Filters
total: 2125
-
Catalog
- Publications 1597 available results
- Journals 192 available results
- Conferences 28 available results
- Publishing Houses 1 available results
- People 87 available results
- Projects 8 available results
- e-Learning Courses 60 available results
- Events 8 available results
- Open Research Data 144 available results
displaying 1000 best results Help
Search results for: SELF-SUPERVISED LEARNING
-
LEARNING AND INDIVIDUAL DIFFERENCES
Journals -
Journal of Learning for Development
Journals -
NEUROBIOLOGY OF LEARNING AND MEMORY
Journals -
LEARNING DISABILITY QUARTERLY
Journals -
Investigations in Mathematics Learning
Journals -
TEACHING AND LEARNING IN MEDICINE
Journals -
Lex Localis-Journal of Local Self-Government
Journals -
Self-normalized density map (SNDM) for counting microbiological objects
Publication -
TEARING THE SPACE APART. RESPONSIBLE PARTICIPATION OR SELF-SERVING PARTICIPATION
Publication -
Molecular Insight into the Self-Assembly Process of Cellulose Iβ Microfibril
Publication -
UV-crosslinkable photoreactive self-adhesive hydrogels based on acrylics
Publication -
Preparation of double-sided self-adhesive tape Si-PSA
Publication -
Self-stabilizing algorithms for graph coloring with improved performance guarantees
PublicationW pracy rozważa się rozproszony model obliczeń, w którym struktura systemu jest reprezentowana przez graf bezpośrednich połączeń komunikacyjnych. W tym modelu podajemy nowy samostabilizujący algorytm kolorowania grafów oparty na konstrukcji drzewa spinającego. Zgodnie z naszą wiedzą jest to pierwszy algorytm z gwarantowaną wielomianową liczbą ruchów, który dokładnie koloruje grafy dwudzielne.
-
Autonomous, Ground Based, Self-Organizing Radiolocation Systems - AEGIR
PublicationThis article describes the construction and operation of autonomous ground-based radiolocation system that was developed as a technology demonstrator at the Technical University of Gdansk. Preliminary results and conclusions will be presented as well as analysis of its effectiveness. There will be also described the basic blocks of the system.
-
A Self-Equalized Waveguide Filter With Frequency-Dependent (Resonant) Couplings
PublicationThis letter presents a design of a fifth-order linear phase filter with frequency-dependent couplings. The filter is composed of a triplet that is directly coupled to two resonators at the input and output. To provide group delay flattening a cross-coupling in the trisection has a strongly dispersive character with a negative slope parameter. To achieve this, an E-plane stub with a septum was used. To further improve the filter...
-
Comprehensive modeling of interferometric hydrophone with self-supported mandrel transducer.
PublicationW pracy przedstawiono wyniki modelowania nowego typu samonośnego przetwornika dla interferometrycznego hydrofonu światłowodowego. Zaprezentowano wyniki analizy statycznej, modowej i dynamicznej przeprowadzonej przy pomocy Metody Elementów Skończonych. W modelowaniu wykorzyastano techniki opracowane dla laminatów, co pozwoliło na uzyskanie dokładnych wyników przy względnie krótkim czasie obliczeń.
-
Self-supporting LSFO films for bolometers made with LTCC technology
PublicationOpisano metodę wytwarzania przewodzących, tlenkowych warstw ceramicznych tlenków lantanowo-strontowo żelazowych (LSFO) technologią low temperature co-fired ceramics (LTCC). Przedstawiono rezultaty pomiarów parametrów warstw pod kątem przydatności do produkcji detektorów IR.
-
Technical State Assessment of Charge Exchange System of Self-Ignition Engine, Based On the Exhaust Gas Composition Testing
PublicationThis paper presents possible use of results of exhaust gas composition testing of self - ignition engine for technical state assessment of its charge exchange system under assumption that there is strong correlation between considered structure parameters and output signals in the form of concentration of toxic compounds (ZT) as well as unambiguous character of their changes. Concentration of the analyzed ZT may be hence considered...
-
Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep 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...
-
Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep 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...
-
Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublicationMachine 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...
-
Towards classification of patients based on surface EMG data of temporomandibular joint muscles using self-organising maps
PublicationThe 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...
-
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...
-
Global Approaches to Reduce Light Pollution from Media Architecture and Non-Static, Self-Luminous LED Displays for Mixed-Use Urban Developments
PublicationUrban 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....
-
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...
-
Olgun Aydin dr
PeopleOlgun 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...
-
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...
-
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...
-
Use of Modified Cuckoo Search algorithm in the design process of integrated power systems for modern and energy self-sufficient farms
PublicationIn 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...
-
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...
-
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...
-
Becoming a Learning Organization Through Dynamic Business Process Management
Publication -
The detection of Alternaria solani infection on tomatoes using ensemble learning
Publication -
Scheduling Repetitive Construction Processes Using the Learning-Forgetting Theory
Publication -
Generation of microbial colonies dataset with deep learning style transfer
Publication -
Meta-Design and the Triple Learning Organization in Architectural Design Process
Publication -
Agent-Based Population Learning Algorithm for RBF Network Tuning
Publication -
An A-Team Approach to Learning Classifiers from Distributed Data Sources
Publication -
An A-Team approach to learning classifiers from distributed data sources
Publication -
Deep learning-based waste detection in natural and urban environments
Publication -
Digital competence learning in secondary adult education in Finland and Poland
Publication -
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...
-
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...
-
Didaktische simulationsmodelle fur E-learning in der IK-ausbildung.
PublicationPrzedstawiono 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.
-
Anita Maria Dąbrowicz-Tlałka dr
PeopleAnita Dąbrowicz-Tlałka graduated from the Faculty of Mathematics and Physics at the University of Gdańsk with an outstanding grade, having written her thesis in the field of geometric topology. She concurrently obtained a diploma in Postgraduate Studies in the Basics of Computer Science at the University of Gdańsk. In 2001 she received a Ph.D. degree in mathematical studies at the Poznań University of Technology after defending...
-
Anna Lisowska-Oleksiak prof. dr hab.
PeopleAnna 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...
-
An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis 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...
-
Vehicle Detection with Self-Training for Adaptative Video Processing Embedded Platform
PublicationTraffic monitoring from closed-circuit television (CCTV) cameras on embedded systems is the subject of the performed experiments. Solving this problem encounters difficulties related to the hardware limitations, and possible camera placement in various positions which affects the system performance. To satisfy the hardware requirements, vehicle detection is performed using a lightweight Convolutional Neural Network (CNN), named...
-
Expansion of the self of activists and nonactivists involved in mass gatherings for collective action
Publication -
Independent and Interdependent? Agentic and Communal? Self-construals of People Fused with a Group
Publication