Filters
total: 2218
-
Catalog
- Publications 1684 available results
- Journals 192 available results
- Conferences 28 available results
- Publishing Houses 1 available results
- People 91 available results
- Projects 8 available results
- e-Learning Courses 60 available results
- Events 8 available results
- Open Research Data 146 available results
displaying 1000 best results Help
Search results for: SELF-SUPERVISED LEARNING
-
A probabilistic concept of load assessment of self-ignition engines
PublicationPrzedstawiono propozycję probabilistycznej interpretacji obciążenia silników spalinowych o zapłonie samoczynnym. Zaproponowano probabilistyczny opis obciążenia tych silników z uwzględnieniem znanych parametrów (wskaźników) ich pracy. Wykazano, że obciążenie tego rodzaju silników, rozpatrywane w dowolnej chwili, może być uważane za zmienną losową. Zwrócono uwagę, że obciążenie to może być uważane za zmienną losową wielowymiarową....
-
Asynchronous and self-organizing radiolocation system — AEGIR
Publication -
Generalized adaptive notch filter with a self-optimization capability
PublicationW pracy przedstawiono samonastrajalny wariant tzw. uogólnionego adaptacyjnego filtru wycinającego. Automatycznym strojeniem objęte są dwa współczynniki wzmocnienia adaptacji, odpowiedzialne za śledzenie amplitud i częstotliwości parametrów identyfikowanego obiektu.
-
Process of self-ignition engine loads and its properties
PublicationW artykule zaproponowano probabilistyczną interpretację obciążenia silników spalinowych o zapłonie samoczynnym z uwzględnieniem znanych parametrów (wskaźników) ich pracy. Wykazano, że obciążenie tego rodzaju silników, rozpatrywane w dowolnej chwili, może być uważane za zmienną losową wielowymiarową. Zmiany obciążenia silnika w czasie jego pracy uznane zostały za proces obciążeń i przedstawione w formie wielowymiarowego procesu...
-
Transfrontier co-operation of self-governments in Euroregion Baltic
Publication...
-
A self-optimization mechanism for generalized adaptive notch smoother
PublicationTracking of nonstationary narrowband signals is often accomplished using algorithms called adaptive notch filters (ANFs). Generalized adaptive notch smoothers (GANSs) extend the concepts of adaptive notch filtering in two directions. Firstly, they are designed to estimate coefficients of nonstationary quasi-periodic systems, rather than signals. Secondly, they employ noncausal processing, which greatly improves their accuracy and...
-
Self diagnostics using smart glasses - preliminary study
Publicationn this preliminary study we analyzed the possibility of the reliable measurement of biomedical signals with some potential hardware extensions of smart glasses. Using specially designed experimental prototypes four category of biomedical signals were measured: electrocardiograms, electromyograms, electroencephalograms and respiration waveforms. Experi- ments with volunteers proved that using even simple construc- tion of sensors...
-
Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2017, part I
Open Research DataThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the year 2017 on their self-assessment of selected digital competencies by gender. The survey was conducted in 2019, two years after the respondents obtained graduate status. The research sample included 1594 respondents. To summarize, in general, respondents...
-
Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2017, part II
Open Research DataThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the year 2017 on their self-assessment of selected digital competencies by gender. The survey was conducted in 2019, two years after the respondents obtained graduate status. The research sample included 1594 respondents. To summarize, in general, respondents...
-
Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2017, part I
Open Research DataThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the year 2017 on their self-assessment of selected digital competencies by gender. The survey was conducted in 2019, two years after the respondents obtained graduate status. The research sample included 1594 respondents. To summarize, in general, respondents...
-
Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2017, part II
Open Research DataThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the year 2017 on their self-assessment of selected digital competencies by gender. The survey was conducted in 2019, two years after the respondents obtained graduate status. The research sample included 1594 respondents. To summarize, in general, respondents...
-
Acid–Base Equilibrium and Self-Association in Relation to High Antitumor Activity of Selected Unsymmetrical Bisacridines Established by Extensive Chemometric Analysis
PublicationUnsymmetrical bisacridines (UAs) represent a novel class of anticancer agents previously synthesized by our group. Our recent studies have demonstrated their high antitumor potential against multiple cancer cell lines and human tumor xenografts in nude mice. At the cellular level, these compounds affected 3D cancer spheroid growth and their cellular uptake was selectively modulated by quantum dots. UAs were shown to undergo metabolic...
-
Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
-
Self-organising maps in the analysis of strains of human abdominal wall to identify areas of similar mechanical behaviour.
PublicationThe study refers to the application of a type of artificial neural network called the Self-Organising Map (SOM) for the identification of areas of the human abdominal wall that behave in a similar mechanical way. The research is based on data acquired during in vivo tests using the digital image correlation technique (DIC). The mechanical behaviour of the human abdominal wall is analysed during changing intra-abdominal pressure....
-
Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublicationCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
-
Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
-
Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublicationIdentification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable...
-
Multimodal learning application with interactive animated character. [Multimodalna aplikacja edukacyjna wykorzystująca interaktywną animowaną postać]
PublicationThe aim of this study is to design a computer application that may assist teachers and therapists in multimodal manner in their work with impaired or disabled children. The application can be operated in many different ways, giving to a child with special educational needs a possibility to learn and train many skills or treat speech disorders. The main stress in this research is on the creation of animated character that will serve...
-
Design of self-cleaning and self-disinfecting paper-shaped photocatalysts based on wood and eucalyptus derived cellulose fibers modified with gCN/Ag nanoparticles
Publication -
Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2018, part I
Open Research DataThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the year 2018 on their self-assessment of selected digital competencies by gender. The survey was conducted in 2020, two years after the respondents obtained graduate status. The research sample included 1315 respondents. To summarize, in general, respondents...
-
Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2016, part I
Open Research DataThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the year 2016 on their self-assessment of selected digital competencies by gender. The survey was conducted in 2018, two years after the respondents obtained graduate status. The research sample included 1947 respondents. To summarize, in general, respondents...
-
Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2018, part II
Open Research DataThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the year 2018 on their self-assessment of selected digital competencies by gender. The survey was conducted in 2020, two years after the respondents obtained graduate status. The research sample included 1315 respondents. To summarize, in general, respondents...
-
Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2016, part II
Open Research DataThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the year 2016 on their self-assessment of selected digital competencies by gender. The survey was conducted in 2018, two years after the respondents obtained graduate status. The research sample included 1947 respondents. To summarize, in general, respondents...
-
Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2016, part II
Open Research DataThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the year 2016 on their self-assessment of selected digital competencies by gender. The survey was conducted in 2018, two years after the respondents obtained graduate status. The research sample included 1947 respondents. To summarize, in general, respondents...
-
Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2016, part I
Open Research DataThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the year 2016 on their self-assessment of selected digital competencies by gender. The survey was conducted in 2018, two years after the respondents obtained graduate status. The research sample included 1947 respondents. To summarize, in general, respondents...
-
Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2018, part II
Open Research DataThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the year 2018 on their self-assessment of selected digital competencies by gender. The survey was conducted in 2020, two years after the respondents obtained graduate status. The research sample included 1315 respondents. To summarize, in general, respondents...
-
Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2018, part I
Open Research DataThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the year 2018 on their self-assessment of selected digital competencies by gender. The survey was conducted in 2020, two years after the respondents obtained graduate status. The research sample included 1315 respondents. To summarize, in general, respondents...
-
Tuning Ferulic Acid Solubility in Choline-Chloride- and Betaine-Based Deep Eutectic Solvents: Experimental Determination and Machine Learning Modeling
PublicationDeep eutectic solvents (DES) represent a promising class of green solvents, offering particular utility in the extraction and development of new formulations of natural compounds such as ferulic acid (FA). The experimental phase of the study undertook a systematic investigation of the solubility of FA in DES, comprising choline chloride or betaine as hydrogen bond acceptors and six different polyols as hydrogen bond donors....
-
Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublicationHigh-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...
-
Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublicationIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
-
Shielded HMSIW-based frequency-tunable self-quadruplexing antenna using different solid/liquid dielectrics
PublicationThis article proposes a frequency-tunable self-quadruplexing antenna based on a shielded half-mode substrate integrated waveguide (S-HMSIW). In order to reduce the size of the HMSIW cavity resonator and to obtain quad-band characteristics, a modied E-shaped slot is engraved on the top of the metal. The experimental validation is carried out after analyzing the data using a circuit model. Flexibility of each resonant frequency is...
-
Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublicationDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
-
Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublicationHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
-
Learning Communities-International Journal of Learning in Social Contexts
Journals -
Project-Based Learning as a Method for Interdisciplinary Adaptation to Climate Change—Reda Valley Case Study
PublicationThe challenges of the global labour market require university authorities to extend traditional forms of education into more innovative and effective solutions. Project-based learning (PjBL) is one of highly effective methods for acquiring knowledge and teaching “soft” skills to future employees. This article describes an experimental use of PjBL at a university with a long history of teaching based on traditional methods—the Gdansk...
-
Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
-
TINKTEP: A fully self-consistent, mutually polarizable QM/MM approach based on the AMOEBA force field
PublicationWe present a novel quantum mechanical/molecular mechanics (QM/MM) approach in which a quantum subsystem is coupled to a classical subsystem described by the AMOEBA polarizable force field. Our approach permits mutual polarization between the QM and MM subsystems, effected through multipolar electrostatics. Self-consistency is achieved for both the QM and MM subsystems through a total energy minimization scheme. We provide an expression...
-
Thermal efficiency investigations on the self-ignition test engine fed with marine low sulfur diesel fuels
PublicationWithin the article an issues of implementing the new kinds of marine diesel fuels into ships’ operation was described taking into ac-count restrictions on the permissible sulphur content introduced by the International Maritime Organization. This is a new situation for ship owners and fuel producers, which forces the necessity to carry out laboratory research tests on especially adapted engine stands. How to elaborate the method...
-
Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublicationWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
-
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...
-
Iterative learning approach to active noise control of highly autocorrelated signals with applications to machinery noise
PublicationThis paper discusses the design and application of iterative learning control (ILC) and repetitive control (RC) for high modal density systems. Typical examples of these systems are structural and acoustical systems considered in active structural acoustic control (ASAC) and active noise control (ANC) applications. The application of traditional ILC and RC design techniques, which are based on a parametric system model, on systems...
-
Mathematical Thinking and Learning
Journals -
Animal Learning and Behavior
Journals -
Learning Environments Research
Journals -
Development and Learning in Organizations
Journals -
Journal of Workplace Learning
Journals -
Information and Learning Science
Journals -
Learning Media and Technology
Journals -
Journal of Learning Styles
Journals -
Journal of Teaching and Learning
Journals