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Katalog Publikacji
Rok 2025
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Monitoring of absorptive model biogas purification process using sensor matrices and gas chromatography
PublikacjaThis study examined the process of purifying model biogas using a new type of absorbent based on a Deep Eutectic Solvent (DES) and a commercially available absorbent (Genosorb) to remove acetone, toluene, and cyclohexane. The main aim of the research was to control the purification efficiency using gas chromatography (GC) and an alternative method based on sensor matrices (SM). As a result of comparing the multidimensional SM signals...
Rok 2024
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Machine Learning and Deep Learning Methods for Fast and Accurate Assessment of Transthoracic Echocardiogram Image Quality
PublikacjaHigh-quality echocardiogram images are the cornerstone of accurate and reliable measurements of the heart. Therefore, this study aimed to develop, validate and compare machine learning and deep learning algorithms for accurate and automated assessment of transthoracic echocardiogram image quality. In total, 4090 single-frame two-dimensional transthoracic echocardiogram...
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Machine learning approach to packaging compatibility testing in the new product development process
PublikacjaThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublikacjaWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublikacjaHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublikacjaIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublikacjaMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublikacjaAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Macrocyclic derivatives of imidazole as chromoionophores for bismuth(III)/lead(II) pair
Publikacja18-membered diazomacrocycles with imidazole or 4-methylimidazole residue as a part of macrocycle were used as chromoionophores in bismuth(III) and lead(II) dual selective optodes for the first time. Cellulose triacetate membranes doped with macrocyclic chromoionophores are bismuth(III) and lead(II) selective with color change from orange/red to different shades of blue and violet, respectively. Results obtained for model and real...
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Magnetic field mapping along a NV-rich nanodiamond-doped fiber
PublikacjaIntegration of NV−-rich diamond with optical fibers enables guiding quantum information on the spin state of the NV− color center. Diamond-functionalized optical fiber sensors have been demonstrated with impressive sub-nanotesla magnetic field sensitivities over localized magnetic field sources, but their potential for distributed sensing remains unexplored. The volumetric incorporation of diamonds into the optical fiber core allows...
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Magnetic hydrophobic deep eutectic solvents for orbital shaker-assisted dispersive liquid-liquid microextraction (MAGDES-OS-DLLME) - determination of nickel and copper in food and water samples by FAAS
PublikacjaIn this work, a cheap and widely applicable dispersive liquid-liquid microextraction (DLLME) method was developed for the extraction of Ni(II) and Cu(II) from water and food samples and analysis using flame atomic absorption spectrometry. DLLME was assisted by orbital shaker, while ferrofluid as an extractant was based on deep eutectic solvent (DES). This ferrofluid was made of hydrophobic DES (hDES), composed of lauric acid and...
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Magnetic superhydrophobic melamine sponges for crude oil removal from water
PublikacjaThis paper proposes the preparation of a new sorbent material based on melamine sponges (MS) with superhydrophobic, superoleophilic, and magnetic properties. This study involved impregnating the surface of commercially available MS with eco-friendly deep eutectic solvents (DES) and Fe3O4 nanoparticles. The DES selection was based on the screening of 105 eutectic mixtures using COSMO-RS modeling. Other parameters affecting the efficiency...
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Magnetyczne i elektromagnetyczne uchwyty obróbkowe - konstrukcja i rozwój
PublikacjaPrzedstawiono współczesne rozwiązania konstrukcyjne obróbkowych uchwytów magnetycznych i elektromagnetycznych. Podano przykłady zastosowania w operacjach obróbki wiórowej i ściernej oraz w różnorodnych procesach spawania. Omówiono ważniejsze zalecenia technologiczne oraz ograniczenia praktyczne.
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Management of ground tire rubber waste by incorporation into polyurethane-based composite foams
PublikacjaRapid economic growth implicated the developing multiple industry sectors, including the automotive branch, increasing waste generation since recycling and utilization methods have not been established simultaneously. A very severe threat is the generation of enormous amounts of post-consumer tires considered burdensome waste, e.g., due to the substantial emissions of volatile organic compounds (VOCs). Therefore, it is essential...
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Managing and funding the innovative path: a close look at the SimLE scientific club at Gdańsk University of Technology, Poland
PublikacjaThis article presents a case study of the simply learn experience (SimLE) scientific club at Gdańsk University of Technology (Gdańsk Tech), Gdańsk, Poland, showcasing an effective model for blending theoretical knowledge with practical engineering applications. This student-led organisation aims to develop soft skills and handson experience through project work, participation in international contests and conferences. This study...
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Managing knowledge in a tourism crisis: case study from Poland
PublikacjaPurpose: This study deals with a tourism organisation from Poland, which experienced not only the COVID-19 pandemic, but also the close war situation in Ukraine which caused a significant decrease in tourist traffic and revenues. Since, based on the literature, knowledge management can be useful for crisis management, this study aims to explore the role and usefulness of KM during crisis situations in tourism. Methodology: Qualitative...
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Mangiferin: A comprehensive review on its extraction, purification and uses in food systems
PublikacjaWith the target of fabricating healthier products, food manufacturing companies look for natural-based nutraceuticals that can potentially improve the physicochemical properties of food systems while being nutritive to the consumer and providing additional health benefits (biological activities). In this regard, Mangiferin joins all these requirements as a potential nutraceutical, which is typically contained in Mangifera indica...
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Manipulating Electrical Properties of Nanopatterned Double-Barrier Schottky Junctions in Ti/TiOx/Fe Systems
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