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Search results for: SELF-SUPERVISED LEARNING
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LANGUAGE LEARNING
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Metacognition and Learning
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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublicationThe process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between...
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Two‐functional μBIST for Testing and Self‐Diagnosis of Analog Circuits in Electronic Embedded Systems
PublicationThe paper concerns the testing of analog circuits and blocks in mixed‐signal Electronic Embedded Systems (EESs), using the Built‐in Self‐Test (BIST) technique. An integrated, two‐functional, embedded microtester (μBIST) based on reuse of signal blocks already present in an EES, such as microprocessors, memories, ADCs, DACs, is presented. The novelty of the μBIST solution is its extended functionality. It can perform 2 testing functions:...
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Diffusible hydrogen management in underwater wet self-shielded flux cored arc welding
PublicationThis article reports the effect of underwater wet welding parameters and conditions on the diffusible hydrogen content in deposited metal for welding with a self-shielded flux cored wire. The diffusible hydrogen content in deposited metal was determined using the glycerin method according to the Plackett-Burman design determining the significance of the effect of the stick out length, welding current, arc voltage, travel speed...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublicationText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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Testing Students’ Entrepreneurial Self-Efficacy as an Early Predictor of Entrepreneurial Activities. Evidence From the SEAS Project
PublicationOver the last forty years, since Bandura (1977) introduced the concept of self-efficacy, there have been a constantly growing number of research publications using this concept. Its early development resulted in the creation of a new construct of entrepreneurial self-efficacy (ESE) proposed for the first time by (Chen et al. 1998). Since then, many different groups of research concerning ESE have emerged - one of them is the study...
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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublicationDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...
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Minimal number of periodic points of smooth boundary-preserving self-maps of simply-connected manifolds
PublicationLet M be a smooth compact and simply-connected manifold with simply-connected boundary ∂M, r be a fixed odd natural number. We consider f, a C1 self-map of M, preserving ∂M . Under the assumption that the dimension of M is at least 4, we define an invariant Dr(f;M,∂M) that is equal to the minimal number of r-periodic points for all maps preserving ∂M and C1-homotopic to f. As an application, we give necessary and sufficient...
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Methodology for assessing end-user requirements in the Ella4Life project: elders’ perspectives about self-monitoring
PublicationThe purpose of this paper is to explore elders’ perspectives about self-monitoring and using specially developed sensor technology for measuring health indicators. The qualitative research method is focus-groups with guidelines that were designed for understanding elder’s requirements about monitoring health indicators. We present them two devices: the first sensor is a device for monitoring of cardiac action potential fixed into...
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The awareness of the profession and the self-reflection of the primary, secondary and upper secondary school teachers on their own practice in the light of empirical studies
PublicationThe article presents the issue of awareness of the profession and the self-reflection of the primary, secondary and upper secondary school teachers’ on their own practice. The text refers to data based on empirical studies.
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Self-Adaptive Mesh Generator for Global Complex Roots and Poles Finding Algorithm
PublicationIn any global method of searching for roots and poles, increasing the number of samples increases the chances of finding them precisely in a given area. However, the global complex roots and poles finding algorithm (GRPF) (as one of the few) has direct control over the accuracy of the results. In addition, this algorithm has a simple condition for finding all roots and poles in a given area: it only requires a sufficiently dense...
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An experimental study of self-sensing concrete enhanced with multi-wall carbon nanotubes in wedge splitting test and DIC
PublicationConcrete is the worldwide most utilized construction material because of its very good performance, forming ability, long-term durability, and low costs. Concrete is a brittle material prone to cracking. Extensive cracking may impact durability and performance over time considerably. The addition of a small amount of carbon nanotubes (CNT) increases the concrete’s overall electrical conductivity, enabling internal structure...
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Projektowanie zajęć prowadzonych na odległość (10h e-learning)
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Frequency of use, moral incongruence, and religiosity and their relationships with self-perceived addiction to pornography, internet use, social networking and online gaming
PublicationBackground and Aims Moral incongruence involves disapproval of a behaviour in which people engage despite their moral beliefs. Although considerable research has been conducted on how moral incongruence relates to pornography use, potential roles for moral incongruence in other putative behavioural addictions have not been investigated. The aim of this study was to investigate the role of moral incongruence in self‐perceived...
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Modeling lignin extraction with ionic liquids using machine learning approach
PublicationLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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Reducing the number of periodic points in the smooth homotopy class of a self-map of a simply-connected manifold with periodic sequence of Lefschetz numbers
PublicationLet f be a smooth self-map of an m-dimensional (m >3) closed connected and simply-connected manifold such that the sequence of the Lefschetz num- bers of its iterations is periodic. For a fixed natural r we wish to minimize, in the smooth homotopy class, the number of periodic points with periods less than or equal to r. The resulting number is given by a topological invariant J[f] which is defned in combinatorial terms and is...
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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublicationIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublicationEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublicationIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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Diagnosis of Damage in a Steel Tank with Self-Supported Roof through Numerical Analysis
PublicationThe safety of civil engineering structures is one of the most important issues of building industry. That is why the assessment of the damage-involved structural response has recently become of major concern to engineers. Among a number of different approaches to diagnosis of damage, the method of measuring the changes in natural frequencies is considered to be one of the most effective indicators of global damage. From the practical...
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Structural Adaptive, Self-Separating Material for Removing Ibuprofen from Waters and Sewage
Publication-cyclodextrin nanosponge (CDM) was used for the adsorption of ibuprofen (IBU) from water and sewage. The obtained material was characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), Brunauer–Emmett–Teller (BET), Barrett– Joyner–Halenda (BJH), Harkins and Jura t-Plot, zeta potential, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and elementary analysis (EA)....
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublicationThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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A consensus-based approach to the distributed learning
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Prototype selection algorithms for distributed learning
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An agent-based framework for distributed learning
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Note on universal algoritms for learning theory
PublicationW 2001 Cucker i Smale zaproponowali nowe podejście do teorii uczenia się w oparciu o problematykę teorii aproksymacji.W 2005 i 2007 Bivev, Cohen, Dahmen, DeVore i Temlyakov opublikowali dwie prace z teorii uczenia się. W omawianej publikacji uogólniliśmy ich rezultaty jednocześnie upraszczając dowody.
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Some aspects of blended-learning education
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E-learning in tourism and hospitality: A map
PublicationThe impact of information and communication technologies (ICT) on tourism and hospitality industries has been widely recognized and investigated as a one of the major changes within the domains in the last decade: new ways of communicating with prospective tourists and new ways of purchasing products arisen are now part of the industries’ everyday life. Poor attention has been paid so far to the role played by new media in education...
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Structure and Randomness in Planning and Reinforcement Learning
PublicationPlanning in large state spaces inevitably needs to balance the depth and breadth of the search. It has a crucial impact on the performance of a planner and most manage this interplay implicitly. We present a novel method \textit{Shoot Tree Search (STS)}, which makes it possible to control this trade-off more explicitly. Our algorithm can be understood as an interpolation between two celebrated search mechanisms: MCTS and random...
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Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control
PublicationIn this paper, a unified nonlinear modeling and control scheme is presented. A self-structuring Takagi-Sugeno (T-S) fuzzymodel is used to approximate the unknown nonlinear plant based on I/O data collected on-line. Both the structure and theparameters of the T-S fuzzy model are updated by an on-line clustering method and a recursive least squares estimation(RLSE) algorithm. The rules of the fuzzy model can be added, replaced or...
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Wireless Body Area Network for Preventing Self-Inoculation Transmission of Respiratory Viral Diseases
PublicationThis paper proposes an idea of Wireless Body Area Networks (WBANs) based on Bluetooth Low-Energy (BLE) standards to recognize and alarm a gesture of touching the face, and in effect, to prevent self-inoculation of respiratory viral diseases, such as COVID-19 or influenza A, B, or C. The proposed network comprises wireless modules placed in bracelets and a necklace. It relies on the received signal strength indicator (RSSI) measurements...
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Testing Question Order Effects of Self-perception of Risk Propensity on Simple Lottery Choices as Measures of the Actual Risk Propensity
PublicationUncertainty together with the necessity of making choices inevitably results in risky decisions. For many years now, scientists have been studying notions connected with risk such as risk management, risk perception or risk propensity. While many sophisticated methods regarding measurement of risk propensity have been developed so far, it seems that little attention has been paid to checking whether they are not inherently flawed....
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Minimal number of periodic points for smooth self-maps of simply-connected manifolds
Open Research DataThe problem of finding the minimal number of periodic points in a given class of self-maps of a space is one of the central questions in periodic point theory. We consider a closed smooth connected and simply-connected manifold of dimension at least 4 and its self-map f. The topological invariant D_r[f] is equal to the minimal number of r-periodic points...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublicationThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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Development and evaluation of RADA-PDGF2 self-assembling peptide hydrogel for enhanced skin wound healing
PublicationBackground: Wound healing complications affect numerous patients each year, creating significant economic and medical challenges. Currently, available methods are not fully effective in the treatment of chronic or complicated wounds; thus, new methods are constantly sought. Our previous studies showed that a peptide designated as PDGF2 derived from PDGF-BB could be a promising drug candidate for wound treatment and that RADA16-I...
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Justyna Płotka-Wasylka dr hab. inż.
PeopleUrodziła się w Słupsku (24.03.1986).W 2005 roku ukończyła I Liceum Ogólnokształcące im. Jana II Sobieskiego w Wejherowie i rozpoczęła studia na Wydziale Chemicznym Politechniki Gdańskiej. Po ich ukończeniu w 2010 rozpoczęła pracę naukową na tej uczelni, uzyskując w 2014 roku stopień doktora nauk chemicznych. Tematem jej rozprawy doktorskiej, wykonywanej pod kierunkiem prof. Marka Biziuka oraz dr Caluma Morrisona (Uniwersytet w...
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Projekt Leonardo da Vinci EMDEL (European Model for Distance Education and Learning) - otwarte szkolenia online.
PublicationW 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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Self-Organization of Graft Copolymers and Retortable iPP-Based Nanoporous Films Thereof
PublicationPolyolefins might become inexpensive alternatives to the existing membranes based on polyethersulfone. Here we disclose the production of retortable, well-defined PP-based nanoporous membranes derived from amphiphilic graft copolymer precursors. The graft copolymers, containing a polypropylene backbone and polyester grafts, were obtained by grafting lactones, specifically δ-valerolactone and ε-caprolactone, from well-defined randomly...
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Feature Reduction Using Similarity Measure in Object Detector Learning with Haar-like Features
PublicationThis paper presents two methods of training complexity reduction by additional selection of features to check in object detector training task by AdaBoost training algorithm. In the first method, the features with weak performance at first weak classifier building process are reduced based on a list of features sorted by minimum weighted error. In the second method the feature similarity measures are used to throw away that features...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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An algorithmic approach to estimating the minimal number of periodic points for smooth self-maps of simply-connected manifolds
PublicationFor a given self-map f of M, a closed smooth connected and simply-connected manifold of dimension m 4, we provide an algorithm for estimating the values of the topological invariant D^m_r [f], which equals the minimal number of r-periodic points in the smooth homotopy class of f. Our results are based on the combinatorial scheme for computing D^m_r [f] introduced by G. Graff and J. Jezierski [J. Fixed Point Theory Appl. 13 (2013),...
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Optimization of Self-Organized TiO2 Nanotube Geometry on Ti and Ti Alloys Using Fuzzy Logic Reasoning
PublicationThe geometry of self-organized TiO2 nanotubes, obtained by electrochemicalanodization, has been determined by using fuzzy reasoning approach. The efficiency of TiO2nanotubular layer in biomedical applications depends on geometry and available surface area ofnanotubes, which can be determined by their diameter and length. The structure of nanotubesdepends on processing parameters of electrochemical anodization, like applied potential,anodization...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis 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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Employees’ self-expansion, work conditions, work engagement and productive behaviours: study 1&2
Open Research DataIn the following studies conducted in Poland, we examined the importance of workplace self-expansion and found that it is a significant mediator between job resources (e.g. compensation and benefits, job tasks) and work engagement (Study 1) as well as task-oriented engagement (Study 2). At the same time, our findings prove that job demands (e.g. role...