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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublikacjaDespite 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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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublikacjaThis 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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Frequency of use, moral incongruence, and religiosity and their relationships with self-perceived addiction to pornography, internet use, social networking and online gaming
PublikacjaBackground 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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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
PublikacjaLet 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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Justyna Płotka-Wasylka dr hab. inż.
OsobyUrodziła 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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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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Diagnosis of Damage in a Steel Tank with Self-Supported Roof through Numerical Analysis
PublikacjaThe 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
Publikacja-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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Minimal number of periodic points for smooth self-maps of simply-connected manifolds
Dane BadawczeThe 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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Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control
PublikacjaIn 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
PublikacjaThis 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
PublikacjaUncertainty 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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Modeling lignin extraction with ionic liquids using machine learning approach
PublikacjaLignin, 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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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublikacjaIn 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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Development and evaluation of RADA-PDGF2 self-assembling peptide hydrogel for enhanced skin wound healing
PublikacjaBackground: 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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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublikacjaIn 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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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublikacjaEEG-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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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublikacjaThis 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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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublikacjaLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
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Self-Organization of Graft Copolymers and Retortable iPP-Based Nanoporous Films Thereof
PublikacjaPolyolefins 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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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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Some aspects of blended-learning education
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Note on universal algoritms for learning theory
PublikacjaW 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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Structure and Randomness in Planning and Reinforcement Learning
PublikacjaPlanning 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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E-learning in tourism and hospitality: A map
PublikacjaThe 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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Optimization of Self-Organized TiO2 Nanotube Geometry on Ti and Ti Alloys Using Fuzzy Logic Reasoning
PublikacjaThe 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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An algorithmic approach to estimating the minimal number of periodic points for smooth self-maps of simply-connected manifolds
PublikacjaFor 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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Employees’ self-expansion, work conditions, work engagement and productive behaviours: study 1&2
Dane BadawczeIn 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...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublikacjaThis 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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Projekt Leonardo da Vinci EMDEL (European Model for Distance Education and Learning) - otwarte szkolenia online.
PublikacjaW 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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Propulsion and Maneuvering Systems’ Characteristics of the U.S. Flagged Great Lakes Self-Unloading Bulk Carriers
PublikacjaPaper contains an overview of the propulsion and maneuvering systems’ characteristics of United States flagged Great Lakes self - unloading bulk carriers. A contrast between the importance of the transport task carried by those vessels to their low number and considerable age suggests the need to review and understand their complexity as well as complexity of their operations in order to provide suitable energy- and operational...
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Isolation and Self-Association Studies of Beta-Lactoglobulin
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Multifrequency self-optimizing narrowband interference canceller
PublikacjaThe problem of cancellation of a nonstationary sinusoidal interference, acting at the output of a linear stable plant, is considered. It is assumed that disturbance is a multifrequency narrowband signal, and that system output is contaminated with wideband noise. It is not assumed that the reference signal is available. Two disturbance cancelling schemes are proposed, one for disturbances with unrelated frequency components, and...
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Energy optimisation in resilient self-stabilizing processes
PublikacjaW 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.
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Self-stabilizing algorithm for edge-coloring of graphs
PublikacjaReferat ten poświęcony jest kolorowaniu grafów w modelu rozproszonym.Podano samostabilizujący się algorytm kolorowania krawędzi grafu wraz z dowodem poprawności oraz oszacowaniem jego czasu działania.
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Coupledfield modelling of interferometric hydrophone with self supportedmandrel.
PublikacjaW pracy przedstawiono nowatorską konstrukcję światłowodowego interferometrycznego przetwornika ciśnienia do zastosowań w hydrofonach. Przetwornik ten składa się z cewki światłowodowej zalanej w żywicy epoksydowej. Zaprezentowano technikę modelowania właściwości przetwornika, wykorzystującą opis przy pomocy parametrów równoważnego materiału ortotropowego i Metodę Elementów Skończonych. Przestawiono wyniki statycznego modelowania...
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Modelling gene expression of a self-regulating protein
PublikacjaWe analyze a model of gene transcription and protein synthesis. We take into account the number of sites on the protein’s promoter at which the protein’s dimers can bind blocking transcription of protein mRNA.
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Self-assessment of competencies of students and graduates participating in didactic projects – Case study
PublikacjaAim/purpose: the aim of this article is to examine the opinions of students and graduates of the faculty of economics of a technical university as regards their selfassessment of their preparation for entering the modern labour market. All the respondents participated during their studies in didactic projects aimed at improving their competencies taking into account the expectations of potential employers. Design/methodology/approach:...
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Feature Reduction Using Similarity Measure in Object Detector Learning with Haar-like Features
PublikacjaThis 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
PublikacjaSince 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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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublikacjaThis 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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Microfluidic SIW-Based Tunable Self-Diplexing Antenna for Sub-6 GHz Band Applications
PublikacjaThis work introduces a novel frequency tunable self-diplexing antenna (SDA) design based on substrate integrated waveguide (SIW) technology. A modified A-shaped slot is employed on the cavity’s top plane, which is excited by two independent 50 Ω microstrip feed lines to operate at each resonant frequency. The frequency flexibility of the proposed antenna allows for fine-tuning at each resonance frequency. The frequency flexibility...
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Shielded HMSIW-Based Self-Triplexing Antenna With High Isolation for WiFi/WLAN/ISM Band
PublikacjaThis article presents a novel design of a miniaturized self-triplexing antenna (STA) based on the shielded half-mode substrate integrated waveguide (S-HMSIW) for WiFi/WLAN/ISM-band applications. The S-HMSIW is constructed by assembling one row of vias and an open slot at the open-ended side of the conventional HMSIW. This configuration increases the quality factor and minimizes unwanted radiation loss, which allows for achieving...
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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 approach to packaging compatibility testing in the new product development process
PublikacjaThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublikacjaPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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An Approach to Data Reduction for Learning from Big Datasets: Integrating Stacking, Rotation, and Agent Population Learning Techniques
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