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Wydział Elektroniki, Telekomunikacji i Informatyki
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Rok 2024
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Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation
PublikacjaTo date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging...
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Antenna Optimization Using Machine Learning with Reduced-Dimensionality Surrogates
PublikacjaIn modern times, antenna design has become more demanding than ever. The escalating requirements for performance and functionality drive the development of intricately structured antennas, where parameters must be meticulously adjusted to achieve peak performance. Often, global adjustments to geometry are necessary for optimal results. However, direct manipulation of antenna responses evaluated with full-wave electromagnetic (EM)...
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Application Of Generative Adversarial Network for Data Augmentation and Multiplication to Automated Cell Segmentation of the Corneal Endothelium
PublikacjaConsidering the automatic segmentation of the endothelial layer, the available data of the corneal endothelium is still limited to a few datasets, typically containing an average of only about 30 images. To fill this gap, this paper introduces the use of Generative Adversarial Networks (GANs) to augment and multiply data. By using the ``Alizarine'' dataset, we train a model to generate a new synthetic dataset with over 513k images....
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Application of the Flipped Learning Methodology at a Business Process Modelling Course – A Case Study
PublikacjaFlipped learning has been known for a long time, but its modern use dates back to 2012, with the publication of Bergmann and Saams. In the last decade, it has become an increasingly popular learning method. Every year, the number of publications on implementing flipped learning experiments is growing, just as the amount of research on the effectiveness of this educational method. The aim of the article is to analyze the possibilities...
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Approximate and analytic flow models for leak detection and identification
PublikacjaThe article presents a comprehensive quantitative comparison of four analytical models that, in different ways, describe the flow process in transmission pipelines necessary in the task of detecting and isolating leaks. First, the analyzed models are briefly presented. Then, a novel model comparison framework was introduced along with a methodology for generating data and assessing diagnostic effectiveness. The study presents basic...
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Approximation algorithms for job scheduling with block-type conflict graphs
PublikacjaThe problem of scheduling jobs on parallel machines (identical, uniform, or unrelated), under incompatibility relation modeled as a block graph, under the makespan optimality criterion, is considered in this paper. No two jobs that are in the relation (equivalently in the same block) may be scheduled on the same machine in this model. The presented model stems from a well-established line of research combining scheduling theory...
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Architectural Modifications to Enhance Steganalysis with Convolutional Neural Networks
PublikacjaThis paper investigates the impact of various modifications introduced to current state-of-the-art Convolutional Neural Network (CNN) architectures specifically designed for the steganalysis of digital images. Usage of deep learning methods has consistently demonstrated improved results in this field over the past few years, primarily due to the development of newer architectures with higher classification accuracy compared to...
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Artificial Intelligence for Wireless Avionics Intra-Communications
PublikacjaThis chapter presents a summary of the description and preliminary results of the use case related to the implementation of artificial intelligence tools in the emerging technology called wireless avionics intra-communications (WAICs). WAICs aims to replace some of the cable buses of modern aircraft. This replacement of infrastructure leads to: (1) complexity reduction of future airplanes, (2) creation of innovative services where...
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Artificial Intelligence in the Diagnosis of Onychomycosis—Literature Review
PublikacjaOnychomycosis is a common fungal nail infection that is difficult to diagnose due to its similarity to other nail conditions. Accurate identification is essential for effective treatment. The current gold standard methods include microscopic examination with potassium hydroxide, fungal cultures, and Periodic acid-Schiff biopsy staining. These conventional techniques, however, suffer from high turnover times, variable sensitivity,...
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Assessment Of the Relevance of Best Practices in The Development of Medical R&D Projects Based on Machine Learning
PublikacjaMachine learning has emerged as a fundamental tool for numerous endeavors within health informatics, bioinformatics, and medicine. However, novices among biomedical researchers and IT developers frequently lack the requisite experience to effectively execute a machine learning project, thereby increasing the likelihood of adopting erroneous practices that may result in common pitfalls or overly optimistic predictions. The paper...
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Auto-Correction of Non-Anechoic Antenna Measurements Based on Multi-Taper Approach
PublikacjaMeasurements of antenna prototypes are normally performed in dedicated, yet costly environments such as anechoic chambers (ACs). However, the AC construction cost might be unjustified when the measurements aim to support education, or budget-tight research. Alternatively, experiments can be realized in non-anechoic regime and refined using appropriate methods. In this letter, a framework for correction of antenna far-field measurements...
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Automated Generation of Modular Assurance Cases with the System Assurance Reference Model
PublikacjaAssurance cases are structured arguments used to demonstrate specific system properties such as safety or security. They are used in many industrial sectors including automotive, aviation and medical devices. Assurance cases are usually divided into modules which address goals allocated to specific system properties, components, functions, modes of operation or environmental conditions. Depending on the system and assurance process...
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Automated hearing loss type classification based on pure tone audiometry data
PublikacjaHearing problems are commonly diagnosed with the use of tonal audiometry, which measures a patient’s hearing threshold in both air and bone conduction at various frequencies. Results of audiometry tests, usually represented graphically in the form of an audiogram, need to be interpreted by a professional audiologist in order to determine the exact type of hearing loss and administer proper treatment. However, the small number of...
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Automated measurement method for assessing thermal-dependent electronic characteristics of thin boron-doped diamond-graphene nanowall structures
PublikacjaThis paper investigates the electrical properties of boron-doped diamond-graphene (B:DG) nanostructures, focusing on their semiconductor characteristics. These nanostructures are synthesized on fused silica glass and Si wafer substrates to compare their behaviour on different surfaces. A specialized measurement system, incorporating Python-automated code, was developed for an in-depth analysis of electronic properties under various...
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Automated Parking Management for Urban Efficiency: A Comprehensive Approach
PublikacjaEffective parking management is essential for ad-dressing the challenges of traffic congestion, city logistics, and air pollution in densely populated urban areas. This paper presents an algorithm designed to optimize parking management within city environments. The proposed system leverages deep learning models to accurately detect and classify street elements and events. Various algorithms, including automatic segmentation of...
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Automatic Correction of Non-Anechoic Antenna Measurements Using Complex Morlet Wavelets
PublikacjaReal-world performance of antennas is normally tested in anechoic chambers (ACs). Alternatively, experimental validation can be performed in non-anechoic environments and refined in the course of post-processing. Unfortunately, the existing methods are difficult to setup and prone to failure. In this letter, a wavelet-based framework for correction of non-anechoic antenna measurements has been proposed. The method involves automatic...
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Beam Steerable MIMO Antenna Based on Conformal Passive Reflectarray Metasurface for 5G Millimeter-Wave Applications
PublikacjaA conformal reflectarray fed by a dual-band multiple-input multiple-output (MIMO) antenna is proposed for low-cost beam steering applications in 5G Millimeter-wave frequency bands. The beam steering is accomplished by selecting a specific port in the MIMO antenna. Each MIMO port is associated with a beam that points in a different direction due to a conformal reflectarray. This novel reflectarray antenna design has the advantages...
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Bi-GRU-APSO: Bi-Directional Gated Recurrent Unit with Adaptive Particle Swarm Optimization Algorithm for Sales Forecasting in Multi-Channel Retail
PublikacjaIn the present scenario, retail sales forecasting has a great significance in E-commerce companies. The precise retail sales forecasting enhances the business decision making, storage management, and product sales. Inaccurate retail sales forecasting can decrease customer satisfaction, inventory shortages, product backlog, and unsatisfied customer demands. In order to obtain a better retail sales forecasting, deep learning models...
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Bimodal deep learning model for subjectively enhanced emotion classification in films
PublikacjaThis research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....
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Bounding conditional entropy of bipartite states with Bell operators
PublikacjaQuantum information theory explores numerous properties that surpass classical paradigms, offering novel applications and benefits. Among these properties, negative conditional von Neumann entropy (CVNE) is particularly significant in entangled quantum systems, serving as an indicator of potential advantages in various information-theoretic tasks, despite its indirect observability. In this paper, we investigate the relationship...
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Category Adaptation Meets Projected Distillation in Generalized Continual Category Discovery
Publikacja"Generalized Continual Category Discovery (GCCD) tackles learning from sequentially arriving, partially labeled datasets while uncovering new categories. Traditional methods depend on feature distillation to prevent forgetting the old knowledge. However, this strategy restricts the model’s ability to adapt and effectively distinguish new categories. To address this, we introduce a novel technique integrating a learnable projector...
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Catheter-induced coronary artery and aortic dissections. A study of the mechanisms, risk factors, and propagation causes
PublikacjaBackground: Only the incidence, management, and prognosis of catheter-induced coronary artery and aortic dissections have been systematically studied until now. We sought to evaluate their mechanisms, risk factors, and propagation causes. Methods: Electronic databases containing 76,104 procedures and complication registries from 2000– –2020 were searched and relevant cineangiographic studies adjudicated. Results: Ninety-six dissections...
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Celowe zanieczyszczanie pilotów w łączu w górę w interfejsie 5G NR
PublikacjaReferat poświęcono zagadnieniu zakłócania sygnałów pilotowych w interfejsie radiowym 5G NR. Przedstawiono charakterystykę sygnału referencyjnego DMRS oraz uwarunkowania możliwości jego selektywnego zakłócenia. Opisano schemat transmisji w kanale fizycznym PUSCH, zaimplementowany w oprogramowaniu Sionna. Zaprezen-towano model symulacyjny oraz założenia badań wpływu zanieczyszczenia pilotów na jakość transmisji. Przedsta-wiono wyniki...
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Circularly Polarized Metalens Antenna Design for 5G NR Sub-6 GHz Communication Systems
Publikacja5G NR (new radio) FR1 range refers to as Sub-6GHz band (410MHz to 7125MHz and 3.4GHz to 6GHz). In this paper, the frequency range of interest is from 3.4 to 6GHz, as many cellular companies are focusing on this Sub-6GHz band. A wideband circularly polarized (CP) antenna radiator is designed with diamond shape patches, fed by a microstrip line at the bottom through a rectangular shape wide slot on a ground plane. The proposed CP...
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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublikacjaCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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CNN-CLFFA: Support Mobile Edge Computing in Transportation Cyber Physical System
PublikacjaIn the present scenario, the transportation Cyber Physical System (CPS) improves the reliability and efficiency of the transportation systems by enhancing the interactions between the physical and cyber systems. With the provision of better storage ability and enhanced computing, cloud computing extends transportation CPS in Mobile Edge Computing (MEC). By inspecting the existing literatures, the cloud computing cannot fulfill...
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Compact Substrate-Integrated Hexagonal Cavity-Backed Self-Hexaplexing Antenna for Sub-6 GHz Applications
PublikacjaA self-multiplexing SIW antenna based on hexagonal SIW cavity is proposed. The self-hexaplexing antenna consists of different sizes of resonating elements, which provide the hexaband operations. The antenna resonates at 5 GHz, 5.17 GHz, 5.32 GHz, 5.53 GHz, 5.62 GHz, and 5.72 GHz by employing different slot lengths between the resonating elements. The proposed antenna provides the individual tunable characteristics of the operating...
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Comparison of 3D Point Cloud Completion Networks for High Altitude Lidar Scans of Buildings
PublikacjaHigh altitude lidar scans allow for rapid acquisition of big spatial data representing entire city blocks. Unfortunately, the raw point clouds acquired by this method are largely incomplete due to object occlusions and restrictions in scanning angles and sensor resolution, which can negatively affect the obtained results. In recent years, many new solutions for 3D point cloud completion have been created and tested on various objects;...
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Comparison of Deep Neural Network Learning Algorithms for Mars Terrain Image Segmentation
PublikacjaThis paper is dedicated to the topic of terrain recognition on Mars using advanced techniques based on the convolutional neural networks (CNN). The work on the project was conducted based on the set of 18K images collected by the Curiosity, Opportunity and Spirit rovers. The data were later processed by the model operating in a Python environment, utilizing Keras and Tensorflow repositories. The model benefits from the pretrained...
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Comparison of Doppler Effect Estimation Methods for MFSK Transmission in Multipath Hydroacoustic Channel
PublikacjaUnderwater wireless communication remains a challenging topic, particularly for applications such as wreck penetration where multipath and Doppler effects are very intense. These effects are becoming even more difficult to mitigate for fast data transmission systems that utilize wideband signals. Due to the low propagation speed of acoustic wave in the water, there is a significant difference between the Doppler shift for lower...
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Continuous Biomedical Monitoring in VR Scenarios of Socially Smart and Safe Autonomous Vehicle Interaction
PublikacjaPedestrians, as vulnerable road users, pose safety challenges for autonomous vehicles (AVs). Their behavior, often unpredictable and subject to change, complicates AV-pedestrian interactions. To address this uncertainty, AV s can enhance safety by communicating their planned trajectories to pedestrians. In this research, we explore the interaction between pedestrians and autonomous vehicles within an industrial environment, focusing...
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Cost-effective methods of fabricating thin rare-earth element layers on SOC interconnects based on low-chromium ferritic stainless steel and exposed to air, humidified air or humidified hydrogen atmospheres
PublikacjaMost oxidation studies involving interconnects are conducted in air under isothermal conditions, but during real-life solid oxide cell (SOC) operation, cells are also exposed a mixture of hydrogen and water vapor. For this study, an Fe–16Cr low-chromium ferritic stainless steel was coated with different reactive element oxides – Gd2O3, CeO2, Ce0.9Y0.1O2 – using an array of methods: dip coating, electrodeposition and spray pyrolysis....
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Cost-Efficient Globalized Parameter Optimization of Microwave Components through Response-Feature Surrogates and Nature-Inspired Metaheuristics
PublikacjaDesign of contemporary microwave devices predominantly utilizes computational models, including both circuit simulators, and full-wave electromagnetic (EM) evaluation. The latter constitutes the sole generic way of rendering accurate assessment of the system outputs that considers phenomena such as cross-coupling or radiation and dielectric losses. Consequently, for reliability reasons, the final tuning of microwave device parameters...
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublikacjaAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublikacjaDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Crank–Nicolson FDTD Method in Media Described by Time-Fractional Constitutive Relations
PublikacjaIn this contribution, we present the Crank-Nicolson finite-difference time-domain (CN-FDTD) method, implemented for simulations of wave propagation in media described by time-fractional (TF) constitutive relations. That is, the considered constitutive relations involve fractional-order (FO) derivatives based on the Grünwald-Letnikov definition, allowing for description of hereditary properties and memory effects of media and processes....
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CuMn1.7Fe0.3O4 – RE2O3 (RE=Y, Gd) bilayers as protective interconnect coatings for Solid Oxide Cells
PublikacjaEfficient replacement of materials based on critical elements such as cobalt is one of the greatest challenges facing the field of solid oxide cells. New generation materials, free of cobalt show potential to replace conventional materials. However, these materials are characterized by poor ability to block chromium diffusion. This article described the study of CuMn1.7Fe0.3O4 (CMFO) spinel combined with single metal oxide (Y2O3...
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Data Domain Adaptation in Federated Learning in the Breast Mammography Image Classification Problem
PublikacjaWe are increasingly striving to introduce modern artificial intelligence techniques in medicine and elevate medical care, catering to both patients and specialists. An essential aspect that warrants concurrent development is the protection of personal data, especially with technology's advancement, along with addressing data disparities to ensure model efficacy. This study assesses various domain adaptation techniques and federated...
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Data fusion of sparse, heterogeneous, and mobile sensor devices using adaptive distance attention
PublikacjaIn environmental science, where information from sensor devices are sparse, data fusion for mapping purposes is often based on geostatistical approaches. We propose a methodology called adaptive distance attention that enables us to fuse sparse, heterogeneous, and mobile sensor devices and predict values at locations with no previous measurement. The approach allows for automatically weighting the measurements according to a priori...
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Data on LEGO sets release dates and worldwide retail prices combined with aftermarket transaction prices in Poland between June 2018 and June 2023
PublikacjaThe dataset contains LEGO bricks sets item count and pricing history for AI-based set pricing prediction. The data spans the timeframe from June 2018 to June 2023. The data was obtained from three sources: Brickset.com (LEGO sets retail prices, release dates, and IDs), Lego.com official web page (ID number of each set that was released by Lego, its retail prices, the current status of the set) and promoklocki.pl web page (the retail...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublikacjaThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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D-Band High Gain Planer Slot Array Antenna using Gap Waveguide Technology
PublikacjaA D-band high gain slot array antenna with corporate-fed distribution network based on gap waveguide structures is proposed at 140GHz. To overcome the fabrication challenges at such high frequency, the gap waveguide technology is deployed in which good electrical contact between different parts of the waveguide structure is not required. The proposed sub-array has four radiating slots that are excited by a groove gap cavity and...
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Decoding imagined speech for EEG-based BCI
PublikacjaBrain–computer interfaces (BCIs) are systems that transform the brain's electrical activity into commands to control a device. To create a BCI, it is necessary to establish the relationship between a certain stimulus, internal or external, and the brain activity it provokes. A common approach in BCIs is motor imagery, which involves imagining limb movement. Unfortunately, this approach allows few commands. As an alternative, this...
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Decoding soundscape stimuli and their impact on ASMR studies
PublikacjaThis paper focuses on extracting and understanding the acoustical features embedded in the soundscape used in ASMR (Autonomous Sensory Meridian Response) studies. To this aim, a dataset of the most common sound effects employed in ASMR studies is gathered, containing whispering stimuli but also sound effects such as tapping and scratching. Further, a comparative analytical survey is performed based on various acoustical features...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublikacjaBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Deep Learning-Based Cellular Nuclei Segmentation Using Transformer Model
PublikacjaAccurate segmentation of cellular nuclei is imperative for various biological and medical applications, such as cancer diagnosis and drug discovery. Histopathology, a discipline employing microscopic examination of bodily tissues, serves as a cornerstone for cancer diagnosis. Nonetheless, the conventional histopathological diagnosis process is frequently marred by time constraints and potential inaccuracies. Consequently, there...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublikacjaThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Deep Video Multi-task Learning Towards Generalized Visual Scene Enhancement and Understanding
PublikacjaThe goal of this thesis was to develop efficient video multi-task convolutional architectures for a range of diverse vision tasks, on RGB scenes, leveraging i) task relationships and ii) motion information to improve multi-task performance. The approach we take starts from the integration of diverse tasks within video multi-task learning networks. We present the first two datasets of their kind in the existing literature, featuring...
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Design and Experimental Validation of a Metamaterial-Based Sensor for Microwave Imaging in Breast, Lung, and Brain Cancer Detection
PublikacjaThis study proposes an innovative geometry of a microstrip sensor for high-resolution microwave imaging (MWI). The main intended application of the sensor is early detection of breast, lung, and brain cancer. The proposed design consists of a microstrip patch antenna fed by a coplanar waveguide with a metamaterial layer-based lens implemented on the back side, and an artificial magnetic conductor (AMC) realized on as a separate...
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Design and experimental verification of multi-layer waveguide using pin/hole structure
PublikacjaThis study presents a novel technique for minimizing RF leakage in metallic hollow waveguides fabricated using the multilayer split-block method. By integrating a pin/hole wall into the split-block multilayers, a substantial reduction of RF leakage can be achieved while reducing the circuit size and mitigating the performance variations. To validate the proposed approach, a slot antenna fed by single ridge waveguide has been prototyped...