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Gdańsk University of Technology

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Publications from the year 2024

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  • Unveiling the electron-induced ionization cross sections and fragmentation mechanisms of 3,4-dihydro-2H-pyran
    • Tomasz Wąsowicz
    • Michał Jurkowski
    • Allison Harris
    • Ivan Ljubić
    2024 Full text JOURNAL OF CHEMICAL PHYSICS

    The interactions of electrons with molecular systems under various conditions are essential to interdisciplinary research fields extending over the fundamental and applied sciences. In particular, investigating electron-induced ionization and dissociation of molecules may shed light on the radiation damage to living cells, the physicochemical processes in interstellar environments, and reaction mechanisms occurring in combustion or plasma. We have, therefore, studied electron-induced ionization and dissociation of the gas phase 3,4-dihydro-2H-pyran (DHP), a cyclic ether appearing to be a viable moiety for developing efficient clinical pharmacokinetics and revealing the mechanisms of biofuel combustion. The mass spectra in the m/z = 10–90 mass range were measured at several different energies of the ionizing electron beam using mass spectrometry. The mass spectra of DHP at the same energies were simulated using on-the-fly semi-classical molecular dynamics (MD) within the framework of the QCxMS formalism. The MD settings were suitably adjusted until a good agreement with the experimental mass spectra intensities was achieved, thus enabling a reliable assignment of cations and unraveling the plausible fragmentation channels. Based on the measurement of the absolute total ionization cross section of DHP (18.1 ± 0.9) × 10−16 cm2 at 100 eV energy, the absolute total and partial ionization cross sections of DHP were determined in the 5–140 eV electron energy. Moreover, a machine learning algorithm that was trained with measured cross sections from 25 different molecules was used to predict the total ionization cross section for DHP. Comparison of the machine learning simulation with the measured data showed acceptable agreement, similar to that achieved in past predictions of the algorithm.

  • Upward convergence patterns in chosen environmental-related SDGs
    • Marta Kuc-Czarnecka
    • Iwona Markowicz
    • Agnieszka Sompolska-Rzechuła
    2024 Full text ECOLOGICAL INDICATORS

    Sustainable development is a challenge facing humanity. EU countries not only strive to reach their specific objectives, but they also work collaboratively towards shared goals. There is a need to balance synergies and compromises to address these objectives effectively. When discussing countries' development and people's well-being, one often focuses on socio-economic development. However, it is crucial not to overlook the environmental repercussions and the need to care for the planet. Thus, our article pays attention to the sustainable development objectives of the “planets” group. We analysed upward convergence in the scope of the “Planet” goals, i.e. the analysis of improving the results of Member States and, at the same time, reducing the differences between them. Convergence trends were examined individually for each variable and then for all variables combined (Planet). Our article fills a research gap because, to our knowledge, analyses of the trajectories of achieving individual goals in such a context have not been analysed so far. The results of our study indicate a favourable situation in the case of six out of eight examined variables. Areas in which intensification of activities is necessary for some EU countries are an increase in energy productivity and a reduction in net greenhouse gas emissions of land use. The second stage of the study concerned the development paths of individual countries. The most challenging situation concerns the variable sdg_07_20 (final energy consumption in households per capita). In this case, as many as 12 countries belong to the weak group.

  • Usability of Mobile Applications: A Consolidated Model
    • Paweł Weichbroth
    2024 Full text IEEE Access

    Mobile devices have become an integral part of the digital ecosystem, connecting people, businesses, and information around the world in ways never before possible. In particular, smartphones, tablets and other handheld devices equipped with mobile applications have changed every aspect of our lives. Today, a user can choose from nearly five million applications available for both Android and iOS operating systems. However, only 0.5 percent of applications succeed in the marketplace. Many factors contribute to their failure, including poor design, lack of value, privacy violations, and usability issues. While usability is often identified as a major concern, there seems to be no agreement between researchers and practitioners on its nature, although many models have been developed. This paper attempts to find a consensus by synthesizing the state of the art literature. More specifically, we aim to develop a consolidated, universal usability model for mobile applications, through the lens of existing human computer interaction theory. In order to achieve this goal, our study uses a mix of qualitative and quantitative methods. Overall, the research methodology consisted of two steps. First, we conducted a systematic literature review to identify, collect, and analyze current research on mobile usability. Second, we used the meta-analysis approach to quantitatively describe the extracted data and summarize the findings. The PACMAD+3 model was developed and discussed in light of the results obtained and the PACMAD model. While our model borrows seven attributes from its ancestor, the remaining three attributes were derived from the synthesis of other studies, along with three external factors adopted from the ISO 9241-11 standard. In addition, we reviewed existing definitions of usability attributes. We expect that this unified approach will lead to a better understanding of mobile usability, including all relevant attributes and factors, thus making a significant contribution to theory. On the other hand, in practice, the PACMAD+3 model can be used to translate abstract attributes into tangible terms, which is particularly useful in empirical research focused on measuring and evaluating the usability of mobile applications.

  • Usability Testing of Mobile Applications: A Methodological Framework
    • Paweł Weichbroth
    2024 Full text Applied Sciences-Basel

    Less than five percent of all mobile applications have become successful throughout 2023. The success of a new mobile application depends on a variety of factors ranging from business understanding, customer value, and perceived quality of use. In this sense, the topic of usability testing of mobile applications is relevant from the point of view of user satisfaction and acceptance. However, the current knowledge seems to be fragmented, scattered across many papers and reports, and sometimes poorly documented. This paper attempts to fill this gap by investigating the current state of knowledge by reviewing the previous literature relevant to the research topic and developing a unified view. In particular, the methodological framework is outlined and discussed, including the discourse on settings for laboratory and field studies, data collection techniques, experimental designs for mobile usability testing, and a generic research framework. Therefore, the paper contributes to both the theory and practice of human–computer interaction by providing methodological foundations for usability testing of mobile applications, paving the way for further studies in this area. Moreover, the paper provides a better understanding of the related topics, in particular shedding light on methodological foundations, key concepts, challenges, and issues, equipping readers with a comprehensive knowledge base to navigate and contribute to the advancement of the field of mobile usability.

  • Use of innovative digital laboratories to train a new generation of architects: integration of education, practice and research for digital cultural heritage
    • Justyna Borucka
    • Sandro Parrinello
    • Francesca Picchio
    • Jakub Szczepański
    2024 Global Journal of Engineering Education

    In this article, the authors outline the potential of using innovative digital laboratories to train a new generation of architects. The evolving built environment and technology continuously challenge architectural educators to take an innovative approach to better understand, preserve and protect the architectural heritage, and ensure development toward a sustainable and green economy. One of those approaches is a methodology based on the integration of education, practice and research on digital cultural heritage (CH) in the form of an alliance of laboratories as a cross-border hub for sustainable development and cultural heritage preservation. The article is focused on the case of three laboratories from Poland and Italy: DAda Lab - UNIPV, Pavia; DAB Lab - Gdańsk Tech; and DARWIN Lab - UNIFI, Florence, which, using common methods, tools and activities, combine practice and research with education of architects and engineers. Through the joint implementation of various European CH projects, the laboratories engage their resources and students in hands-on activities, providing opportunities to experiment with new tools and forms of research-oriented education.

  • User experience evaluation study on the quality of 1K, 2K, and 4K H.265/HEVC video content
    • Przemysław Falkowski-Gilski
    • Tadeus Uhl
    • Christian Hoppe
    2024 Full text Zeszyty Naukowe Akademii Morskiej w Szczecinie

    Nowadays, most content creators focus on distributing rich media at the highest possible resolution. Currently, the majority of sold consoles, media players, computer hardware, as well as displays and TVs are advertised as 4K-compatible. The same trend is observed in the case of popular online streaming services and terrestrial TV broadcasts. Generally speaking, it is assumed that higher bitrates provide higher subjective judgements. In this paper, we present the results of a user experience (UX) evaluation study on the quality of video content coded and transmitted in different resolutions in the internet protocol (IP) environment. The image resolutions include 1K (1920×1080 pixels; full-HD), 2K (2560×1440 pixels; wide-QHD), and 4K (3840×2160 pixels; ultra-HD) content that are processed in the H.265/HEVC (high-efficiency video coding) format. A subjective evaluation is carried out in a laboratory consisting of 20 iMacs with a 21.5-inch 4K Retina (4096×2304 pixels) display. The group of viewers included 28 individuals aged between 21‒35 years old, comprising people with and without visual impairments. The obtained UX results are compared with previous experiments, including both objective quality of service (QoS) and subjective quality of experience (QoE), as well as the impact of down-scaling to 1K from 2K and 4K. The outcomes of this study may be of particular interest to any party interested in video content processing and distribution, as well as consumption and storage.

  • User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
    • Sebastian Urwan
    • Krzysztof Cwalina
    2024 Full text SENSORS

    In this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for the binary classification of user orientation, neural networks achieved accuracy that was more than 9% higher than that for the well-known threshold method. In addition, the classification of user position angles relative to the reference node was analyzed. It was proven that, using the proposed deep learning approach and the channel impulse response, it was possible to estimate the angle of the user’s position in relation to the antenna geometry. Absolute user orientation angle errors of about 4–7◦ for convolutional neural networks and of about 14–15◦ for multilayer perceptrons were achieved in approximately 85% of the cases in both tested scenarios.

  • User-oriented GIS tools in higher education of urban design and planning
    • Weronika Maria Mazurkiewicz
    • Anna Kaczorowska
    • Anna Rubczak
    • Justyna Wieczerzak
    • Dorota Dominika Kamrowska-Załuska
    2024 Full text World Transactions on Engineering and Technology Education

    Geographic information systems (GIS) have emerged as indispensable tools for decision-making, planning and problem-solving tasks across various domains in today’s evolving world. However, there exists a pressing need to augment the utilisation of GIS tools in higher education of urban design and planning to foster a user-oriented approach. This article explores the imperative of integrating GIS tools more comprehensively into higher education curricula to empower students with the skills necessary to leverage geographic information effectively. Selected cases from the Programmes of Architecture and Spatial Development at Gdańsk University of Technology (Gdańsk Tech), Poland, and Physical Planning at the Norwegian University of Science and Technology (NTNU), Trondheim, Norway, demonstrate students’ experience with user-oriented GIS tools. Results reveal there is a growing demand in higher education to integrate GIS tools into service design approaches and participatory practice. Enhancing access to GIS technologies for students and stakeholders will encourage collaboration between education and practice, facilitating real-time adjustments and crossdisciplinary efforts.

  • Utilising AI Models to Analyse the Relationship between Battlefield Developments in the Russian-Ukrainian War and Fluctuations in Stock Market Values
    • Oleksandr Melnychenko
    2024 Forum Scientiae Oeconomia

    This study examines the impact of battlefield developments in the ongoing Russian–Ukrainian war, which to date has lasted over 1000 days, on the stock prices of defence corporations such as BAE Systems, Booz Allen Hamilton, Huntington Ingalls, and Rheinmetall AG. Stock prices were analysed alongside sentiment data extracted from news articles, and processed using machine learning models leveraging natural language processing (NLP). Although the main hypothesis was not confirmed due to methodological and data limitations, the study demonstrated that neural network-based models, specifically long short-term memory (LSTM) networks, effectively captured hidden temporal patterns. The model's performance was evaluated using root mean squared error (RMSE). Alternative models, including XGBoost, ARIMA, and VAR, were also tested but did not yield accurate forecasts. The findings highlight nonlinear patterns in the data and emphasise the importance of hyperparameter optimisation, such as tuning the number of epochs andLSTM layer sizes. Techniques such as Grid Search and Random Search significantly enhanced forecasting performance, resulting in stock price predictions with low RMSE.

  • Utilizing Morphological and Physiological Parameters of Lemna minor for Assessing Tetracyclines’ Removal
    • Łukasz Sikorski
    • Agnieszka Bęś
    • Kazimierz Warmiński
    • Wojciech Truszkowski
    • Przemysław Kowal
    2024 MOLECULES

    Antibiotics with significant environmental toxicity, e.g., tetracyclines (TCs), are often used in large quantities worldwide, with 50–80% of the applied dose ending up in the environment. This study aimed to investigate the effects of exposure to tetracycline hydrochloride (TC) and minocycline hydrochloride (MIN) on L. minor. Our research evaluated the phytotoxicity of the TCs by analyzing plant growth and biomass and evaluating assimilation pigment levels and fluorescence. The research was extended with the ability potential of duckweed as a tool for removing TCs from water/wastewater. The results demonstrated that both TCs influenced Ir, Iy, biomass, and photosynthetic efficiency. The uptake of TC and MIN by duckweed was proportional to the concentration in the growth medium. The TC was absorbed more readily, reaching up to 8.09 mg × g−1 of dry weight (DW) at the highest concentration (19.2 mg × L−1), while MIN reached 6.01 mg × g−1 of DW. As indicated, the consequences of the influence of TC on plants were slightly smaller, in comparison to MIN, while the plants could biosorb this drug, even at the lowest tested concentration. This study has shown that using plants for drug biosorption can be an effective standalone or complementary method for water and wastewater treatment.

  • UV-assisted fluctuation-enhanced gas sensing by ink-printed MoS2 devices
    • Katarzyna Drozdowska
    • Janusz Smulko
    • Jakub Czubek
    • Sergey Rumyantsev
    • Andrzej Kwiatkowski
    2024 Full text Scientific Reports

    In this work, MoS2 flakes were printed on ceramic substrates and investigated toward 1–10 ppm of nitrogen dioxide (NO2), 2–12 ppm of ammonia (NH3), and 2–12 ppm acetone (C3H6O) under UV light (275 nm). The structure of overlapping MoS2 flakes and UV light assistance affected high responsivity to NO2 when DC resistance was monitored, and superior sensitivity to NH3 was obtained from the low-frequency noise spectra. MoS2 exhibited response and recovery times in hundreds of seconds and stability throughout the experiments conducted within a few months. MoS2 sensor exhibited a resistance drift during the detection of a specific relaxation time. Subtracting the baseline burden with exponential drift exposed the direction of changes induced by oxidizing and reducing gases and reduced DL to 80 ppb, 130 ppb, and 360 ppb for NO2, NH3, and C3H6O, respectively. The fluctuation-enhanced sensing (FES) revealed that the adsorption of NO2 on MoS2 decreases the noise intensity, whereas adsorbed NH3 increases the fluctuations of current flowing through the sensor, and these changes are proportional to the concentration of gases. The noise responses for NO2 and NH3 were opposite and higher than DC resistance responses with subtracted baseline (an increase of 50% for 10 ppm of NO2 and an increase of more than 600% for 12 ppm of NH3), showing that FES is a highly sensitive tool to detect and distinguish between these two gases. This way, we introduce a simple and low-cost method of gas sensor fabrication using ink-printed MoS2 and the possibility of enhancing its sensitivity through data processing and the FES method.

  • Vaccinium Species—Unexplored Sources of Active Constituents for Cosmeceuticals
    • Wirginia Kukuła-Koch
    • Natalia Dycha
    • Paulina Lechwar
    • Magdalena Lasota
    • Estera Okoń
    • Paweł Szczeblewski
    • Anna Wawruszak
    • Dominik Tarabasz
    • Jane Hubert
    • Piotr Wilkołek
    • Maria Halabalaki
    • Katarzyna Gaweł-Bęben
    2024 Biomolecules

    The genus Vaccinium is represented by shrubs growing in a temperate climate that have been used for ages as traditional remedies in the treatment of digestive problems, in diabetes, renal stones or as antiseptics due to the presence of polyphenols (anthocyanins, flavonoids and tannins) in their fruits and leaves. Recent studies confirm their marked potential in the treatment of skin disorders and as skin care cosmetics. The aim of this review is to present the role of Vaccinium spp. as cosmetic products, highlight their potential and prove the biological properties exerted by the extracts from different species that can be useful for the preparation of innovative cosmetics. In the manuscript both skin care and therapeutic applications of the representatives of this gender will be discussed that include the antioxidant, skin lightening, UV-protective, antimicrobial, anti-inflammatory, and chemopreventive properties to shed new light on these underestimated plants.

  • Validation of dynamic electrochemical impedance spectrograms using autocorrelation function
    • Kazimierz Darowicki
    • Szymon Wysmułek
    • Anna Karólkowska
    • Łukasz Gaweł
    2024 JOURNAL OF ELECTROANALYTICAL CHEMISTRY

    Validation of impedance data is essential for checking the reliability of experimental data. Kramers – Kronig transformation is used to verify data obtained from classical Electrochemical Impedance Spectroscopy (EIS) measurements. Data obtained from Dynamic Electrochemical Impedance Spectroscopy (DEIS) could be validated in the same way, but in this case, there is no information about internal consistency between every single spectrum in the whole spectrogram. To address these challenges, the authors proposed an approach using the autocorrelation function ACF to validate DEIS time series. The reasoning conducted showed that ACF function is appropriate tool for validating DEIS spectrograms.

  • Valorization of paper-mill sludge laden with 2-chlorotoluene using hydroxyapatite@biochar nanocomposite to enrich methanogenic community: A techno-economic approach
    • Rania H. Hafez
    • Ahmed Tawfik
    • Gamal K. Hassan
    • Magdy Zahran
    • Ahmed A. Younes
    • Aleksandra Ziembińska-Buczyńska
    • Filip Gamoń
    • Mahmoud Nasr
    2024 BIOMASS & BIOENERGY

    While several studies have investigated the anaerobic digestion of paper-mill sludge (PMS), this technology suffers from nutrient insufficiency, inhibition by aromatic compounds, and low bio-CH4 yield. Hence, PMS was anaerobically co-digested with chicken manure (CM) and supplemented by hydroxyapatite@biochar (HAP@BC) nanocomposite for enhancing 2-chlorotoluene degradation and enriching the methanogenic archaea. Multiple continuous stirred tank reactors (CSTRs) were operated at 12.6 h hydraulic retention time (HRT), using PMS (R1), CM (R2), PMS + CM (R3), PMS + CM+100 mg HAP/L (R4), and PMS + CM+100 mg HAP@BC/L (R5). The maximum bio-CH4 yield of 147.5 ± 9.1 mL/g COD and 2-chlorotoluene removal of 91.2 ± 6.8 % were obtained from R5, experiencing a sufficient C/N ratio of 14.7 and the highest activities of acidogenesis (42.0 %), aceto- genesis (37.9 %), and methanogenesis (42.1 %). The abundances of Euryarchaeota, Bacteroidota, and Chloroflexi at the phylum level, and Pseudomonas, and Bacillus at the genus level could highly contribute to the dechlori- nation mechanism and acetate transformation into CH4. This biomass-to-bioenergy project (10 m3/d capacity) could benefit from pollution reduction, biogas recovery, and carbon credit, giving 5.6 yr payback-period, 3503 USD net present value, and 12.1 % internal rate of return. Because R5 exhibited an efficient techno-economic anaerobic biodegradation performance, future studies are required to optimize its HRT condition and HAP@BC dosage.

  • Value co‐creation (VCC) and value co‐destruction (VCD) via open government data (OGD): Empirical case of Tanzania
    • Fredrick Ishengoma
    • Deo Shao
    • Raphael Gouvea da Silva
    • Guillherme Costa Wiedenhoft
    • Charalampos Harris Alexopoulos
    • Nina Rizun
    • Stuti Saxena
    2024 Electronic Journal of Information Systems in Developing Countries

    Having emphasized upon the potential benefits of Open Government Data (OGD) initiatives via value derivation and innovation pursuits of the stakeholders, it falls in place to complement this line of OGD research in the specific case of Tanzania, a developing country, to support the inferences. Specifically, it is important to understand the manner in which OGD VCC-one of the hinges of OGD initiatives- and OGD VCD-a possible fall out of OGD initiatives- happens to pass. Thus, a content analysis of the interviews of 15 public officials and managers was conducted to arrive at its conclusions. Thus, the interviewees aver that OGD Value Co-creation (VCC) may be facilitated on top-priority bases by consistent marketing efforts by the government as also the partnerships with the key stakeholders of the OGD ecosystem, and, among the prominent Value Co-Destruction (VCD) factors may be counted the issues linked with data privacy and resource restriction. Literature on OGD VCC is at a nascent stage and the one on OGD VCD is evolving. As an atypical empirical validation case vis-a-vis the emerging OGD VCC-VCD research, the study is an additional contribution to the extant literature with specific reference to the developing country's experiences where the OGD initiatives are at an evolving stage

  • Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
    • Reyhan Yurt
    • Hamid Torpi
    • Ahmet Kizilay
    • Sławomir Kozieł
    • Peyman Mahouti
    2024 Full text Scientific Reports

    In this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model has been used. The task is to predict simultaneously and independent of each characteristic parameters of a buried object of several radii at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable data structures (raw B-scans, extracted features, consecutive A-scans) with respect to computational cost and accuracy of surrogates. The usage of raw B-scan data and the applications for processing steps on B-scan profiles in the context of object characterization incur high computational cost so it can be a challenging issue. The proposed surrogate model referred to as the deep regression network (DRN) is utilized for time frequency spectrogram (TFS) of consecutive A-scans. DRN is developed with the main aim being computationally efficient (about 13 times acceleration) compared to conventional network models using B-scan images (2D data). DRN with TFS is favorably benchmarked to the state-of-the-art regression techniques. The experimental results obtained for the proposed model and second-best model, CNN-1D show mean absolute and relative error rates of 3.6mm, 11.8mm and 4.7%, 11.6% respectively. For the sake of supplementary verification under realistic scenarios, it is also applied for scenarios involving noisy data. Furthermore, the proposed surrogate modeling approach is validated using measurement data, which is indicative of suitability of the approach to handle physical measurements as data sources.

  • Variable Resolution Machine Learning Optimization of Antennas Using Global Sensitivity Analysis
    • Anna Pietrenko-Dąbrowska
    • Sławomir Kozieł
    2024 Full text Scientific Reports

    The significance of rigorous optimization techniques in antenna engineering has grown significantly in recent years. For many design tasks, parameter tuning must be conducted globally, presenting a challenge due to associated computational costs. The popular bio-inspired routines often necessitate thousands of merit function calls to converge, generating prohibitive expenses whenever the design process relies on electromagnetic (EM) simulation models. Surrogate-assisted methods offer acceleration, yet constructing reliable metamodels is hindered in higher-dimensional spaces and systems with highly nonlinear characteristics. This work suggests an innovative technique for global antenna optimization embedded within a machine-learning framework. It involves iteratively refined kriging surrogates and particle swarm optimization for generating infill points. The search process operates within a reduced-dimensionality region established through fast global sensitivity analysis. Domain confinement enables the creation of accurate behavioral models using limited training data, resulting in low CPU costs for optimization. Additional savings are realized by employing variable-resolution EM simulations, where low-fidelity models are utilized during the global search stage (including sensitivity analysis), and high-fidelity ones are reserved for final (gradient-based) tuning of antenna parameters. Comprehensive verification demonstrates the consistent performance of the proposed procedure, its superiority over benchmark techniques, and the relevance of the mechanisms embedded into the algorithm for enhancing search process reliability, design quality, and computational efficiency.

  • Vehicle type recognition: a case study of MobileNetV2 for an image Classification task
    • Dariusz Kobiela
    • Jan Groth
    • Michał Hajdasz
    • Mateusz Erezman
    2024 Procedia Computer Science

    The goal of the research was to demonstrate the full data science lifecycle through a use case of the MobileNetv2 model for vehicle image Classification task using various validation and test sets, each with different difficulty level. Diverse model variations were employed, each designed to recognize images of ground vehicles and classify them into one of five possible classes: car, truck, motorcycle, bicycle, or bus. In terms of validation accuracy, the highest results were obtained by the model trained with uniformly designed train and val sets (with data normalization and augmentation), where train set also contained validation set. This model also obtained the highest accuracy results on both test sets. The superiority of MODEL 3 BASELINE is confirmed by other metrics as well: test loss, f1-score, AUC and confusion matrices (for both test sets). Results between MODEL 1 BASELINE and MODEL 2 BASELINE differed according to the test set 1 and 2 and other metrics and it was not possible to declare the superiority of one method of datasets preparation over another (original class distribution [no data normalization and no data augmentation] versus uniformly designed [with data normalization and augmentation]). The article also presents challenges and findings - the problems, key issues, and their solutions that arose during the process of data collection and tagging, as well as the preparation and evaluation of the model.

  • Versatile Unsupervised Design of Antennas Using Flexible Parameterization and Computational Intelligence Methods
    • Sławomir Kozieł
    • Anna Pietrenko-Dąbrowska
    • Stanisław Szczepański
    2024 Full text Scientific Reports

    Developing contemporary antennas is a challenging endeavor that requires considerable engineering insight. The most laborious stage is to devise an antenna architecture that delivers the required functionalities, e.g., multiband operation. Iterative by nature (hands-on topology modifications, parametric studies, trial-and-error geometry selection), it typically takes many weeks and requires considerable engagement from a human expert. Consequently, only a few possible design options concerning the fundamental antenna geometry may be considered. Automated topology rendition and geometry parameter optimization are highly relevant, especially from the industrial perspective. Therein, reducing time-to-market and limiting the involvement of trained experts is critical. This research proposes an innovative procedure for unsupervised development of planar antennas. Our method leverages flexible antenna parameterization based on re-sizable elliptical patches. It permits the realization of a massive number of geometries of diverse shapes and complexities using a small number of decision variables. Computational intelligence methods are employed to conduct antenna evolution exclusively based on specifications and possible constraints (e.g., maximum size). Fine-tuning of the structure geometry is achieved through low-cost local search routines. Our methodology is demonstrated by designing several antennas featuring distinct characteristics (broadband, single-, dual- and triple-band). The obtained results, supported by experimental data, underscore the presented approach’s versatility and capability to render unconventional topologies at reasonably low computational expenses. As mentioned earlier, the design process is fully automated without human expert involvement.

  • Virtual Escape Room in Mathematics
    • Radosław Baziak
    • Tomasz Daruk
    • Karol Żyra
    • Dorota Żarek
    • Jacek Lebiedź
    2024

    The paper presents developing a virtual reality-based escape room to teach mathematical concepts. The goal was to create an immersive game to engage students in actively solving math puzzles. The research team built the application for use in the Immersive 3D Visualization Lab at the Gdańsk University of Technology. The escape room comprises an introductory room followed by three themed rooms with 13 puzzles total that involve mathematical thinking. To assess the tool’s educational impact, the team prepared surveys and planed an experiment with students. Key outcomes delivered were the completed application configured for the target lab, plus the surveys to quantitatively measure math comprehension before and after students use the escape room. Overall this project combined virtual reality and game design concepts to create an innovative approach for engaging students in learning math concepts in an interactive, visually stimulating setting.