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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublikacjaDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublikacjaMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Towards classification of patients based on surface EMG data of temporomandibular joint muscles using self-organising maps
PublikacjaThe study considers the need for an effective method of classification of patients with a temporomandibular joint disorder (TMD). The self-organising map method (SOM) was applied to group patients and used together with the cross-correlation approach to interpret the processed (rectified and smoothed by using root mean square (RMS) algorithm) surface electromyography signal (sEMG) obtained from testing the muscles (two temporal...
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Global Approaches to Reduce Light Pollution from Media Architecture and Non-Static, Self-Luminous LED Displays for Mixed-Use Urban Developments
PublikacjaUrban environments have become significantly brighter and more illuminated, and cities now consider media architecture and non-static, self-luminous LED displays an essential element of their strategy to attract residents, visitors, and tourists in the hours after dark. Unfortunately, most often, they are not designed with care, consideration, and awareness, nor do they support the visual wellbeing and circadian rhythms of humans....
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublikacjaSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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Anita Maria Dąbrowicz-Tlałka dr
OsobyUzyskała, z wynikiem bardzo dobrym, tytuł magistra na kierunku matematyka na Wydziale Matematyki Uniwersytetu Gdańskiego. Praca magisterska pt. „Zbiory swojskie i dzikie w R3” była z dziedziny topologia geometryczna. Równolegle ukończyła na Uniwersytecie Gdańskim „Podyplomowe Studium Podstaw Informatyki”. W 2001 roku uzyskała na Politechnice Poznańskiej tytuł doktora nauk matematycznych. Praca doktorska pt. „Iteracje monotoniczne...
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublikacjaPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublikacjaAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublikacjaOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublikacjaTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Anna Lisowska-Oleksiak prof. dr hab.
OsobyAnna Lisowska-Oleksiak, born in 1952, has been working at GUT since 1977. Currently is employed at the Faculty of Chemistry as a full professor. She was employed as a research assistant at the University of St Andrews in the group of C. A. Vincent and P.G. Bruce (1991-1994). She completed a two-month research internship in CEA Grenoble (2011). Anna Lisowska-Oleksiak obtained her MSc in chemistry at Nicolaus Copernicus University...
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Wiktoria Wojnicz dr hab. inż.
OsobyDSc in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2019 PhD in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2009 (with distinction) Publikacje z listy MNiSW (2009 - ) Wojnicz W., Wittbrodt E., Analysis of muscles' behaviour. Part I. The computational model of muscle. Acta of Bioengineering and Biomechanics, Vol. 11, No.4, 2009, p. 15-21 Wojnicz W., Wittbrodt E., Analysis...
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Use of Modified Cuckoo Search algorithm in the design process of integrated power systems for modern and energy self-sufficient farms
PublikacjaIn the face of increasingly stringent pollutant emission regulations, designing an agricultural holding becomes a difficult challenge of connecting a large number of coefficients that describe an energy system of a farm in regard to its ecological and economic efficiency. One way to cope with this issue is to design an energy self-sufficient farm that integrates various technologies, including renewable energy. However, the selection...
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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublikacjaIn 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...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublikacjaNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublikacjaBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Digital competence learning in secondary adult education in Finland and Poland
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Building the Learning Environment for Sustainable Development: a Co-creation approach
PublikacjaEducation for sustainable development supports the improvement of knowledge, skills, attitudes and behaviors related to global challenges such as climate change, global warming and environmental degradation, among others. It is increasingly taking place through projects based on information and communication technologies. The effectiveness of the actions taken depends not only on the quality of the project activities or the...
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Agent-Based Population Learning Algorithm for RBF Network Tuning
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An A-Team Approach to Learning Classifiers from Distributed Data Sources
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An A-Team approach to learning classifiers from distributed data sources
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Becoming a Learning Organization Through Dynamic Business Process Management
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The detection of Alternaria solani infection on tomatoes using ensemble learning
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Scheduling Repetitive Construction Processes Using the Learning-Forgetting Theory
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Generation of microbial colonies dataset with deep learning style transfer
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Deep learning-based waste detection in natural and urban environments
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Meta-Design and the Triple Learning Organization in Architectural Design Process
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Employing a biofeedback method based on hemispheric synchronization in effective learning
PublikacjaIn this paper an approach to build a brain computer-based hemispheric synchronization system is presented. The concept utilizes the wireless EEG signal registration and acquisition as well as advanced pre-processing methods. The influence of various filtration techniques of EOG artifacts on brain state recognition is examined. The emphasis is put on brain state recognition using band pass filtration for separation of individual...
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Didaktische simulationsmodelle fur E-learning in der IK-ausbildung.
PublikacjaPrzedstawiono dydaktyczne modele symulacyjne wykorzystywane w zdalnym kształceniu z zakresu informatyki i technik komunikacyjnych. Pokazano na przykładach zbudowanych symulatorów, w jaki sposób zrealizować lub dostosować modele symulacyjne do zdalnego nauczania. Opisano doświadczenia autorów w wykorzystaniu modeli symulacyjnych w zdalnym nauczaniu.
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Playback detection using machine learning with spectrogram features approach
PublikacjaThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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DentalSegmentator: robust deep learning-based CBCT image segmentation
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublikacjaDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Cyclic voltammograms of WS2/userGOx (composites of tungsten disulfide and ultrafast self-expanded and reduced graphene oxide) and ex-WS2 (exfoliated tungsten disulfide)
Dane BadawczeThese data contain cyclic voltammograms of WS2/userGOx (composites of tungsten disulfide and ultrafast self-expanded and reduced graphene oxide) and ex-WS2 (exfoliated tungsten disulfide). The data were collected for samples obtained from three ex-WS2:GO dispersions - with 1:1, 1:2, and 2:1 weight ratios.
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Raman spectra of WS2/userGOx (composites of tungsten disulfide and ultrafast self-expanded and reduced graphene oxide) and ex-WS2 (exfoliated tungsten disulfide)
Dane BadawczeThese data contain Raman spectra of WS2/userGOx (composites of tungsten disulfide and ultrafast self-expanded and reduced graphene oxide) and ex-WS2 (exfoliated tungsten disulfide). The data were collected for samples obtained from three ex-WS2:GO dispersions - with 1:1, 1:2, and 2:1 weight ratios.
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublikacjaThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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Fractional delayor application in self-tuning sub-sample delay estimator
PublikacjaW artykule przedstawiono nowe rozwiązanie samonastrajalnego estymatora opóźnienia sygnału sinusoidalnego. Estymator działa w czasie dyskretnym. Proponowane rozwiązanie wykorzystuje kaskadowe połączenie cyfrowego filtru ułamkowo opóźniającego służącego do synchronizacji próbkowania i liniowo-fazowego cyfrowego filtru Hilberta. Oryginalność polega na zastosowaniu tu filtrów cyfrowych o bardzo małej złożoności numerycznej. Jest ona...
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Minimal number of periodic points for smooth self-maps of S^3
PublikacjaW pracy wyznaczona została najmniejsza liczba punktów periodycznych w gładkiej klasie homotopii odwzorowania sfery trójwymiarowej w siebie.
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Usefulness of the Free Length Theory for assessment of the self-association of the pure solvents
PublikacjaWykonano pomiary szybkości rozchodzenia się dźwięku i gęstości metanolu, acetonitrylu, N,N-dimetyloformamidu, N,N-dimetyloacetamidu, dimetylosulfotlenku i fosforanu trietylu w zakresie temperatur 294 - 333 K . W oparciu o wyznaczone ściśliwości adiabatyczne zastosowano teorię FLT do oceny wzajemnej asocjacji cząsteczek. Uzyskane wyniki przedyskutowano na tle innych sposobów klasyfikacji rozpuszczalników.
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Gendered Self-Views Across 62 Countries: A Test of Competing Models
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Wear measurements of self-lubricating bearing materials in small oscillatory movement
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Polish Honor and Norwegian Dignity: Life Satisfaction, Acculturation, and Self-Worth
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Ecotoxicity and chemical sediment data classification by the useof self-organising maps
PublikacjaArtykuł dotyczy przedstawiania nowej interpretacji szacowania jakości osadów. To oryginalne podejście bada powiązania między parametrami ekotoksyczności (ostrej i chronicznej) i składnikami chemicznymi (zanieczyszczenia takie jak polichlorowane bifenyle, pestycydy, wielopierścieniowe węglowodory aromatyczne, metale ciężkie) próbek osadów Jeziora Turawskiego (Polska) poprzez zastosowanie samoorganizujących się map (SOM) wobec badanego...
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Expansion of the self of activists and nonactivists involved in mass gatherings for collective action
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Independent and Interdependent? Agentic and Communal? Self-construals of People Fused with a Group
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Comparison of Aging Simulation to Real Aging of Silicone Self-adhesives Tapes
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Influence of UV on the self-adhesive properties of silicone pressure-sensitive adhesives
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Algebraic periods of self-maps of a rational exterior space of rank 2
PublikacjaArtykuł stanowi kompletny opis okresów algebraicznych dla odwzorowań wymiernej przestrzeni zewnętrznej rangi 2 w siebie.
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Modulation of polyene antibiotics self-association by ions from the hofmeister series
PublikacjaZbadano wpływ soli z serii hofmeistera na zjawisko samoasocjacji antybiotyku polienowego amfoterycyny B i jego pochodnych. Wykazano, że sole te zmieniając właściwości wody, wpływają istotnie na strukturę roztworów tych antybiotyków. Sole kosmotropowe zmniejszają rozpuszczalność związków, chaotropowe dają efekt przeciwny. Informacja ta jest istotna dla zrozumienia natury toksyczności amfoterycyny B i jej pochodnych.
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On the growth of the number of periodic points for smooth self maps of a compact manifold
PublikacjaDla ciągłego przekształcenia jednospójnej rozmaitości wymiaru co najmniej 3 w siebie, wykazujemy, że wzrost liczby punktów r-periodycznych w klasie homotopii może być nie szybszy niż liniowy, dla dowolnego, ustalonego r.
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Self-lubricating epoxide composites Kompozyty epoksydowe o właściwościach samosmarujących
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