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- Publikacje 976 wyników po odfiltrowaniu
- Czasopisma 182 wyników po odfiltrowaniu
- Konferencje 26 wyników po odfiltrowaniu
- Osoby 51 wyników po odfiltrowaniu
- Projekty 9 wyników po odfiltrowaniu
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Wyniki wyszukiwania dla: ELEARNING
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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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Robust-adaptive dynamic programming-based time-delay control of autonomous ships under stochastic disturbances using an actor-critic learning algorithm
PublikacjaThis paper proposes a hybrid robust-adaptive learning-based control scheme based on Approximate Dynamic Programming (ADP) for the tracking control of autonomous ship maneuvering. We adopt a Time-Delay Control (TDC) approach, which is known as a simple, practical, model free and roughly robust strategy, combined with an Actor-Critic Approximate Dynamic Programming (ACADP) algorithm as an adaptive part in the proposed hybrid control...
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Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublikacjaCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
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Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublikacjaThe use of metal halide perovskites in photocatalytic processes has been attempted because of their unique optical properties. In this work, for the first time, Pb-free Bi-based perovskites of the Cs3Bi2X9 type (X = Cl, Br, I, Cl/Br, Cl/I, Br/I) were synthesized and subjected to comprehensive morphological, structural, and surface analyses, and photocatalytic properties in the phenol degradation reaction were examined. Furthermore,...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublikacjaThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Iwona Mokwa-Tarnowska dr
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Wioleta Kucharska dr hab. inż.
OsobyWioleta Kucharska holds a position as an Associate Professor at the Faculty of Management and Economics of the Gdansk TECH, Gdansk University of Technology, Fahrenheit Universities Union, Poland. Authored 66 peer-reviewed studies published with Wiley, Springer, Taylor & Francis, Emerald, Elsevier, IGI Global, and Routledge. Recently involved in such topics as tacit knowledge and company culture of knowledge, learning, and collaboration....
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Joanna Kabrońska dr inż. arch.
OsobyDoktorat z wyróżnieniem: Forma rozwiązań architektonicznych jako droga realizacji idei biblioteki przyszłości, 1994 Laureatka IV Międzynarodowego Biennale Architektury w Krakowie, 1991 Stypendystka DAAD post-doctoral scholarship, Berlin, 2002 Autorka publikacji dotyczących relacji architektury, sztuki i pamięci, między innymi monografii Architektura jako forma pamięci. Rola architektury w tworzeniu współczesnego horyzontu wartości,...
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Michał Grochowski dr hab. inż.
OsobyProfessor and a Head of the Department of Intelligent Control and Decision Support Systems at Gdansk University of Technology (GUT). He is also a Member of the Board of the Digital Technologies Center of GUT. He received his M.Sc. degree in Control Engineering in 2000 from the Electrical and Control Engineering Faculty at the GUT. In 2004 he received a Ph.D. degree in Automatic Control and Robotics from this...
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Language Learning Journal (Formerly: British Journal of Language Teaching)
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Learning and Teaching-The International Journal of Higher Education in the Social Sciences
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International Journal of Practice-Based Learning in Health and Social Care
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublikacjaHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Integrating Statistical and Machine‐Learning Approach for Meta‐Analysis of Bisphenol A‐Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival
PublikacjaBisphenols are important environmental pollutants that are extensively studied due to different detrimental effects, while the molecular mechanisms behind these effects are less well understood. Like other environmental pollutants, bisphenols are being tested in various experimental models, creating large expression datasets found in open access storage. The meta‐analysis of such datasets is, however, very complicated for various...
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Cleaner energy for sustainable future using hybrid photovoltaics-thermoelectric generators system under non-static conditions using machine learning based control technique
PublikacjaIn addition to the load demand, the temperature difference between the hot and cold sides of the thermoelectric generator (TEG) module determines the output power for thermoelectric generator systems. Maximum power point tracking (MPPT) control is needed to track the optimal global power point as operating conditions change. The growing use of electricity and the decline in the use of fossil fuels have sparked interest in photovoltaic-TEG...
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Source code - AI models (MLM1-5 - series I-III - QNM opt)
Dane BadawczeSource code - AI models (MLM1-5 - series I-III - QNM opt) for the paper "Computational Complexity and Its Influence on Concrete Compressive Strength Prediction Capabilities of Machine Learning Models for Concrete Mix Design Support" accepted for publication.
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Predicting the Purchase of Electricity Prices for Renewable Energy Sources Based on Polish Power Grids Data Using Deep Learning Models for Controlling Small Hybrid PV Microinstallations
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Interactive Learning Environments
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Photocatalytic and Self-Cleaning Properties of Ag-Doped TiO2~!2009-10-16~!2009-10-30~!2010-01-27~!
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Izabela Mironowicz dr hab. inż. arch.
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Workshop on Logic and Learning
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Algorithmic Learning Theory
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Conference on Learning Theory (Annual Conference on Computational Learning Theory)
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Olgun Aydin dr
OsobyOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Principal Machine Learning Engineer in Nike, and works as Assistant Professor in Gdansk University of Technology in Poland. Dr. Aydin is part of editorial board of "Journal of Artificial Intelligence and Data Science" Dr. Aydin served as Vice-Chairman of Why R? Foundation and is member of Polish Artificial Intelligence Society. Olgun is...
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Review of the Complexity of Managing Big Data of the Internet of Things
PublikacjaTere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...
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Internet Journal on E-learning (Formerly : International Journal of Educational Telecommunications)
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Design of self-cleaning and self-disinfecting paper-shaped photocatalysts based on wood and eucalyptus derived cellulose fibers modified with gCN/Ag nanoparticles
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Conference on Computational Natural Language Learning (Conference on Natural Language Learning)
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Activation of Metabotropic Glutamate Receptor (mGlu2) and Muscarinic Receptors (M1, M4, and M5), Alone or in Combination, and Its Impact on the Acquisition and Retention of Learning in the Morris Water Maze, NMDA Expression and cGMP Synthesis
PublikacjaThe Morris water maze (MWM) is regarded as one of the most popular tests for detecting spatial memory in rodents. Long-term potentiation and cGMP synthesis seem to be among the crucial factors involved in this type of learning. Muscarinic (M1, M4, and M5 receptors) and metabotropic glutamate (mGlu) receptors are important targets in the search for antipsychotic drugs with the potency to treat cognitive disabilities associated with...
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublikacjaThis work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...
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Asian Conference on Machine Learning
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International Conference on Machine Learning
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Computer Supported Collaborative Learning
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European Workshop on Learning Robots
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International Conference on Learning Representations
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Currents in Pharmacy Teaching and Learning
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Language Learning in Higher Education
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Massive Open Online Courses (MOOCs) in hospitality and tourism
PublikacjaThe tourism industry, interesting and challenging, faces structural human resource problems such as skills shortages and staff turnover, seasonality and a high percentage of small to medium enterprises whose employees have limited time for training or education. Large tourism enterprises often span countries and continents, such as hotel chains, airlines, cruise companies and car rentals, where the employees need similar training...
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Vident-synth: a synthetic intra-oral video dataset for optical flow estimation
Dane BadawczeWe introduce Vident-synth, a large dataset of synthetic dental videos with corresponding ground truth forward and backward optical flows and occlusion masks. It can be used for:
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E-learning courses
Kursy OnlineStrona zawiera zbiór kursów prowadzonych metodą e-learning. Kursy te są skierowane do studentów I stopnia kierunku informatyka na VII semestrze profilu Bazy danych, do studentów na kierunku informatyka na II semestrze studiów II stopnia na specjalności ZAD i ISI.
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eLearning Techniques (2018) - Inal Bakhytkyzy
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Random Processes 2022/2023
Kursy OnlineThe e-learning course page for the purpose of the remote or hybrid learning for Random Processes.
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Random Processes 2023/2024
Kursy OnlineThe e-learning course page for the purpose of the remote or hybrid learning for Random Processes.
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International Conference on Machine Learning and Cybernetics
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International Conference on Learning Analytics and Knowledge
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European Conference on Technology Enhanced Learning
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International Conference on Machine Learning and Applications
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The role of self-awareness in enhancing cooperative behaviour among students
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The role of self-awareness in enhancing cooperative behaviour among students
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