Applied sciences

International Journal of Electronics and Telecommunications

Description

International Journal of Electronics and Telecommunications (IJET, eISSN 2300-1933, untill 2013 also print ISSN 2081-8491) is a periodical of Electronics and Telecommunications Committee of Polish Academy of Sciences and it is published by Warsaw Science Publishers of PAS. It continues tradition of the Electronics and Telecommunications Quarterly (ISSN 0867-6747) established in 1955 as the Rozprawy Elektrotechniczne. The IJET is a scientific periodical where papers present the results of original, theoretical, experimental and reviewed works. They consider widely recognized aspects of modern electronics, telecommunications, microelectronics, optoelectronics, radioelectronics and medical electronics.

The authors are outstanding scientists, well‐known experienced specialists as well as young researchers – mainly candidates for a doctor's degree. The papers present original approaches to problems, interesting research results, critical estimation of theories and methods, discuss current state or progress in a given branch of technology and describe development prospects. All the papers published in IJET are reviewed by international specialists who ensure that the publications are recognized as author's scientific output.

The printed periodical is distributed among all those who deal with electronics and telecommunications in national scientific centers as well as in numeral foreign institutions, and it is subscribed by many specialists and libraries. Its electronic version is available at http://ijet.pl.

The papers received are published within half a year if the cooperation between author and the editorial staff is efficient. The papers may be submitted to the editorial office by the journal web page http://ijet.pl.

Journal Metrics:

IMPACT FACTOR 2024: 0.7

CiteScore metrics from Scopus 2024: 1.6

SCImago Journal Rank (SJR) 2024: 0.217

Source Normalized Impact per Paper (SNIP) 2024: 0.452

Citation Indicator (JCI) 2024: 0.14

ISSN

eISSN 2300-1933 (since 2013), ISSN 2081-8491 (until 2012)

Publishers

Polish Academy of Sciences Committee of Electronics and Telecommunications

Editor-in-Chief
Ryszard S. Romaniuk, Warsaw University of Technology, Institute of Electronic Systems, Poland

Managing Editor
Danuta Sobczak-Bartosiewicz, Warsaw University of Technology, Poland

Technical Editors
Maciej Linczuk, Warsaw University of Technology, Institute of Electronic Systems, Poland

Secretary in-Charge
Danuta Ojrzenska-Wojter, Warsaw University of Technology, Institute of Telecommunications, Poland

Administrative Assistant
Danuta Sobczak-Bartosiewicz, Warsaw University of Technology, Poland

Editorial Advisory Board
Prof. Victor-Valeriu Patriciu, Director Doctoral School of Electronics, Informatics and Communications for Defense and Security, Military Technical Academy Bucharest, Romania, Romania

Prof. Bart Scheers, Royal Military Academy, Belgium

Dr. Eli Winjum, Norwegian Defence Research Establishment, Norway

Wladyslaw Skarbek, Warsaw University of Technology, IRE, Poland

Christian Napoli, University of Catania, Italy

Rosario Giunta, University of Catania, Italy

Christopher Chiu, University of Technology Sydney, Australia

Prof. Emiliano Tramontana, University of Catania, Italy

Prof Robin Braun, University of Technology Sydney, Australia

Dr David Davis, University of Technology Sydney, Australia

dr Brian Culshaw, University of Strathclyde, UK, United Kingdom

Grzegorz Chmaj, University of Nevada, United States

Giuseppe Pappalardo, University of Catania, Italy

Michael Affenzeller, University of Applied Sciences Upper Austria

Prof. Stavros Hatzopoulos, Laboratory of Hearing Science Audiology Dept., University of Ferrara, Italy, Italy

Prof Nikita M Ryskin, Saratov State University, Russian Federation

Prof. Adam Wolisz, Technische Universität Berlin, Department of Electrical Engineering and Computer Science Telecommunication Networks

Prof. Edmundo Monteiro, Departamento de Engenharia Informatica Universidade de Coimbra Portugal, Portugal

Prof. Zoubir Mammeri, IRIT, Université Paul Sabatier 118 Route de Narbonne F-31062 Toulouse Cedex 9 FRANCE, France

Dr Paul D Polishuk, IGI, Boston, MA, USA

Giuseppe Macchiarella, Politecnico di Milano,Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Italy

Prof. Bernd Steinbach, Bergakademie Freiberg Fakultät für Mathematik und Informatik Institut, Germany

Jan Szmidt, Warsaw University of Technology, Poland

Zenon Chaczko, University of Technology Sydney, Australia

Józef Modelski, Warsaw University of Technology, Poland

Wiesław Woliński, Warsaw University of Technology, Poland

Ryszard Klempous, Wroclaw University of Technology, Poland

Radomir Stanković, University of Niš, Serbia

Javier Poncela, University of Malaga, Spain

Marek Turowski, CFD Research Corporation, United States

Dawid Zydek, NV Energy, United States

Wojciech Szpankowski, Purdue University, United States

Jacek Żurada, University of Louisville, United States

Tadeusz Luba, Warsaw University of Technology, Poland

Stefan Hahn, Warsaw University of Technology, Poland

Gilbert De Mey, Ghent University, Belgium

Svetlana Yanushkevich, University of Calgary, Canada

Viktor Krozer, Technical University of Denmark, Denmark

Adam Morawiec, European Electronic Chips & Systems Design Initiative, France

Herman Rohling, Technical University of Hamburg, Germany

Franco Davoli, University of Genowa, Italy

Michał Mrozowski, Gdańsk University of Technology, Poland

Włodzimierz Janke, Koszalin University of Technology, Poland</

Principal Contact
Ryszard S. Romaniuk
Professor
Warsaw University of Technology, Institute of Electronic Systems, room 217, Nowowiejska 15/19, Warsaw 00-665, Poland
Phone: +48222345110
Fax: +48228252300
Email: ryszard.romaniuk@pw.edu.pl

Support Contact
Danuta Bartosiewicz
Email: danuta.bartosiewicz@pw.edu.pl

International Journal of Electronics and Telecommunications is an open access journal with all content available with no charge in full text version.

The journal content is available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/.

Volumes
Instructions for authors

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Content

International Journal of Electronics and Telecommunications | 2025 | vol. 71 | No 2

1 CNN and Transfer Learning methods for enhanced dermatological disease detection

Habibulla C. Venkataiah , T. Jayachandra Prasad , G. Gopinath , B. Charitha , G. Dharma Teja , B. Lomith Reddy

International Journal of Electronics and Telecommunications | 2025 | vol. 71 | No 2 | 337-344 | DOI: 10.24425/ijet.2025.153607

Keywords: eczema psoriasis dermatology CNN transfer learning

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Abstract

Since skin diseases generally badly affect lives, the earlier and more accurate the diagnosis, the better the chances of effective treatment and a better prognosis. Deep learning applications, especially CNNs, has revolutionized the domain of disease classification, significantly increasing the accuracy of diagnoses for such common conditions and facilitating early interventions. The huge success behind the ongoing project motivated advancements of the developing in CNN techniques towards detection of skin disease by using the concept of Transfer Learning. So, the older models, which had employed it for detecting Eczema and Psoriasis based on the architectures involving deep CNNs. The Inception ResNet v2 architecture improved the accuracy of that model, with some practical implementations via smartphone integration and web server integration. Some of those innovations are as follows in our project. The earlier work used different CNN architectures. Our approach involved Transfer Learning with a pre-trained ResNet50 model to try to improve performance and efficiency using features learned from large-scale datasets. This reduce the complexity and enhance the accuracy. Besides Transfer Learning adaptation, our project encompasses elaborate preprocessing techniques like resizing, normalization, and data augmentation in fine-tuning the dataset for further model fine-tuning. It has 97.6% accuracy, 95% precision, 99.4% recall, and 97.4% F1-score. rad-CAM techniques have been employed to visualize and interpret model predictions. This final model has been a pragmatic and accessible tool for early detection and diagnosis of skin disease. The feature here is an attempt to provide a more accurate, efficient, and user-friendly diagnostic solution through the incorporation of advanced methods of Transfer Learnin3g and visualization.

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Authors and Affiliations

Habibulla C. Venkataiah

T. Jayachandra Prasad

G. Gopinath

B. Charitha

G. Dharma Teja

B. Lomith Reddy

College of Engineering and Technology, Nandyal, India

2 Learning data characteristics of a session-based recommendation system and their impact on system performance

Urszula Kużelewska

International Journal of Electronics and Telecommunications | 2025 | vol. 71 | No 2 | DOI: 10.24425/ijet.2025.153579

Keywords: session-based recommenders valuation of recommendations data metrics

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Abstract

Recommendation systems are the most effective solution for enhancing user satisfaction and personalising ecommerce services on the internet. These systems use advanced procedures to analyse massive volumes of data, ensuring users receive the most relevant and suitable products available. The success of recommendation systems hinges on the quality of the methods used. However, there is also an impact on the input data. Session-based techniques are the most effective way to generate recommendations. They focus on short-term user interactions organised in sessions. This procedure is the best for real-world scenarios, where one-time users and limited item availability are prevalent. The objective of this study is to examine the relationship between data metrics, including density, shape, and popularity, and the performance of session-based algorithms, in terms of accuracy and coverage.

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Authors and Affiliations

Urszula Kużelewska

Faculty of Computer Science, Bialystok Universityof Technology, Bialystok, Poland

3 Detailed maps conversion technique for usage in realtime 3D mobile games

Maciej Kopczynski

International Journal of Electronics and Telecommunications | 2025 | vol. 71 | No 2 | 353-360 | DOI: 10.24425/ijet.2025.153580

Keywords: map 3D mobile app conversion mobile device

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Abstract

Research presents findings and outlines techniques for converting detailed GIS maps into simplified versions suitable for real-time 3D mobile games, specifically optimized for devices with medium to low processing power. This approach is particularly valuable for developers of mobile 3D applications that incorporate real-world maps, such as tycoon, strategy, or geolocation-based games. The results demonstrate balance between retaining essential map details from the original data and achieving high-performance 3D graphics across a range of mobile devices.

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Authors and Affiliations

Maciej Kopczynski

Faculty of Computer Science, Bialystok Universityof Technology, Bialystok, Poland

4 Dimensionality reduction in kernel-based identification of Wiener system by cyclostationary excitations

Gabriel Maik , Grzegorz Mzyk

International Journal of Electronics and Telecommunications | 2025 | vol. 71 | No 2 | 361-368 | DOI: 10.24425/ijet.2025.153581

Keywords: Nonlinear systems Identification Kernel estimation Wiener structure Curse of dimensionality Cyclostationary signals Nonparametric regression

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Abstract

The topic of nonparametric estimation of nonlinear characteristics in the Wiener system is examined. In this regard, the traditional kernel algorithm faces difficulties stemming from the dimensionality associated with the memory length of the dynamic block. A particular class of input sequences has been proposed, which aids in reducing dimensionality and consequently improves the convergence rate of the estimator to the true characteristics. A theoretical analysis of the suggested method is presented.

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Authors and Affiliations

Gabriel Maik

Grzegorz Mzyk

Faculty of Information and CommunicationTechnology, Wrocław University of Science and Technology, Wrocław, Poland
Faculty of Information and CommunicationTechnology, Wrocław University of Science and Technology, Wrocław, Poland

5 A systematic review of effective data augmentation in cervical cancer detection

Betelhem Zewdu Wubineh , Andrzej Rusiecki , Krzysztof Halawa

International Journal of Electronics and Telecommunications | 2025 | vol. 71 | No 2 | 369-377 | DOI: 10.24425/ijet.2025.153582

Keywords: cervical cancer data augmentation deep learning artificially generated images

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Abstract

The rapid progress of AI has made computer-assisted systems essential in medical fields like cervical cytology analysis. Deep learning requires large datasets, but data scarcity and privacy concerns pose challenges. Data augmentation addresses this by generating additional images and improving model accuracy and generalizability. This review examines effective augmentation techniques and top-performing deep-learning models for segmentation and classification in cervical cancer detection. Analyzing 57 articles, we found that hybrid deep feature fusion with augmentation (rotation, flipping, shifting, brightness adjustments) achieved 99.8% accuracy in binary and 99.1% in multiclass classification. Augmentation is vital for enhancing model performance in limited data scenarios.

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Authors and Affiliations

Betelhem Zewdu Wubineh

e-mail:

ORCID:

Andrzej Rusiecki

e-mail:

ORCID:

Krzysztof Halawa

e-mail:

ORCID:

Wroclaw University of Science and Technology, Poland

6 Analysis of selected mixers in the Bitcoin network

Przemysław Rodwald

International Journal of Electronics and Telecommunications | 2025 | vol. 71 | No 2 | 379-385 | DOI: 10.24425/ijet.2025.153583

Keywords: cryptocurrencies Bitcoin mixers tumblers

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Abstract

The pseudonymous nature of Bitcoin continually generates interest in services aimed at enhancing transaction anonymity. One such solution is the use of Bitcoin mixing services, commonly referred to as mixers, which are employed to increase user privacy. However, their use can be controversial, as while they serve to enhance financial privacy, they can also be exploited for illicit purposes. One of the challenges faced by law enforcement is identifying suspicious Bitcoin addresses. The purpose of this article is to examine the behavior of selected cryptocurrency mixers as a foundation for future research in this area.

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Authors and Affiliations

Przemysław Rodwald

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ORCID:

Department of Computer Science, Polish Naval Academy, Gdynia, Poland

7 Neural-Driven heuristic for strip packing trained with Black-Box optimization

Mariusz Kaleta , Tomasz Śliwiński

International Journal of Electronics and Telecommunications | 2025 | vol. 71 | No 2 | 387-396 | DOI: 10.24425/ijet.2025.153584

Keywords: strip packing problem algorithm selection problem heuristics neural networks reinforcement learning

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Abstract

We address the well-known NP-hard problem of packing rectangular items into a strip, a problem of significant importance in electronics (e.g., packing components on printed circuit boards and macro-cell placement in Very-Large- Scale Integration design) and telecommunications (e.g., allocating data packets over transmission channels). Traditional heuristics and metaheuristics struggle with generalization, efficiency, and adaptability, as they rely on predefined rules or require extensive computational effort for each new problem instance. In this paper, we propose a neural-driven constructive heuristic that leverages a lightware neural network trained via black-box optimization to dynamically evaluate item placement decisions. Instead of relying on static heuristic rules, our approach adapts to the characteristics of each problem instance, enabling more efficient and effective packing strategies. To train the neural network, we employ the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), a state-ofthe- art derivative-free optimization method. Our method learns decision policies by optimizing fill factor improvements over a large dataset of problem instances. Unlike conventional heuristics, our approach dynamically adapts placement decisions based on a broad set of features describing the current partial solution and remaining items. Through extensive computational experiments, we compare our method against well-known strip packing heuristics, including MaxRects and Skyline-based algorithms. The results demonstrate that our approach consistently outperforms the best traditional heuristics, achieving up to 6.74 percentage points of improvement in packing efficiency. Furthermore, our method improves 87.87% of tested instances. Our study highlights the potential of machine learning-driven heuristics in combinatorial optimization and opens avenues for further research into adaptive decision-making strategies in packing and scheduling problems

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Authors and Affiliations

Mariusz Kaleta

Tomasz Śliwiński

Faculty of Electronicsand Information Technology, Warsaw University of Technology, Warsaw

8 A boundle of on-line algorithms for scheduling computational tasks

Dariusz Dorota , Czeslaw Smutnicki

International Journal of Electronics and Telecommunications | 2025 | vol. 71 | No 2 | 397-402 | DOI: 10.24425/ijet.2025.153585

Keywords: Multiprocessor tasks on-line scheduling

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Abstract

We deal with the problem of scheduling the set of computational tasks on parallel identical processors. Each task needs a predefined number of processors to perform. The problem is known in scheduling theory and has been considered up to now by a few authors. Starting from the formal original description of the problem, we provide a mathematical model and then propose, at first, the solution method in the deterministic case. In fact, the paper focuses chiefly on the nondeterministic variant of the problem. We have proposed several online algorithms for this case. These algorithms are evaluated through competitive analysis and experiments. The practical application of the problem can be found in embedded systems with increased dependability obtained through hardware and software redundancy.

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Authors and Affiliations

Dariusz Dorota

Czeslaw Smutnicki

Cracow University of Technology, Crakow, Poland
Wrocław University of Science and Technology, Wrocław, Poland

9 Evaluation and experimental optimization of cheap ultrasonic acoustic linear position sensor

Maciej Zakrzewski , Maciej Ławryńczuk

International Journal of Electronics and Telecommunications | 2025 | vol. 71 | No 2 | 403-412 | DOI: 10.24425/ijet.2025.153586

Keywords: distance measurement ultrasonic sensors low-costsensors sensor optimization

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Abstract

This work is concerned with the adequate selection, evaluation and experimental optimization of a low-cost position sensor in an electromechanical system. The objective is to choose a sensor that satisfies the following criteria: it is very fast, provides accurate measurement, and is relatively inexpensive. Various distance measurement technologies, including vision, laser, acoustic, and touch sensors, have been evaluated. Ultrasonic sensors deliver the best performance in terms of cost-effectiveness and applicability. The developed system undergoes static and dynamic testing, with structural, environmental, and software adjustments improving measurement accuracy. The research significantly reduces measurement errors and enhances result repeatability. The article discusses challenges associated with ultrasonic sensors, such as acoustic resonances and environmental influences, and proposes mitigation strategies. The findings highlight the extensive potential of the system for various industrial and educational applications.

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Authors and Affiliations

Maciej Zakrzewski

Maciej Ławryńczuk

Institute of Control and Computation Engineering,Faculty of Electronics and Information Technology, Warsaw Universityof Technology, Warsaw, Poland

10 Fuel Level Estimation in Tank of Truck in Motion

Pawel Biernacki , Urszula Libal

International Journal of Electronics and Telecommunications | 2025 | vol. 71 | No 2 | 413-418 | DOI: 10.24425/ijet.2025.153587

Keywords: automotive sensors particle filter Sequential Monte Carlo fuel level heavy truck vehicle in motion

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Abstract

The paper presents the results of a case study on estimating the fuel level in the tank of a motor vehicle. A method based on the concept of particle filtering of noisy measurement data is proposed. The algorithm designed using the Sequential Monte Carlo method with Sequential Importance Sampling is combined with classical digital filters used for signal filtering. In the simulations, real data obtained by measuring fuel levels in the tanks of TIR heavy trucks from one of the Polish trucking companies are used. The performance of the applied method was considered in various measurement situations, such as refueling, driving on an uneven road surface, driving on steep roads, and fading of the measurement signals.

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Authors and Affiliations

Pawel Biernacki

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ORCID:

Urszula Libal

e-mail:

ORCID: