijek Josip Juraj Strossmayer University of Osijek Kneza Trpimira 2B Osijek31000 Croatia

ISBN: (纸本)9783031514937

Racing for the global advantage, companies have been paying increasing attention to workplace design, employee safety, workplace satisfaction, labor productivity and product quality. One of the methods that can help them achieve these goals is the 5S method, which is also considered a management tool for better organization and management of the workplace. Although the 5S method is applicable to a wide range of workplaces, using published research results, this paper provides a comprehensive overview of its challenges and benefits in manufacturing companies. They are analyzed and synthesized in a new way and special attention is paid to the method steps and its implementation. The paper points to a wide scope of the method application as companies have to meet various standards and present certificates that guarantee the safety and quality of manufactured products. Since managers are constantly trying to find ways to obtain and maintain them, one of the objectives of this paper is to provide an overview and critical evaluation of existing published research results that show the impact of the method application on increasing the product quality, the production process, health and safety. The methods from the qualitative methodological framework were used and research results that contribute to the scientific discourse related to the results that can be achieved by applying the 5S method in the organization of production plants were presented. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Industrial research

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Highly Efficient Dual-Buck Structured Buck-Boost AC-AC Converter With Versatile Identical Inverting/Noninverting Operations

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IEEE Transactions on Industrial Informatics 2023年第12期19卷 11403-11417页

作者： Ahmed, Hafiz Furqan Alzaabi, Omar El Moursi, Mohamed Shawky Al Hosani, Khalifa National Sun Yat-sen University Department of Electrical Engineering Kaohsiung804201 Taiwan Khalifa University Advanced Power and Energy Center Department of Electrical Engineering and Computer Science Abu Dhabi127788 United Arab Emirates Mansoura University Faculty of Engineering Mansoura35516 Egypt

Single-phase dual-buck ac-ac (DBAC) converters are gaining attention due to their intrinsic protection from shoot-through and open-circuit problems of conventional ac-ac converters. However, research works on DBAC converters are mainly concentrated around unipolar topologies. In a few developed bipolar topologies to date, the inverting buck-boost operations (for series voltage injection and step-variable frequency outputs) are inefficient and burdened by large voltage and current stresses (v in + vo and i in + i o) of switching devices and ripples of passive elements. In this article, an efficient dual-buck structured buck-boost ac-ac converter is proposed, with the following features: no voltage source shoot-through and inductor open-circuit problems, natural attainment of safe commutation without additional protection circuitry or complex control, no need for pulsewidth modulation dead times, and elimination of high-frequency conduction of mosfet's body diodes and related slow reverse recovery issues. The proposed converter provides distinct types of efficient inverting and noninverting buck and boost operations, with smaller switch voltage/current stresses (v in/vo and i in/i o) and passive component ripples. Combined inverting and noninverting buck-boost operations are also proposed with separate tuning of buck and boost voltage transfer ratios. A simple adaptable switching strategy provides the switch control pulses for all circuit operations by modulating the buck and boost control reference signals. The proposed converter provides sustained input/output currents and performs well with nonresistive loads. Extensive theoretical analysis is presented followed by practical verifications on a 400-VA laboratory circuit. © 2005-2012 IEEE.

关键词： Buck-Boost converter

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Exploring Shifted Domain Problem within MNIST Dataset

Exploring Shifted Domain Problem within MNIST Dataset

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2023 International Conference on computer science, Information Technology and engineering, ICCoSITE 2023

作者： Hidayaturrahman Heryadi, Yaya Lukas Suparta, Wayan Arifin, Yulyani Bina Nusatara University BINUS Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350320954

Domain data can be shifted in any direction so it will be shared in different distributions to its original domain. This could be a problem since the model was trained with different distributions. It is found that adversarial domain adaptation using domain adversarial neural networks (DANN) can help to solve this problem on some scale. DANN can minimize the discrepancy between source and target data so the model can work well in both domains. The experiment is done by utilizing MNIST dataset that shifted into some conditions. In a condition when the shifting of distribution is too far, DANN is struggling to maintain the knowledge extracted from source data which leads to underperformance in the source and target domain. In contrast, when the shifting is closer, DANN can easily fit the model so it can perform well in both domains. It proves DANN is one of the good approaches to performing domain adaptation in small discrepancies. © 2023 IEEE.

关键词： Adversarial Domain Adaptation Domain Shifting Problem MNIST Transfer Learning

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Investigating the Impact of Data Augmentation for Fine-Grained Grocery Product Classification Based on Vision Transformer

Investigating the Impact of Data Augmentation for Fine-Grain...

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2023 International Conference on Artificial Intelligence Robotics, Signal and Image Processing, AIRoSIP 2023

作者： Rahmania, Rissa Heryadi, Yaya Lukas, Lukas Suparta, Wayan Sonata, Ilvico Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350327472

The existence of fine-grained image classification supporting smart retail provides effectiveness in recognizing products with high similarity. However, the generic classification method performs poorly in identifying products from a subordinate category. This paper aims to identify augmentation techniques to leverage the Vision Transformer (ViT) model to classify the fine-grained grocery product, which involves embedding patches and transformer encoders to extract the main features. First, we develop a fine-grained image dataset with ColorJitter, CutOut, and combining both augmentations. Secondly, we perform experiments and analysis of ViT size, embedded patch size and image size in the patch embedding process. Lastly, the ViT model are evaluated according to the image sizes 224, 384, and 512 in accuracy, loss, and confusion matrix. The highest accuracy was obtained at 0.9922. The ColorJitter and CutOut improved the confusion matrix in ViT-B/16 and ViT-L/16 with an image size of 384 and 512. The results show that both augmentations in the ViT model are able to distinguish fine-grained grocery products. © 2023 IEEE.

关键词： Embeddings

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Smart-Fragile Authentication Scheme for Robust Detecting of Tampering Attacks on English Text

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computers, Materials & Continua 2022年第5期71卷 2497-2513页

作者： Mohammad Alamgeer Fahd N.Al-Wesabi Huda G.Iskandar Imran Khan Nadhem Nemri Mohammad Medani Mohammed Abdullah Al-Hagery Ali Mohammed Al-Sharafi Department of Information Systems King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen School of Computing Faculty of EngineeringUniversiti Teknologi MalaysiaMalaysia Department of Electrical Engineering University of Engineering and Technology PeshawarPakistan Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Department of Computer Science College of Computers and Information TechnologyUniversity of BishaKSA

Content authentication,integrity verification,and tampering detection of digital content exchanged via the internet have been used to address a major concern in information and communication *** this paper,a text zero-watermarking approach known as Smart-Fragile Approach based on Soft Computing and Digital Watermarking(SFASCDW)is proposed for content authentication and tampering detection of English text.A first-level order of alphanumeric mechanism,based on hidden Markov model,is integrated with digital zero-watermarking techniques to improve the watermark robustness of the proposed *** researcher uses the first-level order and alphanumeric mechanism of Markov model as a soft computing technique to analyze English ***,he extracts the features of the interrelationship among the contexts of the text,utilizes the extracted features as watermark information,and validates it later with the studied English text to detect any *** has been implemented using PHP with VS code *** robustness,effectiveness,and applicability of SFASCDW are proved with experiments involving four datasets of various lengths in random locations using the three common attacks,namely insertion,reorder,and *** SFASCDW was found to be effective and could be applicable in detecting any possible tampering.

关键词： Watermarking soft computing text analysis hidden Markov model content authentication

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Intelligent malware – trends and possibilities

Mendel

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Mendel 2021年第1期27卷 18-22页

作者： Plucar, Jan Frank, Jiří Walter, Daniel Zelinka, Ivan Faculty of Electrical Engineering and Computer Science VŠB-TU Department of Computer Science Czech Republic

In recent months and years, with more and more computers and computer systems becoming the target of cyberattacks. These attacks are gaining strength and the sophistication of the approach in terms of how to attack. Attackers and Defenders are increasingly using artificial intelligence methods to maximize the success of their actions. For a successful defence, we must be able to anticipate future threats that may come. For these reasons, our research group is engaged in creating experimental software with artificial intelligence to test the possibilities and capabilities of such malware in the event of its deployment. This software has not only malware capabilities but also antimalware and can be used on both sides. This article introduces the reader to the main principles of our design, which can serve as a future platform for cyber defence systems. © 2021, Brno University of Technology. All rights reserved.

关键词： Neural networks

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CRISP - DM Process in Smart Building Management 11

CRISP - DM Process in Smart Building Management

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11th International Conference on electrical and Electronics engineering, ICEEE 2024

作者： Dursun, Mahir Sabyrzhan, Moldir Gazi University Faculty of Technology Dept. of Electrical and Electronics Engineering Ankara Turkey Graduate School of Informatics Gazi University Department of Computer Science Ankara Turkey

ISBN: (纸本)9798350362541

Smart Buildings are buildings that integrate and combine intelligence, management, control, materials, and construction as a single system to meet all the needs of the building, such as comfort, energy efficiency, and durability. In universities, laboratories are used less frequently than other facilities and classrooms. Courses and students may change in the same classroom, and the period of use of such classrooms is much more extended than in laboratories. However, classrooms may only be used for classes during long breaks or for short periods of non-use between exams. In addition, there is no provision for when the heating system will start to heat up before classes or when it will be turned off after classes. By planning heating and lightning, energy and costs will be saved. This paper presents data acquisition methods for preparing a dataset to create a machine learning (ML) model to save energy loss in university laboratories. The developed model will predict energy consumption in classrooms and laboratories based on weather conditions. The study is being conducted in two stages. The first stage describes how to collect data using electronic devices such as Internet of Things (IoT) controllers of Smart Building Management Systems. The second stage gave possibilities for data analysis and preparation using the phases of the Cross-Industry Standard Process for Data Mining (CRISP-DM). © 2024 IEEE.

关键词： Information management

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2D Polynomial Regression Modeling for Predictive Analysis of Glucose Concentration in NP-Model Fractal Microwave Sensor Using Frequency and Transmission Coefficient Disparities 13

2D Polynomial Regression Modeling for Predictive Analysis of...

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13th International electrical engineering Congress, iEECON 2025

作者： Nantapanich, Nutyada Mahatthanajatuphat, Pisit Wongsin, Norakamon Lee, Wilaiporn Rajamangala University of Technology Thanyaburi Faculty of Engineering Department of Electronics and Telecommunication Engineering Pathum Thani Thailand Yothinburana School Regular Program in Mathematics-Science Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand

ISBN: (纸本)9798331543952

The article introduces a two-dimensional polynomial regression model for the predictive analysis of glucose concentration in a fractal microwave sensor NP model, utilizing frequency and transmission coefficient differences to examine their correlation with glucose concentration levels. The sensor employed in this investigation is fabricated on an economical FR-4 substrate to minimize costs. The sensor structure is developed with the fractal structure reduction method established by the NP model to operate at a frequency of roughly 2.97 GHz. The CST Studio software is utilized to analyze the findings from the simulation of the suggested sensor structure. Furthermore, the proposed sensor is integrated into a test apparatus comprising a sensor platform and a liquid tube constructed from PPA material. The liquid under examination is a glucose and water mixture at varying concentrations. It was analyzed using a VNA instrument to evaluate its frequency response and the magnitude of the alteration in the transmission coefficient. The values are utilized to create a two-dimensional polynomial regression model. The experiments demonstrated that the proposed sensor model possesses an Adjusted R² value of 0.99499 and an average error of approximately 3.57% for glucose concentration analysis throughout the range of 5% to 30%, with sensitivities of 0.00879 dB/% for insertion loss and 0.092 MHz/% for frequency variation, facilitating accurate glucose concentration prediction analysis. © 2025 IEEE.

关键词： Polynomial regression

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