Lublin University of Technology Journals
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Study of factors affecting the performance of web applications on mobile devices
Get PDFThe aim of the article is to investigate the factors affecting the performance of Progressive Web Applications (PWAs) on mobile devices. For research purposes, a custom PWA website was created, which served as the primary object of analysis. Various optimization techniques were then applied to the site, including resource minimization, lazy loading, and a distributed content delivery network. The performance analysis of the PWA site was conducted using assessment tools such as PageSpeed Insights, DebugBear, Uptrends, and WebPageTest. The research results were grouped according to several criteria, such as page load time, interactivity, and overall application performance. The obtained results were analyzed after each optimization was implemented. Based on the conducted analysis, conclusions were drawn regarding the impact of the applied optimization techniques on the performance of the PWA. The article emphasizes the importance of continuous optimization and monitoring of applications to ensure high-quality user experiences, as well as presenting an effective alternative method for developing applications for mobile devices
Analysis of the use of Angular and Svelte products in mobile web applications
Get PDFThe aim of this article is to analyze the use of Angular and Svelte tools in the development of a web application. The analysis focused on a custom application that allows measuring component rendering times and application build parameters. The research scenarios also considered the popularity of the frameworks. The results indicate higher performance for a small application created with Svelte, while Angular enjoys greater popularity
An ensemble model for maternal health risk classification in Delta State, Nigeria
Get PDFMaternal mortality remains a critical challenge in Sub-Saharan Africa, with Nigeria ranking among the countries with the highest rates. The loss of women in their reproductive years destabilizes families causing emotional trauma, places additional strain on healthcare systems, and has profound economic and national developmental consequences. As a result, one of the United Nations Sustainable Development goals (SDGs) is targetted at reducing maternal mortality and morbidity at all cost. This study explores the application of Artificial Intelligence (AI) in healthcare through the development of a predictive ensemble model to classify maternal health risks as identifying high risk pregnancies can inform timely clinical decision making that mitigates maternal mortality. Maternal health dataset was sourced from three (3) health centers in Delta State, Nigeria.. Nine supervised machine learning classifiers were utilized, including Linear Support Vector Machine, Gaussian Naïve Bayes, Multilayer Perceptron, Decision Tree, Random Forest, Gradient Boosting Decision Tree, Extreme Gradient Boosting, Light Gradient Boosting Machine, and Categorical Boosting. To enhance predictive performance, the classifiers were combined in an ensemble model. Results showed that the Gradient Boosting Decision Tree achieved the highest accuracy at 90% before upsampling and Random Forest achieved an accuracy of 97% at upsampling. The lowest-performing classifier was Linear Support Vector Machine before and after upsampling. The ensemble model surpassed all individual classifiers, achieving 98% accuracy and precision and over 1% increase in accuracy after upsampling. This study highlights the potential of AI-driven predictive models to optimize healthcare resources and improve maternal health outcomes in Delta State, Nigeria
Transforming ERP interfaces in production environments: An empirical evaluation using the User Experience Questionnaire
Get PDFThis study aims to evaluate the user experience (UX) of Enterprise Resource Planning (ERP) system modules in Polish enterprises' information and communication technology-based production environments. The research plan includes quantitative research as part of a doctoral thesis, which will be complemented by qualitative methods such as task-based usability tests, heuristic analysis and in-depth interviews with users. A descriptive research design was employed using an online survey incorporating the User Experience Questionnaire (UEQ) to gather quantitative data. The survey was distributed to a diverse group of respondents, including students, alumni, and production practitioners, to capture perceptions of three screens of the ERP system (General Operations Registration, Personalised Operations Registration, and Employee Panel Operations Registration), which enable the registration of operations. Raw responses from a seven-point Likert scale were transformed into a continuous scale and statistical analyses were conducted to compute descriptive metrics and confidence intervals. The findings indicate that the pragmatic dimensions — namely, perspicuity, efficiency, and dependability — received favourable evaluations, demonstrating robust usability and clear functionality. In contrast, the hedonic dimensions, particularly stimulation and novelty, were rated as neutral to negative. This suggests that, although the ERP modules effectively support routine tasks, they lack innovative appeal and engaging design. Benchmark comparisons revealed that the interfaces generally fell within the lower quartile, highlighting the need for targeted UI/UX refinements to enhance visual attractiveness and user motivation. In conclusion, the study highlights the importance of balancing functional performance with improved aesthetic and hedonic attributes to optimise the effectiveness of ERP systems in production engineering settings
Fuzzy logic in arrhythmia detection: A systematic review of techniques, applications, and clinical interpretability
Get PDFAccurate and interpretable arrhythmia detection is essential for timely diagnosis and intervention, particularly in Medical Decision Support Systems (MDSS). Fuzzy logic, known for its ability to handle uncertainty and enhance interpretability, has emerged as a promising approach. This systematic literature review (SLR) investigates the role of fuzzy logic in advancing arrhythmia detection, focusing on accuracy, interpretability, and integration with computational intelligence. Following the PRISMA guidelines, 13 studies published between 2019 and 2024 were analysed to address four key questions: (Q1) the accuracy and reliability of fuzzy logic systems, (Q2) the effectiveness of hybrid systems combining fuzzy logic with computational intelligence, (Q3) the challenges in developing multi-class fuzzy logic systems, and (Q4) the impact of fuzzy logic on interpretability in MDSS. Techniques such as Adaptive Neural Fuzzy Inference Systems (ANFIS) and hybrid models with neural networks and bio-inspired algorithms were evaluated. ANFIS demonstrated near-perfect accuracy, while hybrid systems enhanced scalability and addressed multi-class classification challenges. Limitations included reliance on benchmark datasets, limited real-world validation, and insufficient focus on explainable artificial intelligence (XAI). Fuzzy logic shows strong potential for developing interpretable and robust MDSS for arrhythmia detection. Future research should prioritise advancing XAI, incorporating diverse datasets, and addressing real-world challenges to improve clinical applicability
Noise source analysis of the nitrogen generation system
Get PDFThis study presents a comprehensive noise source analysis of a nitrogen generation system installed at an industrial production facility. The primary goal of the investigation was to determine the location of the dominant noise sources, as well as to identify their respective sound pressure levels and frequency characteristics under operational conditions. Detailed measurements were conducted using a 16-microphone array combined with the CAE Noise Inspector software for accurate sound field visualisation and analysis. Experimental tests were carried out at three distinct locations within the system: the nitrogen generation installation (location 1), the nitrogen storage tank (location 2), and the ejection tube for exhaust gases (location 3), with the latter further subdivided into three specific measurement points (3a, 3b, 3c) to account for variations along the tube length. Each acoustic measurement session lasted three seconds, with data captured at a high recording frequency of 204,800 Hz to ensure precise resolution across the frequency spectrum. The operational cycle of the nitrogen generator was divided into two main phases: phase 1, characterised by the transient sounds associated with valve actuation, and phase 2, dominated by the continuous noise generated during nitrogen transfer to storage tanks and exhaust gas expulsion. Recordings taken at location 1 captured both operational phases, while measurements at locations 2 and 3 were focused exclusively on phase 2 to isolate relevant noise sources. The results provide a detailed and quantitative characterisation of the acoustic emissions associated with the nitrogen generation process, offering valuable insights that can inform the development of targeted noise reduction strategies and contribute to the future optimisation of the system’s mechanical design and operational efficiency
Samolot z okładki
Get PDFWhat you will find in the current issueO tym, co znajdziesz w aktualnym numerz
Lot marzeń
Get PDFThe contest called “Dream Flight” was organized for children of preschool age. The task of the participants was to build a model of a dream flying ship.Konkurs pod nazwą „Lot marzeń” został zorganizowany z myślą o dzieciach w wieku przedszkolnym. Zadaniem uczestników było zbudowanie makiety wymarzonego statku latającego
Ocena właściwości termoizolacyjnych zrównoważonych materiałów budowlanych w południowej Algierii: badanie gipsu i włókien palmowych
Get PDFThis research addresses the critical need to develop environmentally friendly building materials with effective insulation properties in Southern Algeria, a region increasingly affected by extreme natural phenomena such as intense heat. By exploring the potential of plaster, known for its excellent insulation characteristics, and palm fibres, a sustainable alternative to synthetic fibres, this study offers a promising future for the construction industry in the region. Plaster composites reinforced with 10 mm palm fibres were developed at 2%, 4%, and 6% fibre ratios and water-to-plaster (W/P) ratios of 0.8, 1, and 1.5. After 28 days, physical, mechanical, and thermal properties were evaluated. The results revealed that composites with 6% fibre and a 1.5 W/P ratio exhibited favourable physical properties, particularly a low density of 0.88 g/cm³, making them lightweight. Although the compressive strength decreased to 5.23 MPa with increasing fibre and water content, it remained within acceptable limits. The thermal conductivity decreased to 0.19 W/mK, and the specific heat increased to 1012.17 J/kg·K, highlighting the material's effectiveness as an insulator. This study demonstrates the potential of local, sustainable building materials, positioning date palm fibre-reinforced plaster composites as a viable solution for sustainable construction. The findings encourage further research on optimising these composites for broader environmentally conscious construction applications.Niniejsze badania odpowiadają na krytyczną potrzebę opracowania przyjaznych dla środowiska materiałów budowlanych o skutecznych właściwościach izolacyjnych w południowej Algierii, regionie coraz bardziej dotkniętym ekstremalnymi zjawiskami naturalnymi, takimi jak intensywne ciepło. Poprzez eksplorację potencjału tynku, znanego ze swoich doskonałych właściwości izolacyjnych, oraz włókien palmowych, zrównoważonej alternatywy dla włókien syntetycznych, niniejsze badanie oferuje obiecującą przyszłość dla branży budowlanej w regionie. Kompozyty tynkowe wzmocnione 10-milimetrowymi włóknami palmowymi opracowano przy proporcjach włókien 2%, 4% i 6% oraz współczynnikach wody do tynku (W/P) 0,8, 1 i 1,5. Po 28 dniach oceniono właściwości fizyczne, mechaniczne i termiczne. Wyniki wykazały, że kompozyty z 6% włókien i współczynnikiem W/P 1,5 wykazywały korzystne właściwości fizyczne, w szczególności niską gęstość 0,88 g/cm³, co czyniło je lekkimi. Chociaż wytrzymałość na ściskanie spadła do 5,23 MPa wraz ze wzrostem zawartości włókien i wody, pozostała w dopuszczalnych granicach. Przewodność cieplna spadła do 0,19 W/mK, a ciepło właściwe wzrosło do 1012,17 J/kg·K, co podkreśla skuteczność materiału jako izolatora. Badanie to pokazuje potencjał lokalnych, zrównoważonych materiałów budowlanych, pozycjonując kompozyty tynkowe wzmocnione włóknami palmy daktylowej jako realne rozwiązanie dla zrównoważonego budownictwa. Wyniki zachęcają do dalszych badań nad optymalizacją tych kompozytów pod kątem szerszych zastosowań w budownictwie przyjaznym dla środowiska
Sztuczna inteligencja w edukacji: symulacje oparte na ChatGPT w przygotowaniu nauczycieli
Get PDFToday, the problem of using artificial intelligence (AI) in education is essential. Recent studies have detected several challenges in using AI for correct assessment, academic integrity, etc. So, the problem of finding positive practices for using AI in education needs to be studied more closely. We perceive ChatGPT as a digital tool for teacher training, which makes it possible to simulate students' problem-solving process and analyze it critically. It is shown that ChatGPT makes mistakes in solutions, so the generated false answers become an essential training tool in teacher training. It became the base for experimental teaching. The research aims to substantiate the effectiveness of using ChatGPT as a simulation environment to develop pre-service teachers' critical thinking. The statistical analysis of the experiment results proved that ChatGPT is an effective digital tool for developing mathematics and computer science teachers' critical thinking.Obecnie problem wykorzystania sztucznej inteligencji (AI) w edukacji jest niezwykle istotny. Ostatnie badania wykryły kilka wyzwań związanych z wykorzystaniem sztucznej inteligencji do prawidłowej oceny, uczciwości akademickiej itp. Tak więc problem znalezienia pozytywnych praktyk w zakresie wykorzystania sztucznej inteligencji w edukacji wymaga dokładniejszego zbadania. Postrzegamy ChatGPT jako cyfrowe narzędzie do szkolenia nauczycieli, które umożliwia symulację procesu rozwiązywania problemów przez uczniów i jego krytyczną analizę. Wykazano, że ChatGPT popełnia błędy w rozwiązaniach, więc wygenerowane fałszywe odpowiedzi stają się niezbędnym narzędziem szkoleniowym w szkoleniu nauczycieli. Stało się to podstawą nauczania eksperymentalnego. Badanie ma na celu potwierdzenie skuteczności wykorzystania ChatGPT jako środowiska symulacyjnego do rozwijania krytycznego myślenia nauczycieli. Analiza statystyczna wyników eksperymentu dowiodła, że korzystanie z ChatGPT jest skutecznym narzędziem cyfrowym do rozwijania krytycznego myślenia nauczycieli matematyki i informatyki