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Faculty of Electronics, Telecommunications and Informatics
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Catalog Publications
Year 2023
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Combining MUSHRA Test and Fuzzy Logic in the Evaluation of Benefits of Using Hearing Prostheses
PublicationAssessing the effectiveness of hearing aid fittings based on the benefits they provide is crucial but intricate. While objective metrics of hearing aids like gain, frequency response, and distortion are measurable, they do not directly indicate user benefits. Hearing aid performance assessment encompasses various aspects, such as compensating for hearing loss and user satisfaction. The authors suggest enhancing the widely used...
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Compact Quasi-Elliptic-Type Inline Waveguide Bandpass Filters With Nonlinear Frequency-Variant Couplings
PublicationThis work presents the design techniques to synthesize a class of compact inline quasi-elliptic-type waveguide cavity bandpass filters based on novel nonlinear frequency-variant couplings (NFVCs). These highly dispersive frequency-variant couplings (FVCs) are realized by means of a pair of partial-height posts that are placed at the junctions between every two cavity resonators. Each NFVC produces a transmission pole in between...
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Comparing Apples and Oranges: A Mobile User Experience Study of iOS and Android Consumer Devices
PublicationWith the rapid development of wireless networks and the spread of broadband access around the world, the number of active mobile user devices continues to grow. Each year more and more terminals are released on the market, with the smartphone being the most popular among them. They include low-end, mid-range, and of course high-end devices, with top hardware specifications. They do vary in build quality, utilized type of material,...
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Comparison of Selected Neural Network Models Used for Automatic Liver Tumor Segmentation
PublicationAutomatic and accurate segmentation of liver tumors is crucial for the diagnosis and treatment of hepatocellular carcinoma or metastases. However, the task remains challenging due to imprecise boundaries and significant variations in the shape, size, and location of tumors. The present study focuses on tumor segmentation as a more critical aspect from a medical perspective, compared to liver parenchyma segmentation, which is the...
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Comparison of the Ability of Neural Network Model and Humans to Detect a Cloned Voice
PublicationThe vulnerability of the speaker identity verification system to attacks using voice cloning was examined. The research project assumed creating a model for verifying the speaker’s identity based on voice biometrics and then testing its resistance to potential attacks using voice cloning. The Deep Speaker Neural Speaker Embedding System was trained, and the Real-Time Voice Cloning system was employed based on the SV2TTS, Tacotron,...
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Complexity Issues on of Secondary Domination Number
PublicationIn this paper we study the computational complexity issues of the problem of secondary domination (known also as (1, 2)-domination) in several graph classes. We also study the computational complexity of the problem of determining whether the domination and secondary domination numbers are equal. In particular, we study the influence of triangles and vertices of degree 1 on these numbers. Also, an optimal algorithm for finding...
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Computationally-Efficient Statistical Design and Yield Optimization of Resonator-Based Notch Filters Using Feature-Based Surrogates
PublicationModern microwave devices are designed to fulfill stringent requirements pertaining to electrical performance, which requires, among others, a meticulous tuning of their geometry parameters. When moving up in frequency, physical dimensions of passive microwave circuits become smaller, making the system performance increasingly susceptible to manufacturing tolerances. In particular, inherent inaccuracy of fabrication processes affect...
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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublicationIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....
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Constrained aerodynamic shape optimization using neural networks and sequential sampling
PublicationAerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...
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Continuous blood pressure monitoring by photoplethysmography - signal preprocessing requirements based on blood flow modelling
PublicationObjective. The aim of the study is to investigate the effect of the signal sampling frequency and low-pass filtering on the accuracy of the localisation of the fiducial points of the photoplethysmographic signal (PPG), and thus on the estimation of the blood pressure (i.e. the accuracy of the estimation). Approach. Statistical analysis was performed on 3,799 data samples taken from a publicly available database. Four PPGfiducial...
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Cost-Efficient Two-Level Modeling of Microwave Passives Using Feature-Based Surrogates and Domain Confinement
PublicationA variety of surrogate modelling techniques has been utilized in high-frequency design over the last two decades. Yet, the curse of dimensionality still poses a serious challenge in setting up re-liable design-ready surrogates of modern microwave components. The difficulty of the model-ing task is only aggravated by nonlinearity of circuit responses. Consequently, constructing a practically usable surrogate model, valid across...
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Cross-Lingual Knowledge Distillation via Flow-Based Voice Conversion for Robust Polyglot Text-to-Speech
PublicationIn this work, we introduce a framework for cross-lingual speech synthesis, which involves an upstream Voice Conversion (VC) model and a downstream Text-To-Speech (TTS) model. The proposed framework consists of 4 stages. In the first two stages, we use a VC model to convert utterances in the target locale to the voice of the target speaker. In the third stage, the converted data is combined with the linguistic features and durations...
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublicationIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Dataset Related Experimental Investigation of Chess Position Evaluation Using a Deep Neural Network
PublicationThe idea of training Articial Neural Networks to evaluate chess positions has been widely explored in the last ten years. In this paper we investigated dataset impact on chess position evaluation. We created two datasets with over 1.6 million unique chess positions each. In one of those we also included randomly generated positions resulting from consideration of potentially unpredictable chess moves. Each position was evaluated...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Dekodowanie kodów iterowanych z użyciem sieci neuronowej
PublicationNadmiarowe kody iterowane są jedną z prostych metod pozyskiwania długich kodów korekcyjnych zapewniających dużą ochronę przed błędami. Jednocześnie, chociaż ich podstawowy iteracyjny dekoder jest prosty koncepcyjnie oraz łatwy w implementacji, to nie jest on rozwiązaniem optymalnym. Poszukując alternatywnych rozwiązań zaproponowano, przedstawioną w pracy, strukturę dekodera tego typu kodów wspomaganą przez sieci neuronowe. Zaproponowane...
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Depolarisation Model for a BAN Indoor Scenario
PublicationIn this paper, an analysis of depolarisation in Body Area Networks for Body-to-Infrastructure communications based on a measurement campaign in the 5.8 GHz band in an indoor environment is performed. Measurements were made with an offbody antenna transmitting linearly polarised signals and dualpolarised receiving antennas carried by the user on the body. A Normal Distribution with a mean of 2.0 dB and a standard deviation of 4.3...
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Design and Optimization of a Compact Super-Wideband MIMO Antenna with High Isolation and Gain for 5G Applications
PublicationThis paper presents a super-wideband multiple-input multiple-output (SWB MIMO) antenna with low profile, low mutual coupling, high gain and compact size for microwave and millimeter wave (mm-wave) fifth-generation (5G) applications. A single antenna is a simple elliptical-square shape with a small physical size of 20 × 20 × 0.787 mm3. The combination of both square and elliptical shapes results in an exceptionally broad impedance...
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Design and Optimization of Metamaterial-Based 5G Millimeter Wave Antenna for Gain Enhancement
PublicationIn this brief, a low profile, broadband, high-gain antenna array based on optimized metamaterials (MMs) with dual-beam radiation is reported for 5G millimeters wave (mm-wave) applications. The design is a simple bow tie operating at a 5G band of 28 GHz. It consists of two bow ties with substrate integrated waveguide (SIW)-based power splitter. A broad impedance bandwidth of 26.3−29.8 GHz is obtained by appropriately combining the...
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Design of compact self-quintuplexing antenna with high-isolation for penta-band applications
PublicationThis article presents a novel compact self-quintuplexing antenna architecture based on a substrate-integrated rectangular cavity (SIRC) for pentaband applications. The proposed self-quintuplexing antenna is constructed by employing an SIRC, one Pi-shaped slot (PSS), one T-shaped slot (TSS), and five 50Ω microstrip feedlines. The PSS and TSS are engraved on the top of the SIRC to create five radiating patches, which are excited...
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Design of Frequency-Reconfigurable Branch-Line Crossover Using Rectangular Dielectric Channels
PublicationThis paper presents an efficient yet straightforward passive reconfiguration technique to tune the operating frequency of a branch-line crossover (BLCO). The underlying principle is to fill rectangular dielectric channels (RDCs) prepared beforehand with either air or materials of different relative permittivity. Two configurations (one RDC and three RDCs in each arm) of the branch-line crossover are employed to estimate the tunability...
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Design of novel highly sensitive sensors for crack detection in metal surfaces: theoretical foundation and experimental validation
PublicationThe application of different types of microwave resonators for sensing cracks in metallic structures has been subject of many studies. While most studies have been focused on improving the sensitivity of planar crack sensors, the theoretical foundation of the topic has not been treated in much detail. The major objective of this study is to perform an exhaustive study of the principles and theoretical foundations for crack sensing...
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Detecting Lombard Speech Using Deep Learning Approach
PublicationRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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Detecting type of hearing loss with different AI classification methods: a performance review
PublicationHearing is one of the most crucial senses for all humans. It allows people to hear and connect with the environment, the people they can meet and the knowledge they need to live their lives to the fullest. Hearing loss can have a detrimental impact on a person's quality of life in a variety of ways, ranging from fewer educational and job opportunities due to impaired communication to social withdrawal in severe situations. Early...
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Detection of Water on Road Surface with Acoustic Vector Sensor
PublicationThis paper presents a new approach to detecting the presence of water on a road surface, employing an acoustic vector sensor. The proposed method is based on sound intensity analysis in the frequency domain. Acoustic events, representing road vehicles, are detected in the sound intensity signals. The direction of the incoming sound is calculated for the individual spectral components of the intensity signal, and the components...
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Development of iron doped strontium titanates as oxygen electrode for solid oxide fuel cells
PublicationProducing efficient solid oxide fuel cells (SOFC) without the use of harmful elements is one of the current challenges. Increasing the safety of people and reducing production costs is possible, among others, thanks to the use of iron doped strontium titanates as porous oxygen electrodes. In this thesis, the results of research on iron doped strontium titanates as potential oxygen electrodes for SOFC are presented. The research...
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Development of novel optoelectronic sensory structures utilising colour centres in nanodiamonds and their interactions with analytes
PublicationThe goal of this dissertation was to develop and assess surface modifications of fluorescent nanodiamonds (NDs) for optical sensing. Three modification routes were tested, each aimed at a different application. Modification with poly-L-lysine (pLys) was verified for optical sensing of pH via an interrelationship between electrically negative (NV¯) and neutral (NV0) nitrogen-vacancy centres. Immobilisation of Ochratoxin A (OTA),...
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Development of the System Assurance Reference Model for Generating Modular Assurance Cases
PublicationAssurance 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. Larger assurance cases are usually divided into modules to manage the complexity and distribute the work. Each of the modules is developed to address specific goals allocated to the specific objects i.e. components of the...
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DevEmo—Software Developers’ Facial Expression Dataset
PublicationThe COVID-19 pandemic has increased the relevance of remote activities and digital tools for education, work, and other aspects of daily life. This reality has highlighted the need for emotion recognition technology to better understand the emotions of computer users and provide support in remote environments. Emotion recognition can play a critical role in improving the remote experience and ensuring that individuals are able...
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Digital Transformation and Its Influence on Sustainable Manufacturing and Business Practices
PublicationThe paper focuses on the relationship between businesses and digital transformation, and how digital transformation has changed manufacturing in several ways. Aspects like Cloud Computing, vertical and horizontal integration, data communication, and the internet have contributed to sustainable manufacturing by decentralizing supply chains. In addition, digital transformation inventions such as predictive analysis and big data analytics...
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Dimensionality-Reduced Antenna Modeling with Stochastically Established Constrained Domain
PublicationOver the recent years, surrogate modeling methods have become increasingly widespread in the design of contemporary antenna systems. On the one hand, it is associated with a growing awareness of numerical optimization, instrumental in achieving high-performance structures. On the other hand, considerable computational expenses incurred by massive full-wave electromagnetic (EM) analyses, routinely employed as a major design tool,...
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Direct determination of paraquat herbicide by square-wave voltammetry by two-step transfer mechanism at heterogeneous boron-doped carbon nanowall electrodes
PublicationBoron-doped carbon nanowalls (B:CNW) versus boron-doped diamond (BDD) materials were investigated for the effective electrochemical detection of highly toxic herbicide paraquat (PQ). Depending on the surface morphology and functional groups of BDD and B:CNWs, the electrochemical absorption and detection of the target analyte PQ revealed different detection mechanisms. The surface absorption mechanism was mainly observed for BDD,...
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Direct electrical brain stimulation of human memory: lessons learnt and future perspectives
PublicationModulation of cognitive functions supporting human declarative memory is one of the grand challenges of neuroscience, and of vast importance for a variety of neuropsychiatric, neurodegenerative and neurodevelopmental diseases. Despite a recent surge of successful attempts at improving performance in a range of memory tasks, the optimal approaches and parameters for memory enhancement have yet to be determined. On a more fundamental...
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Discovering relationships between data in an enterprise information system using log analysis
PublicationEnterprise systems are inherently complex and maintaining their full, up-to-date overview poses a serious challenge to the enterprise architects’ teams. This problem encourages the search for automated means of discovering knowledge about such systems. An important aspect of this knowledge is understanding the data that are processed by applications and their relationships. In our previous work, we used application logs of an enterprise...
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Discrete identification of continuous non-linear and non-stationary dynamical systems that is insensitive to noise correlation and measurement outliers
PublicationThe paper uses specific parameter estimation methods to identify the coefficients of continuous-time models represented by linear and non-linear ordinary differential equations. The necessary approximation of such systems in discrete time in the form of utility models is achieved by the use of properly tuned `integrating filters' of the FIR type. The resulting discrete-time descriptions retain the original continuous parameterization...
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Discriminating macromolecular interactions based on an impedimetric fingerprint supported by multivariate data analysis for rapid and label-free Escherichia coli recognition in human urine
PublicationThis manuscript presents a novel approach to address the challenges of electrode fouling and highly complex electrode nanoarchitecture, which are primary concerns for biosensors operating in real environments. The proposed approach utilizes multiparametric impedance discriminant analysis (MIDA) to obtain a fingerprint of the macromolecular interactions on flat glassy carbon surfaces, achieved through self-organized, drop-cast,...
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Distinct hippocampal-prefrontal neural assemblies coordinate memory encoding, maintenance, and recall
PublicationShort-term memory enables incorporation of recent experience into subsequent decision-making. This processing recruits both the prefrontal cortex and hippocampus, where neurons encode task cues, rules, and outcomes. However, precisely which information is carried when, and by which neurons, remains unclear. Using population decoding of activity in rat medial prefrontal cortex (mPFC) and dorsal hippocampal CA1, we confirm that mPFC...
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Dynamic GPU power capping with online performance tracing for energy efficient GPU computing using DEPO tool
PublicationGPU accelerators have become essential to the recent advance in computational power of high- performance computing (HPC) systems. Current HPC systems’ reaching an approximately 20–30 mega-watt power demand has resulted in increasing CO2 emissions, energy costs and necessitate increasingly complex cooling systems. This is a very real challenge. To address this, new mechanisms of software power control could be employed. In this...
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Edge and Pair Queries-Random Graphs and Complexity
PublicationWe investigate two types of query games played on a graph, pair queries and edge queries. We concentrate on investigating the two associated graph parameters for binomial random graphs, and showing that determining any of the two parameters is NP-hard for bounded degree graphs.
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Edge coloring of graphs of signed class 1 and 2
PublicationRecently, Behr (2020) introduced a notion of the chromatic index of signed graphs and proved that for every signed graph (G, σ) it holds that ∆(G) ≤ χ′(G,σ) ≤ ∆(G) + 1, where ∆(G) is the maximum degree of G and χ′ denotes its chromatic index. In general, the chromatic index of (G, σ) depends on both the underlying graph G and the signature σ. In the paper we study graphs G for which χ′(G, σ) does not depend on σ. To this aim we...
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Effective Air Quality Prediction Using Reinforced Swarm Optimization and Bi-Directional Gated Recurrent Unit
PublicationIn the present scenario, air quality prediction (AQP) is a complex task due to high variability, volatility, and dynamic nature in space and time of particulates and pollutants. Recently, several nations have had poor air quality due to the high emission of particulate matter (PM2.5) that affects human health conditions, especially in urban areas. In this research, a new optimization-based regression model was implemented for effective...
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Effects of Storing Flux-Cored Wires under Various Conditions
PublicationWelding processes involving the use of flux-cored wires are becoming increasingly popular, particularly in shipbuilding as well as in off-shore and civil engineering. The article presents characteristics of the welding process, its areas of application as well as advantages and disadvantages (e.g. necessity of ensuring appropriate conditions for the storage of filler metal wires). The satisfaction of quality-related requirements...
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Effects of thermal history on the performance of low-temperature solid oxide fuel cells with Sm0.2Ce0.8O2-δ electrolyte and LiNi0.81Co0.15Al0.04O2 electrodes
PublicationIn this study, low-temperature solid oxide fuel cells with an ∼560 μm thick Sm0.2Ce0.8O2−δ (SDC) electrolyte and ∼890 μm thick LiNi0.81Co0.15Al0.04O2−δ (NCAL) electrodes are constructed and characterized under three experimental conditions. The cell with an NCAL cathode pre-reduced under an H2 atmosphere at 550 °C presents the best electrochemical performance. This is ascribed to facts that the reduction reaction generating Ni–Co...
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Efficient parallel implementation of crowd simulation using a hybrid CPU+GPU high performance computing system
PublicationIn the paper we present a modern efficient parallel OpenMP+CUDA implementation of crowd simulation for hybrid CPU+GPU systems and demonstrate its higher performance over CPU-only and GPU-only implementations for several problem sizes including 10 000, 50 000, 100 000, 500 000 and 1 000 000 agents. We show how performance varies for various tile sizes and what CPU–GPU load balancing settings shall be preferred for various domain...
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Efficient uncertainty quantification using sequential sampling-based neural networks
PublicationUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
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Electro-optical transducer based on indium-tin-oxide-coated optical fiber for analysis of ionized media
PublicationThe paper introduces a concept of an optical fiber based electro-optical transducer for monitoring of ionized media, such as low-temperature plasma. It utilizes optical fiber with a section of a core coated with tailored indium tin oxide (ITO) thin film and thus combines the optical phenomena of lossy-mode resonance (LMR) with the electrostatic probe. ITO is an optically transparent and electrically conductive material and if its...
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Empirical analysis of tree-based classification models for customer churn prediction
PublicationCustomer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...
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EMULACJA ŚRODOWISKA DLA ZASTOSOWANIA PROTOKOŁU IN-BAND NETWORK TELEMETRY
PublicationOkreślenie jakości obsługi strumieni pakietów w sieci przełączników wymaga odpowiedniego środowiska badawczego w którym prowadzi się doświadczenia i pomiary wybranych wielkości. Protokół In-band Network Telemetry jest jednym z narzędzi, które można wykorzystać do realizacji tych zadań. W pracy zaproponowano zwirtualizowane środowisko badawcze w którym można emulować sieć przełączników programowalnych w języku P4 wraz z implementacją...