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Search results for: e-learing
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Experimental research on marine oil-lubricated stern tube bearing
PublicationBearings of propeller shafts are very crucial elements of the propulsion system of each of the ships. The safety of shipping depends on their durability and reliability. The new legal restrictions mean that today we are looking for environmentally friendly solutions. That is why water-lubricated bearings are becoming more and more popular. So, will oil-lubricated shaft bearings belong to the past? The bearing with a white metal...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublicationWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublicationMusic analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Security of export transactions in the offer of leading banks on the Polish market
PublicationThe following article presents the so-called conditioned payment methods, i.e. instruments for securing export transactions, such as letter of credit, documentary collection, bank guarantees, factoring and forfaiting. The characteristics of each particular method are presented as well as the transactions using them are described. In the following paper, the author included also the leading Polish banks, which offer the above- mentioned...
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Playback detection using machine learning with spectrogram features approach
PublicationThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Machine Learning in Multi-Agent Systems using Associative Arrays
PublicationIn this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...
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Methods of Improving Speech Intelligibility for Listeners with Hearing Resolution Deficit
PublicationMethods developed for real-time time scale modification (TSM) of speech signal are presented. They are based onthe non-uniform, speech rate depended SOLA algorithm (Synchronous Overlap and Add). Influence of theproposed method on the intelligibility of speech was investigated for two separate groups of listeners, i.e. hearingimpaired children and elderly listeners. It was shown that for the speech with average rate equal to or...
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Employing a biofeedback method based on hemispheric synchronization in effective learning
PublicationIn this paper an approach to build a brain computer-based hemispheric synchronization system is presented. The concept utilizes the wireless EEG signal registration and acquisition as well as advanced pre-processing methods. The influence of various filtration techniques of EOG artifacts on brain state recognition is examined. The emphasis is put on brain state recognition using band pass filtration for separation of individual...
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Analysis of Learning Outcomes in Medical Education with the Use of Fuzzy Logic
PublicationThe national curricula of the EU member states are structured around learning outcomes, selected according to Bloom’s Taxonomy. The authors of this paper claim that using Bloom’s Taxonomy to phrase learning outcomes in medical education in terms of students’ achievements is difficult and unclear. This paper presents an efficient method of assessing course learning outcomes using Fuzzy Logic.
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Designing acoustic scattering elements using machine learning methods
PublicationIn the process of the design and correction of room acoustic properties, it is often necessary to select the appropriate type of acoustic treatment devices and make decisions regarding their size, geometry, and location of the devices inside the room under the treatment process. The goal of this doctoral dissertation is to develop and validate a mathematical model that allows predicting the effects of the application of the scattering...
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublicationTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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Organizational Wisdom: The Impact of Organizational Learning on the Absorptive Capacity of an Enterprise
PublicationPurpose: In this article, we analyze the concept of organizational wisdom, indicating its key elements and verifieng the relationships between them. Design/Methodology/Approach: The study was conducted at Vive Textile Recycling Sp. z o.o in Poland. Empirical data was collected from 138 managers using the PAPI technique. Structural equation modelling (SEM) was performed to test the research hypotheses. Additionally, the significance...
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Optimisation and field assessment of poroelastic wearing course bond quality
PublicationCompared to typical asphalt mixtures, poroelastic mixtures are characterised by high porosity and high flexibility, which are desirable for traffic noise reduction. However, the same properties increase the risk of debonding from the lower layer, which is a significant source of premature damage. The study investigates which of the factors – tack coat agent, type and texture of the lower layer – have the greatest impact on interlayer...
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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublicationThis study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...
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Deep learning-based waste detection in natural and urban environments
PublicationWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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Noise profiling for speech enhancement employing machine learning models
PublicationThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Impact of Spatial Noise Correlation on Bearing Accuracy in DIFAR Systems
PublicationDIFAR type underwater passive systems are one of the more commonly used tools for detecting submarines. At the design stage, which usually uses computer simulations, it is necessary to generate acoustic noise of the sea. It has been shown that correlating noise significantly reduces these errors compared to the assumption that noise is uncorrelated. In addition, bearing errors have been shown to be the same in systems with a commonly...
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Design of poroelastic wearing course with the use of direct shear test
PublicationPoroelastic Road Surfaces (PERS) are characterized by porous structure with at least 20% of air void content and stiffness almost 10 times lower than typical asphalt course. Such properties enable noise reduction up to 12 dB in comparison to SMA 11 mixture. However, the main disadvantage of previously used poroelastic mixtures, based on resin type binders, was their low durability, which resulted in raveling and delamination from...
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Diagnosis of bearing damage in induction motors by instantaneous power analysis
PublicationResearch of the machine with simulated bearing damages has been carried out, where variable load torque, simulating bearing damage, was introduced. The results show that components which can be used for bearings diagnosis appear in the spectrum of the product of current and supply voltage instantaneous values. These components are easier to identify than the components of current spectrum, which have been used so far in diagnostic...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Rebuttal from L. E. K. Ratcliffe, W. Pijacka, F. D. McBryde, A. P. Abdala, D. J. Moraes, P. A. Sobotka, E. C. Hart, K. Narkiewicz, A. K. Nightingale and J. F. R. Paton
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System wspomagający zarządzanie Wydziałem Elektroniki, Telekomunikacji i Informatyki Politechniki GdańskiejW : Perspektywy Rozwoju e-Uczelni w Kontekście Globalnej Informatyzacji; - e-uczelnia, konferencja krajowa; 14-15 maja 2009, Gdańsk. - [skrypt prezentacji]
PublicationW artykule przedstawiono założenia projektowe, architekturę i implementację systemu przeznaczonego do wspomagania zarządzania wydziałem wyższej uczelni. System jest realizowany dla Wydziału Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej, w technologiach typu open-source. Artykuł opisuje poszczególne komponenty systemu oraz aspekty technologiczne jego budowy. Opisano założenia przyjęte na początku projektu, architekturę...
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Susceptibility of the LLC Resonance Generator for Induction Heating on Changes in Load Parameters Caused by Heating the Charge
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Effect of Sieve Drum Inclination Angle on Wheat Grain Cleaning in a Novel Rotary Cleaning Device
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Analysis of the Sieve Unit Inclination Angle in the Cleaning Process of Oat Grain in a Rotary Cleaning Device
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Magdalena Rucka prof. dr hab. inż.
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Reading Teacher (The)
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ELearning Papers
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Journal of Reading
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TECHNICAL SOARING
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Reading Psychology
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Reading and Writing
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J-Reading
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Physical effects of radiation processes in poly(aliphatic/aromatic-ester)s modified with e-beam radiation
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A comparative pathogenicity analysis of two adenovirus strains, 1/A and 8a/E, isolated from poultry in Poland
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Modyfikacja transakcji zawieranych na rynku masowych produktów rolnych zorganizowanym przez E-WGT S.A.
PublicationCelem artykułu jest przedstawienie zmian jakie wprowadzono w handlu elektronicznym masowymi produktami rolnymi w Polsce.
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3-[(E)-2-(5,7-dichloro-8-hydroxyquinolin-2-yl)vinyl]-4-hydroxyphenyl acetate
PublicationTytułowy związek otrzymano w reakcji 2,5 dihydroksybenzaldehydu z równomolową ilością 5,7-dichloro-2-metylochinolin-8-olu. Strukturę C19H13Cl2NO4 wyznaczono metodą rentgenowskiej analizy strukturalnej. Zawarte w komórce elementarnej cząsteczki posiadają konfiguracje E a długości wiązań C=C wynoszą w tym przypadku C10-C11 1.328(3) Å oraz C29-C30 1.330(3) Å. Cząsteczki otrzymanego związku stabilizowane są przez układ...
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Sektor B2C w Polsce - badanie działań rynkowych stosowanych przez wybrane serwisy e-commerce
PublicationPoznanie preferencji konsumentów w odniesieniu do czynników, poprzez które serwisy handlowe starają się oddziaływać na internautów, pozwala na ich lepsze dopasowanie do oczekiwań konsumentów oraz na opracowanie skutecznych form komunikacji wspierającej sprzedaż. Artykuł prezentuje wybrane wyniki trzech etapów badań empirycznych.
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The Prevalence of Cigarette and E-cigarette Smoking Among Students in Central and Eastern Europe—Results of the YUPESS Study
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Attitude towards cigarette or e-cigarette use and the smoking initiation year among young European adults
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Educare le fanciulle al sacramento del matrimonio. Testimonianze di scrittori e predicatori medievali
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I doveri della moglie secondo gli insegnamenti di alcuni predicatori e scrittori tardomedievali
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublicationWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this...
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Bewertung der qualität von online lernmodulen = Próba oceny jakości e-Lerningowych modułów online
PublicationW pracy dokonano klasyfikacji rozwiązań modułów (systemów) e-Learning wg. sposobu ich tworzenia (tj. systemy autorskie, komercyjne, otwarte, zamknięte, standardowe, niestandardowe), funkcjonalności, interaktywności, obciążania sieci. Przedstawiono również wybrane kryteria (tj. merytoryczne, dydaktyczne i multimedialne) oceny jakości modułów dostępnych online pod kątem ich wykorzystywania w systemach zdalnego nauczania. Na zakończenie...
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CFD COUPLING OF VOF MODEL WITH ARRHENIUS EQUATION FOR ANALYSIS OF LASER-INDUCED THERMAL DEACTIVATION OF E. COLI
PublicationUnderstanding bacterial deactivation at the micro-scale, particularly with E. coli, is crucial for advancing microbiology and has promising applications in biomedical research. In this research contribution, we investigate the thermal inactivation of E. coli bacteria using gold nanoparticles irradiated by a green 1-W laser within a microfluidic chamber. The microfluidic device comprises a fluidic chamber filled with a thin film...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublicationWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this objective...