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Search results for: ELEARNING PROGRAMME
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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The effects of relational and psychological capital on work engagement: the mediation of learning goal orientation
PublicationPurpose – This paper proposes a research model in which learning goal orientation (LGO) mediates the impacts of relational capital and psychological capital (PsyCap) on work engagement. Design/methodology/approach – Data obtained from 475 managers and employees in the manufacturing and service industries in Poland were utilized to assess the linkages given above. Common method variance was controlled by the unmeasured latent method...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublicationThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublicationTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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LOS and NLOS identification in real indoor environment using deep learning approach
PublicationVisibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublicationIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublicationEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublicationThe process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between...
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublicationBiochar 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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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublicationThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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Looking through the past: better knowledge retention for generative replay in continual learning
PublicationIn this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublicationIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublicationWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublicationEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublicationThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Supervised-learning-based development of multi-bit RCS-reduced coding metasurfaces
PublicationCoding metasurfaces have been introduced as efficient tools allowing meticulous control over the electromagnetic (EM) scattering. One of their relevant application areas is radar cross section (RCS) reduction, which principally relies on the diffusion of impinging EM waves. Despite its significance, careful control of the scattering properties poses a serious challenge at the level of practical realization. This article is concerned...
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Wisdom from Experience Paradox: Organizational Learning, Mistakes, Hierarchy and Maturity Issues
PublicationOrganizations often perceive mistakes as negligence and low-performance indicators, yet they can be a precious learning resource. However, organizations cannot learn from mistakes if they have not accepted them. This study aimed to explore how organizational hierarchy and maturity levels influence the relationship between mistakes acceptance and the ability to change. A sample composed of 380 Polish employees working in knowledge-driven...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublicationHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublicationThis work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublicationThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Machine learning approach to packaging compatibility testing in the new product development process
PublicationThe 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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The chromatographic analysis of extracts from poplar (Populus sp.) - Laying program GC-MS
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Engineering and Management of Space Systems (EMSS) - an international joint Master's double-degree program
PublicationDynamic development of the space sector of European, and especially of Polish and German economies results in a necessity for suitable Higher Education Institution graduates. The increasing digitization, distribution and networking of technical systems leads to the necessity of a degree programme teaching “the systems view” and “interdisciplinarity” methods and skills. Furthermore, it is necessary to consider the entire life cycle...
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Tests of bond between concrete and steel bars – literature background and program of own research
PublicationThis article deals with the issue of the bond between concrete and reinforcement. The bond is crucial for reinforced concrete elements because it is possible to transfer forces (stresses) from concrete to the reinforcement. Basic information related to the cooperation of concrete and rebars was recalled in the article. Selected issues concerning theoretical and numerical analysis as well as experiments of the bond phenomenon were...
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Program rewitalizacji planowanej na terenie Polski śródladowej drogi wodnej E-70
PublicationOmówiono zasadnicze problemy wznowienia ruchu transportowego i możliwości wynikające z opracowanych planów rewitalizacji drogi wodnej E-70 wraz z identyfikacją podstawowych barier technicznych.Wskazano kierunki prac majacych na celu aktywizację transportu śródladowego oraz założenia programu strategii rewitalizacji.
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Vital and health statistics. Ser. 1: Programs and collection procedures
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Krzysztof Jan Kaliński prof. dr hab. inż.
PeopleKrzysztof J. Kaliński completed his MSc study at Gdańsk University of Technology (GUT) Faculty of Production Engineering (1980, result – get a first). He obtained PhD at GUT Faculty of Machine Building (1988, result – get a first), DSc at GUT Faculty of Mechanical Engineering (ME) (2002, result – get a first), and professor’s title – w 2013 r. In 2015 r. he became full professor.His research area includes: theoretical and applied...
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Znajomość własnego ciśnienia tętniczego i rozpowszechnienie nadciśnienia tętniczego w populacji wiejskiej - Program Kiełpino = The cognizance of patient's own blood pressure values and the hypertension prevalence among rural population - Kiełpino program
PublicationNadciśnienie tętnicze jest jedną z najczęstszych chorób przewlekłych występujących w Polsce. Nieleczone nadciśnienie tętnicze prowadzi do licznych powikłań, jest przyczyna przedwczesnej umieralności, wpływa na pogorszenie komfortu życia pacjenta i zwiększa koszty leczenia. Ocena znajomości własnego ciśnienia tętniczego krwi oraz rozpowszechnienia nadciśnienia tętniczego u pacjentów w wiejskiej praktyce lekarza rodzinnego - jest...
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eLearning im Wandel der Zeit am Beispiel der TU Gdansk und der FH Flensburg
PublicationW referacie omówiono zmiany systemów eLearning na przykładzie ich rozwoju na Politechnice Gdańskiej i w Wyższej Szkole Zawodowej we Flensburgu. Dokonano analizy pierwszych rozwiązań, w tym własnych systemów i narzędzi, jak również dokonanego na obu uczelniach zwrotu w kierunku otwartych systemów LMS. Podkreślono rolę oceny jakości(QoS) systemów zdalnego nauczania.
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Light4Health eLearning Course: health research for interior lighting design. Re-thinking design approaches based on science
PublicationThis paper presents the results of 'Light4Health' (L4H), a three-year EU Erasmus+ Strategic Partnership grant project (2019-2021), which investigated, systematized and taught health-related research on the impact of natural and artificial light on human health and well-being relevant to indoor lighting design. The objective was to re-think evidence-based lighting design approaches for residential, working/educational, and healthcare...
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Edyta Gołąb-Andrzejak dr hab.
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Microfiltration of post-fermentation broth with backflushing membrane cleaning
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Dworzec kolejowy – jaki był, jaki jest i jaki być powinien
PublicationWzorem innych krajów winien być w Polsce przeprowadzony program reformy dworców i przystanków kolejowych jako jednorodnego, zestandaryzowanego, narodowego systemu. Przygotowując program polskiej reformy dworcowej należy się posiłkować wynikami podobnych programów w innych krajach europejskich. Programy te skrótowo opisano w artykule. Opisano i oceniono również pierwsze realizacje polskie powstałe po 2008r.
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Symulator komputerowy "Refrigerating Plant" nowoczesnym narzędziem w kształceniu mechaników okrętowych
PublicationW artykule przedstawiono możliwości kształcenia prowadzonego w oparciu o program komputerowy typu cbt - Chłodnia Prowiantowa. Omówiono jego strukturę i zawartość merytoryczną. Przedstawiono sposób oceny osoby szkolonej wykorzystującej ten program. Wskazano na korzyści płynące z zastosowania programów tego typu w kształceniu mechaników okrętowych. Materiał bogato ilustrowano przykładami ekranów z prezentowanego programu.
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A computer-based training program : Refrigerating Plant as an example of recent didactic means in maritime engineering education
PublicationW referacie przedstawiono możliwości kształcenia prowadzonego w oparciu o program komputerowy typu cbt - Chłodnia Prowiantowa. Omówiono jego strukturę i zawartość merytoryczną. Przedstawiono sposób oceny osoby szkolonej wykorzystującej ten program. Wskazano na korzyści płynące z zastosowania programów tego typu w kształceniu mechaników okrętowych. Materiał bogato ilustrowano przykładami ekranów z prezentowanego programu.
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Case study 1.2C: Road infrastructure cost in Poland, Annex to Deliverable D3, Marginal cost case studies for road and rail transport. GRACE. Funded by Sixth Framework Programme.
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Study of Phase Transitions Occurring in a Catalytic System of ncFe-NH3/H2 with Chemical Potential Programmed Reaction (CPPR) Method Coupled with In Situ XRD
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Wpływ programów rewitalizacji na rozwój wybranych obszarów miejskich w warunkach wsparcia funduszami strukturalnymi UE.
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Zastosowanie programów Mathematica i 20-sim do modelowania i analizy układów o parametrach rozłożonych
PublicationCelem pracy jest zaprezentowanie zastosowania pojęcia transmitancji układów o parametrach rozłożonych do konstruowania modalnych grafów wiązań dla układów zawierających jednowymiarowe podukłady o parametrach rozłożonych. Zaprezentowano sposób i efekty zastosowania programów Mathematica (do przygotowania parametrów modeli) i programu 20-Sim (do konstruowania modeli i do symulacji) w procesie modelowania i analizy układów zawierających...
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Rewitalizacja struktur miejskich i możliwości w kształtowaniu przestrzeni na przykładzie programów rewitalizacji miast niemieckich.
PublicationW artykule omówione zostały ogólne założenia programów rewitalizacji struktur miejskich na przykładzie miast niemieckich. Wyszczególnione zostały urbanistyczne wskaźniki rewitalizacji wedle niemieckiego prawa budowlanego oraz dokładne przestudiowane dwa założenia położone w landzie Badenia-Wirtembergia tj.: śródmieście Althengstett i dawne koszary we Fryburgu.
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Praca bibliotekarza w erze cyfrowej: 20 darmowych programów i aplikacji do wykorzystania w bibliotece
PublicationArtykuł prezentuje 20 darmowych programów komputerowych, wykorzystywanych w Bibliotece Głównej Gdańskiego Uniwersytetu Medycznego. Przedstawione aplikacje mogą wzbogacić warsztat pracy bibliotekarzy, którzy zajmują się: tworzeniem szkoleń, edycją bibliotecznych stron internetowych oraz komunikacją z użytkownikami.
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Polityka regionalna województwa pomorskiego w latach 2007-2013 (na podstawie Regionalnego Programu Operacyjnego)
PublicationArtykuł przedstawia główne założenia Regionalnego Programu Operacyjnego dla Województwa Pomorskiego na lata 2007-2013 będącego jednym z ważniejszych dokumentów strategicznych dotyczących polityki regionalnej. Analizę poprzedzono omówieniem zmian, jakie zaszły w polityce regionalnej od momentu rozpoczęcia procesu integracji europejskiej. Opisano także kwestie związane ze wsparciem finansowym, zwłaszcza aktualne zasady i zagadnienia,...