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Exposure of a small Arctic seabird, the little auk (Alle alle) breeding in Svalbard, to selected elements throughout the course of a year
PublicationThe Arctic marine ecosystem can be altered by processes of natural and anthropogenic origin. Spatio-temporal variation in species exposure to contamination is still poorly understood. Here, we studied elemental concentrations in the non-lethally collected samples from the most numerous seabird in European Arctic, the little auk (Alle alle) nesting in one breeding colony in Svalbard. This seabird spent the breeding season in the...
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E. Rogala BP
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite 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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How does the Relationship Between the Mistakes Acceptance Component of Learning Culture and Tacit Knowledge-Sharing Drive Organizational Agility? Risk as a Moderator
PublicationChanges in the business context create the need to adjust organizational knowledge to new contexts to enable the organizational agile responses to secure competitiveness. Tacit knowledge is strongly contextual. This study is based on the assumption that business context determines tacit knowledge creation and acquisition, and thanks to this, the tacit knowledge-sharing processes support agility. Therefore, this study aims to expose...
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublicationPopularity 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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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment 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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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublicationAir 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
PublicationOne 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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Magnetic anisotropy and structural flexibility in the f ield-induced single ion magnets [Co{(OPPh2) (EPPh2)N}2], E = S, Se, explored by experimental and computational methods
PublicationDuring the last few years, a large number of mononuclear Co(II) complexes of various coordination geometries have been explored as potential single ion magnets (SIMs). In the work presented herein, the Co(II) S = 3/2 tetrahedral [Co{(OPPh2)(EPPh2)N}2], E = S, Se, complexes (abbreviated as CoO2E2), bearing chalcogenated mixed donor-atom imidodiphosphinato ligands, were studied by both experimental and computational techniques. Specifically,...
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Structure redetermination, transport and thermal properties of the YNi3Al9 compound
PublicationSingle crystals of completely ordered variant of the YNi3Al9 compound were grown by self-flux method with excess of aluminum. The crystal structure of the title compound was redetermined from single crystal X-ray diffraction data. The structure adopts ErNi3Al9 type, space group R32, parameters of the unit cell a = 7.2838(2) Å, c = 27.4004(8) Å. The growth of relatively large single crystals of the YNi3Al9 compound, having completely...
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Assessment of Failure Occurrence Rate for Concrete Machine Foundations Used in Gas and Oil Industry by Machine Learning
PublicationConcrete machine foundations are structures that transfer loads from machines in operation to the ground. The design of such foundations requires a careful analysis of the static and dynamic effects caused by machine exploitation. There are also other substantial differences between ordinary concrete foundations and machine foundations, of which the main one is that machine foundations are separated from the building structure....
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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublicationIn 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
PublicationNowadays, 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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L'industria e la Storia. La lezione di Giorgio Mori
PublicationThe wide contribution of Giorgio Mori for a better understanding of the long-term historical relationships between history and industry is the focus of this chapter. By analysing the long list of books and articles written all along his scientific and academic life it is possible to trace a sort of fil rouge that permits to appreciate the huge effort made by this scholar in offering a fresh and never banal interpretation of the...
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Anglojęzyczne nauczanie matematyki - problemy oraz ich e-learningowe rozwiązania
PublicationPrzedstawię krótką charakterystykę anglojęzycznych kierunków prowadzonych na Politechnice Gdańskiej oraz listę problemów wynikających z anglojęzycznego nauczania matematyki. Następnie przedstawię najważniejsze opcje anglojęzycznego portalu matematycznego www.pg.gda.pl/math. Zaprezentuję także wyniki sprawdzianów kompetencyjnych wiedzy z zakresu podstaw matematyki ze szkoły średniej oraz zdawalności egzaminów z matematyki na poszczególnych...
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Ochrona danych osobowych w branży e-commerce w Polsce
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Creating the e-decisional community through the knowledge supply chan system
PublicationW pracy przedstawiono zasady tworzenia społeczeństwa cyfrowego opartego na wymianie wiedzy dostępnej w nośnikach internetowych. Omówiono zasady modelowania takiej wiedzy i budowy tzw. łańcucha zaopatrzenia w wiedzę.
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Istota e-franchisingu oraz możliwości jego rozwoju w Polsce
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A proposal for knowledge sharing in the e-Decisional community using Decisional DNA
PublicationZaproponowano model platformy wspomagającej wymianę wiedzy w społeczeństwie decyzyjnym opartym na decyzyjnym DNA.
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E-Beam Irradiation and Ozonation as an Alternative to the Sulphuric Method of Wine Preservation
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Environmental stress cracking in e-glass and aramid/glass epoxy composites
PublicationKompozyty epoksydowe wzmocnione włóknami szklanymi są dość odporne na wpływy środowiskowe w stanie nieobciążonym, jednak po przyłożeniu obciążeń łatwo pękają w środowisku wody i rozcieńczonych kwasów. Charakterystyki propagacji pęknięć środowiskowych w laminatach szklano/epoksydowych były przedmiotem szeregu prac, jednak brak jest danych na temat zachowania laminatów o wzmocnieniu hybrydowym aramidowo-szklanym stosowanych w budowie...
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Metodyka tworzenia materiałów multimedialnych dla e-edukacji− propozycje autorskie
PublicationW artykule przedstawiono metodykę tworzenia i wykorzystania akademickich podreczników multimedialnych przeznaczonych do udostępniania w sieci. Opisana metodyka określana jest mianem UCD (User Centered Design). Sczegółowo omówiono trzy etapy procesu, a mianowicie: analizę, projektowanie i testowanie. Przedstawione przykłady szczegółowych rozwiazań funkcjonalnych i graficznych pochodzą z autorskich pdręczników stworzonych w technologii...
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Wykorzystanie transportowe drogi wodnej E-70 - marzenie czy konieczność?
PublicationPrzedstawiono przesłanki wskazujace konieczność rozwoju polskiej żeglugi śródlądowej w zakresie obsługi portów kontenerowych oraz towarów masowych. Wskazano kierunki polityki inwestycyjnejoraz uwarunkowania w zakresie rewitalizacji i rozwoju dróg wodnych ze szczególnym uwzględnieniem zespołu portowego Gdańsk -Gdynia oraz odcinka Dolnej Wisły.
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Ag(e)ing and Degradation of Supercapacitors: Causes, Mechanisms, Models and Countermeasures
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LE STIME ECONOMICHE DELLA CIA E L’IMPREVEDIBILE FINE DELL’URSS
PublicationIn this article, we will analyze the debate that took place around the assessments that the CIA gave of the economic situation in the Soviet Union, a clearly decisive key to understanding the overall health of the main political-military opponent of the United States. The article will include the discussions that flared up in the American political establishment starting in 1990, after the fall of the Berlin Wall and the initial...
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Recent Advancements in Cyclodextrin-Based Adsorbents for the Removal of Hazardous Pollutants from Waters
PublicationWater is an essential substance for the survival on Earth of all living organisms. However, population growth has disturbed the natural phenomenon of living, due to industrial growth to meet ever expanding demands, and, hence, an exponential increase in environmental pollution has been reported in the last few decades. Moreover, water pollution has drawn major attention for its adverse effects on human health and the ecosystem....
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass 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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Employing a biofeedback method based on hemispheric synchronization in effective learning
PublicationIn 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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Becoming a Learning Organization Through Dynamic Business Process Management
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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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Meta-Design and the Triple Learning Organization in Architectural Design Process
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Deep learning-based waste detection in natural and urban environments
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The detection of Alternaria solani infection on tomatoes using ensemble learning
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Building the Learning Environment for Sustainable Development: a Co-creation approach
PublicationEducation 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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DentalSegmentator: robust deep learning-based CBCT image segmentation
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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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Digital competence learning in secondary adult education in Finland and Poland
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Playback detection using machine learning with spectrogram features approach
PublicationThis 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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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning 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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Anna Soczyńska, Polish course for Erasmus, sem. 1, 22/23l
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Anna Soczyńska, Polish course for Erasmus, sem. 2, 22/23l
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PG_00053641 Projekt Dyplomowy I. Grupa E. Marczak 2021/22
e-Learning CoursesKurs przeznaczony dla studentów realizujących przedmiot Projekt Dyplomowy I w r.a. 21/22 pod opieką E. Marczak.
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E-POLYMERS
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E-METHODOLOGY
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