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Wyniki wyszukiwania dla: SELF-SUPERVISED LEARNING
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„Active learning w praktyce” - 17. Szkolenie certyfikowane 13.12.2022 r.
Kursy Online -
„Active learning w praktyce” - 4. Szkolenie certyfikowane 21.10.2022 r.
Kursy Online -
Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublikacjaIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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Publicly available lecture webcasts - e-learning or promotion tool? case study
PublikacjaThis paper aims to show how universities interact with Internet users by webcasting selected courses. Paper has exploratory case-study character, presenting example of Berkeley Webcast initiative of University of California, Berkeley, webcasting undergraduate courses and on-campus events. On the base of short introduction to webcasting usage as an e-learning and promotional tool, the analysis of 3 purposely chosen different courses...
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Project and problem-based learning (PPBL): wprowadzenie
WydarzeniaZapraszamy na warsztaty, na których m.in. zrozumiesz założenia metody pracą projektu w oparciu o rozwiązywanie realnego problemu, poznasz etapy pracy zespołu metodą projektu oraz rolę nauczyciela i studentów w PPBL.
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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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User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
PublikacjaIn this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...
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Impact of technology on learning paradigms and teaching practices
PublikacjaArtykuł stara się omówić różne kwestie dotyczące wpływu technologii na proces nauczania poprzez zaprezentowanie określonych przykładów. Jest próbą sformułowania ogólnych wniosków oraz zweryfikowania kontrowersyjnych opinii.
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Comparative study of learning methods for artificial network
PublikacjaW artykule przedstawiono wyniki badań porównawczych metod uczenia sieci neuronowych takich jak: metoda propagacji wstecznej błędów, rekurencyjna metoda najmniejszych kwadratów, metoda Zangwill'a, metoda algorytmów ewolucyjnych. Celem tych badań jest dobieranie najefektywniejszej metody uczenia do projektowania adaptacyjnego neuronowego regulatora napięcia generatora synchronicznego.metody uczenia, sieć neuronowa, neuronowy regulator...
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The Use of Photographs in the Teaching/Learning of Descriptive Geometry
PublikacjaThe article presents the concept of enriching the Descriptive Geometry course with photographs and several simplified real-life engineering tasks. The photographic images used for the exercises are tightly linked to engineering structures, the given specialization and the surrounding world. The photo image as a record of central projection of a real space can be useful for presentation and analysis of the properties of perspective....
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Quality negotiation mechanism for e-learning platforms
PublikacjaZarządzanie jakością w aplikacjach działających w środowiskach sieci WEB opiera się na zadaniach związanych z wykrywaniem jakości połączenia klient - serwer oraz na optymalnym przydziale zasobów wedle jakości takowego połączenia. Optymalne zarządzanie jakością zależy od wypracowanego kompromisu pomiędzy jakością łącza a jakości transportowanego łączem zasobu. Artykuł opisuje możliwy do implementacji mechanizm odpowiedzialny za...
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Intelligent video and audio applications for learning enhancement
PublikacjaThe role of computers in school education is briefly discussed. Multimodal interfaces development history is shortly reviewed. Examples of applications of multimodal interfaces for learners with special educational needs are presented, including interactive electronic whiteboard based on video image analysis, application for controlling computers with facial expression and speech stretching audio interface representing audio modality....
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Designing learning-skills towards industry 4.0
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Deep learning for recommending subscription-limited documents
PublikacjaDocuments recommendation for a commercial, subscription-based online platform is important due to the difficulty in navigation through a large volume and diversity of content available to clients. However, this is also a challenging task due to the number of new documents added every day and decreasing relevance of older contents. To solve this problem, we propose deep neural network architecture that combines autoencoder with...
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Decision making process using deep learning
PublikacjaEndüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...
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Self-assembly of vertically oriented graphene nanostructures: multivariate characterisation by Minkowski functionals and fractal geometry
PublikacjaThe enormous self-assembly potential that graphene and its derived layered materials offer for responding to the contemporary environmental challenges has made it one of the most investigated materials. Hence, tuning its extraordinary properties and understanding the effect at all scales is crucial to tailoring highly customised electrodes. Vertically oriented graphene nanostructures, also known as carbon nanowalls (CNWs), due...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublikacjaComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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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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Gdańsk University of Technology graduates’ self-assessment of the use of digital skills in professional work – the year 2017
Dane BadawczeThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the year 2017 on their self-assessment of the use of digital skills in professional work. The survey was conducted in 2019, two years after the respondents obtained graduate status. The research sample included 1594 respondents. To summarize, the vast majority...
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Gdańsk University of Technology graduates’ self-assessment of the use of digital skills in professional work – the year 2018
Dane BadawczeThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the year 2018 on their self-assessment of the use of digital skills in professional work. The survey was conducted in 2020, two years after the respondents obtained graduate status. The research sample included 1315 respondents. To summarize, the vast majority...
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Gdańsk University of Technology graduates’ self-assessment of the use of digital skills in professional work – the year 2016
Dane BadawczeThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the year 2016 on their self-assessment of the use of digital skills in professional work. The survey was conducted in 2018, two years after the respondents obtained graduate status. The research sample included 1947 respondents. To summarize, the vast majority...
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Chlorinated solvents in a petrochemical wastewater treatment plant: Anassessment of their removal using self-organising maps
PublikacjaThe self-organising map approach was used to assess the efficiency of chlorinated solvent removal frompetrochemical wastewater in a refinery wastewater treatment plant. Chlorinated solvents and inorganicanions (11 variables) were determined in 72 wastewater samples, collected from three different purificationstreams. The classification of variables identified technical solvents, brine from oil desalting andrunoff sulphates as pollution...
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Systemy z Uczeniem Maszynowym / Systems with Machine Learning 2022/2023
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Service and Path Discovery Extensions for Self-forming IEEE 802.11s Wireless Mesh Systems
PublikacjaWith the rapid growth of the quantity and capabilities of end-user electronic devices, both stationary and mobile, they are employed in increasing number of applications. In this situation, wireless network technologies begin to play a crucial role as networks access technologies, as cable-based solutions tend to be of limited utility in case of easily portable or mobile devices. Resulting development of wireless technologies reached...
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Frequency-Reconfigurable Hybrid SIW-Based Self-Diplexing Antenna Using Solid and Liquid Dielectric Loading
PublikacjaThis paper presents a novel frequencyreconfigurable self-diplexing antenna (SDA) utilizing a hybrid substrate-integrated waveguide (SIW). The antenna comprises a radiating slot, a feeding network, and a hybrid SIW cavity featuring half-mode circular and half-mode rectangular SIW structures. The unique feature of this antenna lies in its fine-tuning capability of each resonant frequency by inserting or injecting solid and liquid...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublikacjaIn 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,...
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Comparative Study of Self-Organizing Maps vs. Subjective Evaluation of Quality of Allophone Pronunciation for Nonnative English Speakers
PublikacjaThe purpose of this study was to apply Self-Organizing Maps to differentiate between the correct and the incorrect allophone pronunciations and to compare the results with subjective evaluation. Recordings of a list of target words, containing selected allophones of English plosive consonants, the velar nasal and the lateral consonant, were made twice. First, the target words were read from the list by 9 non-native speakers and...
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Asynchronous and self-organizing radiolocation system — AEGIR
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Generalized adaptive notch filter with a self-optimization capability
PublikacjaW 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.
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Process of self-ignition engine loads and its properties
PublikacjaW 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...
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Self-organization of imidazolium ionic liquids in aqueous solution
PublikacjaW pracy przeanalizowano i podsumowano wyniki badań nad samoorganizacją oraz tworzeniem micel cieczy jonowych w roztworach wodnych otrzymane przez wiele zespołów badawczych. Średnio i długołańcuchowe imidazoliowe ciecze jonowe wykazują aktywność powierzchniową zależną od długości łańcucha alkilowego w kationie, analogicznie do kationowych surfaktantów. Wskazano na liczne zagadnienia, które wymagają dalszych systematycznych badań
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A probabilistic concept of load assessment of self-ignition engines
PublikacjaPrzedstawiono 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....
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Transfrontier co-operation of self-governments in Euroregion Baltic
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Self diagnostics using smart glasses - preliminary study
Publikacjan 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...
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A self-optimization mechanism for generalized adaptive notch smoother
PublikacjaTracking 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...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublikacjaCirculating 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...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany 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...
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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublikacjaIdentification 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...
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Multimodal learning application with interactive animated character. [Multimodalna aplikacja edukacyjna wykorzystująca interaktywną animowaną postać]
PublikacjaThe 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...
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Acid–Base Equilibrium and Self-Association in Relation to High Antitumor Activity of Selected Unsymmetrical Bisacridines Established by Extensive Chemometric Analysis
PublikacjaUnsymmetrical 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...
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Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2017, part I
Dane BadawczeThe 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...
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Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2017, part II
Dane BadawczeThe 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...
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Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2017, part I
Dane BadawczeThe 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...
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Gdańsk University of Technology graduates’ self-assessment of selected digital competencies by gender – the year 2017, part II
Dane BadawczeThe 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...
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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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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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Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublikacjaIn 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...
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Self-organising maps in the analysis of strains of human abdominal wall to identify areas of similar mechanical behaviour.
PublikacjaThe 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....
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublikacjaDue 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...
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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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