Applied sciences

International Journal of Electronics and Telecommunications

Content

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

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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
1
T. Jayachandra Prasad
1
G. Gopinath
1
B. Charitha
1
G. Dharma Teja
1
B. Lomith Reddy
1

  1. College of Engineering and Technology, Nandyal, India
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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
1

  1. Faculty of Computer Science, Bialystok Universityof Technology, Bialystok, Poland
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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
1

  1. Faculty of Computer Science, Bialystok Universityof Technology, Bialystok, Poland
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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
1
Grzegorz Mzyk
2

  1. Faculty of Information and CommunicationTechnology, Wrocław University of Science and Technology, Wrocław, Poland
  2. Faculty of Information and CommunicationTechnology, Wrocław University of Science and Technology, Wrocław, Poland
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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
1
ORCID: ORCID
Andrzej Rusiecki
1
ORCID: ORCID
Krzysztof Halawa
1
ORCID: ORCID

  1. Wroclaw University of Science and Technology, Poland
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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
1
ORCID: ORCID

  1. Department of Computer Science, Polish Naval Academy, Gdynia, Poland
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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
1
Tomasz Śliwiński
1

  1. Faculty of Electronicsand Information Technology, Warsaw University of Technology, Warsaw
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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
1
Czeslaw Smutnicki
2

  1. Cracow University of Technology, Crakow, Poland
  2. Wrocław University of Science and Technology, Wrocław, Poland
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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
1
Maciej Ławryńczuk
1

  1. Institute of Control and Computation Engineering,Faculty of Electronics and Information Technology, Warsaw Universityof Technology, Warsaw, Poland
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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
1
ORCID: ORCID
Urszula Libal
1
ORCID: ORCID

  1. University of Science andTechnology, Faculty of Electronics, Photonics and Microsystems, Departmentof Acoustics, Multimedia and Signal Processing, Wroclaw, Poland
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Abstract

The challenge of enhancing purchasing strategies within a large organization, taking into account non-linear constraints, has been thoroughly examined and formalized. The increase in demand for resources over time, changes in prices and the costs of tender procedures are taken into account. The purchasing strategy integrates forecasts derived from historical data and is in accordance with the capacity plan. A simple, linear autoregressive model is used to predict demand changes and a predictive control technique with a moving horizon. Furthermore, the findings from experiments utilizing the genetic algorithm are presented. Finally, important open problems are discussed, the solution of which would expand the scope of applicability and universality of the developed tool.
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Authors and Affiliations

Szymon Niewiadomski
1
Grzegorz Mzyk
1

  1. Faculty of Information and Communication Technology, University of Science and Technology, Wrocław, Poland
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Abstract

Implemented project-based learning using drones is more fun and the concepts delivered are easily understood by students. This research has built a DIY drone using an F450 quadcopter to improve the quality of the learning process such as basic concepts of atmospheric physics. The main system of the drone is a Pixhawk 2.4.8 flight controller where the system is set up via Mission Planner to work on autopilot. For atmospheric physics learning, atmospheric data such as temperature, relative humidity, and air pressure is collected using BME280 sensors on the drone and on the ground. The sensor is controlled by Arduino Uno and a data logger has also been developed to store data into a Micro SD card for post hoc analysis. Once the drone is tested for flight stability, it can be applied to measure atmospheric parameters including flight altitude and precipitable water vapor. With this development, the system can be utilized to quantitatively show the relationship between atmospheric parameters and ultimately can predict other related parameters as well as able to provide interpretation of measurement results as evidence of improved understanding.
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Authors and Affiliations

Wayan Suparta
1
ORCID: ORCID

  1. Naresuan University, Department of Electrical and Computer Engineering, Faculty of Engineering, Thailand
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Abstract

Recent advancements in large language models (LLMs) have demonstrated their potential beyond conventional natural language processing tasks. This study demonstrates that GPT-4, a state-of-the-art large language model, can semiautonomously generate and execute side-channel attacks, specifically Correlation Power Analysis (CPA) and timing attacks. By letting the model build and execute code on physical hardware as well as collect and analyze power traces and timing information I’ll show that a non-expect operator equipped with an LLM can execute CPAs against industry-standard embedded encryption libraries. The findings suggest that LLMs’ capabilities present both opportunities for accelerated research and challenges related to the potential misuse of such technologies.
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Authors and Affiliations

Witold Waligóra
1

  1. Myre Laboratories, an independent R&D firm
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Abstract

Randomness testing is one of the essential and easiest tools for evaluating cryptographic primitives. The faster we can test with more refined tests, the greater volume of data that can be reliably tested. This paper we analyze three tests. Starting with a range of observations made for a well-known frequency test for overlapping vectors in binary sequence testing, for which we have obtained precise chi-square statistic computed in O dt 2dt instead of O 22dt time, without precomputed tables. Next we focused on two tests from Dieharder: the DAB Fill Tree Test and the DAB Fill Tree 2 Test — for which the probability functions originally were determined empirically. We also draw attention to the errors found in their implementations and the insufficient exploration of the tested sequence in the second test. Even though these tests have been in the package for over 10 years, their significant shortcomings have not been noticed until now.
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Authors and Affiliations

Krzysztof Mańk
1

  1. Military University of Technology, Poland
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Abstract

EdDSA is a Schnorr signature scheme instantiated on top of Edwards curves, which admit fast, constant-time arithmetic, but suffer from the presence of a non-trivial cofactor, where the order of the group of points is a large prime times a small integer (4 or 8). Current standards permit for points present in the signature (commitment and/or public key) to have a component in the small-order subgroup of the group of points. This is done by sanctioning two variants of the signature verification equation and specifying precedence of one over the other. This last point, however, seems to be widely misunderstood and the two variants are given equal footing, allowing different “compliant” implementations to use different verification algorithms. This in turn lets malicious actors create signatures which are accepted by some parties, but rejected by others, threatening, e.g., consensus in a blockchain network setting. We add to the discussion on practical consequences of such discrepancies by formulating the consensus problem in the context of load-shedding attacks. We argue that the standards are in fact very specific about the set of valid signatures, despite lacking in explicitness and emphasis. We further show that two mainstream cryptographic libraries, namely, OpenSSL and CIRCL, accidentally (and in a manner not immediately apparent when inspecting the code) use the correct variant of the verification equation for one parameter set of EdDSA, but incorrect for another. In OpenSSL, this is traced back to careless copying of refcode. We conclude by proposing remedies to the chaotic status quo described.
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Authors and Affiliations

Adrian Cinal
1
Oliwer Sobolewski
1

  1. Department of Cryptology, NASK National Research Institute, Warsaw, Poland
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Abstract

Global digitalization has accelerated, leading to continuous online shopping and services growth. However, the centralized nature of traditional e-commerce platforms raises concerns about data control, privacy, and potential single points of failure. Blockchain technology offers a decentralized alternative that addresses these issues, improving online transactions with enhanced privacy and anonymity for users. This article explores the problem of anonymization in web services by developing an anonymous online auction system using blockchain and zero-knowledge proof (ZKP). We propose a solution that employs ZKP in two stages: first, to verify that a user is eligible to participate in the auction, thereby creating a list of potential bidders; second, to prove that a bid is placed by a user from this list without disclosing their identity. This approach allows participants to engage in auctions anonymously, protecting their interests from competitors and sellers. The system eliminates the need for a trusted third party by leveraging the blockchain immutable ledger for transparency, giving users full control over their data and participation. We present the architecture and implementation details of the system, demonstrating its feasibility and potential to enhance privacy and security in online auctions.
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Authors and Affiliations

Marlena Broniszewska
1
Wiktor B. Daszczuk
1
Denny B. Czejdo
2

  1. Warsaw University of Technology, Department of Electronics and Information Technology, Warsaw, Poland
  2. Fayetteville State University, Department of Mathematics and Computer Science, Fayetteville, NC 28301, USA
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Abstract

An estimation of the nonlinear degrees for the forward and inverse permutations of the Ascon algorithm is made in this work. This estimation is made by analyzing higher order differentials. The obtained results of nonlinear degree are significantly lower than the known data. Instead of the generally accepted values sr (where s is nonlinear degree of substitution and r is number of rounds), the computational experiments demonstrated the value s(r-1)+1 in all the considered cases. These results allow to clarify the complexity of constructing the best known distinguisher - the zero-sum distinguisher - for a multiround transformations. Thus, instead of the known complexity values of 285 and 2130 for 11 and 12 rounds of transformations, according to our data, the complexity for 11 rounds is 235 and for 12 rounds is 270.
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Authors and Affiliations

Victor Ruzhentsev
1

  1. Kharkiv National University of Radioelectronics
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Abstract

The demand for low-power, high-speed, and area efficient digital circuits has driven the exploration of alternative logic families such as Pass Transistor Logic (PTL). The design of a multiplier circuit that leverages the inherent advantages of PTL to achieve significant improvements in power consumption, operational speed and silicon area usage. The proposed multiplier using PTL-based logic gates to generate partial products, followed by a reduction tree and a final addition stage, all optimized for performance and efficiency. Key design challenges, such as voltage degradation and level restoration inherent in PTL circuits, is addressed through carefully designed voltage restoration techniques and custom PTL cells. The architecture is compared against conventional CMOS-based multipliers to demonstrate its superiority in terms of power efficiency and speed. All the circuits are simulated using ECAD tools to analyze the power, delay, area and Power-Delay-Product (PDP) of the multiplier to highlight a substantial reduction in power consumption and a faster operation, making the PTL-based multiplier an ideal circuit for high-performance and low-power applications in modern digital systems. The proposed work contributes to the field of low-power digital design by showcasing the potential of PTL in creating multipliers which are not only efficient but also scalable for future technology nodes.
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Authors and Affiliations

D. Satyanarayana
1
M. Chennakesavulu
1
N. Fouzia Sulthana
1
K. Upendra
1
D. Sashidhar
1
K. Ramachandra Reddy
1
N. Naga Sai Vikranth
1
V. Devendra
1

  1. Dept. of ECE, Rajeev Gandhi Memorial College of Engineering and Technology, Andhra Pradesh, India
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Abstract

Integrating memristor technology with traditional CMOS has led to innovative designs for ternary logic, significantly enhancing the performance and efficiency of digital integrated circuits. This hybrid approach takes advantage of the unique properties of memristors, including low power consumption, compact size, and non-volatility, to develop ternary logic circuits that outperform conventional binary systems in terms of area and energy efficiency. This article presents two new low-power ternary decoders designed using a hybrid memristor- MOS logic approach. The decoders were simulated and analyzed using SPICE, and their performance was compared with existing circuits. The results indicate that the power-efficient decoder uses 44.44% fewer transistors and dissipates 97.78% less power than previously documented circuits.
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Authors and Affiliations

Ramesh Kumar
1
Bal Chand Nagar
1

  1. National Institute of Technology (NIT), Patna, India
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Abstract

Owing to the benefits that they offer over traditional acoustic and RF communication, including higher data rates, reduced latency, and enhanced safety, underwater wireless optical communication (UWOC) systems have gained a solid focus. However, the transmission range is rather small compared with traditional radio frequency and acoustic communications because of turbulence which makes the light beam inside the water channel fade, absorb, and scatter. In this paper, a UWOC channel model mapped with LDPC and BCH error correction techniques is used to analyze the impulse response of the channel in coastal and harbor waters. The performance of the system based on its transmission length and bit error rate (BER) is evaluated. The link distance is determined to find the maximum link distance ensuring quality UWOC. The best performance has been observed with the 4-QAM-OFDM mapped channel with LDPC codes with maximum distance of 62 m in harbor water and 161.9 m in coastal water.
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Authors and Affiliations

Lenin Joseph
1
Sangeetha Anandan
1

  1. VIT University, Vellore, India
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Abstract

This research examines how Nextgen wireless systems can benefit from Orthogonal Time Frequency Space (OTFS) modulation in different high-mobility channel situations. We test the BER performance of OTFS and OFDM with varying lengths of symbol under varied transmit power (TX power) conditions utilizing simulations employing Doubly-Selective, Extended Vehicular A (EVA), Unmanned Aerial Vehicle (UAV), and Extended Typical Urban (ETU) channel models. Compared to OFDM, OTFS reliably reduces the impact of multipath propagation and Doppler spread more effectively. Importantly, to maximize BER performance in UAV channel simulations, the OTFS symbol length had to be carefully selected; increasing the symbol length without thinking about it led to decreasing results. It was shown that OTFS is connected to a few resources in the ETU channel due to its minimal demand on TX Power. Based on these results, OTFS seems to be a good modulation technique for demanding mobile communication applications, particularly for UAV communications where picking the right parameters is key. Methods for adaptive OTFS that can change symbol length and other parameters in reaction to channel circumstances in real-time should be the focus of future studies.
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Authors and Affiliations

Sura H. Khadum
1
Thamer M. Jamel
1
Hassan F. Kkhazaal
2

  1. Department of Communications Engineering, University of Technology, Baghdad, Iraq
  2. Department of Electrical Engineering, Wasit University, Wasit, Iraq
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Abstract

This paper demonstrates the feasibility of increasing the measurement frequency range of material shielding effectiveness using the flanged coaxial transmission line. Furthermore, the authors presented their original solutions of measurement adapters and an analysis of the properties and measurement parameters of these adapters. A modification of the test stand was proposed, which will facilitate measuring samples in a wider frequency range and of much larger sizes. The authors also demonstrated modified methods for calibrating the test stands and measuring the shielding effectiveness of various materials, including thick materials.
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Authors and Affiliations

Jarosław M. Janukiewicz
1
Tadeusz W. Więckowski
1

  1. Wrocław University of Science and Technology (WUST), Poland
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Abstract

The article discusses the issue of measuring electrical energy consumption. Measurements and analyses of power consumption by selected receivers and electrical circuits are described. The measurements were carried out in selected university campus buildings. The authors included statistical data, also broken down by working period and time of day. Averaged charts are presented on a daily and weekly basis. Knowing the receivers on individual circuits (and their applications), attempts were made to analyze consumption and the possibilities of reducing electricity consumption. The paper also includes analyses related to further work and the possibilities of using the data collected from the energy consumption measurement in other applications and research.
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Authors and Affiliations

Paweł Poczekajło
1
Piotr Suszyński
1
Andrzej Antosz
1

  1. Koszalin University of Technology, Faculty of Electronics and Computer Science, Koszalin, Poland
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Abstract

Fiber Optics celebrates 50th anniversary of development in Poland. The conferences on Optical Fibers and Their Applications, organized in the country for 50 years, have played an important role in the development of the national scientific and technical community of optical fiber technology, or as we call it today, optical fiber photonics. This branch of photonics includes optical fiber telecommunications and instrumental photonics, including optical fiber components and sensors. Each optical fiber system requires an ultra-low-loss, or specialized, transmission medium in the form of a fiber or planar optical waveguides. The medium can be active or passive, sensitive or insensitive to external influences. Optical fiber spatially limits the spread of an optical wave using the refractive method or using a photonic band gap. To build a modern optical fiber system, light sources and detectors are necessary, as well as various optical and photonic components, preferably integrated or optical fiber, and not necessarily volumetric. Volume solutions in photonic systems are being gradually abandoned due to the reduction of costs and workload, and the increase in the reliability of photonic components and systems. The conference has published its materials in the Proc.SPIE publishing series for many years and is known internationally as Optical Fibers and Their Applications OFTA. The XXI OFTA2025 Conference gathered over 60 participants and over 50 papers and posters were presented. The article reviews the proceedings of the OFTA2025 conference. A version of this paper in Polish was published in Elektronika Monthly by SEP.
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Authors and Affiliations

Ryszard S. Romaniuk
1
Jan Dorosz
2

  1. Białystok University of Technology, Poland
  2. Warsaw University of Technology, Poland
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Abstract

 The paper is devoted to the signal- and frequency characteristics of 2-D causal systems. Two different approaches to this problem are presented. First, the 2-D complex Fourier transformation of the 2-D causal impulse response ��(����, ����) of a 2-D system defines the 2-D complex frequency response ��(����, ����). The modulus |��(����, ����)| is the 2-D magnitude response and ������ ��(����, ����) is the 2-D phase response of a system. On the other hand, applying the Pei’s formula relating the 2-D complex Fourier transform with the 2-D right-sided quaternion Fourier transform we introduce a concept of the quaternion-valued frequency response ���� (����, ����) of a 2-D causal system. We define the 2-D magnitude system response |����(����, ����)| and three 2-D phase responses. These concepts constitute an original contribution of this paper. The theoretical aspects are illustrated with examples of magnitude and phase responses of a causal 2-D analog low-pass filter.

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Authors and Affiliations

Kajetan M. Snopek
1

  1. Warsaw University of Technology, Faculty ofElectronics and Information Technology, Institute of Radioelectronics andMultimedia Technology, Poland
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Abstract

This paper presents the results of a study on developing a gait biometrics system based on motion sensors (an accelerometer and gyroscope), embedded in a smartphone. The experiments were conducted using a publicly available 13-person data corpus, with subjects participating in three data collection sessions. The study used CNN, CNN with attention and Multi-Input CNN neural networks. The training scenario from the first day resulted in an accuracy of 0.66 F1 score, 0.71 F1 score for training with the samples from the second day and 0.90 F1 score in the combined sets. It has been shown that it is more profitable to combine historical data than to update it with newer samples. Enriching the training set with a set of 30% synthetic samples produced by the LSTM-MDN generative models allowed to increase to accuracy to 0.94 F1-score. It was shown that synthetic samples can improve the generalization properties of the CNN network.
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Authors and Affiliations

Aleksander Sawicki
1
ORCID: ORCID
Khalid Saeed
1
ORCID: ORCID

  1. Białystok University of Technology, Poland
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Abstract

Palmprint biometrics is the best method of identifying an individual with a unique palmprint for every person. The present paper formulates a new methodology towards the identification of 3D palmprints using the Modified Four- Patch Local Binary Pattern (MFPLBP). It improves upon the conventional Four-Patch Local Binary Pattern (FPLBP) by integrating the adaptive weight with the improved texture extraction. Both approaches are created to support the intricate surface information of 3D palmprints. The MFPLBP can exactly capture local variations and is noise and illumination invariant. There are extensive experiments done in this paper and establish that MFPLBP outperforms traditional LBP methods and other stateof- the-art methods in recognition rates. The experiments establish that MFPLBP is a efficient and effective method of making use of 3D palmprints in real-world biometric verification.
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Authors and Affiliations

Musab T.S. Al-Kaltakchi
1
Manhal Ahmad Saleh Al-Hussein
2
Raid Rafi Omar Al-Nima
3

  1. Department of Electrical Engineering,College of Engineering, Mustansiriyah University, Baghdad, Iraq
  2. Technical Engineering Collegeof Mosul, Northern Technical University, Iraq. & The Directorate of CivilAffairs, Passports and Residency in Ninewa Governorate
  3. Technical Engineering College of Mosul,Northern Technical University, Iraq
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Abstract

One of the dominant common denominators of the Space 4.0 idea in the domain of space technologies are small satellites. The characteristic features of this group of technologies are relatively low costs, the possibility of very rapid hardware prototyping and modularization, the construction of hardware and software libraries for quick reuse, a significant number of manufactured and orbited satellites, incomparably easier ability to test numerous varieties of new technologies, while maintaining high reliability in a relatively short period of their orbital operation. It is small satellites that have become a solid foundation for the rapid development of the Space 4.0 idea. They require a completely different, much simpler ecosystem to maintain and safely, efficiently operate, especially large, highly functional microsatellites constellations throughout their life span between orbit and deorbit. The year 2012 can be considered the beginning of the development of the small satellite industry, a few years before the formal definition of the idea of Space 4.0. Small satellites and the involvement of the private sector in their production and operation were the engines thanks to which the technological and economic components of the Space 4.0 idea were defined. From the perspective and experience of over a decade of development of the small satellite industry, we look into the future and analyse trends also in terms of the situation of the space sector in Poland. A version of this paper in Polish was published in Elektronika Monthly by SEP.
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Authors and Affiliations

Ryszard S. Romaniuk
1
Piotr Orleański
2

  1. Warsaw University of Technology, Poland
  2. Space Research Centre, Polish Academy of Sciences, Poland
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Abstract

Swarm Intelligence (SI) is a kind of Artificial Intelligence that emerges from local interactions. By principle, systems based on SI are decentralized - they do not have access to the global knowledge. The initial study on SI was on the natural swarms, e.g., ants, flocks of birds, and schools of fish. Swarms have an ability to self-organize, which brings a unique set of features and applications. Despite their origin in biology, SI systems were adopted into technology. At the very beginning, they were used to solve optimization problems, e.g., Ant Colony Optimization and Particle Swarm Optimization; however, they were later adopted in the field of robotics, which is called swarm robotics. Although those are two primary fields of research in SI, other applications, such as in telecommunications, are also presented in this article. Furthermore, the problem of creating SI systems and the current methods used for designing and modeling the swarm systems are presented.
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Authors and Affiliations

Bartłomiej Mastej
1

  1. Doctoral School, Warsaw University of Technology, Warsaw, Poland
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Abstract

Financial institutions continue to face evolving cyber security threats that require immediate detection and mitigation to prevent significant damage. Classical-based cyber security mechanisms struggle to keep up with these emerging threats due to their limitations in processing power and scalability, especially when dealing with distributed attacks. Quantum computing promises an unmatched level of scalable parallel processing with increased accuracy, speed, and timely response to realtime threats. This research evaluates the application of quantum computing algorithms, specifically Continuous-Variable Quantum Neural Networks (CV-QNN), Crystals-Kyber cryptographic methods, and Quantum-enhanced Monte Carlo simulations, within financial IT infrastructures. Our findings indicate that quantum algorithms substantially enhance threat detection accuracy, reduce response latency, and ensure secure communication against quantum-powered threats. However, practical implementation of quantum computing solutions faces challenges such as high error rates, environmental sensitivity, and integration complexities. Addressing these issues requires further technological advancement and strategic planning. This research contributes actionable insights for financial institutions, guiding the strategic adoption of quantum technologies to strengthen cyber security resilience.
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Authors and Affiliations

Jean Marie Vianney Sindayigaya
1

  1. Warsaw University of Technology, Poland

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