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Wyniki wyszukiwania dla: ELEARNING PROGRAMME
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Cloud solutions as a platform for building advanced learning platform, that stimulate the real work environment for project managers
PublikacjaImproving skills of managers and executives require, that during the transfer of knowledge (in different ways: during studies, trainings, workshops and other forms of education) it is necessary to use tools and solutions that are (or will be) used in real world environments, where people being educated are working or will work. Cloud solutions allow educational entities (universities, training companies, trainers, etc.) to provide...
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Can Evaluation Patterns Enable End Users to Evaluate the Quality of an e-learning System? An Exploratory Study.
PublikacjaThis paper presents the results of an exploratory study whose main aim is to verify if the Pattern-Based (PB) inspection technique enables end users to perform reliable evaluation of e-learning systems in real work-related settings. The study involved 13 Polish and Italian participants, who did not have an HCI background, but used e-learning platforms for didactic and/or administrative purposes. The study revealed that the participants...
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Assessment of Failure Occurrence Rate for Concrete Machine Foundations Used in Gas and Oil Industry by Machine Learning
PublikacjaConcrete 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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Projekt Leonardo da Vinci EMDEL (European Model for Distance Education and Learning) - otwarte szkolenia online.
PublikacjaW referacie zaprezentowano główne zadania oraz ofertę szkoleniową Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej (CEN PG) w kontekście realizowanych projektów Unii Europejskiej. Przedstawiono projekt Leonardo da Vinci EMDEL - European Model for Distance Education and learning - realizowany przez CEN PG w latach 2001-2005 oraz opisano doświadczenia w zakresie adaptacji i lokalizacji opracowanych przez partnerów projektu...
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Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublikacjaThe rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...
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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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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublikacjaAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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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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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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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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Towards the 4th industrial revolution: networks, virtuality, experience based collective computational intelligence, and deep learning
PublikacjaQuo vadis, Intelligent Enterprise? Where are you going? The authors of this paper aim at providing some answers to this fascinating question addressing emerging challenges related to the concept of semantically enhanced knowledge-based cyber-physical systems – the fourth industrial revolution named Industry 4.0.
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublikacjaOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
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NLITED - New Level of Integrated Techniques for Daylighting Education: Preliminary Data on the Use of an E-learning Platform
PublikacjaProject NLITED – New Level of Integrated Techniques for Daylighting Education - is an educational project for students and professionals. The project's objective is to create and develop an online eLearning platform with 32 eModules dedicated to daylight knowledge. The project also offers e-learners two summer school training where the theory is put into practice. The platform was launched on January 31, 2022. The paper...
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublikacjaThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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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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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublikacjaOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
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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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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublikacjaWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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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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Technological vs. Non-Technological Mindsets: Learning From Mistakes, and Organizational Change Adaptability to Remote Work
PublikacjaThe permanent implementation of the change in working methods, e.g., working in the virtual space, is problematic for some employees and, as a result, for management leaders. To explore this issue deeper, this study assumes that mindset type: technological vs. non-technological, may influence the organizational adaptability to change. Moreover, the key interest of this research is how non-technological mindsets...
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The Impact of Selected Parameters on the efficiency of PV Installations - Simulation Test of the 1 MW PV Farm in the PVSyst Program
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The Study Program of "Entrepreneurship and Finance" at the University of Economics in Katowice as an Example of Practical Education in Poland’s Higher Education System
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Ocena inwestycji Program 10+ zrealizowanej w ramach Grupy LOTOS S.A. w latach 2007 - 2011
PublikacjaW artykule zaprezentowano pozytywny wpływ jednej z inwestycji nazwanej Program 10+, zarówno na wyniki operacyjne gdańskiego koncernu, jak i rynek paliwowy w Polsce. Program ten został przeprowadzony w Grupie LOTOS SA. Wybór charakterystyki tego przedsięwzięcia i jego korzystnego wpływu na otoczenie ma m.in. związek ze skalą tej inwestycji oraz poniesionymi na nią nakładami finansowymi.
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Biblioteka Główna realizuje Program Ministra Kultury i Dziedzictwa Narodowego - "Ochrona i cyfryzacja dziedzictwa kulturowego"
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Uczenie na błędach w nauczaniu programowania w systemie e-learningu
PublikacjaJedną z kluczowych umiejętności, które muszą posiąść adepci programowania, stanowi umiejętność poprawiania kodu programu zawierającego błędy. Jest to działanie bardzo złożone, wymagające znajomości składni języka, rozumienia semantyki kodu, znajomości zasad testowania oraz rozumienia działania algorytmu. W artykule autor proponuje własną metodę kształtowania umiejętności poprawiania kodu programu wykorzystującą narzędzia do nauczania...
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A decade of Poland`s integrated Road Safety Programme - economic develop-ment vs. road unsafety. W: [CD-ROM]. Conference proceedings. SORIC´02. 2nd Safety on Road Internationaload International Conference. Kingdom of Bah- rain, 21-23 October 2002. Bahrain: CTRS Univ. Bahrain**2002 [8 s. 5 rys. bibliogr. 5 poz. 10 lat Krajowego Programu Bezpieczeństwa Ruchu Drogowego w Polsce - rozwój ekonomiczny a niebezpieczeństwo ruchu.
PublikacjaReferat zawiera analizę doświadczeń z dziesięciu lat pracy oraz wdrożeń Kra-jowego Programu Bezpieczeństwa Ruchu Drogowego GAMBIT. Przedstawia również analizę przyczyn gwałtownego spadku liczby- śmiertelnych ofiar wypadków dro-gowych w Polsce w roku 2001.
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Does the community-based combined Meeting Center Support Programme (MCSP) make the pathway to day-care activities easier for people living with dementia? A comparison before and after implementation of MCSP in three European countries
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Modyfikacja programu szkolenia kierowców wieloosiowych pojazdów specjalnych, uwzględniająca wyniki badań eksperymentalnych i symulacyjnych eksplozyjnego uszkodzenia opon
PublikacjaAktualnie obowiązujący program szkolenia kierowców specjalnych pojazdów wojskowych obejmuje zagadnienia związane z budową pojazdu, zasadami jego poprawnej eksploatacji i techniką jazdy w podstawowym zakresie. Program porusza, co prawda również problemy związane z prawidłowym postępowaniem przy wystąpieniu awarii układu napędowego, ale nie obejmuje kompleksowo techniki jazdy w przypadku poważnego uszkodzenia jednego lub więcej kół...
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Realizacja układu sterowania blokiem wymienników ciepła w postaci programu komputerowego wykorzystującego zmodyfikowany algorytm regulacji predykcyjnej DMC
PublikacjaW artykule przedstawiono eksperymentalny układ sterowania blokiem wymienników ciepła elektrociepłowni wykorzystujący zmodyfikowany algorytm regulacji predykcyjnej DMC. Na początku krótko opisano obiekt sterowania, zadania stawiane przed układem regulacji i wybrany algorytm sterowania. Następnie omówiono sposób realizacji regulatora opartego na idei programu komputerowego uruchamianego na stacji operatorskiej i komunikującego się...
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Relevance of the EU Structural Funds’ Allocation to the Needs of Combating Air Pollution in Poland. Analysis of the Operational Programmes of Regions Threatened With Critical Air Pollution from Distributed Energy Sources
PublikacjaRecent years, the European Environmental Agency, has been reporting air quality parameters in Poland, as the poorest among all the EU countries. Despite of adoption of the EU legislation on energy efficiency and energy performance of buildings, existing legal solutions occur insufficient in reducing air pollution in Polish regions. Lack of an effective schemes supporting complex thermal renovation of buildings, exchange of inefficient...
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METHODOLOGICAL IDENTIFICATION OF OPPORTUNITIES FOR DEVELOPMENT OF SMART SPECIALISATION IN POMERANIAN VOIVODESHIP IN POLAND
PublikacjaThe subject of the presented research was projects co financed with European Union funds realised in years 2007–2013 in small towns of Pomeranian Voivodship. Projects which were included belong to 3 programmes: Innovative Economy Programme, Infrastructure and Environment Programme and Regional Operational Programme. The aim of the researches was study of the structure of projects according to its kind and town division. The other...
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The Effects of a Combined Pre- and Post-Operative Anterior Cruciate Ligament Reconstruction Rehabilitation Program on Lower Extremity Muscle Imbalance
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PREVALENCE OF METABOLIC SYNDROME AMONG PATIENTS WITH SCHIZOPHRENIA FROM LONG CARE UNIT IN FORENSIC PSYCHIATRY PROGRAM: AN OBSERVATIONAL STUDY
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Evaluation of a neurotherapy program for a child with ADHD with Benign Partial Epilepsy with Rolandic Spikes (BPERS) using event-related potentials
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Zintegrowany Program Rozwoju Politechniki Gdańskiej – Moduł 1. Poprawa jakości kształcenia na studiach stacjonarnych II stopnia
PublikacjaPolitechnika Gdańska realizuje od 1 kwietnia 2018 roku projekt „Zintegrowany Program Rozwoju Politechniki Gdańskiej” (POWER 3.5) dofinansowywany ze środków Unii Europejskiej z Europejskiego Funduszu Społecznego w ramach Programu Operacyjnego „Wiedza Edukacja Rozwój”. W artykule zostały przedstawione informacje dotyczące realizacji zadań szczegółowych modułu 1, będącego pierwszym zadaniem z trzech określonych w projekcie. Artykuł...
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Calculation Program Supporting Switched Capacitor DC-DC Charge Pump Design (CP Design Calculator) - PartI: Preface
PublikacjaPrzedmiot badań i motywy podjęcia pracy. Metoda badawcza. Nota historyczna nt. konwertera Fibonacciego (Fibonacci multiplier) i pompy ładunkowej Makowskiego ("Makowski charge pump"). Przewidywane cele pracy. Podziękowania
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ProSIL software for computer aided functional Safety management = Program komputerowy ProSIL do wspomagania zarządzaniem bezpieczeństwa funkcjonalnego
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Bilingual advantage? Literacy and phonological awareness in Polish-speaking early elementary school children learning English simultaneously
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Night shifts as a learning experience among nursing students across Europe: Findings from a cross-sectional survey
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
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Perceived technostress while learning a new mobile technology: Do individual differences and the way technology is presented matter?
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E-learning jako narzędzie wspierające kształcenie osób 50+. Rozważania w oparciu o projekt MAYDAY
PublikacjaRozdział przedstawia zalety i wady szkoleń e-learningowych ze szczególnym uwzględnieniem uczestników w wieku 50+, analizę szkolenia przeprowadzonego w ramach projektu MAYDAY oraz wytyczne i rekomendacje do tworzenia kursów e-learnignowych dla osób powyżej 50-go roku życia.
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Presentation of Novel Architecture for Diagnosis and Identifying Breast Cancer Location Based on Ultrasound Images Using Machine Learning
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader's behavior must align for the best learning effects....
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning effects....
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublikacjaThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublikacjaComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublikacjaExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing
PublikacjaRubbers combine the flexibility with mechanical strength, supporting myriad applications, but suffer from inherent flammability. Formulation and production of flame-retardant rubber composites (FRRCs) have intensively been practiced over years, but not comprehensively reviewed. This necessity has outlined collecting, analyzing, screening, classifying, and interpreting the literature with the aim of classifying the FRRCs. We quantified...
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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...