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Gdańsk University of Technology

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Publications from the year 2024

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  • Anisotropy and compaction gradient assessment on rammed earth specimens through sonic tomography approach
    • J.d. Rodríguez-Mariscal
    • Monika Zielińska
    • Magdalena Rucka
    • M. Solís
    2024 Full text ENGINEERING STRUCTURES

    Rammed earth is a traditional construction technique that has recently gained attention because of its benefits from an ecological perspective. The conservation of the existing valuable cultural heritage sites and the quality control of new constructions built with this material require the development and application of practical inspection techniques. This paper explores the application of sonic tests and sonic tomography as practical tools for monitoring the state of conservation of existing structures and the identification of heterogeneities or damaged areas. Two groups of 6 rammed earth specimens were manufactured and tested. The manufacturing process of each group allowed the application of compression loads and the identification of the Sonic Wave Propagation Velocities along directions parallel and perpendicular to the compaction forces during manufacturing. The SWPV were identified for the different paths between 9 measuring points located at two opposite sides of the specimens, leading to up to 6 different planes for each specimen. The SWPV are identified by identifying the Time-of-Flight of the elastic wave between each pair of excitation and receiver points. A discretized coloured map of the SWPV distribution for each plane defined by the measurement points array is obtained by the application of an algorithm already developed by the authors to obtain tomographic images for other materials and applications. The SWPV are identified after 2 different increasing values of a uniform compressive load is applied to each specimen. The results show that the analysis of the SWPV and tomographic images is sensitive to heterogeneities, such as compaction gradients from the manufacturing process, and also to the accumulated damage in the solid. The paper demonstrates that the proposed technique can be potentially used for a qualitative inspection of the state of conservation of specific rammed earth constructions.

  • Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation
    • Michał Bałdyga
    • Kacper Barański
    • Jakub Belter
    • Mateusz Kalinowski
    • Paweł Weichbroth
    2024 Full text SENSORS

    To date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging infrastructure, and adverse environmental conditions on the one hand, and the scale, complexity, and critical safety implications of railway systems on the other. Our study is underpinned by the three objectives. Specifically, we aim to identify time series anomaly detection methods applied to railway sensor device data, recognize the advantages and disadvantages of these methods, and evaluate their effectiveness. To address the research objectives, the first part of the study involved a systematic literature review and a series of controlled experiments. In the case of the former, we adopted well-established guidelines to structure and visualize the review. In the second part, we investigated the effectiveness of selected machine learning methods. To evaluate the predictive performance of each method, a five-fold cross-validation approach was applied to ensure the highest accuracy and generality. Based on the calculated accuracy, the results show that the top three methods are CatBoost (96%), Random Forest (91%), and XGBoost (90%), whereas the lowest accuracy is observed for One-Class Support Vector Machines (48%), Local Outlier Factor (53%), and Isolation Forest (55%). As the industry moves toward a zero-defect paradigm on a global scale, ongoing research efforts are focused on improving existing methods and developing new ones that contribute to the safety and quality of rail transportation. In this sense, there are at least four avenues for future research worth considering: testing richer data sets, hyperparameter optimization, and implementing other methods not included in the current study.

  • Antenna Optimization Using Machine Learning with Reduced-Dimensionality Surrogates
    • Sławomir Kozieł
    • Anna Pietrenko-Dąbrowska
    • Leifur Leifsson
    2024 Scientific Reports

    In modern times, antenna design has become more demanding than ever. The escalating requirements for performance and functionality drive the development of intricately structured antennas, where parameters must be meticulously adjusted to achieve peak performance. Often, global adjustments to geometry are necessary for optimal results. However, direct manipulation of antenna responses evaluated with full-wave electromagnetic (EM) simulation models using conventional nature-inspired methods entails significant computational costs. Alternatively, surrogate-based techniques show promise but are impeded by dimensionality-related challenges and nonlinearity of antenna outputs. This study introduces an innovative technique for swiftly optimizing antennas. It leverages a machine learning framework with an infill criterion employing predicted enhancement of the merit function, utilizing a particle swarm optimizer as the primary search engine, and employs kriging for constructing the underlying surrogate model. The surrogate model operates within a reduced-dimensionality domain, guided by directions corresponding to maximum antenna response variability identified through fast global sensitivity analysis, tailored explicitly for domain determination. Operating within this reduced domain enables building dependable metamodels at a significantly lower computational cost. To address accuracy loss resulting from dimensionality reduction, the global optimization phase is supplemented by local sensitivity-based parameter adjustment. Extensive comparative experiments involving various planar antennas demonstrate the competitive operation of the presented technique over machine learning algorithms operating in full-dimensionality space and direct EM-driven bio-inspired optimization techniques.

  • Anticancer Study on IrIII and RhIII Half-Sandwich Complexes with the Bipyridylsulfonamide Ligand
    • Mateusz Kowalik
    • Joanna Masternak
    • Mateusz Olszewski
    • Natalia Maciejewska
    • Katarzyna Kazimierczuk
    • Jerzy Sitkowski
    • Aleksandra Dąbrowska
    • Agnieszka Chylewska
    • Mariusz Makowski
    2024 INORGANIC CHEMISTRY

    Two non-platinum compounds, organometallic half-sandwich complexes [(η 5 -Cp)IrCl(L)]PF 6 (1) and [(η 5 -Cp)RhCl(L)]PF 6 (2) were prepared by treating pentamethylcyclopentadienyl chloride dimers of iridium(III) or rhodium(III) with the obtained 4-amino-N-(2,2'-bipyridin-5- yl)benzenesulfonamide ligand (L) and ammonium hexafluorophosphate. The crystal structures of ligand (L) and complexes 1 and 2 were obtained and then analyzed. Coordination reactions of the bipyridylsufonamide ligand (L) to the central ions were confirmed by UV- Vis, FT-IR, NMR ( 1 H, 13 C, and 15 N) spectroscopies, and stability study. Moreover, the interactions between the sulfaligand, Ir(III) and Rh(III) complexes with carbonic anhydrase (CA), human serum albumin (HSA) and also with CT-DNA have been investigated. Additionally, the reactivity of complexes toward GSH and NADH has been spectrophotometrically tested. A low affinity of complex 2 to GSH seems to be beneficial regarding its potential cytotoxic activity. The obtained compounds were then evaluated for their antiproliferative activity against four cancer cell lines from different origins: non-small cell lung cancer A549, colon cancer HCT-116, breast cancer MCF7, lymphoblastic leukemia Nalm-6, and a nonmalignant human embryonic kidney cell line HEK293. It has been observed that the iridium(III) complex (1) was found to exhibit a lack of antiproliferative properties against the tested cancer cell lines. The sulfonamide ligand (L) and the rhodium(III) complex (2) were studied in detail for colon cancer HCT-116 cell line, and the detailed biological analysis was reported and discussed.

  • Applicability of edible Candelilla wax composite blended with Bryophyllumpinnatum extract to prolong shelf life of fruits/vegetables
    • Amber Fatima
    • Fatima Tahir
    • Ayesha Mohyuddin
    • Tabassum Munir
    • Sohail Nadeem
    • Mohsin Javed
    • Mohd Hafiz Dzarfan Othman
    • Hui Hwang Goh
    • Hussein Al-Hazmi
    • Faissal Aziz
    • Abdelkader Anouzla
    • Tonni Agustiono Kurniawan
    2024 Journal of Food Measurement and Characterization

    Candelilla wax (CW) is a natural lipid source that can be used to make biodegradable and edible coatings and films for fruits. However, CW alone does not provide sufficient antimicrobial and antioxidant properties to prevent microbial spoilage and oxidative deterioration of fresh products. This study aims at evaluating the applicability of CW blended with Bryophyllum pinnatum extract (BPE), a plant with medicinal and phytochemical properties, to enhance the shelf life of fruits. CW and BPE were mixed at different ratios and applied as coatings on banana, cucumber, lemon, and apple. The coated fruits were stored at room temperature for several days and evaluated for weight loss (WL), pH, and physical appearance. The results showed that the edible CW coating mixed with B. pinnatum extract could extend the shelf-life of selected fruits by lowering their weight loss (WL), as compared to those without coating (p≤0.05; paired t-test). It was observed that % WL of banana was significantly higher in the control group than in the coated banana (p≤0.05; paired t-test) and that the highest WL (4.5%) was reached on the 4th day. The lowest WL (2.7%) was observed in the banana with edible coating with methanolic extract (ECME) formulation. The coating formed a complex layer that blocked the movement of H2O molecules through the selected fruits, preventing water loss. The smallest pH change was observed in the banana coated with the extract, indicating that the coating was suitable for extending the shell life of banana. Overall, CW enriched with BPE maintained the quality of their products for marketability.

  • Application of commercial microwave links (CMLs) attenuation for quantitative estimation of precipitation
    • Magdalena Pasierb
    • Zofia Bałdysz
    • Jan Szturc
    • Grzegorz Nykiel
    • Anna Jurczyk
    • Katarzyna Ośródka
    • Mariusz Figurski
    • Marcin Wojtczak
    • Cezary Wojtkowski
    2024 Full text METEOROLOGICAL APPLICATIONS

    Precipitation estimation models are typically sourced by rain gauges, weather radars and satellite observations. A relatively new technique of precipitation estimation relies on the network of Commercial Microwave Links (CMLs) employed for cellular communication networks: the rain-inducted attenuation in the links enables the precipitation estimation. In the paper, it is analysed to what extent the precipitation derived from CML attenuation data is useful in estimation of the precipitation field with the high temporal and spatial resolution required in nowcasting models. Two methods of determination of precipitation along CMLs from attenuation of signal with several frequencies were proposed. Then, in order to generate precipitation field, three approaches for assigning appropriate precipitation values to a specific point or set of pixels along the link are developed and tested. The CML-based estimates are compared with point observations from manual rain gauges and multi-source precipitation fields using daily and half-hourly accumulations. It was found that the CML-based precipitation fields are much worse than radar-derived estimates. At the same time, they had slightly poorer reliability than spatially interpolated telemetric rain gauge data and significantly higher reliability than satellite estimates. Furthermore, the impact of link characteristics, such as length and frequency, on the reliability of CML-based precipitation estimates is analysed.

  • Application Of Generative Adversarial Network for Data Augmentation and Multiplication to Automated Cell Segmentation of the Corneal Endothelium
    • Karolina Nurzyńska
    • Krystian Jandy
    • Paweł Weichbroth
    2024 Full text

    Considering the automatic segmentation of the endothelial layer, the available data of the corneal endothelium is still limited to a few datasets, typically containing an average of only about 30 images. To fill this gap, this paper introduces the use of Generative Adversarial Networks (GANs) to augment and multiply data. By using the ``Alizarine'' dataset, we train a model to generate a new synthetic dataset with over 513k images. A portion of this artificial dataset is then used to train a semantic segmentation model for endothelial layer segmentation and its performance is evaluated showing that in average the mean intersection over union for all datasets is equal to 81\%. In our opinion, the images of the endothelial layer, together with the corresponding masks generated by the GAN, effectively represent the desired data. The obtained results seem optimistic after visual inspection, since the segmentation is very precise.

  • Application of human bile salts for in vitro digestion models
    • Dorota Dulko
    2024 Full text

    In this study, experimental in vitro models simulating the environment of the human gastrointestinal tract were used to assess the impact of physiological surfactants, such as bile salts, on the kinetics of digestion. Bile salts are biosurfactants synthesised in the liver and secreted together with bile into the small intestine. There are many reports on the role of bile salts in lipolysis, but the knowledge of their influence on other nutrients, such as proteins, is very limited. The experiments I conducted included the comparison of a model system (individual bile salts) with real human bile (containing different concentrations of bile salts, phospholipids, and other substances) during in vitro lipolysis and proteolysis. Human bile samples were obtained in cooperation with a clinical hospital. For the first time, a quantitative analysis of the effects of human bile on the digestion of a model food protein and lipid was performed. Moreover, for the first time, the currently used static in vitro digestion models were validated from the point of view of the physiological role of bile salts in the human digestive tract. In this respect, it has been demonstrated in vitro how the effect of human bile on the proteolysis and lipolysis can be reliably reproduced by applying mixtures of individual bile salt and phospholipids.

  • Application of multicriteria decision analysis to assess the greenness of molecularly imprinted polymers synthesis components
    • Mariusz Marć
    • Katarzyna Pokajewicz
    • Marek Tobiszewski
    2024 MICROCHEMICAL JOURNAL

    The study applies multicriteria decision analysis (MCDA) to rank the components of molecularly imprinted polymers (MIPs) synthesis according to their greenness. The components are taken from papers that are describing synthesis of MIPs for persistent organic pollutants (POPs) sorbents. Functional monomers (n = 14), target/surrogate molecules (n = 10), porogens (n = 8), cross-linking agents (n = 8) and initiators (n = 4) are described with 10 criteria referring to their safety of application, toxicity, environmental persistence and bioaccumulability. The rankings are performed according to three scenarios, with the application of different weights. The ranking results give a specific guide on the selection of green synthesis components for polybrominated biphenyl ethers (PBDEs) as representatives of POPs, by identification of problematic and recommended chemicals. The results are useful in designing MIP synthesis protocols.

  • Application of quartz crystal microbalance and dynamic impedance spectroscopy to the study of copper corrosion inhibitors
    • Dominika Parasińska
    • Hubert Kwiatkowski
    • Paweł Ślepski
    2024 Journal of Materials and Manufacturing

    The study investigates the application of Dynamic Electrochemical Impedance Spectroscopy (DEIS) and Electrochemical Quartz Crystal Microbalance (EQCM) techniques to examine the corrosion inhibition of copper by Benzotriazole and Sodium Folate in a 0.1 M NaCl solution. DEIS, an advanced version of Electrochemical Impedance Spectroscopy (EIS), allows for real-time monitoring of non-stationary electrochemical systems, while EQCM enables the detection of minute mass changes during electrochemical reactions. Through 24-hour chronopotentiometric measurements, the study observed the effects of 5 mM Benzotriazole and 10 mM Sodium Folate on copper corrosion. Results indicated that Benzotriazole significantly enhances corrosion resistance by forming a protective layeron the copper surface, as evidenced by increased impedance and stable mass changes. Conversely, Sodium Folate exhibited a less effective, dynamic interaction with the copper surface. This research highlights the synergistic use of DEIS and EQCM in understanding corrosion mechanisms and inhibitor efficiency, providing insights into optimizing corrosion protection strategies. The findings suggest that whileboth inhibitors improve corrosion resistance, Benzotriazole demonstrates superior performance, underscoring its potential for more effective corrosion control in various industrial applications.

  • Application of the Heavy-Atom Effect for (Sub)microsecond Thermally Activated Delayed Fluorescence and an All-Organic Light-Emitting Device with Low-Efficiency Roll-off
    • Michał Mońka
    • Szymon Gogoc
    • Karol Kozakiewicz
    • Vladyslav Ievtukhov
    • Daria Grzywacz
    • Olga Ciupak
    • Aleksander Kubicki
    • Piotr Bojarski
    • Przemysław Data
    • Illia E. Serdiuk
    2024 Full text ACS Applied Materials & Interfaces

    Thefeatureof abundantandenvironmentallyfriendlyheavyatoms(HAs)like bromineto acceleratespin-forbiddentransitionsin organicmoleculeshas beenknownforyears.In combinationwiththe easinessof incorporation,brominederivativesof organicemittersshowingthermallyactivateddelayedfluorescence(TADF)emergeas a cheapand efficientsolutionforthe slowreverseintersystemcrossing(rISC)problemin suchemittersand strongefficiencyroll-offof all-organiclight-emittingdiodes(OLEDs).Here,we presenta comprehensivephotophysicalstudyof atri-PXZ-TRZemitterreportedpreviouslyanditshexabromoderivativeshowinga remarkableenhancementof rISCof up to 9 timesand a shortlifetimeof delayedfluorescenceof 2μs. Analysisof the key molecularvibrationsand TADFmechanismindicatesalmostcompeteblockageof the spin-fliptransitionbetweenthe charge-transferstatesof differentmultiplicity3CT→1CT.In sucha case,rISCas well as its enhancementby the HA is realizedvia the3LE→1CT transition,where3LE is the tripletstatelocalizedon the samebrominatedphenoxazinedonorinvolvedin the formationof the1CT state.Interestingly,the spin−orbitcoupling(SOC)withtwo other3LE statesis negligiblebecausethey are localizedon differentdonorsand not involvedin1CT. Weconsiderthis as an exampleof an additional“localization”criterionthat completesthe well-knownEl Sayedrule on the differentnatureof statesfor nonzeroSOC.The applicativepotentialof sucha hexabromoemitteris testedin a “hyperfluorescent”systemcontaininga red fluorescentdopant(tetraphenyldibenzoperiflanthene,DBP)as an acceptorof Försterresonanceenergytransfer,affordinga narrow-bandred-emittingsystem,withmostof the emissionin the submicroseconddomain.In fact, the fabricatedredOLEDdevicesshowremarkableimprovementof efficiencyroll-offfrom2−4 timesdependingon the luminance,mostlybecauseofthe increaseof the rISCconstantrate and the decreaseof the overalldelayedfluorescencelifetimethanksto the HA effect.

  • Approaches Towards Better Immunosuppressive Agents
    • Juliusz Walczak
    • Dorota Iwaszkiewicz-Grześ
    • Grzegorz Cholewiński
    2024 CURRENT TOPICS IN MEDICINAL CHEMISTRY

    Several classes of compounds are applied in clinics due to their immunosuppressive properties in transplantology and the treatment of autoimmune diseases. Derivatives of mycophe-nolic acid, corticosteroids and chemotherapeutics bearing heterocyclic moieties like methotrexate, azathioprine, mizoribine, and ruxolitinib are active substances with investigated mechanisms of action. However, improved synthetic approaches of known drugs and novel derivatives are still being reported to attempt better accessibility and therapeutic properties. In this review article, we present the synthesis of the designed chemical structures based on recent literature reports con-cerning novel compounds as promising immunosuppressive drugs. Moreover, some of the dis-cussed derivers revealed also other types of activities with prospective medicinal potential.

  • Approximation algorithms for job scheduling with block-type conflict graphs
    • Hanna Furmańczyk
    • Tytus Pikies
    • Inka Sokołowska
    • Krzysztof Turowski
    2024 COMPUTERS & OPERATIONS RESEARCH

    The problem of scheduling jobs on parallel machines (identical, uniform, or unrelated), under incompatibility relation modeled as a block graph, under the makespan optimality criterion, is considered in this paper. No two jobs that are in the relation (equivalently in the same block) may be scheduled on the same machine in this model. The presented model stems from a well-established line of research combining scheduling theory with methods relevant to graph coloring. Recently, cluster graphs and their extensions like block graphs were given additional attention. We complement hardness results provided by other researchers for block graphs by providing approximation algorithms. In particular, we provide a 2-approximation algorithm for and a PTAS for the case when the jobs are unit time in addition. In the case of uniform machines, we analyze two cases. The first one is when the number of blocks is bounded, i.e. . For this case, we provide a PTAS, improving upon results presented by D. Page and R. Solis-Oba. The improvement is two-fold: we allow richer graph structure, and we allow the number of machine speeds to be part of the input. Due to strong NP-hardness of , the result establishes the approximation status of . The PTAS might be of independent interest because the problem is tightly related to the NUMERICAL -DIMENSIONAL MATCHING WITH TARGET SUMS problem. The second case that we analyze is when the number of blocks is arbitrary, but the number of cut-vertices is bounded and jobs are of unit time. In this case, we present an exact algorithm. In addition, we present an FPTAS for graphs with bounded treewidth and a bounded number of unrelated machines. The paper ends with extensive tests of the selected algorithms.

  • Arabinoxylans: A review on protocols for their recovery, functionalities and roles in food formulations
    • Fernanda Jimena Hernández-Pinto
    • Juan Daniel Miranda-Medina
    • Abril Natera-Maldonado
    • Óscar Vara-Aldama
    • Mary Pily Ortueta-Cabranes
    • Jorge A. Vázquez del Mercado-Pardiño
    • Safaa A.M. El-Aidie
    • Shahida Anusha Siddiqui
    • Roberto Castro Munoz
    2024 INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES

    Arabinoxylans (AXs) are compounds with high nutritional value and applicability, including prebiotics or supplementary ingredients, in food manufacturing industries. Unfortunately, the recovery of AXs may require advanced separation and integrated strategies. Here, an analysis of the emerging techniques to extract AXs from cereals and their by-products is discussed. This review covers distinct methods implemented over the last 2–3 years, identifying that the type of method, extraction source, AX physicochemical properties and pre-treatment conditions are the main factors influencing the recovery yield. Alkaline extraction is among the most used methods nowadays, mostly due to its simplicity and high recovery yield. Concurrently, recovered AXs applied in food applications is timely reviewed, such as potential bread ingredient, prebiotic and as a wall material for probiotic encapsulation, in beer and non-alcoholic beverage manufacturing, complementary ingredient in bakery products and cookies, improvers in Chinese noodles, 3D food printing and designing of nanostructures for delivery platforms.

  • Architectural Modifications to Enhance Steganalysis with Convolutional Neural Networks
    • Remigiusz Martyniak
    • Bartosz Czaplewski
    2024

    This paper investigates the impact of various modifications introduced to current state-of-the-art Convolutional Neural Network (CNN) architectures specifically designed for the steganalysis of digital images. Usage of deep learning methods has consistently demonstrated improved results in this field over the past few years, primarily due to the development of newer architectures with higher classification accuracy compared to their predecessors. Despite the advances made, further improvements are desired to achieve even better performance in this field. The conducted experiments provide insights into how each modification affects the classification accuracy of the architectures, which is a measure of their ability to distinguish between stego and cover images. Based on the obtained results, potential enhancements are identified that future CNN designs could adopt to achieve higher accuracy while minimizing their complexity compared to current architectures. The impact of modifications on each model’s performance has been found to vary depending on the tested architecture and the steganography embedding method used.

  • Architecture at the Sites of the Former Nazi Concentration Camps. Functional Changeability of Commemoration
    • Agnieszka Gębczyńska-Janowicz
    2024 Full text

    The monograph presents a comprehensive analysis of the architectural structures created in the former concentration camps in Europe under the SS Main Economy and Administration Office. It delves into the history of memorial site creation in these areas, emphasizing the unique characteristics of monuments dedicated to the victims of terror. Additionally, the study covers the post-war architectural transformations in these areas, offering a detailed understanding of the historical and structural aspects of these memorial sites and monuments. This research highlights that architecture serves as more than just a structure; it is a powerful means of reorganizing space to establish a place that embodies memory. It demonstrates how architecture shapes space to commemorate the crimes committed and honor the victims, emphasizing the crucial role of design in preserving history.

  • Are creative users more apt in reusing and adopting Open Government Data (OGD)? Gender differences
    • Charalampos Harris Alexopoulos
    • Stuti Saxena
    • Nina Rizun
    • Ricardo Matheus
    • Marijn Janssen
    2024 Thinking Skills and Creativity

    Open Government Data (OGD) has been considered as a potent instrument for value creation and innovation by a range of stakeholders. Given that individual ingenuity is a function of individual and environmental factors, it is important to understand how the OGD adoption and usage is a factor of creative performance behaviors (CPB), viz., Problem Identification (PI), Information Search (IS), Idea Generation (IG) and Idea Promotion (IP) as well as creative self-efficacy (CSE). Invoking the adapted Unified Theory of Acceptance and Use of Technology (UTAUT) constructs alongside the moderating effects of CPB and CSE constructs and also gender, the present study seeks to underline the behavioural intention towards OGD adoption and usage among 362 undergraduate and postgraduate university students in India. Findings show that there are gender differences across the CPB and CSE constructs. The study’s contribution lies in furthering our understanding of OGD adoption and use with creativity literature

  • Artificial Intelligence for Wireless Avionics Intra-Communications
    • Samano Ramiro Robles
    • R. Venkatesha Prasad
    • Ad Arts
    • Mateusz Rzymowski
    • Łukasz Kulas
    2024

    This chapter presents a summary of the description and preliminary results of the use case related to the implementation of artificial intelligence tools in the emerging technology called wireless avionics intra-communications (WAICs). WAICs aims to replace some of the cable buses of modern aircraft. This replacement of infrastructure leads to: (1) complexity reduction of future airplanes, (2) creation of innovative services where wireless links are more flexible than wireline links, and mainly (3) a considerable weight reduction, which in turn leads to fuel consumption efficiency, increase of payload, as well as range extension. Therefore, WAICs is expected to have a large impact on the aeronautics industry, propelling a new generation of greener, more efficient, and less expensive aeronautical services. However, there are still several reliability, trust, interoperability and latency issues that need to be addressed before this technology becomes commercial. It is expected that AI will boost the applicability of this technology, contributing to the realization of the concept of “fly-by-wireless”.

  • Artificial intelligence in architectural education - green campus development research
    • Jan Cudzik
    • Lucyna Nyka
    • Jakub Szczepański
    2024 Full text Global Journal of Engineering Education

    The rapid advancement of artificial intelligence (AI) technologies has introduced new possibilities and challenges in design education. This article explores the need for changes and adaptations in the teaching process of design as AI-related technologies, based on image generation, transform the creative process and offer novel opportunities. In a research-by-design studio in an architectural faculty in Poland, students who utilised AI tools achieved more innovative and pioneering results than those designed with traditional tools. Based on these results, three alternative methods of working with AI tools were identified. In the semi-traditional approach, AI-generated images served for inspirational purposes solely. In the hybrid system, students integrated fragments of these images into their own urban decisions. Finally, in the hybrid-interactive approach, students used the higher-order loops in computer-human interaction to achieve more site-specific results. The research underscores the vast potential of AI integration, using image generation models in reshaping architectural design methodologies based on best practice.

  • Artificial Intelligence in the Diagnosis of Onychomycosis—Literature Review
    • Barbara Bulińska
    • Magdalena Mazur-Milecka
    • Martyna Sławińska
    • Jacek Rumiński
    • Roman Janusz Nowicki
    2024 Journal of Fungi

    Onychomycosis is a common fungal nail infection that is difficult to diagnose due to its similarity to other nail conditions. Accurate identification is essential for effective treatment. The current gold standard methods include microscopic examination with potassium hydroxide, fungal cultures, and Periodic acid-Schiff biopsy staining. These conventional techniques, however, suffer from high turnover times, variable sensitivity, reliance on human interpretation, and costs. This study examines the potential of integrating AI (artificial intelligence) with visualization tools like dermoscopy and microscopy to improve the accuracy and efficiency of onychomycosis diagnosis. AI algorithms can further improve the interpretation of these images. The review includes 14 studies from PubMed and IEEE databases published between 2010 and 2024, involving clinical and dermoscopic pictures, histopathology slides, and KOH microscopic images. Data extracted include study type, sample size, image assessment model, AI algorithms, test performance, and comparison with clinical diagnostics. Most studies show that AI models achieve an accuracy comparable to or better than clinicians, suggesting a promising role for AI in diagnosing onychomycosis. Nevertheless, the niche nature of the topic indicates a need for further research.