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Faculty of Electronics, Telecommunications and Informatics
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Catalog Publications
Year 2022
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Aplikacja demonstrująca działanie kodów fontannowych
PublicationIstotną cechą kodów fontannowych jest możliwość odtwarzania nadawanych danych niezależnie od jakości kanału. Wynika to z tego, że kody te nie mają z góry założonej zawartości informacyjnej, a kolejne symbole nadmiarowe są generowane, dopóki jest taka potrzeba. Jest to szczególnie przydatne w transmisjach broadcastowych, bo każdy z odbiorców może zdekodować dane tak wcześnie, na ile pozwala jakość łącza. Aby przybliżyć funkcjonowanie...
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Application of Doubly Connected Dominating Sets to Safe Rectangular Smart Grids
PublicationSmart grids, together with the Internet of Things, are considered to be the future of the electric energy world. This is possible through a two-way communication between nodes of the grids and computer processing. It is necessary that the communication is easy and safe, and the distance between a point of demand and supply is short, to reduce the electricity loss. All these requirements should be met at the lowest possible cost....
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Architecture Design of a Networked Music Performance Platform for a Chamber Choir
PublicationThis paper describes an architecture design process for Networked Music Performance (NMP) platform for medium-sized conducted music ensembles, based on remote rehearsals of Academic Choir of Gdańsk University of Technology. The issues of real-time remote communication, in-person music performance, and NMP are described. Three iterative steps defining and extending the architecture of the NMP platform with additional features to...
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Architektury klasyfikatorów obrazów
PublicationKlasyfikacja obrazów jest zagadnieniem z dziedziny widzenia komputerowego. Polega na całościowej analizie obrazu i przypisaniu go do jednej lub wielu kategorii (klas). Współczesne rozwiązania tego problemu są w znacznej części realizowane z wykorzystaniem konwolucyjnych głębokich sieci neuronowych (convolutional neural network, CNN). W tym rozdziale opisano przełomowe architektury CNN oraz ewolucję state-of-the-art w klasyfikacji...
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ARIMA vs LSTM on NASDAQ stock exchange data
PublicationThis study compares the results of two completely different models: statistical one (ARIMA) and deep learning one (LSTM) based on a chosen set of NASDAQ data. Both models are used to predict daily or monthly average prices of chosen companies listed on the NASDAQ stock exchange. Research shows which model performs better in terms of the chosen input data, parameters and number of features. The chosen models were compared using...
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Asynchroniczna metoda jednoczesnej estymacji położenia i orientacji obiektu za pomocą dwóch nadajników
PublicationW artykule opisano nową metodę lokalizowania obiektów dla szerokiej gamy zastosowań, w tym Internetu Rzeczy. Zaproponowana metoda umożliwia estymację położenia i orientacji obiektu na płaszczyźnie lub w przestrzeni, również będącego w spoczynku, za pomocą sygnałów lokalizacyjnych wysyłanych jednocześnie z dwóch nadajników umieszczonych na obiekcie w znanej odległości od siebie. Przedstawiono matematyczną analizę metody oraz wyniki...
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Atomic-Scale Finite-Element Modeling of Elastic Mechanical Anisotropy in Finite-Sized Strained Phosphorene Nanoribbons
PublicationNanoribbons are crucial nanostructures due to their superior mechanical and electrical properties. This paper is devoted to hybrid studies of the elastic mechanical anisotropy of phosphorene nanoribbons whose edges connect the terminals of devices such as bridges. Fundamental mechanical properties, including Young’s modulus, Poisson’s ratio, and density, were estimated from first-principles calculations for 1-layer, 3-layer, and...
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Automatic Breath Analysis System Using Convolutional Neural Networks
PublicationDiseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is common for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected as...
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Automatic Breath Analysis System Using Convolutional Neural Networks
PublicationDiseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is not uncommon for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected...
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Automatic Emotion Recognition in Children with Autism: A Systematic Literature Review
PublicationThe automatic emotion recognition domain brings new methods and technologies that might be used to enhance therapy of children with autism. The paper aims at the exploration of methods and tools used to recognize emotions in children. It presents a literature review study that was performed using a systematic approach and PRISMA methodology for reporting quantitative and qualitative results. Diverse observation channels and modalities...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Badanie jakości transmisji w sieciach komórkowych na przestrzeni lat 2019-2021: wpływ pandemii Covid-19 na poziom świadczonych usług
PublicationPandemia COVID-19 znacząco ograniczyła mobilność użytkowników, a w szczególności studentów. Nauka zdalna miała szczególny wpływ na sposób przydziału zasobów w sieciach komórkowych. Niniejsza praca przedstawia wyniki badań dotyczących jakości transmisji w środowisku zewnątrzbudynkowym. Kampanię pomiarową w latach 2019-2021 przeprowadzono na terenie kampusu uczelni technicznej. Każdego roku badania wykonano przy użyciu własnej autorskiej...
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Badanie wpływu przydziału rdzeni procesora na wydajność w środowisku skonteneryzowanym oparte na wybranym serwerze warstawy pośredniej w IoT - obserwacje i rekomendacje
PublicationInternet Rzeczy cieszy się coraz większym zainteresowaniem. Za- gadnienie to jest szeroko omawiane zarówno w środowisku nauko- wym, jak i w przemyśle. Ze względu na jego wielowymiarowość jest wiele aspektów, które wymagają zbadania i obserwacji. Jednym z nich jest efektywne wdrożenie i uruchomienie aplikacji w kontekście wykorzystania zasobów sprzętowych. Innym, równie istotnym, za- gadnieniem jest konteneryzacja platform IoT....
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Bayesian Optimization for solving high-frequency passive component design problems
PublicationIn this paper, the performance of the Bayesian Optimization (BO) technique applied to various problems of microwave engineering is studied. Bayesian optimization is a novel, non-deterministic, global optimization scheme that uses machine learning to solve complex optimization problems. However, each new optimization scheme needs to be evaluated to find its best application niche, as there is no universal technique that suits all...
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Biometric identity verification
PublicationThis chapter discusses methods which are capable of protecting automatic speaker verification systems (ASV) from playback attacks. Additionally, it presents a new approach, which uses computer vision techniques, such as the texture feature extraction based on Local Ternary Patterns (LTP), to identify spoofed recordings. We show that in this case training the system with large amounts of spectrogram patches may be difficult, and...
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Blockchain based Secure Data Exchange between Cloud Networks and Smart Hand-held Devices for use in Smart Cities
PublicationIn relation to smart city planning and management, processing huge amounts of generated data and execution of non-lightweight cryptographic algorithms on resource constraint devices at disposal, is the primary focus of researchers today. To enable secure exchange of data between cloud networks and mobile devices, in particular smart hand held devices, this paper presents Blockchain based approach that disperses a public/free key...
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BP-EVD: Forward Block-Output Propagation for Efficient Video Denoising
PublicationDenoising videos in real-time is critical in many applications, including robotics and medicine, where varying light conditions, miniaturized sensors, and optics can substantially compromise image quality. This work proposes the first video denoising method based on a deep neural network that achieves state-of-the-art performance on dynamic scenes while running in real-time on VGA video resolution with no frame latency. The backbone...
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Broadening the scope of measurement and analysis of vibrations of an organ pipe employing intensity probe, simulations, and highspeed camera
PublicationThis paper shows an integrated approach to measure, analyze, and model phenomena occurring in an organ pipe driven by pressurized air. The aim of this paper is two-fold, i.e., to measure the pressure signal and the intensity field around the mouth by means of an intensity probe and to visualize and observe the motion of the air jet, which represents the excitation mechanism of the system. This is realized through two techniques,...
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Categorization of emotions in dog behavior based on the deep neural network
PublicationThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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Cellular network quality evaluation at a university campus on the eve of 5G
PublicationThanks to the availability of mobile devices and the spread of broadband access around the world, the number of network users continues to grow. This has raised user awareness when it comes to the quality of content they consume. Many service providers and operators focus on monitoring QoN (Quality of Network) and QoS (Quality of Service) parameters, particularly those influenced by bandwidth and latency. However, for most end-users,...
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Clinical studies of detecting COVID-19 from exhaled breath with electronic nose
PublicationThe COVID‑19 pandemic has attracted numerous research studies because of its impact on society and the economy. The pandemic has led to progress in the development of diagnostic methods, utilizing the polymerase chain reaction (PCR) as the gold standard for coronavirus SARS‑CoV‑2 detection. Numerous tests can be used at home within 15 min or so but of with lower accuracy than PCR. There is still a need for point‑of‑care tests available...
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Co stymuluje rozwój współczesnej teleinformatyki i jakie są istotne kierunki tego rozwoju?
PublicationCorocznie dokonuje się oceny stanu sztuki i tendencji w rozwoju światowej telekomunikacji i (tele)informatyki przywołując „mierzalne” i „niemierzalne” zmiany. W artykule przedstawiono charakter tych zmian oraz wskazano wyzwania badawcze i wdrożeniowe istotne dla rozwoju tych dyscyplin. Zaprezentowano i scharakteryzowano ewolucję infrastruktury sieciowej prowadzącą do sieci programowalnych SDN (Software Defined Network) oraz wykorzystania...
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Cognitive neuroscience: Theta network oscillations coordinate development of episodic memory
PublicationOur ability to remember life events matures through childhood and adolescence. A new study has revealed how theta oscillations between two anatomical brain regions supporting memory and executive functions are synchronized and develop across age through functional and structural connectivity.
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ColorNephroNet: Kidney tumor malignancy prediction using medical image colorization
PublicationRenal tumor malignancy classification is one of the crucial tasks in urology, being a primary factor included in the decision of whether to perform kidney removal surgery (nephrectomy) or not. Currently, tumor malignancy prediction is determined by the radiological diagnosis based on computed tomography (CT) images. However, it is estimated that up to 16% of nephrectomies could have been avoided because the tumor that had been...
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Combined chemoresistive and in situ FTIR spectroscopy study of nanoporous NiO films for light-activated nitrogen dioxide and acetone gas sensing
PublicationThe chemoresistive sensor response of nanoporous NiO films prepared by advanced gas deposition was investigated by combined resistivity and in situ FTIR spectroscopy, with and without simultaneous light illumination, to detect NO2 and acetone gases. The sensitivity towards NO2 increased dramatically under UV irradiation employing 275 nm light. Improved sensitivity was observed at an elevated temperature of 150 °C. In situ FTIR...
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Compact Electromagnetic Lens Antennas Using Cascaded Metasurfaces for Gain Enhancement and Beam Steering Applications
PublicationElectromagnetic (EM) lens antenna designs using cascaded metasurfaces for gain enhancement and beam steering applications are proposed. Two different lens aperture designs are proposed and populated with aperiodic unit cells of size 0.2λo × 0.2λo. In lens Design 1, the unit cells of different phases are distributed in concentric circular zones, whereas in lens Design 2, the unit cells of different phases are distributed in vertical...
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Compact, Order Extensible and Wide-Stopband Bandpass Filter Based on SIW Cavity with Rectangular Ring Slot
PublicationThis article introduces novel architectures of bandpass filters (BPFs) using a substrate integrated waveguide (SIW) cavity with a rectangular ring slot (RRS) for compact size, extensible order, and broad stopband responses. Two bandpass filters, which demonstrate a second-and a fourth-order Chebyshev response, respectively, are realized by employing identical cavities with RRS, without increasing the physical size of the circuit....
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Comparison of image pre-processing methods in liver segmentation task
PublicationAutomatic liver segmentation of Computed Tomography (CT) images is becoming increasingly important. Although there are many publications in this field there is little explanation why certain pre-processing methods were utilised. This paper presents a comparison of the commonly used approach of Hounsfield Units (HU) windowing, histogram equalisation, and a combination of these methods to try to ascertain what are the differences...
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Computationally Efficient Surrogate-Assisted Design of Pyramidal-Shaped 3D Reflectarray Antennas
PublicationReflectarrays (RAs) have been attracting considerable interest in the recent years due to their appealing features, in particular, a possibility of realizing pencil-beam radiation patterns, as in the phased arrays, but without the necessity of incorporating the feeding networks. These characteristics make them attractive solutions, among others, for satellite communications or mobile radar antennas. Notwithstanding, available microstrip...
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Computer Aided Telediagnostics System for Stoma Patients
PublicationStoma surgery may concern patients with colorectal cancer and inflammatory bowel disease. More than half of patients diagnosed with colon cancer present at an advanced stage, and palliative treatment may involve stoma formation. This type of surgery may change the patient’s life strongly, therefore they should receive special medical care. The paper presents the assumptions, concept, and architecture of the Stoma-Alert diagnosis...
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Computer-assisted pronunciation training—Speech synthesis is almost all you need
PublicationThe research community has long studied computer-assisted pronunciation training (CAPT) methods in non-native speech. Researchers focused on studying various model architectures, such as Bayesian networks and deep learning methods, as well as on the analysis of different representations of the speech signal. Despite significant progress in recent years, existing CAPT methods are not able to detect pronunciation errors with high...
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Condition-Based Monitoring of DC Motors Performed with Autoencoders
PublicationThis paper describes a condition-based monitoring system estimating DC motor degradation with the use of an autoencoder. Two methods of training the autoencoder are evaluated, namely backpropagation and extreme learning machines. The root mean square (RMS) error in the reconstruction of successive fragments of the measured DC motor angular-frequency signal, which is fed to the input of autoencoder, is used to determine the health...
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Conditions for Multiple Acquisition of Echoes from Stationary Targets in Successive Transmissions of Active Sonars
PublicationIn echolocation, the highest possible number of contacts with a detected target is clearly decisive on the possibilities of echo processing to optimise the estimation of distinctive characteristics of the observed target. In hydrolocation, the slow propagation of acoustic waves in water reduces the number of contacts of echosounders and sonars with detected targets. The article considers model conditions for acquiring multiple...
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Conductive printable electrodes tuned by boron-doped nanodiamond foil additives for nitroexplosive detection
PublicationAn efficient additive manufacturing-based composite material fabrication for electrochemical applications is reported. The composite is composed of commercially available graphene-doped polylactide acid (G-PLA) 3D printouts and surface- functionalized with nanocrystalline boron-doped diamond foil (NDF) additives. The NDFs were synthesized on a tantalum substrate and transferred to the 3D-printout surface at 200 °C. No other electrode...
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Constant-Factor Approximation Algorithm for Binary Search in Trees with Monotonic Query Times
PublicationWe consider a generalization of binary search in linear orders to the domain of weighted trees. The goal is to design an adaptive search strategy whose aim is to locate an unknown target vertex of a given tree. Each query to a vertex v incurs a non-negative cost ω(v) (that can be interpreted as the duration of the query) and returns a feedback that either v is the target or the edge incident to v is given that is on the path towards...
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Constrained multi-objective optimization of compact microwave circuits by design triangulation and pareto front interpolation
PublicationDevelopment of microwave components is an inherently multi-objective task. This is especially pertinent to the design closure stage, i.e., final adjustment of geometry and/or material parameters carried out to improve the electrical performance of the system. The design goals are often conflicting so that the improvement of one normally leads to a degradation of others. Compact microwave passives constitute a representative case:...
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Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublicationNematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...
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Corrigendum to “T1 relaxation time callibration in magnetic resonance imaging using nanodiamond phantoms” [Phys Med 94 (2022) S119–S120/EPV029]
PublicationThe authors want to update the incorrect funding information. The correct funding note is: “The authors acknowledge the financial support from Gdańsk University of Technology by the 4/2020/IDUB/III.4.1/Tc grant under the Technetium Talent Management Grants ‘Excellence Initiative – Research University’. The financial support from Gdańsk University of Technology by the 1/2021/IDUB/II.2/Np grant under NEPTUNIUM Enhancing Baltic Region...
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Cost-Efficient Optical Fronthaul Architectures for 5G and Future 6G Networks
PublicationFifth-generation and Beyond (5GB) wireless networks have introduced new centralized architectures such as cloud radio access network (CRAN), which necessitate extremely high-capacity low latency Fronthaul (FH). CRAN has many advantageous features in terms of cost reduction, performance enhancement, ease of deployment, and centralization of network management. Nevertheless, designing and deploying a cost-efficient FH is still a...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Crack Detection in Metallic Surfaces Based on Dumbbell-Shaped Defected Ground Structures in Microstrip Technology
PublicationIn this paper, a novel crack detection sensor using a microstrip loaded with a Dumbbell-Shaped Defected Ground Structure (DS-DGS) is proposed. The sensing element is etched in the ground plane of a microstrip line and it is easy to fabricate. The electromagnetic (EM) field of the microstrip couples to the DS-DGS, thus demonstrating a bandstop behavior. It is shown that in the presence of a crack in a metallic surface underneath the...
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Creating a radiological database for automatic liver segmentation using artificial intelligence.
PublicationImaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.
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Creating a Remote Choir Performance Recording Based on an Ambisonic Approach
PublicationThe aim of this paper is three-fold. First, the basics of binaural and ambisonic techniques are briefly presented. Then, details related to audio-visual recordings of a remote performance of the Academic Choir of the Gdańsk University of Technology are shown. Due to the COVID-19 pandemic, artists had a choice, namely, to stay at home and not perform or stay at home and perform. In fact, staying at home brought in the possibility...
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Creating new voices using normalizing flows
PublicationCreating realistic and natural-sounding synthetic speech remains a big challenge for voice identities unseen during training. As there is growing interest in synthesizing voices of new speakers, here we investigate the ability of normalizing flows in text-to-speech (TTS) and voice conversion (VC) modes to extrapolate from speakers observed during training to create unseen speaker identities. Firstly, we create an approach for TTS...
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Deciphering the Molecular Mechanism of Substrate-Induced Assembly of Gold Nanocube Arrays toward an Accelerated Electrocatalytic Effect Employing Heterogeneous Diffusion Field Confinement
PublicationThe complex electrocatalytic performance of gold nanocubes (AuNCs) is the focus of this work. The faceted shapes of AuNCs and the individual assembly processes at the electrode surfaces define the heterogeneous conditions for the purpose of electrocatalytic processes. Topographic and electron imaging demonstrated slightly rounded AuNC (average of 38 nm) assemblies with sizes of ≤1 μm, where the dominating patterns are (111) and...
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Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Defending against Fake VIP in Scant-Transparency Information Systems with QoS Differentiation
PublicationIn client-server information systems with quality of service (QoS) differentiation, Client may deplete Server’s resources by demanding unduly high QoS level. Such QoS abuse has eluded systematic treatment; known defenses using Client authorization, payments, or service request inspection prior to QoS assignment, are heuristic and environment-specific. We offer a game-theoretic approach on the premise that a service request is occasionally...
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DEPO: A dynamic energy‐performance optimizer tool for automatic power capping for energy efficient high‐performance computing
PublicationIn the article we propose an automatic power capping software tool DEPO that allows one to perform runtime optimization of performance and energy related metrics. For an assumed application model with an initialization phase followed by a running phase with uniform compute and memory intensity, the tool performs automatic tuning engaging one of the two exploration algorithms—linear search (LS) and golden section search (GSS), finds...