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Faculty of Electronics, Telecommunications and Informatics
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Catalog Publications
Year 2024
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Comparison of ambisonic and object-based spatial sound recording techniques
PublicationThis article presents a comparison of spatial sound recording techniques based on scene-based and object-based audio. The study aimed to make different mixes from a recording which consists of a higher-order ambisonic microphone and spot microphones. For spot microphones simple ambisonics encoding was used, which allows panning the individual channels on an ambisonic sphere as objects. Recordings were combined in various variants...
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Comparison of Deep Learning Approaches in Classification of Glacial Landforms
PublicationGlacial landforms, created by the continuous movements of glaciers over millennia, are crucial topics in geomorphological research. Their systematic analysis affords invaluable insights into past climatic oscillations and augments understanding of long-term climate change dynamics. The classification of these types of terrain traditionally depends on labor-intensive manual or semi-automated methods. However, the emergence of automated...
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Comparison of Deep Neural Network Learning Algorithms for Mars Terrain Image Segmentation
PublicationThis 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
PublicationUnderwater 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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Connectivity Improvement in Wireless Sensor Networks Using ESPAR Antennas with Dielectric Overlays
PublicationThis article presents an electrically steerable parasitic array radiator (ESPAR) switched beam antenna with a dielectric overlay to miniaturize the antenna and modify the radiation pattern in the vertical plane. The antenna is intended for a gateway in a wireless sensor network (WSN) and is located on the ceiling of a room. Because the ESPAR antenna consists of an array of vertical monopoles, there is a deep minimum in the radiation...
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Continuous Biomedical Monitoring in VR Scenarios of Socially Smart and Safe Autonomous Vehicle Interaction
PublicationPedestrians, 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
PublicationMost 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
PublicationDesign 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
PublicationAir 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
PublicationDesigning 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
PublicationIn 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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C-reactive protein (CRP) evaluation in human urine using optical sensor supported by machine learning
PublicationThe rapid and sensitive indicator of inflammation in the human body is C-Reactive Protein (CRP). Determination of CRP level is important in medical diagnostics because, depending on that factor, it may indicate, e.g., the occurrence of inflammation of various origins, oncological, cardiovascular, bacterial or viral events. In this study, we describe an interferometric sensor able to detect the CRP level for distinguishing between...
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CuMn1.7Fe0.3O4 – RE2O3 (RE=Y, Gd) bilayers as protective interconnect coatings for Solid Oxide Cells
PublicationEfficient 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
PublicationWe 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
PublicationIn 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
PublicationThe 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
PublicationThe 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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Decision-making under stress: A psychological and neurobiological integrative model
PublicationUnderstanding the impact of stress on cognitive processes, particularly decision-making, is crucial as it underpins behaviors essential for survival. However, research in this domain has yielded disparate results, with inconsistencies evident across stress-induction paradigms and drug administration protocols designed to investigate specific stress pathways or neuromodulators. Building upon empirical studies, this research identifies...
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Decoding imagined speech for EEG-based BCI
PublicationBrain–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
PublicationThis 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
PublicationBiometric 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
PublicationAccurate 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
PublicationThe 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
PublicationThe 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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Degradation mechanisms and protective coatings for ferritic stainless-steel interconnects of solid oxide fuel cells: A review
PublicationFerritic stainless steels (FSSs) are promising interconnect materials for solid oxide fuel cells (SOFCs). However, FSSs undergo fast thermal-oxidation during SOFC operation, generating poorly-conductive oxide scales and volatile chromium-oxides detrimental to cathodes. Developing protective coatings is crucial for inhibiting degradation of FSS-interconnects. This article starts with a brief discussion of the oxidation behavior...
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Design and Experimental Validation of a Metamaterial-Based Sensor for Microwave Imaging in Breast, Lung, and Brain Cancer Detection
PublicationThis 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
PublicationThis 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...
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Design and Implementation of Multi-Band Reflectarray Metasurface for 5G Millimeter Wave Coverage Enhancement
PublicationA compact low-profile multi-band millimeter-wave (mm-wave) reflectarray metasurface design is presented for coverage enhancement in 5G and beyond cellular communication. The proposed single-layer metasurface exhibits a stable reflection response under oblique incidence angles of up to 60o at 24 and 38 GHz, and transmission response at 30 GHz, effectively covering the desired 5G mm-wave frequency bands. The proposed reflectarray...
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Design and Optimization of Metamaterial-based Highly-isolated MIMO Antenna with High Gain and Beam Tilting Ability for 5G Millimeter Wave Applications
PublicationThis paper presents a wideband multiple-input multiple-output (MIMO) antenna with high gain and isolation, as well as beam tilting capability, for 5G millimeter wave (MMW) applications. A single bow-tie antenna fed by a substrate-integrated waveguide (SIW) is proposed to cover the 28 GHz band (26.5–29.5 GHz) with a maximum gain of 6.35 dB. To enhance the gain, H-shaped metamaterial (MM)-based components are incorporated into the...
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Design and Validation of Ultra-Compact Metamaterial-Based Biosensor for Non-Invasive Cervical Cancer Diagnosis in Terahertz Regime
PublicationCervical cancer belongs to the most dangerous types of cancers posing considerable threat to women’s survival. It is most often diagnosed in the advanced stages as precancerous lesions are often symptom-free and difficult to identify. Microwave imaging, especially in terahertz (THz) range, is a convenient and noninvasive cancer detection tool. It enables characterization of biological tissues and discrimination between healthy...
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Design of a Cellular Dual-Band Sticker Antenna for Thickness-Independent 3D-Printed Substrates
PublicationAdditive manufacturing technology provides high flexibility in designing custom enclosures for prototype devices such as nodes of distributed sensor networks. Although integration of components is desired from the perspective of sensor mobility, it might negatively affect the performance of radio-connectivity due to couplings between the antenna and system peripherals, as well as other unaccounted effects of the 3D printed enclosure....
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Design of a Wideband High-Gain Monopulse Antenna for X- and Ku-Bands Applications
PublicationThe present study provides a wideband high-gain monopulse antenna based on a dielectric lens operating in X- and Ku-bands, in which a wideband dielectric lens is designed and employed to fulfill the radiation pattern and bandwidth necessities of a monopulse antenna. The proposed configuration has four horns allowing for the simultaneous creation of 1 and 6 designs in two perpendicular planes. The main advantages of the proposed...
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Design of Compact and Wideband Groove Gap Waveguide-Based Directional Couplers
PublicationThis paper proposes a compact cross-shaped groove gap waveguide structure for creating wideband and compact directional couplers with different coupling levels. Groove gap waveguide technology is applied to overcome fabrication challenges of printed and hollow waveguide structures in high frequency bands. The validity of the novel concept is demonstrated through the design and evaluation of several compact broadband directional...
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Designing a high-sensitivity dual-band nano-biosensor based on petahertz MTMs to provide a perfect absorber for early-stage non-melanoma skin cancer diagnostic
PublicationThe purpose of this study is development of a novel high-performance low-Petahertz (PHz) biosensor for non-melanoma skin cancer (NMSC) diagnosis. The presented device is designed to work within a microwave imaging regime, which is a promising alternative to conventional diagnostic methods such as visual examination, dermoscopy, and biopsy. The suggested biosensor incorporates a dual-band perfect absorber (operating bands at 0.909...
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Designing a High-sensitivity Microscale Triple-band Biosensor based on Terahertz MTMs to provide a perfect absorber for Non-Melanoma Skin Cancer diagnostic
PublicationNon-melanoma skin cancer (NMSC) is among the most prevalent forms of cancer originating in the top layer of the skin, with basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) being its primary categories. While both types are highly treatable, the success of treatment hinges on early diagnosis. Early-stage NMSC detection can be achieved through clinical examination, typically involving visual inspection. An alternative,...
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Designing high-performance asymmetric and hybrid energy devices via merging supercapacitive/pseudopcapacitive and Li-ion battery type electrodes
PublicationWe report a strategic development of asymmetric (supercapacitive–pseudocapacitive) and hybrid (supercapacitive/pseudocapacitive–battery) energy device architectures as generation–II electrochemical energy systems. We derived performance-potential estimation regarding the specific power, specific energy, and fast charge–discharge cyclic capability. Among the conceived group, pseudocapacitor–battery hybrid device is constructed with...
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Detecting Objects of Various Categories in Optical Remote Sensing Imagery Using Neural Networks
PublicationThe effective detection of objects in remote sensing images is of great research importance, so recent years have seen a significant progress in deep learning techniques in this field. However, despite much valuable research being conducted, many challenges still remain. A lot of research projects focus on detecting objects of a single category (class), while correctly detecting objects of different categories is much harder. The...
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Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
PublicationIntroduction: Alzheimer’s Disease (AD) is a degenerative brain disorder characterized by cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the mortality rate through slowing down its progression. The prevention and detection of AD is the emerging research topic for many researchers. The structural Magnetic Resonance Imaging (sMRI) is an extensively used imaging technique in detection of AD, because...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublicationCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublicationEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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Developing a Low SNR Resistant, Text Independent Speaker Recognition System for Intercom Solutions - A Case Study
PublicationThis article presents a case study on the development of a biometric voice verification system for an intercom solution, utilizing the DeepSpeaker neural network architecture. Despite the variety of solutions available in the literature, there is a noted lack of evaluations for "text-independent" systems under real conditions and with varying distances between the speaker and the microphone. This article aims to bridge this gap....
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Developing high-performance oxygen electrodes for intermediate solid oxide cells (SOC) prepared by Ce0.8Gd0.2O2−δ backbone infiltration
PublicationGd0.2Ce0.8O 2−δ (GDC) porous backbone infiltration with La0.6Sr0.4CoO3−δ (LSC), PrOx and LSC: PrOx as a composite oxygen electrode for intermediate solid oxide cells are conducted within the scope of this work. Samples were characterized using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), and electrochemical impedance spectroscopy (EIS). A uniform distribution of the infiltrated material inside...
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Development of a Planar LTCC GRIN Lens for 60 GHz Open-Ended Waveguide Antenna
PublicationThis study deals with the design, realization and evaluation of a gradient index lens (GRIN) made of low-temperature cofired ceramic (LTCC) for millimeter-wave communication systems at a frequency of 60 GHz. The LTCC GRIN lens presented here utilizes a radial refractive index profile achieved by varying the dielectric properties within the LTCC structure by punching 100 µm holes in the green LTCC sheets. We present the optimization...
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Development of a Terahertz Metamaterial Micro-Biosensor for Ultrasensitive Multispectral Detection of Early-Stage Cervical Cancer
PublicationThis research introduces an innovative design for a metamaterial-based compact multi-band biosensor aimed at early-stage cervical cancer detection. The device operates within the terahertz (THz) frequency range, specifically from zero to six THz. The proposed sensor architecture features a metamaterial layer composed of a patterned aluminum structure deposited on a polyimide substrate. The primary design objective is to optimize...
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Diagnostics of the Peripheral Artery Disease with use of Glucose Sensor - A Proof of Concept
PublicationIt is estimated that 13% of population over 50 years old suffer from symptomatic or asymptomatic peripheral artery disease (PAD). Ankle-brachial index (ABI) is viewed as a useful parameter in diagnostics of peripheral arterial disease, however screening tests with usage of this method are not advised. Hypoxia causes increase in lactate values and decrease in blood glucose. We hypothesize that the deficit in blood supply to the...
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Diagnostics of the Peripheral Artery Disease with use of Glucose Sensor - A Proof of Concept
PublicationIt is estimated that 13 % of population over 50 years old suffer from symptomatic or asymptomatic peripheral artery disease (PAD). Ankle-brachial index (ABI) is viewed as a useful parameter in diagnostics of peripheral arterial disease, however screening tests with usage of this method are not advised. Hypoxia causes increase in lactate values and...
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Diamond-Based Supercapacitors with Ultrahigh Cyclic Stability Through Dual-Phase MnO2-Graphitic Transformation Induced by High-Dose Mn-Ion Implantation
PublicationWhile occasionally being able to charge and dischargemore quickly than batteries, carbon-based electrochemical supercapacitors(SCs) are nevertheless limited by their simplicity of processing, adjustableporosity, and lack of electrocatalytic active sites for a range of redox reactions.Even SCs based on the most stable form of carbon (sp3carbon/diamond)have a poor energy density and inadequate capacitance retention during longcharge/discharge...
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Divide and not forget: Ensemble of selectively trained experts in Continual Learning
PublicationClass-incremental learning is becoming more popular as it helps models widen their applicability while not forgetting what they already know. A trend in this area is to use a mixture-of-expert technique, where different models work together to solve the task. However, the experts are usually trained all at once using whole task data, which makes them all prone to forgetting and increasing computational burden. To address this limitation,...
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Do stress hormones influence choice? A systematic review of pharmacological interventions on the HPA axis and/or SAM system
PublicationThe hypothalamus–pituitary–adrenal axis (HPA axis) and the sympathetic–adrenal–medullary system (SAM system), two neuroendocrine systems associated with the stress response, have often been implicated to modulate decision-making in various domains. This systematic review summarizes the scientific evidence on the effects of pharmacological HPA axis and SAM system modulation on decision-making. We found 6375 references, of which...
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Domain adaptation for inpainting-based face recognition studies
PublicationRecent inpainting methods have demonstrated im-pressive outcomes in filling missing parts of images, especially for reconstructing facial areas obscured by occlusions. However, studies show that these models are not adequately effective in real-world applications, primarily due to data bias and the distribution of faces in images. This research focuses on domain adaptation of the commonly used Labeled Faces in the Wild (LFW) dataset,...