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Open AccessEditorial

Preface: The International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025)

by Teodor Iliev, Ivaylo Stoyanov, Grigor Mihaylov, Panagiotis Kogias and Jacob Fantidis

Eng. Proc. 2025, 104(1), 96; https://doi.org/10.3390/engproc2025104096 - 16 Sep 2025

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Abstract

The fourth edition of the International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025) was held in hybrid mode in Alexandroupolis, Greece, from 18 to 20 June 2025 [...] Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

1 pages, 139 KB

Open AccessEditorial

Statement of Peer Review

by Teodor Iliev, Ivaylo Stoyanov, Grigor Mihaylov, Panagiotis Kogias and Jacob Fantidis

Eng. Proc. 2025, 104(1), 97; https://doi.org/10.3390/engproc2025104097 - 17 Sep 2025

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Abstract

In submitting conference proceedings to Engineering Proceedings, the volume editors of the proceedings certify to the publisher that all papers published in this volume have been subjected to peer review administered by the volume editors [...] Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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15 pages, 3863 KB

Open AccessProceeding Paper

Fast Parallel Gaussian Filter Based on Partial Sums

by Atanaska Bosakova-Ardenska, Hristina Andreeva and Ivan Halvadzhiev

Eng. Proc. 2025, 104(1), 1; https://doi.org/10.3390/engproc2025104001 - 21 Aug 2025

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Abstract

As a convolutional operation in a space domain, Gaussian filtering involves a large number of computational operations, a number that increases when the sizes of images and the kernel size also increase. Thus, finding methods to accelerate such computations is significant for overall [...] Read more.

As a convolutional operation in a space domain, Gaussian filtering involves a large number of computational operations, a number that increases when the sizes of images and the kernel size also increase. Thus, finding methods to accelerate such computations is significant for overall time complexity enhancement, and the current paper proposes the use of partial sums to achieve this acceleration. The MPI (Message Passing Interface) library and the C programming language are used for the parallel program implementation of Gaussian filtering, based on a 1D kernel and 2D kernel working with and without the use of partial sums, and then a theoretical and practical evaluation of the effectiveness of the proposed implementations is made. The experimental results indicate a significant acceleration of the computational process when partial sums are used in both sequential and parallel processing. A PSNR (Peak Signal to Noise Ratio) metric is used to assess the quality of filtering for the proposed algorithms in comparison with the MATLAB implementation of Gaussian filtering, and time performance for the proposed algorithms is also evaluated. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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10 pages, 1274 KB

Open AccessProceeding Paper

An Embedded Control System for a 3D-Printed Robot for Training

by Zhelyazko Terziyski, Nikolay Komitov and Margarita Terziyska

Eng. Proc. 2025, 104(1), 2; https://doi.org/10.3390/engproc2025104002 - 21 Aug 2025

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Abstract

This study explores the application of 3D printing as a strategic tool in engineering education and robotics development. An embedded control system for a 3D-printed MK2 manipulator is implemented, including an Arduino microcontroller, servo motors, an analog joystick interface, and an LCD, with [...] Read more.

This study explores the application of 3D printing as a strategic tool in engineering education and robotics development. An embedded control system for a 3D-printed MK2 manipulator is implemented, including an Arduino microcontroller, servo motors, an analog joystick interface, and an LCD, with software developed in Arduino IDE. The design uses PLA material and a modular architecture for flexibility and extensibility. The platform is applied in laboratory training to develop algorithmic thinking and engineering creativity, demonstrating the potential of 3D printing as an integrated educational and engineering tool. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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11 pages, 2649 KB

Open AccessProceeding Paper

Resilience of UNet-Based Models Under Adversarial Conditions in Medical Image Segmentation

by Dina Koishiyeva, Jeong Won Kang, Teodor Iliev, Alibek Bissembayev and Assel Mukasheva

Eng. Proc. 2025, 104(1), 3; https://doi.org/10.3390/engproc2025104003 - 21 Aug 2025

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Abstract

Adversarial modifications of input data can degrade the stability of deep neural networks in medical image segmentation. This study evaluates the robustness of UNet and Att-UNet++ architectures using the NuInsSeg dataset with annotated nuclear regions from various tissue sources. Both models were trained [...] Read more.

Adversarial modifications of input data can degrade the stability of deep neural networks in medical image segmentation. This study evaluates the robustness of UNet and Att-UNet++ architectures using the NuInsSeg dataset with annotated nuclear regions from various tissue sources. Both models were trained and tested under eight perturbation types, including gradient-based, iterative, and stochastic methods, with identical parameter settings. In the absence of distortions, Att-UNet++ produced higher segmentation results with a Dice of 0.7160 and a mean IoU of 0.6190 compared to 0.6424 and 0.4732 for UNet. Under NI-FGSM and Gaussian noise, Att-UNet++ experienced a greater reduction in mean IoU, reaching 0.1215 and 0.0658, while UNet maintained 0.1968 and 0.2329. Loss landscape analysis showed smoother surfaces for Att-UNet++, yet revealed increased responsiveness to directional gradients. The findings suggest that improvements in segmentation accuracy through architectural modifications may be accompanied by increased vulnerability to input changes, highlighting the necessity of robustness evaluation in model development for medical image analysis. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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7 pages, 752 KB

Open AccessProceeding Paper

Usage of OLAP Cubes as a Data Model for DSS

by Nikolai Scerbakov, Alexander Schukin and Eugenia Rezedinova

Eng. Proc. 2025, 104(1), 4; https://doi.org/10.3390/engproc2025104004 - 22 Aug 2025

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Abstract

A decision support system (DSS) is a software application designed to determine suitable actions for specific organizational situations. Its main component is a data repository analyzed to produce decisions. This paper describes the data organization (Data Model) as a multi-dimensional OLAP cube with [...] Read more.

A decision support system (DSS) is a software application designed to determine suitable actions for specific organizational situations. Its main component is a data repository analyzed to produce decisions. This paper describes the data organization (Data Model) as a multi-dimensional OLAP cube with amendments for decision-making support. We present DSS functionality as building (slicing) hyper-cubes into decision sub-cubes. The system’s adjustment and evolution involve changing the granularity of these sub-cubes. We discuss the merging and splitting of hyper-cubes, arguing that this functionality is adequate for creating complex, real-time DSSs for various incidents, such as cybersecurity incidents. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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9 pages, 1645 KB

Open AccessProceeding Paper

End-to-End Automation and Optimization of Assembly Line for Climate Control Units in Automotive Industry

by Vanya Georgieva and Elena Balova

Eng. Proc. 2025, 104(1), 5; https://doi.org/10.3390/engproc2025104005 - 22 Aug 2025

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Abstract

This paper explores the role of automation in the production of climate control units for the automotive industry, emphasizing the latest technological advancements and optimization strategies. Automation has become a key factor in enhancing production efficiency, reducing costs, and ensuring high-quality output. The [...] Read more.

This paper explores the role of automation in the production of climate control units for the automotive industry, emphasizing the latest technological advancements and optimization strategies. Automation has become a key factor in enhancing production efficiency, reducing costs, and ensuring high-quality output. The article also delves into the principles of automated assembly lines, which leverage robots and smart technologies for faster, more precise operations. Additionally, robotic manipulators have revolutionized the handling of delicate components, ensuring high accuracy and minimizing human error. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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6 pages, 1627 KB

Open AccessProceeding Paper

A Reinforcement Learning Solution for Queue Management in Public Utility Services

by Todor Dobrev, Miroslav Markov and Valentina Markova

Eng. Proc. 2025, 104(1), 6; https://doi.org/10.3390/engproc2025104006 - 22 Aug 2025

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Abstract

This paper presents a reinforcement learning-based approach for optimizing queue management in public utility service environments. Using one year of real operational data from a utility office, a simulation model is developed to replicate daily service dynamics. A Q-learning agent is trained to [...] Read more.

This paper presents a reinforcement learning-based approach for optimizing queue management in public utility service environments. Using one year of real operational data from a utility office, a simulation model is developed to replicate daily service dynamics. A Q-learning agent is trained to allocate service types to counters dynamically, aiming to minimize client waiting time. The model treats the environment as a Markov Decision Process and uses an epsilon-greedy policy for learning optimal actions. Experimental results across multiple counter configurations demonstrate significant reductions in average waiting times, confirming the effectiveness and adaptability of the proposed method in dynamic service environments. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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7 pages, 1744 KB

Open AccessProceeding Paper

Simulator of Safe Interaction Between Driver, Pedestrian, Car, Road and Environment

by Mirkan Zyuhtyu and Georgi Krastev

Eng. Proc. 2025, 104(1), 7; https://doi.org/10.3390/engproc2025104007 - 22 Aug 2025

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Abstract

Road safety is a major concern for global society, with the main users in traffic being drivers, pedestrians and vehicles. Despite advances in technology, the interaction between these components still represents a significant safety risk. The simulation of these interactions can play an [...] Read more.

Road safety is a major concern for global society, with the main users in traffic being drivers, pedestrians and vehicles. Despite advances in technology, the interaction between these components still represents a significant safety risk. The simulation of these interactions can play an important role in the training of drivers, pedestrians and the development of new safety technologies, such as autonomous vehicles and intelligent road systems. This paper presents a concept for a simulator that models the interaction between driver, pedestrian, vehicle, road and environment, with comprehensive testing of new technologies and safety training methods. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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12 pages, 2906 KB

Open AccessProceeding Paper

Study of Influence of Printing Speed and Layer Height on Dimensional Accuracy of 3D-Printed Carbon Fiber-Reinforced Polyamide Parts

by Valeri Bakardzhiev, Sabi Sabev and Konstantin Chukalov

Eng. Proc. 2025, 104(1), 8; https://doi.org/10.3390/engproc2025104008 - 22 Aug 2025

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Abstract

Engineering parts have increasingly higher requirements for geometric accuracy and shape deviation. In 3D printing, optimal physical and mechanical properties and dimensional accuracy are often sought, as parts produced with this technology are increasingly used not only for prototypes but also for responsible [...] Read more.

Engineering parts have increasingly higher requirements for geometric accuracy and shape deviation. In 3D printing, optimal physical and mechanical properties and dimensional accuracy are often sought, as parts produced with this technology are increasingly used not only for prototypes but also for responsible technical products. This requires precise studies of 3D printing parameters of engineering filaments. Accuracy is how close the measured size is to the CAD model. Carbon fiber-reinforced polymers are characterized by high strength and stiffness. In this article, dimensional accuracy of 3D-printed parts made of carbon fiber-reinforced polyamide was studied. For this purpose, eight samples were produced in the shape of a rectangular prism with two types of through holes—hexagonal and round. The dimensional accuracy of the overall dimensions and the holes was studied. The data was processed statistically with the aim of building an adequate mathematical model that analytically synthesizes the expected dimensional accuracy for different combinations of the selected 3D-printed parameters. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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7 pages, 656 KB

Open AccessProceeding Paper

Using Large Language Models for Ontology Development

by Darko Andročec

Eng. Proc. 2025, 104(1), 9; https://doi.org/10.3390/engproc2025104009 - 22 Aug 2025

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Abstract

This paper explores the application of Large Language Models (LLMs) for ontology development, focusing specifically on cloud service ontologies. We demonstrate how LLMs can streamline the ontology development process by following a modified Ontology Development 101 methodology using Perplexity AI. Our case study [...] Read more.

This paper explores the application of Large Language Models (LLMs) for ontology development, focusing specifically on cloud service ontologies. We demonstrate how LLMs can streamline the ontology development process by following a modified Ontology Development 101 methodology using Perplexity AI. Our case study shows that LLMs can effectively assist in defining scope, identifying existing ontologies, generating class hierarchies, creating properties, and populating instances. The resulting cloud service ontology integrates concepts from multiple standards and existing ontologies. While LLMs cannot fully automate ontology creation, they significantly reduce development time and complexity, serving as valuable assistants in the ontology engineering process. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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8 pages, 2724 KB

Open AccessProceeding Paper

Low-Cost Device for Collecting Data from Acceleration Sensors

by Stefan Ivanov

Eng. Proc. 2025, 104(1), 10; https://doi.org/10.3390/engproc2025104010 - 25 Aug 2025

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Abstract

This article presents the development of a device for collecting data from acceleration sensors. The developed device uses a 32-bit ESP32 microcontroller, which offers good computational capabilities and rich communication peripherals. The current work examines the structure of the developed system, as well [...] Read more.

This article presents the development of a device for collecting data from acceleration sensors. The developed device uses a 32-bit ESP32 microcontroller, which offers good computational capabilities and rich communication peripherals. The current work examines the structure of the developed system, as well as its operational algorithm. The text presents the main components of the device and the method used for data acquisition. Vibration data was collected using a digital accelerometer. The configuration and parameterization of the device were carried out via a JSON file, which controlled the number of measurements and the rate at which they were performed. The acquired data can be easily filtered and processed using mathematical software, allowing it to be presented in a format suitable for further use in machine learning algorithms and artificial neural networks. The developed solution represents a low-cost alternative to similar vibration data acquisition systems, enabling condition monitoring of various machine components and predictive maintenance at a low hardware cost. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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14 pages, 4687 KB

Open AccessProceeding Paper

Blockchain Model for Tracking Employees’ Location in the Company’s Premises

by Venelin Maleshkov, Veneta Aleksieva and Hristo Valchanov

Eng. Proc. 2025, 104(1), 11; https://doi.org/10.3390/engproc2025104011 - 25 Aug 2025

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Abstract

In the ever-evolving world full of technologies, blockchain proves itself to be the most secure way of dealing with tampering of data. This paper proposes an innovative model for tracking employees within facilities using RFID, IoT devices and blockchain technology implemented on the [...] Read more.

In the ever-evolving world full of technologies, blockchain proves itself to be the most secure way of dealing with tampering of data. This paper proposes an innovative model for tracking employees within facilities using RFID, IoT devices and blockchain technology implemented on the Hyperledger Fabric platform. The blockchain system supports a secure and tamper-proof recording of employee movement because it keeps the data in a decentralized system. Smart contracts automate activities like control access, generate alerts and create audit trails without the need for centralized management. This implementation shows a high level of security and efficiency, making it a good approach to improve monitoring and compliance within organizations. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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10 pages, 1390 KB

Open AccessProceeding Paper

Students’ Success Rate Enhancement in an Electrical Machines Subject Through a Hybrid Flipped Classroom–Socratic Method

by Mbika Muteba

Eng. Proc. 2025, 104(1), 12; https://doi.org/10.3390/engproc2025104012 - 25 Aug 2025

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Abstract

In this paper, a hybrid flipped classroom–Socratic method (HFC-SBM) is proposed as an active and effective method of teaching and learning to enhance the success rate in the subject of electrical machines. The proposed method was applied in the third year of a [...] Read more.

In this paper, a hybrid flipped classroom–Socratic method (HFC-SBM) is proposed as an active and effective method of teaching and learning to enhance the success rate in the subject of electrical machines. The proposed method was applied in the third year of a Bachelor of Engineering Technology program. Most students were new to the subject of electrical machines and did not have any prior knowledge of the principle of energy conversion in electrical machines. The traditional method (TRM), the flipped classroom method (FCM), and the Socratic-based method (SBM) were applied and then compared with the proposed HFC-SBM. The students were assessed each time they completed a specific teaching and learning method. The assessment results revealed that the proposed HFC-SBM improved the students’ success rate tremendously by 300%, 160%, and 80% when compared to the TRM, FCM, and SBM, respectively. A single-factor Analysis of Variance (ANOVA) test has been carried out on the statistical data to assess the significance of the different teaching and learning methods on the students’ success rate. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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8 pages, 4933 KB

Open AccessProceeding Paper

Detecting Emotions Using EEG Signals

by Ivan Ralev and Georgi Krastev

Eng. Proc. 2025, 104(1), 13; https://doi.org/10.3390/engproc2025104013 - 25 Aug 2025

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Abstract

Emotions represent the internal state of a person. They can be detected by observing external signs or by using specialized equipment. The aim of this paper is to investigate the possibility of determining emotions using a digital electroencephalograph. At the beginning of the [...] Read more.

Emotions represent the internal state of a person. They can be detected by observing external signs or by using specialized equipment. The aim of this paper is to investigate the possibility of determining emotions using a digital electroencephalograph. At the beginning of the paper, a definition of emotion is given in order to determine rules for distinguishing individual emotions. A presentation of the equipment used during the study is made. An analysis of the results obtained is carried out. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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9 pages, 575 KB

Open AccessProceeding Paper

Methodology for Electric Conversion of a Small City Car

by Atanas Nikolov and Vasil Dimitrov

Eng. Proc. 2025, 104(1), 14; https://doi.org/10.3390/engproc2025104014 - 25 Aug 2025

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Abstract

This paper proposes a methodology for selecting and converting a suitable mass-produced car with an internal combustion engine into an electric car for operation mainly in the city. For sufficient range and economical operation, a compact car model with low mass and low [...] Read more.

This paper proposes a methodology for selecting and converting a suitable mass-produced car with an internal combustion engine into an electric car for operation mainly in the city. For sufficient range and economical operation, a compact car model with low mass and low frontal aerodynamic resistance was chosen. For good traction on the drive wheels and space for passengers and luggage, a car with a rear-mounted engine driving the rear wheels is preferred. Since extra-urban driving is sometimes required, an induction motor with the necessary power reserve was selected. The conversion offers alternative batteries—budget lead–acid batteries and lithium–iron–phosphate batteries for increased range. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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11 pages, 1164 KB

Open AccessProceeding Paper

Evaluating Low-Code Development Platforms: A MULTIMOORA Approach

by Danial Serekov, Alibek Bissembayev, Teodor Iliev, Assel Mukasheva and Jeong Won Kang

Eng. Proc. 2025, 104(1), 15; https://doi.org/10.3390/engproc2025104015 - 25 Aug 2025

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Abstract

Swiftly advancing low-code development platforms (LCDPs) have created a new branch in software development, allowing for the rapid creation of applications with minimal knowledge of coding. However, in spite of the great opportunities gained, problems related to choosing the most appropriate platform from [...] Read more.

Swiftly advancing low-code development platforms (LCDPs) have created a new branch in software development, allowing for the rapid creation of applications with minimal knowledge of coding. However, in spite of the great opportunities gained, problems related to choosing the most appropriate platform from a wide range of alternatives that differ in features, usage scenarios, and performance metrics make it difficult to determine the most suitable solution. The use of the MULTIMOORA method can greatly facilitate the selection process, along with a strong evaluation and weighting system, which has a positive impact on the results. The evaluation system provides ten global criteria with internal sub-criteria of different factors. The list of tested platforms includes the seven most popular ones: Kissflow, Salesforce App Cloud, Zoho Creator, OutSystems, MS Power App, Mendix, and Appian. The results show the genuine value of this method, by accentuating the strengths of the proven platforms and the method itself. This study offers a multifaceted and sustainable approach to platform validation that allows the use of LCDPs for various applications and helps to make rational decisions. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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14 pages, 7467 KB

Open AccessProceeding Paper

Entropy-Based Optimization in Chaotic Image Encryption Algorithms with Implementation of Artificial Intelligence

by Hristina Stoycheva and Georgi Mihalev

Eng. Proc. 2025, 104(1), 16; https://doi.org/10.3390/engproc2025104016 - 25 Aug 2025

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Abstract

This paper addresses the challenge of determining optimal parameters in chaotic systems used for image encryption algorithms based on chaos theory. A baseline algorithm employing a third-order Lorenz chaotic system is examined, incorporating core procedures such as permutation (shuffling) and diffusion. Graphical results [...] Read more.

This paper addresses the challenge of determining optimal parameters in chaotic systems used for image encryption algorithms based on chaos theory. A baseline algorithm employing a third-order Lorenz chaotic system is examined, incorporating core procedures such as permutation (shuffling) and diffusion. Graphical results are presented to illustrate the variation of image entropy in relation to changes in system parameters. The analysis reveals a distinct region in the parameter space where entropy reaches its highest values. Based on these observations, an optimality criterion is formulated, defining an objective function that captures the entropy’s sensitivity to two key system parameters, including the bifurcation parameter. A complex objective function is derived, and the optimization problem is solved using a modified version of the Price algorithm enhanced with artificial intelligence techniques. The proposed modification demonstrates superior performance in locating the global extremum of the objective function, resulting in enhanced security of the encrypted image. Numerical and graphical results for various images are provided, along with a comparative analysis between the standard and the modified Price method. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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11 pages, 1807 KB

Open AccessProceeding Paper

Analysis of Loss Functions for Colorectal Polyp Segmentation Under Class Imbalance

by Dina Koishiyeva, Jeong Won Kang, Teodor Iliev, Alibek Bissembayev and Assel Mukasheva

Eng. Proc. 2025, 104(1), 17; https://doi.org/10.3390/engproc2025104017 - 25 Aug 2025

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Abstract

Class imbalance is a persistent limitation in polyp segmentation, commonly resulting in biased predictions and reduced accuracy in identifying clinically relevant structures. This study systematically evaluated 12 loss functions, including standard, weighted, and compound formulas, applied to colon polyp segmentation using the UNet-VGG16 [...] Read more.

Class imbalance is a persistent limitation in polyp segmentation, commonly resulting in biased predictions and reduced accuracy in identifying clinically relevant structures. This study systematically evaluated 12 loss functions, including standard, weighted, and compound formulas, applied to colon polyp segmentation using the UNet-VGG16 fixed architecture on the Kvasir-SEG dataset. The encoder was frozen to isolate the effect of loss functions under the same training conditions. A fixed random seed was used in all experiments to ensure reproducibility and control variance during training. The results reveal that the combined loss functions, namely WBCE combined with Dice and Tversky combined with Focal, achieved the top Dice scores of 0.8916 and 0.8917, respectively. Tversky plus Focal also provided the highest sensitivity of 0.8885, and WBCE obtained the best average IoU of 0.8120. Tversky loss showed the lowest error rate of 4.99, indicating stable optimization. These results clarify the influence of loss function selection on segmentation performance in scenarios characterized by considerable class imbalance. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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9 pages, 1570 KB

Open AccessProceeding Paper

Analysis of Failures of Automatic Level Crossing Devices

by Emiliya Dimitrova, Vasil Dimitrov and Dragomira Dimitrova

Eng. Proc. 2025, 104(1), 18; https://doi.org/10.3390/engproc2025104018 - 25 Aug 2025

Viewed by 554

Abstract

The safety of automatic level crossing devices (ALDs) is of utmost importance due to the need to ensure safe passage through railway crossings—accidents must not be allowed. In this paper, an analysis of failures of ALDs in the railway infrastructure in Bulgaria for [...] Read more.

The safety of automatic level crossing devices (ALDs) is of utmost importance due to the need to ensure safe passage through railway crossings—accidents must not be allowed. In this paper, an analysis of failures of ALDs in the railway infrastructure in Bulgaria for the period 2020–2022 is performed. First, a statistical evaluation of failures and their duration are calculated. Then, simple reliability indicators have been defined (the time for failure-free operation for different periods, the statistical assessment of the intensity of the failures flow and MTBF) in two ways—considering all failures and their duration or only those due to technical reasons. Finally, the coefficients of availability and unavailability are determined (also in both ways). A comparison was made with the availability coefficients of the indoor devices. The results obtained can be used in determining guidelines for the reconstruction and renovation of signaling systems and railway lines, as well as in identifying conflict points where multi-level crossings should be implemented. It should be noted that performing only a statistical analysis is not enough, it is necessary to determine the reliability indicators and, above all, the availability coefficient. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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16 pages, 1492 KB

Open AccessProceeding Paper

Hardware Challenges in AI Sensors and Innovative Approaches to Overcome Them

by Filip Tsvetanov

Eng. Proc. 2025, 104(1), 19; https://doi.org/10.3390/engproc2025104019 - 25 Aug 2025

Viewed by 1564

Abstract

Intelligent sensors with embedded AI are key to modern cyber-physical systems. They find applications in industrial automation, medical diagnostics and healthcare, smart cities, and autonomous systems. Despite their significant potential, they face several hardware challenges related to computing power, energy consumption, communication capabilities, [...] Read more.

Intelligent sensors with embedded AI are key to modern cyber-physical systems. They find applications in industrial automation, medical diagnostics and healthcare, smart cities, and autonomous systems. Despite their significant potential, they face several hardware challenges related to computing power, energy consumption, communication capabilities, and security, which limit their effectiveness. This article analyzes factors influencing the production and deployment of AI sensors. The key limitations are energy efficiency, computing power, scalability, and integration of AI sensors in real-time conditions. Among the main problems are the high requirements for data processing, the limitations of traditional microprocessors, and the balance between performance and energy consumption. To meet these challenges, the article presents several practical and innovative approaches, including the development of specialized microprocessors and optimized architectures for “edge computing,” which promise radical reductions in latency and power consumption. Through a synthesis of current research and practical examples, the article emphasizes the need for intermediate hardware–software solutions and standardization for mass deployment of AI sensors. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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12 pages, 1245 KB

Open AccessProceeding Paper

Implementing Artificial Intelligence in Chaos-Based Image Encryption Algorithms

by Hristina Stoycheva, Stanimir Sadinov, Krasen Angelov, Panagiotis Kogias and Michalis Malamatoudis

Eng. Proc. 2025, 104(1), 20; https://doi.org/10.3390/engproc2025104020 - 25 Aug 2025

Viewed by 1598

Abstract

This paper presents a modification of an image encryption algorithm combining chaos and the Fibonacci matrix by integrating artificial intelligence via a Generative Pre-Trained Transformer (GPT). The goal is to improve the robustness of the algorithm by dynamically adapting the parameters of the [...] Read more.

This paper presents a modification of an image encryption algorithm combining chaos and the Fibonacci matrix by integrating artificial intelligence via a Generative Pre-Trained Transformer (GPT). The goal is to improve the robustness of the algorithm by dynamically adapting the parameters of the chaotic system and generating cryptographic keys based on image characteristics. The proposed methodology includes two main innovations: the implementation of GPT for automated generation of the initial parameters of the chaotic system, which allows for greater variability and security in encryption, and the use of GPT for dynamic determination of the Fibonacci Q-matrix, which provides additional complexity and increased resistance to attacks. The method is realized in the MATLAB (R2023a) environment through integration with OpenAI API and the MATLAB–Python interface for requesting GPT models. The efficiency and reliability of the modified algorithm are compared with those of standard chaotic encryption algorithms, and its robustness to various cryptographic attacks is also studied. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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11 pages, 2784 KB

Open AccessProceeding Paper

Simulation of a Two-Phase Fluid Flow in a Design Solution of a Secondary Radial Settling Tank for Wastewater Treatment

by Aleksandrina Bankova, Anastas Yangyozov, Stefan Tenev and Asparuh Atanasov

Eng. Proc. 2025, 104(1), 21; https://doi.org/10.3390/engproc2025104021 - 25 Aug 2025

Viewed by 1490

Abstract

This report examined a design solution for a wastewater treatment facility in which—based on input data such as the amount of suspension at the inlet—the solid content in the suspension and sludge, the relative weight of the particles, the sedimentation rate, the diameter [...] Read more.

This report examined a design solution for a wastewater treatment facility in which—based on input data such as the amount of suspension at the inlet—the solid content in the suspension and sludge, the relative weight of the particles, the sedimentation rate, the diameter and height of the radial settler were determined. After determining the parameters, the design solution was created in the SolidWorks 2024 environment. In the design process, the shape of the fastening device was modified, which is of significant importance in the design of the facility, as it affects in a specific way the concentration of suspended substances in the thickened sludge and in the recirculated sludge flow. The design was transferred into the ANSYS CFX 2017 software for subsequent simulation of its purification function. Based on techniques in fluid mechanics, the boundary and end conditions for the analysis of the fluid flow were set. The study focused on the analysis of a CFD model to describe the movement of a two-phase fluid consisting of rainwater and sand with a particle size of 1–10 mm. Based on the analysis, the results of the influence of rotating elements on the movement of the solid phase and water in the fluid domain were reported. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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13 pages, 4412 KB

Open AccessProceeding Paper

Approximation of Dynamic Systems Using Deep Neural Networks and Laguerre Functions

by Georgi Mihalev

Eng. Proc. 2025, 104(1), 22; https://doi.org/10.3390/engproc2025104022 - 25 Aug 2025

Viewed by 280

Abstract

This article presents a hybrid approach that combines Laguerre orthonormal functions with deep neural networks (DNN) for effective approximation of impulse responses of dynamic systems. Attention is given to key limitations in approximation with Laguerre functions, such as the selection of the optimal [...] Read more.

This article presents a hybrid approach that combines Laguerre orthonormal functions with deep neural networks (DNN) for effective approximation of impulse responses of dynamic systems. Attention is given to key limitations in approximation with Laguerre functions, such as the selection of the optimal scaling factor, the number of functions used, and computational complexity. By training compact DNNs that directly predict the decomposition coefficients, increased functionality is achieved, as well as greater flexibility and efficiency in the context of implementing MPC. The proposed architecture provides good scalability, robustness, and computational efficiency, making it applicable in tasks related to system approximation and identification under uncertainty and noise conditions. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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10 pages, 3241 KB

Open AccessProceeding Paper

Development of LTE (4G) Antenna Design for Highest Efficiency Achievement

by Miroslav Tomov, Konstantinos Tramantzas, Dimitrios Kazolis and Stanimir Sadinov

Eng. Proc. 2025, 104(1), 23; https://doi.org/10.3390/engproc2025104023 - 25 Aug 2025

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Abstract

The quality of RF signal coverage of mobile networks, and for example, the parameters of LTE signals at many places, is not reliable enough for intensive data transfer. This fact causes mobile service customers to look for and to apply additional local devices [...] Read more.

The quality of RF signal coverage of mobile networks, and for example, the parameters of LTE signals at many places, is not reliable enough for intensive data transfer. This fact causes mobile service customers to look for and to apply additional local devices or systems for amplification of the initially supplied RF signal level to improve the quality of the service. This local improvement covers a small area around the customer’s residence. This paper shares some useful results of design, analyses, and optimization for effective performance of the tranceiving antenna for LTE (4G) signals. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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13 pages, 4677 KB

Open AccessProceeding Paper

Hyperspectral Analysis of Apricot Quality Parameters Using Classical Machine Learning and Deep Neural Networks

by Martin Dejanov

Eng. Proc. 2025, 104(1), 24; https://doi.org/10.3390/engproc2025104024 - 25 Aug 2025

Viewed by 223

Abstract

This study focuses on predicting β-carotene content using hyperspectral images captured in the near-infrared (NIR) region during the drying process. Several machine learning models are compared, including Partial Least Squares Regression (PLSR), Stacked Autoencoders (SAEs) combined with Random Forest (RF), and Convolutional Neural [...] Read more.

This study focuses on predicting β-carotene content using hyperspectral images captured in the near-infrared (NIR) region during the drying process. Several machine learning models are compared, including Partial Least Squares Regression (PLSR), Stacked Autoencoders (SAEs) combined with Random Forest (RF), and Convolutional Neural Networks (CNNs) in three configurations: 1D-CNN, 2D-CNN, and 3D-CNN. The models are evaluated using R², Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE). The PLSR model showed excellent results with R² = 0.97 for both training and testing, indicating minimal overfitting. The SAE-RF model also performed well, with R² values of 0.82 and 0.83 for training and testing, respectively, showing strong consistency. The CNN models displayed varying results: 1D-CNN achieved moderate performance, while 2D-CNN and 3D-CNN exhibited signs of overfitting, especially on testing data. Overall, the findings suggest that although CNNs are capable of capturing complex patterns, the PLSR and SAE-RF models deliver more reliable and robust predictions for β-carotene content in hyperspectral imaging. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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14 pages, 824 KB

Open AccessProceeding Paper

The Role of Aggregators in Digital Energy

by Nikolay Nikolov, Dimitrina Koeva, Vladimir Zinoviev and Zornitsa Dimitrova

Eng. Proc. 2025, 104(1), 25; https://doi.org/10.3390/engproc2025104025 - 26 Aug 2025

Viewed by 2289

Abstract

This study examines the role of aggregators in the context of digital energy and the integration of renewable energy sources (RES). The primary economic functions of aggregators are examined, including their role in optimizing energy markets and enhancing the flexibility and resilience of [...] Read more.

This study examines the role of aggregators in the context of digital energy and the integration of renewable energy sources (RES). The primary economic functions of aggregators are examined, including their role in optimizing energy markets and enhancing the flexibility and resilience of electricity systems. Different business models are presented, including the Energy as a Service (EaaS) model, and the effects of aggregators’ participation in electricity markets and balancing markets are examined. Special attention is paid to models for optimizing trading strategies and energy storage management. A comparative assessment of two scenarios for the distribution of the energy mix between solar and wind energy in the period 2022–2024 is conducted, evaluating the necessary storage capacities to achieve energy sustainability. The study highlights the importance of aggregators for grid stability, the integration of RES, and achieving higher efficiency through digitalisation and decentralisation in the context of European energy policy and the transition to a low-carbon economy. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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15 pages, 1516 KB

Open AccessProceeding Paper

Modeling and Control of Permanent Magnet Generators with Fractional-Slot Concentrated Windings Working with Active Converters for Wind Power

by Hung Vu Xuan

Eng. Proc. 2025, 104(1), 26; https://doi.org/10.3390/engproc2025104026 - 26 Aug 2025

Viewed by 735

Abstract

This paper presents modeling for an external rotor permanent magnet generator (PMG) with fractional-slot concentrated windings working with a power electronic converter in the rotor magnetic field coordinate—the model is also called the DQ model. The model is needed to synthesize controllers of [...] Read more.

This paper presents modeling for an external rotor permanent magnet generator (PMG) with fractional-slot concentrated windings working with a power electronic converter in the rotor magnetic field coordinate—the model is also called the DQ model. The model is needed to synthesize controllers of the PMG. Additionally, modeling for an active rectifier of the PMG is also investigated. The models of PMG and the active rectifier with two closed loops, namely the current loop and dc voltage loop, are verified by simulation in Matlab/Simulink. By modeling PMG in the rotor magnetic field coordinate, vector current can be decomposed in two independent currents, namely active current and reactive current. By controlling the active current, active power or electromagnetic torque or DC bus voltage can be controlled. By setting a relevant reactive current, the power factor or reactive power or rotor magnetic flux of PMG can be controlled. Simulation results of control PMG working with an active converter, such as pulse width modulation voltage, current, DC voltage, or power, are reported. The simulation helps to synthesize controllers and improve performances of the PMG working with the converter in wind applications. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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13 pages, 3147 KB

Open AccessProceeding Paper

Implementation of a Decision Support Mechanism on a Mobile Platform Using Clinical Evidence-Based Dynamic Insulin Dosage Adjustment for Artificial Intelligence-Enabled Diabetes Care (AIDCARE) System

by Ömer Faruk Üçer, Adnan Kavak, Yeliz Demirhan, Medine Uzun, Betül Savaş, Alpaslan Burak İnner, Özlem Alkan, Berrin Çetinarslan, Zeynep Cantürk, Alev Selek, Emre Gezer, Umut Yiğit, Ayaz Aktaş, Ahmet Tarık Fırat, Muhammed Ahmet Demirtaş, Göksel Okandan, Kevser Ünlü, Saliha Ünersoy and Özgür Çakır

Eng. Proc. 2025, 104(1), 27; https://doi.org/10.3390/engproc2025104027 - 25 Aug 2025

Viewed by 418

Abstract

Adjusting the insulin dose in patients with diabetes is crucial for maintaining optimal blood glucose levels. Currently, the insulin dose adjustment of patients registered at the Diabetes Clinic of Kocaeli University Hospital is followed manually using clinical forms, which is time-consuming and often [...] Read more.

Adjusting the insulin dose in patients with diabetes is crucial for maintaining optimal blood glucose levels. Currently, the insulin dose adjustment of patients registered at the Diabetes Clinic of Kocaeli University Hospital is followed manually using clinical forms, which is time-consuming and often fails to adequately account for individual variations. In this study, a rule-based insulin dose adjustment algorithm was developed based on clinical guidelines. The algorithm analyzes blood glucose levels measured at specific times over the past three days to determine the necessary insulin dose adjustments. The algorithm is implemented as part of the measurement module in a mobile application, the so-called AIDCARE application, which provides an artificial intelligence-enabled self-management tool for diabetic patients. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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11 pages, 1375 KB

Open AccessProceeding Paper

Unveiling Cyber Threats: An In-Depth Study on Data Mining Techniques for Exploit Attack Detection

by Abdallah S. Hyassat, Raneem E. Abu Zayed, Eman A. Al Khateeb, Ahmad Shalaldeh, Mahmoud M. Abdelhamied and Iyas Qaddara

Eng. Proc. 2025, 104(1), 28; https://doi.org/10.3390/engproc2025104028 - 25 Aug 2025

Viewed by 343

Abstract

The number of people and applications using the internet has increased substantially in recent years. The increased use of the internet has also resulted in various security issues. As the volume of data increases, cyber-attacks become increasingly sophisticated, exploiting vulnerabilities in network structures. [...] Read more.

The number of people and applications using the internet has increased substantially in recent years. The increased use of the internet has also resulted in various security issues. As the volume of data increases, cyber-attacks become increasingly sophisticated, exploiting vulnerabilities in network structures. The incorporation of modern technologies, particularly data mining, emerges as an essential method for analyzing huge amounts of data in real time, enabling the proactive detection of anomalies and potential security breaches. This research seeks to identify the most robust machine learning model for exploit detection. It applies five feature selection techniques and eight classification models to the UNSW-NB15 dataset. A comprehensive evaluation is conducted based on classification accuracy, computational efficiency, and execution time. The results demonstrate the efficiency of the Decision Tree model using Random Forest for feature selection in the real-time detection of exploit attacks, exhibiting an accuracy of 87.9%, along with a very short training (0.96 s) and testing time (0.29 ms/record). Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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9 pages, 2377 KB

Open AccessProceeding Paper

Electromagnetic Compatibility Analysis in the Design of Reliable Energy Systems of a Telecommunication Equipment

by Ivelin Stoykov, Grigor Mihaylov, Teodora Hristova, Katerina Gabrovska-Evstatieva, Peyo Hristov, Ognyan Fetfov and Boyko Ganchev

Eng. Proc. 2025, 104(1), 29; https://doi.org/10.3390/engproc2025104029 - 25 Aug 2025

Viewed by 361

Abstract

The reliability of power supply systems is of utmost importance for telecommunications. In our daily lives, we are used to having constant access to the power grid with negligible risks. Standards and practices established over the years guarantee minimal problems for the household [...] Read more.

The reliability of power supply systems is of utmost importance for telecommunications. In our daily lives, we are used to having constant access to the power grid with negligible risks. Standards and practices established over the years guarantee minimal problems for the household consumer and accidents in their electrical appliances. Often, the biggest inconvenience of a power failure for the average person is having to set the clock on the stove or use the flashlight on their phone. However, we rarely realize how fragile the balance on which all this is based is, but telecom companies are fully aware of this fact. Regardless of whether the problem comes from natural phenomena, accidental or intentional damage, or defects in the equipment, the equipment used in telecommunications technologies is extremely sensitive, and it is necessary to take protective measures. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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13 pages, 1341 KB

Open AccessProceeding Paper

Predicting Nurse Stress Levels Using Time-Series Sensor Data and Comparative Evaluation of Classification Algorithms

by Ayşe Çiçek Korkmaz, Adem Korkmaz and Selahattin Koşunalp

Eng. Proc. 2025, 104(1), 30; https://doi.org/10.3390/engproc2025104030 - 22 Aug 2025

Viewed by 351

Abstract

This study proposes a machine learning-based framework for classifying occupational stress levels among nurses using physiological time-series data collected from wearable sensors. The dataset comprises multimodal signals including electrodermal activity (EDA), heart rate (HR), skin temperature (TEMP), and tri-axial accelerometer measurements (X, Y, [...] Read more.

This study proposes a machine learning-based framework for classifying occupational stress levels among nurses using physiological time-series data collected from wearable sensors. The dataset comprises multimodal signals including electrodermal activity (EDA), heart rate (HR), skin temperature (TEMP), and tri-axial accelerometer measurements (X, Y, Z), which are labeled into three categorical stress levels: low (0), medium (1), and high (2). To enhance the usability of the raw data, a resampling process was performed to aggregate the measurements into one-minute intervals, followed by the application of the Synthetic Minority Over-sampling Technique (SMOTE) to mitigate severe class imbalance. Subsequently, a comparative classification analysis was conducted using four supervised learning algorithms: Random Forest, XGBoost, k-Nearest Neighbors (k-NN), and LightGBM. Model performances were evaluated based on accuracy, weighted F1-score, and confusion matrices to ensure robustness across imbalanced class distributions. Additionally, temporal pattern analyses by the day of the week and the hour of the day revealed significant trends in stress variation, underscoring the influence of circadian and organizational factors. Among the models tested, ensemble-based methods, particularly Random Forest and XGBoost with optimized hyperparameters, demonstrated a superior predictive performance. These findings highlight the feasibility of integrating real-time, sensor-driven stress monitoring systems into healthcare environments to support proactive workforce management and improve care quality. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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9 pages, 2593 KB

Open AccessProceeding Paper

Experimental Study on the Influence of Load-Equalizing Devices on Planet Loads in a Planetary Gear Set

by Vladislav Ivanov, Angel Alexandrov, Elitsa Tomova-Damyanova, Konstantina Vountzoukli, Mustafa Safa Yilmaz, Aikaterini Amygdalopoulou, Veselin Tsonev and Nikola Kuzmanov

Eng. Proc. 2025, 104(1), 31; https://doi.org/10.3390/engproc2025104031 - 25 Aug 2025

Viewed by 328

Abstract

The uneven load distribution between the planets in planetary gear trains has found multiple solutions including high manufacturing precision, targeted compliance or kinematic mobility of the components of the gear train. This paper presents an experimental investigation of the influence of three different [...] Read more.

The uneven load distribution between the planets in planetary gear trains has found multiple solutions including high manufacturing precision, targeted compliance or kinematic mobility of the components of the gear train. This paper presents an experimental investigation of the influence of three different load-equalizing devices on planetary gears’ pin loads in a planetary gear train with three planets. Two of the equalizing devices are designed to increase the radial resilience of the planets, and the third one increases the radial and tangential resilience of the sun gear. Using fast Fourier transform (FFT), the pins’ bending stresses are presented as a function of time and the gear wheels’ rotational frequency. For the experiments, a mechanical closed-loop test rig, designed at the Technical University of Sofia, was used. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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10 pages, 4186 KB

Open AccessProceeding Paper

Indirect Crop Line Detection in Precision Mechanical Weeding Using AI: A Comparative Analysis of Different Approaches

by Ioannis Glykos, Gerassimos G. Peteinatos and Konstantinos G. Arvanitis

Eng. Proc. 2025, 104(1), 32; https://doi.org/10.3390/engproc2025104032 - 25 Aug 2025

Viewed by 303

Abstract

Growing interest in organic food, along with European regulations limiting chemical usage, and the declining effectiveness of herbicides due to weed resistance, are all contributing to the growing trend towards mechanical weeding. For mechanical weeding to be effective, tools must pass near the [...] Read more.

Growing interest in organic food, along with European regulations limiting chemical usage, and the declining effectiveness of herbicides due to weed resistance, are all contributing to the growing trend towards mechanical weeding. For mechanical weeding to be effective, tools must pass near the crops in both the inter- and intra-row areas. The use of AI-based computer vision can assist in detecting crop lines and accurately guiding weeding tools. Additionally, AI-driven image analysis can be used for selective intra-row weeding with mechanized blades, distinguishing crops from weeds. However, until now, there have been two separate systems for these tasks. To enable simultaneous in-row weeding and row alignment, YOLOv8n and YOLO11n were trained and compared in a lettuce field (Lactuca sativa L.). The models were evaluated based on different metrics and inference time for three different image sizes. Crop lines were generated through linear regression on the bounding box centers of detected plants and compared against manually drawn ground truth lines, generated during the annotation process, using different deviation metrics. As more than one line appeared per image, the proposed methodology for classifying points in their corresponding crop line was tested for three different approaches with different empirical factor values. The best-performing approach achieved a mean horizontal error of 45 pixels, demonstrating the feasibility of a dual-functioning system using a single vision model. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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8 pages, 678 KB

Open AccessProceeding Paper

Investigation of Saturation in Iron Core Induction Motors with a Model in MATLAB/Simulink

by Ivanka Dimitrova, Albena Taneva and Teodora Hristova

Eng. Proc. 2025, 104(1), 33; https://doi.org/10.3390/engproc2025104033 - 26 Aug 2025

Viewed by 217

Abstract

Asynchronous motors are used in industry and in the electric drives of cars, trains and bicycles, as they are cheap, easy to maintain and have low energy consumption. In recent years, their importance has increased due to their high efficiency and safety, and [...] Read more.

Asynchronous motors are used in industry and in the electric drives of cars, trains and bicycles, as they are cheap, easy to maintain and have low energy consumption. In recent years, their importance has increased due to their high efficiency and safety, and their application in IoT systems has begun even in responsible areas such as the mining industry. There are many methods for their control, but this depends on the parameters of the motor itself, which must be studied. In this study, a precise simulation model of asynchronous motors was developed in MATLAB/Simulink. In this case study, the comparative results are obtained for the proposed model of a specific motor. The analysis shows saturation due to stronger oscillations and more extreme negative peaks under saturation conditions. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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11 pages, 1722 KB

Open AccessProceeding Paper

Industry 4.0 Technologies for MTM-1 Analysis Improvement for the Automotive Industry

by Krasimir Markov and Pavel Vitliemov

Eng. Proc. 2025, 104(1), 34; https://doi.org/10.3390/engproc2025104034 - 26 Aug 2025

Viewed by 2331

Abstract

The MTM-1 analysis has a very high level of detail and takes a very long time for to perform. A possible way to reduce the performance time while maintaining accuracy is by using Industry 4.0 technologies. The goal of the article is to [...] Read more.

The MTM-1 analysis has a very high level of detail and takes a very long time for to perform. A possible way to reduce the performance time while maintaining accuracy is by using Industry 4.0 technologies. The goal of the article is to investigate the potential for the implementation of Industry 4.0 technologies in the preparation of MTM-1 analysis for improving its speed and accuracy in the automotive industry, based on a unique survey. The results indicate that speed reduction and accuracy increase mainly depend on which Industry 4.0 technology is chosen and its capabilities. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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10 pages, 2169 KB

Open AccessProceeding Paper

Comparative Performance Analysis of Data Transmission Protocols for Sensor-to-Cloud Applications: An Experimental Evaluation

by Filip Tsvetanov and Martin Pandurski

Eng. Proc. 2025, 104(1), 35; https://doi.org/10.3390/engproc2025104035 - 25 Aug 2025

Viewed by 357

Abstract

This paper examines some of the most popular protocols for transmitting sensor data to cloud structures from publish/subscribe and request/response IoT models. The selection of a highly efficient message transmission protocol is essential, as it depends on the specific characteristics and purpose of [...] Read more.

This paper examines some of the most popular protocols for transmitting sensor data to cloud structures from publish/subscribe and request/response IoT models. The selection of a highly efficient message transmission protocol is essential, as it depends on the specific characteristics and purpose of the developed IoT system, which includes communication requirements, message size and format, energy efficiency, reliability, and cloud specifications. No standardized protocol can cover all the diverse application scenarios; therefore, for each developed project, the most appropriate protocol must be selected that meets the project’s specific requirements. This work focuses on finding the most appropriate protocol for integrating sensor data into a suitable open-source IoT platform, ThingsBoard. First, we conduct a comparative analysis of the studied protocols. Then, we propose a project that represents an experiment for transmitting data from a stationary XBee sensor network to the ThingsBoard cloud via HTTP, MQTT-SN, and CoAP protocols. We observe the parameters’ influence on the delayed transmission of packets and their load on the CPU and RAM. The results of the experimental studies for stationary sensor networks collecting environmental data give an advantage to the MQTT-SN protocol. This protocol is preferable to the other two protocols due to the lower delay and load on the processor and memory, which leads to higher energy efficiency and longer life of the sensors and sensor networks. These results can help users make operational judgments for their IoT applications. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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12 pages, 3494 KB

Open AccessProceeding Paper

A Numerical Study on Ag/CZTS/n-Si/Al Heterojunction Solar Cells Fabricated via Laser Ablation

by Serap Yigit Gezgin, Yasemin Gundogdu Kabakci and Hamdi Sukur Kilic

Eng. Proc. 2025, 104(1), 36; https://doi.org/10.3390/engproc2025104036 - 25 Aug 2025

Viewed by 249

Abstract

CZTS (C-I/C-II) ultrathin films in 61 nm and 313 nm thicknesses were grown on microscopic glass and n-Si wafer substrates via laser ablation, respectively. C-II ultrathin film with higher thickness has a more developed crystal structure and consists of larger particles compared to [...] Read more.

CZTS (C-I/C-II) ultrathin films in 61 nm and 313 nm thicknesses were grown on microscopic glass and n-Si wafer substrates via laser ablation, respectively. C-II ultrathin film with higher thickness has a more developed crystal structure and consists of larger particles compared to C-I ultrathin film with reduced thickness. C-II ultrathin film absorbs more photons and has a lower band gap. The photovoltaic performance of the produced Ag/CZTS (C-II)/n-Si/Al solar cell is higher compared to the other solar cell-based C-I ultrathin film. The more improved crystal structure of C-II ultrathin film has increased the efficiency of the solar cell. The calculated photovoltaic parameters of the solar cells modeled with the SCAPS-1D simulation program were found to be compatible with the experimental parameters. This situation has proven that the operating performance of solar cells is reliable. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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9 pages, 886 KB

Open AccessProceeding Paper

Gamification Approach in Cloud-Based Corporate Training

by Margarita Gocheva, Elena Somova and Lilyana Rusenova

Eng. Proc. 2025, 104(1), 37; https://doi.org/10.3390/engproc2025104037 - 26 Aug 2025

Viewed by 1634

Abstract

This paper presents a corporate training approach that relies on cloud infrastructure and business process models to improve employee development. It introduces a cloud-based corporate hierarchy model that forms the basis for designing and implementing training materials and courses to achieve corporate strategy [...] Read more.

This paper presents a corporate training approach that relies on cloud infrastructure and business process models to improve employee development. It introduces a cloud-based corporate hierarchy model that forms the basis for designing and implementing training materials and courses to achieve corporate strategy goals. The approach is based on business processes designed as BPMN diagrams to provide clarity of the process execution structure in the organization. The training course is also modelled using BPMN diagrams, which allows for a systematic and consistent presentation of the training content in all processes in which employees participate. The paper describes an experiment of simulated collaborative corporate training conducted during the learning process at one Bulgarian university. Within the experiment, gamification was integrated using game elements, game techniques, and competitive challenges, which stimulated the engagement of the learners and strengthened their motivation for active participation in corporate training. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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12 pages, 1574 KB

Open AccessProceeding Paper

Intelligent Agent-Based Control of Distributed Sensor Networks for Environmental Monitoring and Disaster Prediction

by Kalliopi Kravari, Maria Roussi, Kalliopi Ladomenou, Anna Thysiadou and Michail Chalaris

Eng. Proc. 2025, 104(1), 38; https://doi.org/10.3390/engproc2025104038 - 26 Aug 2025

Viewed by 1592

Abstract

Environmental monitoring and early disaster prediction require sensor networks that can dynamically reconfigure their operation based on environmental conditions and potential threats. Moving beyond traditional management requires autonomous and adaptive control systems with the ability for intelligent decision-making at the network edge. This [...] Read more.

Environmental monitoring and early disaster prediction require sensor networks that can dynamically reconfigure their operation based on environmental conditions and potential threats. Moving beyond traditional management requires autonomous and adaptive control systems with the ability for intelligent decision-making at the network edge. This paper presents an intelligent agent-based system for autonomous control and optimization of large-scale, distributed electronic sensor networks used for environmental monitoring and disaster prediction. The approach aims at promoting the accuracy and timeliness of disaster prediction by using sensor characteristics knowledge, environmental processes, and network control protocols. The paper presents the architecture and decision-making with potential applications. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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11 pages, 1492 KB

Open AccessProceeding Paper

Studying Influence of 3D Printing Parameters of PETG to Improve Hardness and Maximum Tensile Strength

by Valeri Bakardzhiev, Sabi Sabev and Konstantin Chukalov

Eng. Proc. 2025, 104(1), 39; https://doi.org/10.3390/engproc2025104039 - 25 Aug 2025

Viewed by 385

Abstract

3D printing is increasingly used in industrial practice as an important additive technology. Both the choice of material and the printing parameters play a critical role in the mechanical and physical characteristics of parts 3D printing parameters play a major role in the [...] Read more.

3D printing is increasingly used in industrial practice as an important additive technology. Both the choice of material and the printing parameters play a critical role in the mechanical and physical characteristics of parts 3D printing parameters play a major role in the strength of parts, the efficiency of the technology, and the production time. All this requires solving optimization issues using mathematical models in order to find balanced technological solutions. In this article, the main mechanical properties of PETG—hardness and maximum tensile strength, produced with different printing parameters—will be investigated. This study was conducted through a planned experiment with the aim of reducing the experimental samples without compromising the experimental results. The experimental results were statistically processed using MiniTab 13 experimental samples were tested with the following printing parameters—speed in the range of 40–120 m/min and a layer thickness between 0.1 to 0.4 mm. The aim of the article is to investigate in which discrete zone of 3D printing parameters the parts have the highest strength characteristicshardness and maximum tensile strength. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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11 pages, 2770 KB

Open AccessProceeding Paper

Active Microgrids with Dispersed Renewable Generation and Their Power Quality Performance Challenges

by Dimitrina Koeva and Georgi Bankov

Eng. Proc. 2025, 104(1), 40; https://doi.org/10.3390/engproc2025104040 - 25 Aug 2025

Viewed by 238

Abstract

The research and analyses presented in this paper are an attempt to prove the concept that a flexible and efficient energy transformation requires a gradual digitalization of the energy system, starting from the inside out, i.e., from the low-voltage micro- and nano-grids, which [...] Read more.

The research and analyses presented in this paper are an attempt to prove the concept that a flexible and efficient energy transformation requires a gradual digitalization of the energy system, starting from the inside out, i.e., from the low-voltage micro- and nano-grids, which mostly integrate low-power photovoltaic power plants and consumers with similar demand profiles. This approach is supported by the two main advantages of these grids: they are almost similar in structure and they are scalable, the two characteristics indicating a possible successful digitalization. For this to happen, we need to study the problems in these grids and be aware of the technological maturity of the energy facilities. This paper (the first of several to follow) examines the electricity performance problems caused by the stochastic nature of solar generation. A technique for monitoring and predictive load analysis is proposed, as well as technical measures for implementing decentralised control. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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12 pages, 2172 KB

Open AccessProceeding Paper

A Low-Cost Perception Improvement of an Electromechanical Gripper for Non-Destructive Fruit Harvesting

by Dimitrios Loukatos, Nikolaos Sideris, Ioannis-Vasileios Kyrtopoulos, Georgios Xanthopoulos and Konstantinos G. Arvanitis

Eng. Proc. 2025, 104(1), 41; https://doi.org/10.3390/engproc2025104041 - 26 Aug 2025

Cited by 1 | Viewed by 1484

Abstract

Modern intelligent robotic systems offer farmers a promising solution to labor shortages caused by socio-economic instability and/or pandemics. Efficient harvesting of delicate fruits is one of the main needs in this area. In this context, this work presents a simple and low-cost improvement [...] Read more.

Modern intelligent robotic systems offer farmers a promising solution to labor shortages caused by socio-economic instability and/or pandemics. Efficient harvesting of delicate fruits is one of the main needs in this area. In this context, this work presents a simple and low-cost improvement of the ability of a servo-electric gripper to adjust its force when picking delicate fruits without damaging them. Specifically, this module utilizes a microcontroller that intercepts the current consumed by the servomotor during the gripping action and properly adjusts its aperture, with respect to the force limits suitable for each type of fruit. Experiments were performed on various objects, from elastic balls to oranges, tomatoes and sweet bell peppers. These experiments revealed that the relationship between current consumption and applied force can be accurately approximated by nonlinear expression equations and verified the good performance of the proposed force limitation technique. Consequently, there is scope for adoption by a wide range of agricultural automation systems. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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10 pages, 3844 KB

Open AccessProceeding Paper

Optimization of the Operation of a Flexible Automated Assembly Line Using the Seven Basic Quality Tools

by Velizar Vassilev, Reneta Dimitrova and Stiliyan Nikolov

Eng. Proc. 2025, 104(1), 42; https://doi.org/10.3390/engproc2025104042 - 26 Aug 2025

Viewed by 323

Abstract

This paper proposes an algorithm for optimizing the operation of flexible automated assembly lines using the seven basic quality tools. Using the proposed algorithm, analysis of a flexible automated assembly line FMS-200 was performed, using several of the seven basic quality tools sequentially. [...] Read more.

This paper proposes an algorithm for optimizing the operation of flexible automated assembly lines using the seven basic quality tools. Using the proposed algorithm, analysis of a flexible automated assembly line FMS-200 was performed, using several of the seven basic quality tools sequentially. Based on the analysis results, corrective measures for optimization of line operation have been proposed. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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12 pages, 5055 KB

Open AccessProceeding Paper

Comprehensive Analysis of Cryptographic Algorithms: Implementation and Security Insights

by Rashid Muhenga, Fatima Sapundzhi, Metodi Popstoilov, Slavi Georgiev and Venelin Todorov

Eng. Proc. 2025, 104(1), 43; https://doi.org/10.3390/engproc2025104043 - 27 Aug 2025

Viewed by 1515

Abstract

This study surveys some cryptographic algorithms in a detailed manner; it mainly focuses on symmetric key cryptography and asymmetric key cryptography with hash functions following them. Regarding the importance of cryptography for securing communications and data integrity in the digital era, we show—using [...] Read more.

This study surveys some cryptographic algorithms in a detailed manner; it mainly focuses on symmetric key cryptography and asymmetric key cryptography with hash functions following them. Regarding the importance of cryptography for securing communications and data integrity in the digital era, we show—using practical examples with Python 3.10 and Crypto 2 tool—how a few implementations of such encryption techniques work. To clarify this further, Caesar Cipher represents a very simple varying key, and each round of stream ciphers or block ciphers exhibits highly advanced symmetric techniques. Then, we discuss asymmetric cryptography using RSA encryption with public–private key pairs for a secure communication. Furthermore, research has been conducted into the hash functions SHA-1 and SHA-2, which form unique digital fingerprints of the information provided. This approach allows us to highlight all the positive and negative aspects of the above tools and to identify the comparative characteristics of their degree of security. This fact is highly important in determining the applicability of the security tools described above, depending on the conditions of work and threats. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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10 pages, 1043 KB

Open AccessProceeding Paper

A Hybrid System for Automated Diagnosis of Inflammatory Skin Diseases: Neural Networks and Survey-Based Prediction

by Ayshe Shaban, Milena Karova and Gergana Spasova

Eng. Proc. 2025, 104(1), 44; https://doi.org/10.3390/engproc2025104044 - 27 Aug 2025

Viewed by 959

Abstract

This article presents an integrated system for automated diagnosis, combining convolutional neural networks (CNNs) for dermatological image analysis with a patient survey for clinical data collection. The goal is to evaluate the effectiveness of this hybrid approach compared to traditional diagnostic methods. The [...] Read more.

This article presents an integrated system for automated diagnosis, combining convolutional neural networks (CNNs) for dermatological image analysis with a patient survey for clinical data collection. The goal is to evaluate the effectiveness of this hybrid approach compared to traditional diagnostic methods. The system was tested on a curated dataset composed of images collected from DermNet and publicly available dermatological image databases. The results demonstrate high diagnostic accuracy for inflammatory skin diseases, with the combined approach outperforming standalone methods. These findings highlight the potential of integrating machine learning with patient-reported data to enhance dermatological diagnostics. The proposed system can be implemented in clinical practice and integrated into existing medical platforms, aiding dermatologists in decision-making and improving patient care. Future research will focus on expanding the system to diagnose a broader range of skin conditions and incorporating additional clinical data to enhance its performance. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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11 pages, 4579 KB

Open AccessProceeding Paper

Restoration of Working Surfaces for Forming Elements from Molds for High-Pressure Casting of Non-Ferrous Metals by Laser Surfacing

by Vladimir Dunchev, Kalin Anastasov, Vladimir Todorov, Vasil Chobanov and Milka Atanasova

Eng. Proc. 2025, 104(1), 45; https://doi.org/10.3390/engproc2025104045 - 27 Aug 2025

Viewed by 316

Abstract

The article presents a study of the possibilities for restoring the working surfaces of molds for high-pressure casting of non-ferrous metals by laser surfacing using a filler material. Test specimens with parameters of real forming elements were manufactured. The influence of nitriding on [...] Read more.

The article presents a study of the possibilities for restoring the working surfaces of molds for high-pressure casting of non-ferrous metals by laser surfacing using a filler material. Test specimens with parameters of real forming elements were manufactured. The influence of nitriding on welded layers and basic material was studied in comparison with one without nitriding. The X-ray diffraction method was used to obtain the phase composition of the surface of the samples in areas submitted to nitriding. Scanning electron microscopy (SEM) was used to determine the microstructure of the nitriding layers, welded layers and bulk material. Energy-dispersive X-ray spectrometry (EDX) was applied to investigate the chemical composition in the welded and nitrided zone. Mechanical property means of microhardness measurements were studied. Four zones were identified after nitriding in the weld area. The first zone closest to the surface with a thickness of 0.025 mm is characterized by a higher microhardness, which reaches 700 HV. The second zone, which is part of the diffusion zone, is 0.1 mm thick, and it is characterized by the same size grains with a similar shape and microhardness, which reaches 600 HV. The microhardness measured in the welded zone after nitriding is 50% greater than that without nitriding. The thickness of the diffusion zone in 1.2343 steel reaches about 0.15 mm, and the microhardness is about 900 HV near the edge, but quickly decreases to 400 HV. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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10 pages, 2101 KB

Open AccessProceeding Paper

ZigBee Cyberattacks Simulation

by Marieta Haka, Aydan Haka, Veneta Aleksieva and Hristo Valchanov

Eng. Proc. 2025, 104(1), 46; https://doi.org/10.3390/engproc2025104046 - 27 Aug 2025

Viewed by 404

Abstract

ZigBee technology is well-known for wireless network communication and enables low-cost devices operating at low transmission speed and low power consumption in IoT networks. The technology is used for wireless networks through which a large amount of sensitive information passes, which requires ensuring [...] Read more.

ZigBee technology is well-known for wireless network communication and enables low-cost devices operating at low transmission speed and low power consumption in IoT networks. The technology is used for wireless networks through which a large amount of sensitive information passes, which requires ensuring a higher level of security. This creates a need to develop tools to analyze vulnerabilities in such networks. The massive occurrence of cyberattacks requires a more in-depth study to propose adequate and effective approaches for improving security in ZigBee networks. Such research can be performed both in real and simulated environments. In this paper, a new module is proposed for simulating Sniffing, Brute Force, and Dictionary attacks. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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10 pages, 590 KB

Open AccessProceeding Paper

Approach and Tool for Creating Sustainable Learning Video Resources Through Integration of AI Subtitle Translator

by Hristo Hristov, Kostadin Bekirski, Elena Somova, Angel Ignatov, Stefan Stavrev and Zlatozar Poptolev

Eng. Proc. 2025, 104(1), 47; https://doi.org/10.3390/engproc2025104047 - 27 Aug 2025

Viewed by 361

Abstract

The article presents an approach and software tool aimed at achieving quality, accessible, and sustainable education. The approach is based on reusable learning objects—educational video materials that can be repeatedly used and adapted for different languages and audiences. The proposed learning model uses [...] Read more.

The article presents an approach and software tool aimed at achieving quality, accessible, and sustainable education. The approach is based on reusable learning objects—educational video materials that can be repeatedly used and adapted for different languages and audiences. The proposed learning model uses quality learning resources (regardless of their language) and integrates them into courses and educational processes, regardless of the language proficiency of the learners. The approach relies on the integration of subtitle translation technologies into educational video resources, aiming to overcome language barriers in education. The software tool, AI Subtitle Translator, is developed using artificial intelligence (AI) and offers automated subtitle translation. It utilizes OpenAI models (GPT-4o and GPT-4.5) to provide translation services. The workflow, architecture, implementation, and operational scenario of the software tool are also presented. The discussed approach serves as a solution to enhance accessibility to global educational content. By combining reusable learning objects with AI Subtitle Translator, effective education without language constraints is ensured. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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10 pages, 264 KB

Open AccessProceeding Paper

Optimal Placement Algorithms for Base and Central Stations in Mining Quarries

by Tatyana Golubeva and Ivan Hristov Beloev

Eng. Proc. 2025, 104(1), 48; https://doi.org/10.3390/engproc2025104048 - 27 Aug 2025

Viewed by 284

Abstract

This paper proposes algorithms for optimal placement of base stations (BSs) and central stations (CSs) in mining quarries to ensure reliable radio communication for automated machinery. The BS placement is modeled as a minimum dominating set problem, solved using integer linear programming with [...] Read more.

This paper proposes algorithms for optimal placement of base stations (BSs) and central stations (CSs) in mining quarries to ensure reliable radio communication for automated machinery. The BS placement is modeled as a minimum dominating set problem, solved using integer linear programming with cutting-plane methods. The CS placement is formulated as a nonlinear programming problem, addressed via a minimum circle covering algorithm. Applied in a 200 km² quarry, the approach achieves full coverage with nine BSs and one CS, minimizing costs and ensuring robust performance. Comparative analyses show superior optimality, scalability, and adaptability, offering a scalable framework for industrial communication infrastructure. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

6 pages, 2134 KB

Open AccessProceeding Paper

Modeling Energy Losses in a Wireless Sensor Network for Monitoring Environmental Parameters in a Livestock Building

by Tsvetelina Georgieva, Stanislav Penchev, Belma Gaazi, Eleonora Nedelcheva and Plamen Daskalov

Eng. Proc. 2025, 104(1), 49; https://doi.org/10.3390/engproc2025104049 - 27 Aug 2025

Viewed by 1114

Abstract

This article presents a study related to the determination of the energy losses in the nodes of a wireless sensor network during its operation. The sensor network is designed to collect real-time data on some environmental parameters in a livestock building. Measurements of [...] Read more.

This article presents a study related to the determination of the energy losses in the nodes of a wireless sensor network during its operation. The sensor network is designed to collect real-time data on some environmental parameters in a livestock building. Measurements of the charge level of the batteries powering the network nodes were carried out and models describing the process of battery discharge over time were obtained. It was found that the most suitable for describing the process of battery discharge over time is the linear model, with the coefficient of determination R² in this case varying between 0.96 and 0.99. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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7 pages, 4009 KB

Open AccessProceeding Paper

Investigation of Laser-Based Mo-Doped ZnO Nanoparticle Production and Photocatalysis Application

by Yasemin Gündoğdu Kabakcı, Serap Yiğit Gezgin and Hamdi Şükür Kılıç

Eng. Proc. 2025, 104(1), 50; https://doi.org/10.3390/engproc2025104050 - 27 Aug 2025

Viewed by 510

Abstract

One of the most sensible, economical, and ecologically friendly methods for treating wastewater is photocatalytic treatment. The most widely used and easily accessible photocatalyst for wastewater treatment is zinc oxide (ZnO). This study used laser ablation to create ZnO, Mo, and Mo-doped ZnO [...] Read more.

One of the most sensible, economical, and ecologically friendly methods for treating wastewater is photocatalytic treatment. The most widely used and easily accessible photocatalyst for wastewater treatment is zinc oxide (ZnO). This study used laser ablation to create ZnO, Mo, and Mo-doped ZnO photocatalysts. The nanoparticles were then characterized using linear absorbance, X-ray diffraction (XRD), transmission electron microscopy (TEM), high-resolution TEM scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR). The degradation of methylene blue under UV-Vis spectroscopy was used to evaluate the photocatalytic activity of the photocatalysts and the reaction’s kinetics. The Mo doping of ZnO enhanced photocatalytic degradation efficiency, according to the analytical data. This study’s 90 min photocatalytic degradation experiments showed about 94.11% methylene blue degradation efficiency. Mo-doped ZnO nanoparticle photocatalysts have a promising future for treating wastewater, according to this study, which calls for more research in this area. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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8 pages, 1728 KB

Open AccessProceeding Paper

Application of Gear Profile Shift Coefficients for Adjusting Dimensions and Assembly Conditions in AA Planetary Gear Trains

by Angel Alexandrov

Eng. Proc. 2025, 104(1), 51; https://doi.org/10.3390/engproc2025104051 - 27 Aug 2025

Viewed by 296

Abstract

This study explores the application of profile shift coefficients as a design strategy to eliminate the need for stepped planet gears in a specific type of planetary gear train, referred to as the AA gear train. By appropriately selecting gear tooth numbers and [...] Read more.

This study explores the application of profile shift coefficients as a design strategy to eliminate the need for stepped planet gears in a specific type of planetary gear train, referred to as the AA gear train. By appropriately selecting gear tooth numbers and applying compensating profile shifts to the two central gears, it is possible to equalize their diameters, enabling the use of simple single-step spur gears as planet gears. This significantly simplifies manufacturing, may improve power branching capabilities, and reduces the cost and volume. This paper outlines the geometric and functional limitations of this approach, including the practically allowable range of profile shift values and their impact on the tooth strength, contact ratio, and potential interference. Additionally, the influence of the planet count on assembly conditions and profile shift requirements is examined. The design may offer advantages in compactness and manufacturability (for moderate gear ratios) within a single stage. However, limitations in efficiency, power branching, and self-locking—especially at high ratios—must be considered. While the method provides a viable alternative to conventional stepped planet designs in certain cases, its applicability remains constrained by profile shift limitations and system-specific design compromises. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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12 pages, 2624 KB

Open AccessProceeding Paper

Designing a Remote Room Monitoring System with Arduino and BME280 Sensor

by Gergana Spasova and Iliyan Boychev

Eng. Proc. 2025, 104(1), 52; https://doi.org/10.3390/engproc2025104052 - 27 Aug 2025

Viewed by 457

Abstract

This article describes the hardware and software implementation of an application for monitoring parameters in a room. The reported values are visualized in a web application, which allows for the data to be viewed from anywhere in the world. The development made and [...] Read more.

This article describes the hardware and software implementation of an application for monitoring parameters in a room. The reported values are visualized in a web application, which allows for the data to be viewed from anywhere in the world. The development made and the sensor used allow for measuring temperature, humidity, and pressure in a room. This is of particular importance for people who work with food products, materials that are dependent on temperature conditions, for families with children who want to maintain a certain home temperature and humidity, and many others. Each parameter is of particular importance for a person’s health. All measurement data is stored in a database and can be used for statistics and analysis of changes in the room. The components used in the hardware implementation of the project are a Wi-Fi board ESP8266, Arduino UNO, and a sensor for simultaneous measurement of temperature, humidity, and pressure—BME280. The technologies used in the design of the software implementation of the project are JAVA, PHP, MySQL, Arduino IDE, hosting server, and domain name. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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10 pages, 1826 KB

Open AccessProceeding Paper

Research on the Energy Efficiency of the Wireless Sensor Network for Measurement of the Main Physicochemical Parameters of the Soil

by Tsvetelina Georgieva, Nadezhda Paskova, Eleonora Nedelcheva, Stanislav Penchev and Plamen Daskalov

Eng. Proc. 2025, 104(1), 53; https://doi.org/10.3390/engproc2025104053 - 27 Aug 2025

Viewed by 584

Abstract

This article presents a study of the energy efficiency of a wireless sensor network for measuring the main physicochemical parameters of soil. The main physicochemical parameters of soil are measured—acidity and electrical conductivity. The study on the transmission of measured data on the [...] Read more.

This article presents a study of the energy efficiency of a wireless sensor network for measuring the main physicochemical parameters of soil. The main physicochemical parameters of soil are measured—acidity and electrical conductivity. The study on the transmission of measured data on the main soil parameters is conducted through simulation, with program modules developed in the MATLAB environment. Four main protocols for data routing are studied—the LEACH (Low-Energy Adaptive Clustering Hierarchy), EAMMH (Energy-Aware Multi-Hop Multi-Path Hierarchical), SEP (Stable Election Protocol for clustered heterogeneous WSN), and TEEN (Threshold-sensitive Energy Efficient Network). The results of the main energy indicators are obtained and a comparative analysis of the two protocols is carried out. The results obtained show that the SEP and TEEN routing protocols have better performance and efficiency with respect to inactive nodes in the network compared to the other two protocols. The EAMMH and LEACH routing protocols are the best in terms of the energy consumption by sensors in the network. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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8 pages, 2553 KB

Open AccessProceeding Paper

Arduino-Based Sensor System Prototype for Microclimate Monitoring of an Experimental Greenhouse

by Ivaylo Belovski, Todor Mihalev, Elena Koleva and Aleksandar Mandadzhiev

Eng. Proc. 2025, 104(1), 54; https://doi.org/10.3390/engproc2025104054 - 27 Aug 2025

Viewed by 511

Abstract

Arduino-based sensor systems are gaining widespread adoption in modern technological applications due to their accessibility, low-cost components, diverse sensor compatibility, high reliability, and user-friendly programming. Because of these advantages, such a system was selected to monitor and control microclimate parameters in a small-scale [...] Read more.

Arduino-based sensor systems are gaining widespread adoption in modern technological applications due to their accessibility, low-cost components, diverse sensor compatibility, high reliability, and user-friendly programming. Because of these advantages, such a system was selected to monitor and control microclimate parameters in a small-scale experimental greenhouse. The greenhouse will cultivate several vegetable species in soils with varying zeolite concentrations. The aim of this paper is to present the design and prototype development of a sensor system capable of tracking key environmental parameters, including temperature, humidity, atmospheric pressure, and soil moisture, while also enabling automated irrigation. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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9 pages, 1906 KB

Open AccessProceeding Paper

Development of a Machine Learning Algorithm for Predicting Electrical Consumption

by Dimitrios Kazolis, Jacob Fantidis and Christos Dionyshs Fotakis

Eng. Proc. 2025, 104(1), 55; https://doi.org/10.3390/engproc2025104055 - 28 Aug 2025

Viewed by 1119

Abstract

In the contemporary era, the pursuit of precise predictions based on datasets is predominantly motivated by the science of computer systems. Therefore, this study attempts to further enhance prediction efforts. A city-wide electricity consumption dataset, which includes temporal and environmental characteristics, is analyzed. [...] Read more.

In the contemporary era, the pursuit of precise predictions based on datasets is predominantly motivated by the science of computer systems. Therefore, this study attempts to further enhance prediction efforts. A city-wide electricity consumption dataset, which includes temporal and environmental characteristics, is analyzed. This dataset is subjected to rigorous preprocessing to extract relevant characteristics. A wide range of machine learning models, such as XGBoost and Python’s Scikit, are used to build prediction models. These models are then rigorously trained and tuned using sophisticated optimization techniques for optimal performance. Finally, the evaluation of their efficiency, interpretability, and computational efficiency is derived. Furthermore, programming techniques are investigated, and new structures and learning methods elucidate intricate patterns and relationships in the data. This approach facilitates a more comprehensive understanding of the pivotal factors influencing electrical consumption trends and enables the identification of the most suitable methodologies for specific prediction tasks. In conclusion, the present study contributes by utilizing the knowledge gained from previous research for the advancement of predictive analysis. The findings have the potential to be useful in decision-making processes, optimizing resource allocation, and improving urban planning and management practices. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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13 pages, 6582 KB

Open AccessProceeding Paper

Development of a FATEK PLC Simulator for Industrial Processes

by Iliyan Boychev and Gergana Spasova

Eng. Proc. 2025, 104(1), 56; https://doi.org/10.3390/engproc2025104056 - 27 Aug 2025

Viewed by 1051

Abstract

In this article, the development of the software system—a virtual simulator for FATEK programmable controllers for industrial processes—is proposed. The main purpose of the development is to create a virtual tool that emulates the operation of FATEK controllers, with the primary task being [...] Read more.

In this article, the development of the software system—a virtual simulator for FATEK programmable controllers for industrial processes—is proposed. The main purpose of the development is to create a virtual tool that emulates the operation of FATEK controllers, with the primary task being the receiving and sending of data related to the controller’s resources, using the FACON communication protocol. The simulator implements a protocol that is described in the FACON documentation. The simulator works as a slave device and returns a response only to a received request from the master device (this can be any program—SCADA or HM). The communication is asynchronous, i.e., receiving messages occurs independently of the operation of the simulator itself. The simulator is implemented as a desktop GUI application using the C++ programming language and the C++ Builder platform. This simulator can be used to manage tested SCADA and HMI programs for technological processes, etc. The main part of this work is the correct reading/writing of controller memory data (inputs/outputs/memory bits and registers). Through the developed simulator, you are fully tested under conditions of impossibility of using a real programmable controller. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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7 pages, 1952 KB

Open AccessProceeding Paper

Design and Implementation of a Mobile Application for IoT-Based Autoclave Management

by Todor Todorov and Valentin Tonkov

Eng. Proc. 2025, 104(1), 57; https://doi.org/10.3390/engproc2025104057 - 28 Aug 2025

Viewed by 827

Abstract

This paper presents a case study on the integration of embedded IoT hardware with a modern Android application, demonstrated through the development of a compact autoclave system for small-scale food sterilization. The device is controlled by an ESP8266-based module and communicates securely with [...] Read more.

This paper presents a case study on the integration of embedded IoT hardware with a modern Android application, demonstrated through the development of a compact autoclave system for small-scale food sterilization. The device is controlled by an ESP8266-based module and communicates securely with a Kotlin-based Android app via MQTT using HiveMQ. The app incorporates advanced Android design patterns such as coroutines, LiveData, Navigation UI, and DataStore. Each device is uniquely addressable and fully configurable from the mobile interface. The work highlights Android’s role as a powerful interface for managing embedded IoT systems. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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11 pages, 2134 KB

Open AccessProceeding Paper

Determination of Anteroposterior and Posteroanterior Imaging Positions on Chest X-Ray Images Using Deep Learning

by Fatih Gökçimen, Alpaslan Burak İnner and Özgür Çakır

Eng. Proc. 2025, 104(1), 58; https://doi.org/10.3390/engproc2025104058 - 28 Aug 2025

Viewed by 971

Abstract

This study proposes a deep learning framework to classify anteroposterior (AP) and posteroanterior (PA) chest X-ray projections automatically. Multiple convolutional neural networks (CNNs), including ResNet18, ResNet34, ResNet50, DenseNet121, EfficientNetV2-S, and ConvNeXt-Tiny, were utilized. The NIH Chest X-ray Dataset, with 112,120 images, was used [...] Read more.

This study proposes a deep learning framework to classify anteroposterior (AP) and posteroanterior (PA) chest X-ray projections automatically. Multiple convolutional neural networks (CNNs), including ResNet18, ResNet34, ResNet50, DenseNet121, EfficientNetV2-S, and ConvNeXt-Tiny, were utilized. The NIH Chest X-ray Dataset, with 112,120 images, was used with strict patient-wise splitting to prevent data leakage. ResNet34 achieved the highest performance: 99.65% accuracy, 0.9956 F1 score, and 0.9994 ROC-AUC. Grad-CAM visualized model decisions, and expert-reviewed misclassified samples were removed to enhance dataset quality. This methodology highlights the importance of robust preprocessing, model interpretability, and clinical applicability in radiographic view classification tasks. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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12 pages, 1083 KB

Open AccessProceeding Paper

Optimization of Work Order Scheduling in Weaving Looms Using Genetic Algorithms

by Mansur Dinçer, Gökhan Uçkan and Emre Çomak

Eng. Proc. 2025, 104(1), 59; https://doi.org/10.3390/engproc2025104059 - 28 Aug 2025

Viewed by 687

Abstract

Efficient scheduling of work orders in weaving looms is crucial for improving production efficiency and meeting tight delivery deadlines in the textile industry. This study proposes a genetic algorithm (GA)-based model to optimize work order assignments, minimize type changeover durations, and balance machine [...] Read more.

Efficient scheduling of work orders in weaving looms is crucial for improving production efficiency and meeting tight delivery deadlines in the textile industry. This study proposes a genetic algorithm (GA)-based model to optimize work order assignments, minimize type changeover durations, and balance machine workloads. The model uses real-world ERP data, supports job splitting for parallel production, and dynamically classifies type changes into variant, linked warp, and full setup changes. Experimental results show significant improvements in planning time, changeover reduction, and delivery performance. The proposed GA approach offers a scalable and intelligent solution that can be readily adopted for modern textile manufacturing challenges. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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8 pages, 707 KB

Open AccessProceeding Paper

Scalable Parallel Processing: Architectural Models, Real-Time Programming, and Performance Evaluation

by Mirela Sino and Ervin Domazet

Eng. Proc. 2025, 104(1), 60; https://doi.org/10.3390/engproc2025104060 - 28 Aug 2025

Viewed by 934

Abstract

This research paper analyzes and highlights the benefits of parallel processing to enhance performance and computational efficiency in modern computing systems. It explores two primary models of parallelism—single instruction, multiple data (SIMD) and multiple instruction, multiple data (MIMD)—by examining their architectures and real-world [...] Read more.

This research paper analyzes and highlights the benefits of parallel processing to enhance performance and computational efficiency in modern computing systems. It explores two primary models of parallelism—single instruction, multiple data (SIMD) and multiple instruction, multiple data (MIMD)—by examining their architectures and real-world use cases such as artificial intelligence, image processing, and cloud computing. Special emphasis is placed on the role of parallel programming in real-time systems, with a focus on APIs such as OpenMP and Ada, which facilitate structured parallelism. To demonstrate the practical advantages of parallelism, a comparative study is presented between a parallel merge-sort algorithm and its serial counterpart. Experimental analysis across datasets ranging from 100,000 to 1,000,000 elements shows that execution time can be reduced by up to 60–70% when using eight-core parallelization compared to serial execution. These results illustrate the scalability and effectiveness of parallel processing in handling large-scale computations. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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9 pages, 1801 KB

Open AccessProceeding Paper

Prototype of an Integrated Electronic System for Increased Safety and Comfort in a Car

by Snezhinka Zaharieva, Iordan Stoev, Veselin Chobanov, Presian Enev, Adriana Borodzhieva and Yavor Neikov

Eng. Proc. 2025, 104(1), 61; https://doi.org/10.3390/engproc2025104061 - 29 Aug 2025

Viewed by 1435

Abstract

This paper presents a simulation study and development of a prototype of an integrated electronic system, specifically designed to enhance both the safety and the comfort of passengers and drivers in modern vehicles. The proposed system provides intelligent assistance during parking maneuvers by [...] Read more.

This paper presents a simulation study and development of a prototype of an integrated electronic system, specifically designed to enhance both the safety and the comfort of passengers and drivers in modern vehicles. The proposed system provides intelligent assistance during parking maneuvers by alerting the driver to nearby obstacles, and it also actively monitors the internal environment of the car cabin to detect the presence of harmful gases such as carbon monoxide, thereby improving occupant safety. In order to accomplish these objectives, a detailed functional algorithm was created and a corresponding structural scheme was designed. Simulation studies were carried out using the Tinkercad platform to validate the theoretical model and to test the behavior of the system components under realistic conditions. After a successful simulation, the physical prototype of the system was assembled and tested in a laboratory environment. The core of the system is based on the Arduino UNO microcontroller, which offers flexibility, ease of programming, and integration capabilities with various sensors and actuators. The study demonstrates the potential of low-cost microcontroller-based solutions for intelligent automotive systems focused on active safety and enhanced user experience. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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9 pages, 629 KB

Open AccessProceeding Paper

Forecasting the Operation of a Gas Turbine Unit on Hydrogen Fuel

by Ivan Beloev, Elvira Zvereva, George Marin, Iliya K. Iliev and Yuliya Valeeva

Eng. Proc. 2025, 104(1), 62; https://doi.org/10.3390/engproc2025104062 - 28 Aug 2025

Viewed by 293

Abstract

The development of hydrogen energy can significantly reduce the negative impact on the environment. For the successful implementation of hydrogen technologies, it is necessary to transform existing models of production, distribution, and consumption of both thermal and electrical energy. The processes of fuel [...] Read more.

The development of hydrogen energy can significantly reduce the negative impact on the environment. For the successful implementation of hydrogen technologies, it is necessary to transform existing models of production, distribution, and consumption of both thermal and electrical energy. The processes of fuel conversion and combustion are complex and, in some cases, insufficiently studied. A complete replacement of natural gas with hydrogen requires an assessment of energy and environmental characteristics. This study aims to evaluate the operation of a gas turbine unit when transitioning to hydrogen fuel. The GE 6FA engine was chosen as the object of study. Mathematical modeling of this engine was conducted using the software complex “AS GRET” (Automated System for Gas Dynamic Calculations of Power Turbomachinery). Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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11 pages, 2379 KB

Open AccessProceeding Paper

Comparative Analysis of Modern Robotic Demining Complexes and Development of an Automated Mission Planning Algorithm

by Yerkebulan Nurgizat, Aidos Sultan, Nursultan Zhetenbayev, Abu-Alim Ayazbay, Arman Uzbekbayev, Gani Sergazin and Kuanysh Alipbayev

Eng. Proc. 2025, 104(1), 63; https://doi.org/10.3390/engproc2025104063 - 29 Aug 2025

Viewed by 490

Abstract

This paper presents a comparative analysis of ten state-of-the-art robotic de-mining systems, grouped into (i) sensor-centric platforms for high-precision detection and (ii) rapid mechanical-contact vehicles for clearance. Building on these findings, we propose a lightweight tracked platform (~1.9 T) equipped with a four-channel [...] Read more.

This paper presents a comparative analysis of ten state-of-the-art robotic de-mining systems, grouped into (i) sensor-centric platforms for high-precision detection and (ii) rapid mechanical-contact vehicles for clearance. Building on these findings, we propose a lightweight tracked platform (~1.9 T) equipped with a four-channel sensing suite-RGB/IR camera, 32-layer LiDAR, pulsed-induction metal detector, and 2.45 GHz microwave thermography—integrated in an adaptive Bayesian “detect → confirm → neutralize” loop. The modular end-effector permits either pinpoint mechanical intervention or deployment of a linear charge. Modelling indicates an expected detection sensitivity ≥ 95% with a false-positive rate ≤ 5% in humanitarian demining mode and a clearance throughput above 1.5 ha·h⁻¹ in breaching mode. Ongoing work includes CFD analysis of the thermal front, fabrication of a prototype, and performance testing in accordance with IMAS 10.20. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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7 pages, 874 KB

Open AccessProceeding Paper

Full-Coverage Radar Antenna

by Adamantios Karakilidis, Ioannis Gavriilidis, Apostolos-Christos Tsafaras and Theodoros Kaifas

Eng. Proc. 2025, 104(1), 64; https://doi.org/10.3390/engproc2025104064 - 29 Aug 2025

Viewed by 220

Abstract

In the work at hand, we contribute a system study of a full-coverage antenna array for applications ranging from wireless communication base station transceivers to aerospace applications. There are two main objectives in the road toward achieving active, electronically scanned array antennas: the [...] Read more.

In the work at hand, we contribute a system study of a full-coverage antenna array for applications ranging from wireless communication base station transceivers to aerospace applications. There are two main objectives in the road toward achieving active, electronically scanned array antennas: the passage from mechanical to electronic steering and the subsequent accommodation of a large number of simultaneously active, independent beams and respective Tx-Rx chains. The first objective comes with the unwanted introduction of scanning losses, which degrade the system’s performance. This problem is solved in the current work by employing a toroidal array antenna and scanning the beam by exploiting the double curvature of the host surface. Furthermore, the second issue, of signal path routing complexity, is also resolved by the contributed 2D, hierarchical (exhibiting both horizontal and vertical organization) beam-forming network. The stated results successfully validate our contribution. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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11 pages, 2758 KB

Open AccessProceeding Paper

Cyber-Physical System for Treatment of River and Lake Water

by Diana Syulekchieva, Blagovesta Midyurova, Aleksandar Mandadzhiev, Ivaylo Belovski, Todor Mihalev and Elena Koleva

Eng. Proc. 2025, 104(1), 65; https://doi.org/10.3390/engproc2025104065 - 29 Aug 2025

Viewed by 719

Abstract

Water plays a fundamental role in sustaining biological processes, ecological functions, and economic systems. However, the progressive pollution of water sources compromises these functions, posing significant threats to water purity, human well-being, and environmental sustainability. Human activities, such as industrial waste, agriculture, and [...] Read more.

Water plays a fundamental role in sustaining biological processes, ecological functions, and economic systems. However, the progressive pollution of water sources compromises these functions, posing significant threats to water purity, human well-being, and environmental sustainability. Human activities, such as industrial waste, agriculture, and urbanization, alongside natural processes, are major contributors to the deterioration of surface water quality, which in turn leads to environmental and economic risks. The decline in water quality results in issues such as waterborne diseases, loss of biodiversity, and a shortage of clean water for consumption and industrial use. This paper emphasizes the critical need for maintaining good water quality and the importance of implementing effective strategies for the removal of physical, chemical, and biological contaminants. In response, this work presents an intelligent embedded system (electronic control unit, ECU) developed as part of a modular filtration system designed to improve surface water quality, provide more precise water analyses, and perform tests within a controlled environment. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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16 pages, 2102 KB

Open AccessProceeding Paper

Comparative Analysis of Symmetric Cryptographic Algorithms and Cryptanalysis Methods Through a Practical Software Tool for Educational Purposes

by Diyan Dinev and Venelin Maleshkov

Eng. Proc. 2025, 104(1), 66; https://doi.org/10.3390/engproc2025104066 - 28 Aug 2025

Viewed by 546

Abstract

This paper presents the design and evaluation of an educational software tool aimed at facilitating the practical exploration of symmetric cryptographic algorithms. The application integrates widely used algorithms, including AES, DES, TripleDES, RC2, Blowfish, Twofish, and Camellia, allowing users to perform encryption, decryption, [...] Read more.

This paper presents the design and evaluation of an educational software tool aimed at facilitating the practical exploration of symmetric cryptographic algorithms. The application integrates widely used algorithms, including AES, DES, TripleDES, RC2, Blowfish, Twofish, and Camellia, allowing users to perform encryption, decryption, and cryptanalysis via dictionary and brute-force attacks. It provides performance benchmarking by measuring encryption and decryption speed, computational overhead, throughput, and resistance to attacks. Visual elements such as real-time charts and histograms aid in comparing algorithmic behavior. The tool is tailored for educational use, supporting cybersecurity and computer science students in understanding cryptographic principles, algorithm effectiveness, and cryptanalytic techniques. Its goal is to bridge theory and practice in a user-friendly and interactive manner, promoting deeper engagement with modern cryptographic methods. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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8 pages, 852 KB

Open AccessProceeding Paper

Method for Measuring Soil Density by Assessing the Surface Tension in the Plough Stem

by Asparuh Atanasov and Aleksandrina Bankova

Eng. Proc. 2025, 104(1), 67; https://doi.org/10.3390/engproc2025104067 - 1 Sep 2025

Viewed by 700

Abstract

Introduced in the present study is a novel method for measuring soil density during standard tillage operations. The methodology involves the use of a strain gauge to measure the surface tensions of the plough body stem, reflecting the resistance force in the soil, [...] Read more.

Introduced in the present study is a novel method for measuring soil density during standard tillage operations. The methodology involves the use of a strain gauge to measure the surface tensions of the plough body stem, reflecting the resistance force in the soil, through which the calculation of the density becomes feasible. The sensor is conveniently mounted above the contact area with the soil, allowing for easy replacement as required. Due to the small forces of surface deformation in the metal, a weight sensor with a capacity of 300 grams is used. The measurement process is continuous, and all plough bodies can be equipped with sensors. The results obtained demonstrate a high level of accuracy, with a Multiple R = 0.95 and R Square = 0.90 compared to tests conducted with a standard penetrometer, confirming the effectiveness and appropriateness of the proposed method. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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8 pages, 743 KB

Open AccessProceeding Paper

A Prototype of Integrated Remote Patient Monitoring System

by Georgi Patrikov, Teodora Bakardjieva, Antonina Ivanova, Andriana Ivanova and Fatima Sapundzhi

Eng. Proc. 2025, 104(1), 68; https://doi.org/10.3390/engproc2025104068 - 29 Aug 2025

Viewed by 421

Abstract

The ongoing global shortage of healthcare personnel, exacerbated by demographic changes and the aftermath of the COVID-19 pandemic, has highlighted the need for efficient workforce utilization and innovative technological support in healthcare. This paper presents LifeLink Monitoring, a prototype of an integrated remote [...] Read more.

The ongoing global shortage of healthcare personnel, exacerbated by demographic changes and the aftermath of the COVID-19 pandemic, has highlighted the need for efficient workforce utilization and innovative technological support in healthcare. This paper presents LifeLink Monitoring, a prototype of an integrated remote patient monitoring system designed to optimize clinical workflows, support medical personnel, and enhance patient care without replacing human expertise. The system enables real-time patient observation through AI-powered devices, providing automated alerts, live video feeds, and intelligent task management to reduce the burden of non-clinical duties on healthcare professionals. Applications include hospitals, hospices, home care, and remote locations. Key features include seamless integration with medical devices and national health records, advanced computer vision and audio analysis, multi-level deployment models, and a blockchain-secured architecture ensuring high data privacy and cybersecurity standards. Additionally, LifeLink incorporates an entertainment module aimed at improving patient emotional well-being. The solution represents a convergence of artificial and human intelligence to improve healthcare delivery, personnel efficiency, and patient outcomes. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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10 pages, 1396 KB

Open AccessProceeding Paper

Wireless Power Harvesting Skin

by Ioannis Gavriilidis, Adamantios Karakilidis, Apostolos-Christos Tsafaras and Theodoros Kaifas

Eng. Proc. 2025, 104(1), 69; https://doi.org/10.3390/engproc2025104069 - 29 Aug 2025

Viewed by 236

Abstract

Contributing to the quest for renewable energy harvesting, we present, in the work at hand, a conceptual model of a large-scale wireless microwave power harvester that takes the structure of a smart reconfigurable harvesting surface. This structure is assembled by numerous elementary harvesters [...] Read more.

Contributing to the quest for renewable energy harvesting, we present, in the work at hand, a conceptual model of a large-scale wireless microwave power harvester that takes the structure of a smart reconfigurable harvesting surface. This structure is assembled by numerous elementary harvesters that, as a whole, present both wide solid angle coverage and high receiving antenna gain. This is achieved by employing two levels of organization, both in the horizontal and in the vertical planes. The horizontal plane, which is the host receiving surface, is tiled by employing square radiators and forms hierarchical subarray structures. At the same time, hieratical structures are also employed in the vertical plane where the beamforming network collects the received power in a drainage-basin fashion (one receiving port is fed by its assigned and also its neighboring antenna elements) achieving, in this way, increased efficiency. The presented results verify the contributed design. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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14 pages, 2389 KB

Open AccessProceeding Paper

Obtaining a Digital Twin of Systems via Approximation with DNN and Kautz Functions

by Georgi Mihalev

Eng. Proc. 2025, 104(1), 70; https://doi.org/10.3390/engproc2025104070 - 29 Aug 2025

Viewed by 144

Abstract

This paper proposes a hybrid architecture for obtaining digital twins of dynamic systems under conditions of parametric uncertainties and unmodeled dynamics through approximation using deep neural networks (DNNs) and orthonormal Kautz functions. In the classical framework of digital twin operation based on supervised [...] Read more.

This paper proposes a hybrid architecture for obtaining digital twins of dynamic systems under conditions of parametric uncertainties and unmodeled dynamics through approximation using deep neural networks (DNNs) and orthonormal Kautz functions. In the classical framework of digital twin operation based on supervised machine learning, orthonormal Kautz functions are used to approximate systems with real and complex poles, thereby extending the applicability of the approach. A DNN architecture has been developed for extracting the decomposition coefficients, ensuring high accuracy even in the presence of noise and parameter variations. The proposed method has been tested and validated using both simulation and experimental data. The data were obtained from a real electrohydraulic system via a measurement and control setup. Graphical results are presented, confirming the high accuracy and practical applicability of Kautz functions in the digital twin structure. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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15 pages, 1646 KB

Open AccessProceeding Paper

Software Application for Automated Evaluation and Selection of a Rational Technological Process

by Teodora Peneva, Tanya Avramova and Plamen Georgiev

Eng. Proc. 2025, 104(1), 71; https://doi.org/10.3390/engproc2025104071 - 25 Aug 2025

Viewed by 149

Abstract

In the conditions of modern production, the choice of a rational technological process is crucial for the competitiveness and efficiency of enterprises. Traditional decision-making methods are often accompanied by subjectivity and insufficient precision, which determines the need for the implementation of modern information [...] Read more.

In the conditions of modern production, the choice of a rational technological process is crucial for the competitiveness and efficiency of enterprises. Traditional decision-making methods are often accompanied by subjectivity and insufficient precision, which determines the need for the implementation of modern information technologies. This paper addresses the selection of an optimal technological process through the application of a developed web-based software application. The software application integrates an algorithm in which a multi-criteria decision-making (MCDM) method—FUCOM (Full Consistency Method)—is implemented, which allows the evaluation and comparison of alternative technological processes according to criteria such as price, time to produce, accuracy, roughness, shape deviation, etc. To confirm the effectiveness of the application, real production data is used, and the results show a significant reduction in time and subjectivity in decision-making. The developed application can be successfully implemented in enterprises of different industries, contributing to the increase in the efficiency of production processes and the optimization of resources. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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13 pages, 2852 KB

Open AccessProceeding Paper

A Reduced Reaction Model for Combustion of n-Pentanol

by Jaime Tiburcio-Cortés, Juan C. Prince and Asunción Zárate

Eng. Proc. 2025, 104(1), 72; https://doi.org/10.3390/engproc2025104072 - 3 Sep 2025

Viewed by 241

Abstract

n-Pentanol, a promising biofuel, can reduce greenhouse gas emissions while remaining compatible with internal combustion engines. We present a reduced kinetic mechanism comprising 66 species and 292 reactions that captures both high- and low-temperature ignition and flame propagation dynamics for this fuel. The [...] Read more.

n-Pentanol, a promising biofuel, can reduce greenhouse gas emissions while remaining compatible with internal combustion engines. We present a reduced kinetic mechanism comprising 66 species and 292 reactions that captures both high- and low-temperature ignition and flame propagation dynamics for this fuel. The mechanism, developed by integrating a detailed n-pentanol sub-mechanism with the San Diego mechanism and applying sensitivity and steady-state approximations criteria as reduction strategies, accurately reproduces key phenomena, including the negative temperature coefficient behavior (NTC). Validation against experimental data for ignition delay times, laminar flame speeds, and speciation measurements in a jet-stirred reactor confirms its predictive capability across a wide range of conditions. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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6 pages, 2229 KB

Open AccessProceeding Paper

Investigation of Methods for Generating Smooth Continuous Curves Resulting from the Intersection of Conical Surfaces

by Zoya Tsoneva

Eng. Proc. 2025, 104(1), 73; https://doi.org/10.3390/engproc2025104073 - 3 Sep 2025

Viewed by 305

Abstract

Studied extensively in the present paper is a geometric problem related to the intersection of two conical surfaces with crossed axes. The goal was to derive a spatial intersection curve between the surfaces that resembles the classical Viviani curve but is defined as [...] Read more.

Studied extensively in the present paper is a geometric problem related to the intersection of two conical surfaces with crossed axes. The goal was to derive a spatial intersection curve between the surfaces that resembles the classical Viviani curve but is defined as the inter-section of two rotational conical surfaces with crossed axes, forming an asymmetric spatial figure-of-eight shape. These unique spatial curves, as variations of the Viviani curve, possess intriguing geometric properties and are likely to have a wide range of potential applications in the fields of construction and engineering. Their presence can often be linked to the development of complex geometric shapes in architecture, particularly in the design of bridges with unconventional curves in their support structures or situations where inclined support beams intersect with other structural components. They are commonly employed in the construction of tunnels with conical and cylindrical shapes, in addition to various types of vaults and domes. These curves are critical in optimizing structures, such as roofs with intricate geometries or decorative façade elements, and can greatly enhance both their stability and aesthetic appeal. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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8 pages, 1167 KB

Open AccessProceeding Paper

Assessing Musculoskeletal Health Risks in Standing Occupations

by Valentina Markova, Zornitsa Petrova and Ivalena Valcheva-Georgieva

Eng. Proc. 2025, 104(1), 74; https://doi.org/10.3390/engproc2025104074 - 3 Sep 2025

Viewed by 288

Abstract

This study investigates the risk of developing musculoskeletal disorders (MSDs) in individuals performing standing tasks, with a focus on real-time posture assessment using motion capture technology. Improper body posture and repetitive movements during daily work activities can impose strain on the musculoskeletal system, [...] Read more.

This study investigates the risk of developing musculoskeletal disorders (MSDs) in individuals performing standing tasks, with a focus on real-time posture assessment using motion capture technology. Improper body posture and repetitive movements during daily work activities can impose strain on the musculoskeletal system, increasing the likelihood of discomfort and long-term injury. Data were collected from five male and female participants using the Perception Neuron motion capture system, with body-mounted sensors tracking posture and movement. Joint angles were calculated to distinguish between correct and incorrect postures based on ISO 11226:2000 ergonomic guidelines. Key physical risk factors identified included prolonged forward trunk inclination, elevated arm positions, and repetitive actions. The analysis revealed that participants frequently adopted moderate- to high-risk postures, especially when working at non-ergonomic desk heights, suggesting a heightened risk of MSDs such as back and upper limb pain. These findings underscore the importance of real-time ergonomic monitoring and adaptive workstation design to reduce musculoskeletal risks in standing work environments. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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13 pages, 2482 KB

Open AccessProceeding Paper

Applied Methods for Designing Developments of Composite Transition Surfaces from Sheet Material for Industrial and Construction Purposes

by Zoya Tsoneva, Sonya Vachinska, Prolet Deneva and Plamen Parushev

Eng. Proc. 2025, 104(1), 75; https://doi.org/10.3390/engproc2025104075 - 3 Sep 2025

Viewed by 221

Abstract

This paper explores construction and modelling methods used to create composite transition surfaces from sheet material, with an emphasis on the fabrication of their developments. The main objective is to present effective approaches for generating developments that ensure precision in the design of [...] Read more.

This paper explores construction and modelling methods used to create composite transition surfaces from sheet material, with an emphasis on the fabrication of their developments. The main objective is to present effective approaches for generating developments that ensure precision in the design of transition surfaces for a variety of industrial applications. The geometric aspects of designing diverse transitional forms are fully examined, along with optimisation opportunities in the design of their developments through the use of modern CAD technologies. Practical examples and theoretical analysis highlight the key factors with significant impact on the quality and efficiency in the design of composite transition surfaces made from sheet material in the context of modern industrial production and construction. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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11 pages, 1535 KB

Open AccessProceeding Paper

Automated Control of Dynamic Loads in Drive Systems

by Alina Fazylova, Kuanysh Alipbayev, Teodor Iliev and Alisher Aden

Eng. Proc. 2025, 104(1), 76; https://doi.org/10.3390/engproc2025104076 - 4 Sep 2025

Viewed by 812

Abstract

This article discusses the automated control of dynamic loads in drive systems using the example of a wind turbine screw drive. A mathematical model was developed, including differential equations of system motion, the voltage balance of the electric motor, and transfer functions of [...] Read more.

This article discusses the automated control of dynamic loads in drive systems using the example of a wind turbine screw drive. A mathematical model was developed, including differential equations of system motion, the voltage balance of the electric motor, and transfer functions of the control system. The Laplace transform was applied to obtain the system’s frequency and time characteristics. Numerical calculations and simulation results are presented, demonstrating the system’s stability and the effectiveness of the proposed control method. The generated amplitude–frequency and transient response graphs confirm the system’s operability. The proposed approach enhances the reliability of the screw drive, reduces mechanical loads, and extends the equipment’s service life. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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13 pages, 3205 KB

Open AccessProceeding Paper

Overview of Memory-Efficient Architectures for Deep Learning in Real-Time Systems

by Bilgin Demir, Ervin Domazet and Daniela Mechkaroska

Eng. Proc. 2025, 104(1), 77; https://doi.org/10.3390/engproc2025104077 - 4 Sep 2025

Viewed by 660

Abstract

With advancements in artificial intelligence (AI), deep learning (DL) has become crucial for real-time data analytics in areas like autonomous driving, healthcare, and predictive maintenance; however, its computational and memory demands often exceed the capabilities of low-end devices. This paper explores optimizing deep [...] Read more.

With advancements in artificial intelligence (AI), deep learning (DL) has become crucial for real-time data analytics in areas like autonomous driving, healthcare, and predictive maintenance; however, its computational and memory demands often exceed the capabilities of low-end devices. This paper explores optimizing deep learning architectures for memory efficiency to enable real-time computation in low-power designs. Strategies include model compression, quantization, and efficient network designs. Techniques such as eliminating unnecessary parameters, sparse representations, and optimized data handling significantly enhance system performance. The design addresses cache utilization, memory hierarchies, and data movement, reducing latency and energy use. By comparing memory management methods, this study highlights dynamic pruning and adaptive compression as effective solutions for improving efficiency and performance. These findings guide the development of accurate, power-efficient deep learning systems for real-time applications, unlocking new possibilities for edge and embedded AI. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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8 pages, 2108 KB

Open AccessProceeding Paper

Development of a Software Tool for Hall Parameter Evaluation in Semiconductor Structures

by Gergana Mironova and Goran Goranov

Eng. Proc. 2025, 104(1), 78; https://doi.org/10.3390/engproc2025104078 - 4 Sep 2025

Viewed by 507

Abstract

The Hall effect is widely used in magnetic field sensors and contactless measurement systems. Accurate modeling of Hall-effect elements is essential for optimizing performance, especially in high-sensitivity applications under controlled conditions like vacuum. This paper introduces a graphical software tool for calculating key [...] Read more.

The Hall effect is widely used in magnetic field sensors and contactless measurement systems. Accurate modeling of Hall-effect elements is essential for optimizing performance, especially in high-sensitivity applications under controlled conditions like vacuum. This paper introduces a graphical software tool for calculating key electrical parameters of Hall elements, such as Hall voltage, Hall coefficient, and carrier mobility. Users can input variables like semiconductor thickness, current, and magnetic field, with built-in models for materials like silicon, germanium, and gallium arsenide. Designed for vacuum operation, the tool supports simulation-based analysis, aiding researchers and educators in understanding and evaluating Hall-effect devices. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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7 pages, 561 KB

Open AccessProceeding Paper

Hybrid 3D Mesh Reconstruction Models of CT Images for Deep Learning Based Classification of Kidney Tumors

by Muhammed Ahmet Demirtaş, Alparslan Burak İnner and Adnan Kavak

Eng. Proc. 2025, 104(1), 79; https://doi.org/10.3390/engproc2025104079 - 4 Sep 2025

Viewed by 285

Abstract

We present a comparative analysis of three hybrid methodologies for transforming 3D kidney tumor segmentations of volumetric NIfTI data into highly accurate network representations. Exploiting the KiTS23 dataset, we evaluate edge-preserving reconstruction pipelines integrating anisotropic diffusion, multiscale Gaussian filtering and KNN-based network optimisation. [...] Read more.

We present a comparative analysis of three hybrid methodologies for transforming 3D kidney tumor segmentations of volumetric NIfTI data into highly accurate network representations. Exploiting the KiTS23 dataset, we evaluate edge-preserving reconstruction pipelines integrating anisotropic diffusion, multiscale Gaussian filtering and KNN-based network optimisation. Model 1 uses Gaussian smoothing with Marching Cubes, while Model 2 uses spline interpolation and Perona-Malik filtering for improved resolution. Model 3 extends this structure with normal sensitive vertex smoothing to preserve critical anatomical interfaces. Quantitative metrics (Dice score, HD₉₅) demonstrated the advantage of Model 3, which achieved a 22% reduction in the Hausdorff distance error rate compared to conventional methods while maintaining segmentation accuracy (Dice > 0.92). The proposed unsupervised pipeline bridges the gap between clinical interpretability and computational accuracy, providing a robust infrastructure for further applications in surgical planning and deep learning-based classification. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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17 pages, 3051 KB

Open AccessProceeding Paper

Review and Comparative Analysis of Modern Knee Prostheses with Development of a Conceptual Design

by Akhmejanov Sayat, Zhetenbayev Nursultan, Nurgizat Yerkebulan, Sultan Aidos, Uzbekbayev Arman, Sergazin Gani, Ozhikenov Kassymbek and Nurmangaliyev Asset

Eng. Proc. 2025, 104(1), 80; https://doi.org/10.3390/engproc2025104080 - 4 Sep 2025

Viewed by 357

Abstract

This paper provides a comprehensive review of the structural features and biomechanical functions of modern passive and semi-active knee prostheses, followed by comparative analysis. Based on findings from scientific literature and engineering practice, a new conceptual knee prosthesis was developed using a modular [...] Read more.

This paper provides a comprehensive review of the structural features and biomechanical functions of modern passive and semi-active knee prostheses, followed by comparative analysis. Based on findings from scientific literature and engineering practice, a new conceptual knee prosthesis was developed using a modular design approach. The proposed structure was modeled in SolidWorks, and its kinematic behavior and structural integrity were quantitatively evaluated through finite element analysis (FEA). The knee module was specifically designed to integrate with previously developed ankle and foot prosthetic components via an adapter interface. This modular approach allows the prosthesis to be configured according to the individual clinical needs of the patient. Simulation results confirmed that the proposed design meets the requirements for motion accuracy and structural reliability. In future work, the physical prototype will be manufactured using 3D printing with PLA plastic as an initial test material, followed by fabrication with high-strength engineering plastics or metal alloys. This study represents a critical early step toward the development of a fully functional, adaptive lower-limb prosthetic system. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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13 pages, 2651 KB

Open AccessProceeding Paper

Automatic Evaluation Visual Characteristics of Corn Snacks Using Computer Vision

by Angel Danev, Atanaska Bosakova-Ardenska, Radoslava Gabrova and Hristina Andreeva

Eng. Proc. 2025, 104(1), 81; https://doi.org/10.3390/engproc2025104081 - 5 Sep 2025

Viewed by 4503

Abstract

The process of extrusion is a part of many modern manufacturing technologies that are applied in various industrial productions. In the food industry, the process of extrusion is used to produce popular foods such as cereal mixes, confectionery products, pet foods, etc. The [...] Read more.

The process of extrusion is a part of many modern manufacturing technologies that are applied in various industrial productions. In the food industry, the process of extrusion is used to produce popular foods such as cereal mixes, confectionery products, pet foods, etc. The advantages of extrusion technology are continuously applied in many studies in order to develop foods with more significant functional properties that could be produced in a time-effective and cost-effective way. In recent years, computer vision has become one of the preferred technologies in the development of new methods for quality control of food product production. This paper proposes a system for the evaluation of the quality parameters of extruded foods using a computer vision method. This system combines hardware and software modules that are developed for the discussed topic. A justification of the proposed system is provided on the basis of an experiment using extruded corn snacks made with different ingredients. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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20 pages, 8118 KB

Open AccessProceeding Paper

Effective Electromagnetic Models for the Design of Axial Flux Permanent Magnet Generators in Wind Power

by Hung Vu Xuan and Vinh Nguyen Trong

Eng. Proc. 2025, 104(1), 82; https://doi.org/10.3390/engproc2025104082 - 8 Sep 2025

Viewed by 2323

Abstract

Axial flux permanent magnet (AFPM) machines offer some advantages over conventional radial flux machines for the case of a limited space in the axial direction, such as high torque density, compact structure, and modular design ability. They, therefore, are increasingly used in wind [...] Read more.

Axial flux permanent magnet (AFPM) machines offer some advantages over conventional radial flux machines for the case of a limited space in the axial direction, such as high torque density, compact structure, and modular design ability. They, therefore, are increasingly used in wind power and electrical vehicles. This paper focuses on developing an effective analytical model and equivalent auto-finite element method (FEM), including rotor linear motion for the design of axial flux permanent magnet generators in vertical axis wind turbines. The initial design of a 1.35 kW-AFPM generator with an outer double rotor and double layer concentrated windings is based on analytical equations, and then it is refined using equivalent time-stepping transient FEM, including rotor linear motion to calculate voltage, electromagnetic force, and torque. The automatic generation of an equivalent transient 2D-FEM model to replace a time-consuming 3D-FEM model is investigated. As a consequence, the influence of slotting the effect on a 1.35 kW-AFPM machine’s performances, such as air gap flux density, internal voltage, and cogging torque, is announced. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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6 pages, 918 KB

Open AccessProceeding Paper

Prediction of Torque Arm Fatigue Life by Fuzzy Logic Method

by Caner Baybaş, Mustafa Acarer and Fevzi Doğaner

Eng. Proc. 2025, 104(1), 83; https://doi.org/10.3390/engproc2025104083 - 7 Sep 2025

Viewed by 3672

Abstract

In this study, a fuzzy-logic-based decision support model is developed to predict the fatigue life of load-bearing system elements such as torque arm. Traditional methods for fatigue life prediction are mostly based on certain mathematical expressions and fixed parameters and do not adequately [...] Read more.

In this study, a fuzzy-logic-based decision support model is developed to predict the fatigue life of load-bearing system elements such as torque arm. Traditional methods for fatigue life prediction are mostly based on certain mathematical expressions and fixed parameters and do not adequately take into account the uncertainties caused by many factors such as material structure, surface condition, loading pattern and heat treatment. In order to overcome these deficiencies, the fuzzy logic method is preferred. The model is based on a fuzzy logic system and predicts outputs according to specific input conditions using rules derived from expert knowledge and experience. The input parameters of the model are material type, surface hardness, maximum applied stress level, and type of heat treatment. Although these parameters can be expressed numerically in the classical sense, the relationship between them is often imprecise and based on experience and engineering interpretation. Therefore, a more realistic and flexible prediction model has been created with the linguistic variables and rule-based approach of fuzzy logic. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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8 pages, 1451 KB

Open AccessProceeding Paper

Development of a System for Flexible Feeding of Parts with Robot and Machine Vision

by Penko Mitev

Eng. Proc. 2025, 104(1), 84; https://doi.org/10.3390/engproc2025104084 - 6 Sep 2025

Viewed by 1757

Abstract

This article presents a design solution for feeding cylindrical parts with axial orientation. A working algorithm was developed to control and synchronize the main components, which was verified via a simulation. The pneumatic and electrical circuits were designed using a software platform for [...] Read more.

This article presents a design solution for feeding cylindrical parts with axial orientation. A working algorithm was developed to control and synchronize the main components, which was verified via a simulation. The pneumatic and electrical circuits were designed using a software platform for engineering purposes. Based on the CAD project created, a real prototype was built. The energy consumption of the system was tested and evaluated. The results from the prototype verified the solution. This article emphasizes the use of specific sensors for detecting part orientation and their role in improving process reliability. The system is suitable for industrial implementation due to its functionality, stable operation, low energy consumption, and ability to be integrated into automated production systems. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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8 pages, 1371 KB

Open AccessProceeding Paper

Design of a Forklift Hydraulic System with Unloading Valves for Load Handling

by Yordan Stoyanov, Atanasi Tashev and Penko Mitev

Eng. Proc. 2025, 104(1), 85; https://doi.org/10.3390/engproc2025104085 - 6 Sep 2025

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Abstract

This paper presents the design and analysis of a forklift hydraulic system utilizing an open-center configuration equipped with unloading (safety-overflow) valves and an emergency lowering mechanism. The hydraulic system includes an external gear pump, double-acting power cylinders, hydraulic distributors, and control valves. A [...] Read more.

This paper presents the design and analysis of a forklift hydraulic system utilizing an open-center configuration equipped with unloading (safety-overflow) valves and an emergency lowering mechanism. The hydraulic system includes an external gear pump, double-acting power cylinders, hydraulic distributors, and control valves. A comprehensive approach is undertaken to select system components based on catalog data and to model the flow rate, required torque, and power characteristics of the pump, along with load handling performance as a function of cylinder dimensions and hydraulic pressure. System behavior under various operating conditions is simulated using Automation Studio, enabling performance optimization and fault response assessment. The inclusion of unloading valves and an emergency button enhances system safety by enabling controlled pressure relief and emergency actuation. The impact of thermal effects, filter efficiency, and reservoir design on hydraulic fluid integrity is also addressed. This study aims to improve reliability, efficiency, and safety in hydraulic forklift systems while supporting informed design decisions using simulation-driven methodologies. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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12 pages, 1156 KB

Open AccessProceeding Paper

Energetic Analysis for the Improvement of a Cupola Furnace

by Axel Vargas Sánchez, Ricardo Galindo Bulos, Juan C. Prince, Asunción Zárate and Miguel A. Gijón

Eng. Proc. 2025, 104(1), 86; https://doi.org/10.3390/engproc2025104086 - 6 Sep 2025

Viewed by 1866

Abstract

Cupola furnaces rank among the oldest melting technologies in steelmaking, relying predominantly on coke as the primary fuel. In this study, a detailed energy analysis was conducted on a cupola unit used for gray and ductile iron production. Energy and thermal analyses were [...] Read more.

Cupola furnaces rank among the oldest melting technologies in steelmaking, relying predominantly on coke as the primary fuel. In this study, a detailed energy analysis was conducted on a cupola unit used for gray and ductile iron production. Energy and thermal analyses were performed on the furnace to improve efficiency and minimize energy losses in the system. Computational simulations with an equation solving program quantified an exhaust-gas heat loss of 1.5 Gigajoules. To recover this waste heat, a heat exchanger was proposed to preheat the incoming combustion air. Numerical simulations of the modified system demonstrate a 3% increase in overall furnace efficiency and a reduction of about ten percent of coke per charge, equivalent to 716 kg per day for the unit under evaluation. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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8 pages, 1554 KB

Open AccessProceeding Paper

Magnetic Nanoparticles for Toxic Wastewater Cleaning:Experimental Study on Phenol

by Lacramioara Oprica, Larisa Popescu-Lipan, Liviu Sacarescu, Mihai Costache, Cosmin Hincu and Dorina Creanga

Eng. Proc. 2025, 104(1), 87; https://doi.org/10.3390/engproc2025104087 - 6 Sep 2025

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Abstract

This study focuses on the possibility of cleaning of industrial wastewater with catalytically active magnetic nanoparticles. Cobalt ferrite synthesized by the co-precipitation method was used, as prepared or after surface modification with a silica precursor. Electronic absorption spectra were recorded and analyzed to [...] Read more.

This study focuses on the possibility of cleaning of industrial wastewater with catalytically active magnetic nanoparticles. Cobalt ferrite synthesized by the co-precipitation method was used, as prepared or after surface modification with a silica precursor. Electronic absorption spectra were recorded and analyzed to obtain the phenol degrading rate for various experimental design variants. Treating with pristine magnetic nanoparticles under simultaneous exposure to ultraviolet radiation resulted in similar degrading rates for 4 g/L and 8 g/L pristine nanoparticles, while, for silanized nanoparticles, the degrading rates were slightly increased. Along with ultraviolet irradiation and magnetic nanoparticles, hydrogen peroxide was also added, which led to significant enhancement of phenol degradation, for both pristine and silanized nanoparticles. It is proposed that photo-Fenton processes, triggered by metal ions at the nanoparticle surface and water photolysis and sustained by hydrogen peroxide decomposition, occurred to gradually decompose phenol to simpler compounds. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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7 pages, 831 KB

Open AccessProceeding Paper

Modeling the Thermal State of a Wind Turbine Generator Considering External Factors

by Alina Fazylova, Yaroslav Napadailo, Galina V. Rybina, Baurzhan Tultayev, Teodor Iliev and Ivaylo Stoyanov

Eng. Proc. 2025, 104(1), 88; https://doi.org/10.3390/engproc2025104088 - 8 Sep 2025

Viewed by 1657

Abstract

This paper presents the mathematical modeling of the thermal state of a 1000 W wind turbine generator (WTG) integrated into a vertical-axis wind turbine (VAWT) system, taking into account external environmental factors, mechanical losses, and the operation of the cooling system. The developed [...] Read more.

This paper presents the mathematical modeling of the thermal state of a 1000 W wind turbine generator (WTG) integrated into a vertical-axis wind turbine (VAWT) system, taking into account external environmental factors, mechanical losses, and the operation of the cooling system. The developed model considers the influence of ambient temperature, wind speed, air humidity, ventilation openings, radiator cooling, and mechanical losses. An analysis was conducted over a range of operating conditions from −20 °C to 50 °C, with wind speeds from 0.5 m/s to 15 m/s and air humidity from 10% to 90%. The nonlinear dependence of the winding temperature on these factors was investigated, and critical operating conditions leading to potential overheating were identified. It was found that high humidity (>70%) increases the winding temperature by 5–10% compared to low humidity (<30%). The developed model can be used to optimize cooling systems and improve the reliability of wind turbines in various climatic conditions. In addition, the proposed model is intended to be integrated into fault detection and diagnosis systems for wind turbines, enabling the identification of potential faults related to thermal overload. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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7 pages, 367 KB

Open AccessProceeding Paper

Developing a Portal for Learning Relational Databases with Automatic SQL Validation

by Natalia Spiridonova, Ekaterina Andrianova, Eugenia Rezedinova and Alexander Schukin

Eng. Proc. 2025, 104(1), 89; https://doi.org/10.3390/engproc2025104089 - 8 Sep 2025

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Abstract

Databases are essential to modern information systems, ensuring reliable and structured data storage. PostgreSQL, a leading database management system, ranked fourth globally in 2022 and offers advantages such as free access and cross-platform compatibility. This research focuses on developing educational materials for learning [...] Read more.

Databases are essential to modern information systems, ensuring reliable and structured data storage. PostgreSQL, a leading database management system, ranked fourth globally in 2022 and offers advantages such as free access and cross-platform compatibility. This research focuses on developing educational materials for learning PostgreSQL through a contemporary electronic resource. Utilizing technologies like React, Node.js, and Express, the project aims to create functional test databases and a server-side component for an interactive learning platform. Key tasks include studying relevant technologies, preparing learning materials, developing a student evaluation system, and designing test database structures. The project ultimately seeks to enhance database programming education and promote exploration of modern development technologies. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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7 pages, 394 KB

Open AccessProceeding Paper

An Approach to Prediction Using Networked Multimedia

by Vladislav Hinkov and Georgi Krastev

Eng. Proc. 2025, 104(1), 90; https://doi.org/10.3390/engproc2025104090 - 8 Sep 2025

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Abstract

One of the tasks of statistical analysis is related to the development of forecasts with different horizons. The results of modeling the development trend can also be used for prognostic purposes. At the same time, the assumption is made that during the forecast [...] Read more.

One of the tasks of statistical analysis is related to the development of forecasts with different horizons. The results of modeling the development trend can also be used for prognostic purposes. At the same time, the assumption is made that during the forecast period, the phenomenon under study will exhibit the same patterns of development that it exhibited during the base period. Network multimedia is a unifying link in the parallel development of multimedia and communication technologies. The integrated interaction of technological solutions in the field of multimedia and computer networks is a condition for achieving a greater final application effect in the presentation of information. Experimental studies of modern network multimedia in operational conditions are important for revealing bottlenecks in their functioning. On this basis, recommendations can be made to improve performance indicators, such as performance, reliability, mode of service, etc. This publication is devoted to the experimental study of the trend and the possibility of predicting network multimedia with time series. The implemented algorithm for automated trend determination examines pre-set different trends–linear, quadratic, cubic, hyperbolic, fractional-rational, logarithmic, exponential, exponential, combined–and chooses the most effective of them. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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20 pages, 2230 KB

Open AccessProceeding Paper

Synthesis and Analysis of Active Filters Using the Multi-Loop Negative Feedback Method

by Adriana Borodzhieva and Snezhinka Zaharieva

Eng. Proc. 2025, 104(1), 91; https://doi.org/10.3390/engproc2025104091 - 9 Sep 2025

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Abstract

This paper offers a comprehensive methodology for the synthesis and analysis of active filters, including low-pass, high-pass, and band-pass configurations, utilizing operational amplifiers and multi-loop negative feedback systems. The approach involves deriving explicit analytical expressions for the design and optimization of eight distinct [...] Read more.

This paper offers a comprehensive methodology for the synthesis and analysis of active filters, including low-pass, high-pass, and band-pass configurations, utilizing operational amplifiers and multi-loop negative feedback systems. The approach involves deriving explicit analytical expressions for the design and optimization of eight distinct filter circuit solutions: one low-pass, one high-pass, and six band-pass filters with varying specifications. These derivations include the calculation of normalized and denormalized component values (resistors and capacitors), enabling precise tuning and practical implementation of the filters. Furthermore, the methodology encompasses the determination of key filter parameters such as passband gain, pole quality factor (Q-factor), and cut-off/center frequency, after selecting standard resistor and capacitor values suitable for the target application. The analytical framework facilitates a systematic approach to filter design, ensuring that the resulting circuits meet specific frequency response criteria while maintaining optimal stability and performance. The proposed methodology can be effectively applied in the development of various active filtering systems for signal processing, communication, and instrumentation, offering engineers a reliable foundation for designing high-performance, tailored filter solutions. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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6 pages, 505 KB

Open AccessProceeding Paper

Building Application for Software-Defined Network

by Delyan Genkov, Tsvetan Raykov and Miroslav Slavov

Eng. Proc. 2025, 104(1), 92; https://doi.org/10.3390/engproc2025104092 - 11 Sep 2025

Viewed by 210

Abstract

Software-defined networks are a modern approach to computer networks. With this concept, network devices can be monitored and configured centrally. While the lower layers of a software-defined network—devices and controllers—are relatively well known and standardized, the upper layers consist of APIs and software [...] Read more.

Software-defined networks are a modern approach to computer networks. With this concept, network devices can be monitored and configured centrally. While the lower layers of a software-defined network—devices and controllers—are relatively well known and standardized, the upper layers consist of APIs and software applications and are not standard. This article aims to propose one possible way to interact with a software-defined network and to build applications for monitoring and configuring such networks. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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11 pages, 1274 KB

Open AccessProceeding Paper

Multilevel Voltage Source Inverters with Improved Selective Harmonic Elimination Using a PAM-PWM Control Topology

by Sadeq Hamed and Reem Mousa

Eng. Proc. 2025, 104(1), 93; https://doi.org/10.3390/engproc2025104093 - 15 Sep 2025

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Abstract

Power inverters are extensively employed in a wide range of applications such as VSD, PV, UPS, and Vehicle-to-Grid systems. Different control topologies are used in power electronic inverters. Of these, PWM and MLVSIs are implemented to minimize the harmonic contents of the generated [...] Read more.

Power inverters are extensively employed in a wide range of applications such as VSD, PV, UPS, and Vehicle-to-Grid systems. Different control topologies are used in power electronic inverters. Of these, PWM and MLVSIs are implemented to minimize the harmonic contents of the generated waveforms, as well as to minimize the complexity and cost of these systems. Although PWM inverters offer an acceptable waveform quality, the switching losses of the power elements is considered a major drawback. MLVSIs provide excellent waveform quality at reasonable switching losses, but at the expense of a relatively higher cost and design complexity. However, when applied to constant voltage constant frequency applications such as PV, UPS, and Vehicle-to-Grid systems, the cost and design complexity become reasonable. In this paper, a generalized analytical analysis and solution of an M-Stage MLVSI with a certain selective harmonic elimination (SHE) control topology is reported. This leads to completely eliminate certain lower-order harmonics of the generated waveforms. The number of harmonics that can be eliminated depends upon the number of the system DC link stages. The results show that as the number of stages increases, a significant improvement of the waveform quality is achieved. However, the tendency of this quality to further improve as the number of stages increases is remarkably reduced. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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7 pages, 928 KB

Open AccessProceeding Paper

Using Infrared Thermography to Study the Impact of Dangerous Heat Stress on Thigh and Udder Temperature in Dairy Cows

by Hristo Hristov

Eng. Proc. 2025, 104(1), 94; https://doi.org/10.3390/engproc2025104094 - 15 Sep 2025

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Abstract

The aim of this study was to evaluate the influence of factors determining the state of danger heat stress on the udder and thigh temperature of dairy cows. Heat stress was classified by measuring the temperature–humidity index (THI). Surface temperatures in the areas [...] Read more.

The aim of this study was to evaluate the influence of factors determining the state of danger heat stress on the udder and thigh temperature of dairy cows. Heat stress was classified by measuring the temperature–humidity index (THI). Surface temperatures in the areas of interest were measured using infrared thermography (IRT). The correlation coefficient between THI and thigh surface temperatures ranged from 0.67 to 0.87. The correlation coefficient between udder surface temperature and THI was 0.81. The rate of increase in thigh surface temperature ranged from 0.33 to 0.45. The rate of increase in udder surface temperature was 0.64. The results showed that under danger heat stress, the surface temperature of the udder and thigh was strongly affected and the cows’ body showed a strong tendency to cool down. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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8 pages, 1487 KB

Open AccessProceeding Paper

Graphical Dependencies and Mechanical Unit Selection for Driving a Work Machine

by Stefan Ilchev Tenev

Eng. Proc. 2025, 104(1), 95; https://doi.org/10.3390/engproc2025104095 - 15 Sep 2025

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Abstract

The machine unit design for driving a specific work machine is a complex process, in which factors such as power machine type, power transmission drives, total efficiency coefficient, and total gear ratio determine an accurate model for calculating the drive. The correct choice [...] Read more.

The machine unit design for driving a specific work machine is a complex process, in which factors such as power machine type, power transmission drives, total efficiency coefficient, and total gear ratio determine an accurate model for calculating the drive. The correct choice of the above-described factors will lead to the construction of a machine unit with high performance while meeting the requirements of the client. Full article

(This article belongs to the Proceedings of International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025))

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