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Search results for: —TRANSFER LEARNING, DEEP LEARNING, PROTEIN STRUCTURE, FUNCTION, AND INTERACTION PREDICTION, SEQUENCE MODELLING
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NEUROBIOLOGY OF LEARNING AND MEMORY
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LEARNING DISABILITY QUARTERLY
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Investigations in Mathematics Learning
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TEACHING AND LEARNING IN MEDICINE
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Earthquake-induced pounding between equal height multi-storey buildings considering soil-structure interaction
PublicationThe present paper investigates the coupled effect of the supporting soil flexibility and pounding between neighbouring, insufficiently separated equal height buildings under earthquake excitation. Two adjacent three-storey structures, modelled as inelastic lumped mass systems with different structural characteristics, have been considered in the study. The models have been excited using a suit of ground motions with different peak...
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Numerical FDM modelling of wave propagation in concrete structure
PublicationThe article presents application of finite difference method to damage detection and its size evaluation in concrete structure by elastic wave propagation method. The simulations of wave propagation in concrete structure were performed for six different damage scenarios. Damages were modelled as areas with changed material properties. Investigation focused on the influence of damage size on the energy of wave reflection. Presented...
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Modeling protein structures with the coarse-grained UNRES force field in the CASP14 experiment
PublicationThe UNited RESidue (UNRES) force field was tested in the 14th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP14), in which larger oligomeric and multimeric targets were present compared to previous editions. Three prediction modes were tested (i) ab initio (the UNRES group), (ii) contact-assisted (the UNRES- contact group), and (iii) template-assisted (the UNRES-template...
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Data Reduction Algorithm for Machine Learning and Data Mining
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Learning from the often-forgotten Jan Heweliusz disaster
PublicationPrzedstawiono konieczność przeprowadzenia badań nad zatonięciem promu Jan Heweliusz, którego katastrofa - w odróżnieniu od innych promów - została przemilczana i nie wywołała żadnych badań naukowych.
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The role and construction of educational agents in distance learning environments
PublicationArtykuł przedstawia definicję oraz klasyfikację agentów edukacyjnych. Wskazuje typowe cele i zadania agentów, a także omawia schemat ich budowy i funkcjonowania. Wskazano także różnorodność możliwości, jakie stwarzają różne rodzaje agentów w procesie nauczania. W artykule opisano także wytworzony w ramach badań prototyp agenta WAS, którego zadaniem jest wspomaganie uczniów w zakresie pracy z materiałami edukacyjnymi.
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IEEE 802.11 LAN capacity: incentives and incentive learning
PublicationPrzedstawiono matematyczny model zgodności motywacyjnej dla gier niekooperacyjnych wywiązujących się przy autonomicznym ustawianiu parametrów mechanizmu dostępu do medium transmisyjnego. Zaproponowano koncepcję przewidywania wyniku gry w zależności od stopnia wyrafinowania strategii terminala oraz jego możliwości energetycznych. Analiza symulacyjna potwierdziła dobrą wynikową wydajność sieci przy niewielu terminalach silnie uzależnionych...
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Using similar classification tasks in feature extractor learning
PublicationThe article presents and experimentally verify the idea of automatic construction of feature extractors in classification problems. The extractors are created by genetic programming techniques using classification examples taken from other problems then the problem under consideration.
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IEEE 802.11 LAN capacity: incentives and incentive learning
PublicationMotywację stacji sieci lokalnej IEEE 802.11 do przeprowadzenia racjonalnego ataku na mechanizm MAC można wyrazić liczbowo jako punkt stały pewnego przekształcenia dwuwymiarowego. Model taki został następnie rozszerzony o możliwość stosowania przez stacje strategii wyrafinowanego przewidywania zachowań innych stacji. Pokazano, w jaki sposób wpływa to na przepustowość sieci i sprawiedliwość dostępu do medium transmisyjnego, uwzględniając...
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Scent emitting multimodal computer interface for learning enhancement
PublicationKomputerowy interfejs aromatyczny stanowi ważne uzupełnienie procesu stymulacji polisensorycznej. Stymulacja ta odgrywa kluczową rolę w terapii i kształceniu dzieci z zaburzeniami rozwoju (np. w przypadku autyzmu czy ADHD). Opracowany interfejs może stać się elementem wyposażenia tzw. sal doświadczania świata, ale może być także stosowany niezależnie stanowiąc znaczące wzbogacenie komputerowych programów edukacyjnych. Dzięki możliwości...
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Machine learning applied to bi-heterocyclic drugs recognition
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Learning from examples with data reduction and stacked generalization
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Stacking-Based Integrated Machine Learning with Data Reduction
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INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublicationThe Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...
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PERFORMANCE COMPARISON OF MACHINE LEARNING ALGORITHMS FOR PREDICTIVE MAINTENANCE
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Machine Learning for Sensorless Temperature Estimation of a BLDC Motor
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Machine learning system for estimating the rhythmic salience of sounds.
PublicationW artykule przedstawiono badania dotyczące wyszukiwania danych rytmicznych w muzyce. W pracy przedstawiono postać funkcji rankingujacej poszczególnych dźwięków frazy muzycznej. Opracowano metodę tworzenia wszystkich możliwych hierarchicznych struktur rytmicznych, zwanych hipotezami rytmicznymi. Otrzymane hipotezy są następnie porządkowane w kolejności malejącej wartości funkcji rankingującej, aby ustalić, która ze znalezionych...
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Endoscopy images classification with kernel based learning algorithms.
PublicationPrzedstawiono zastosowanie algorytmów opartych na wektorach wspierających zbudowanych na dwóch różnych funkcjach straty do klasyfikacji obrazów endoskopowych przełyku. Szczegółowo omówiono sposób ekstrakcji cech obrazów oraz algorytm klasyfikacji. Klasyfikator został zastosowany do problemu rozpoznawania zdjęć guzów złośliwych i łagodnych.
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E-learning w małych i średnich przedsiębiorstwach
PublicationW rozdziale przedstawiono podstawowych zagadnienia e-learningu w małych i średnich przedsiębiorstwach oraz przykłady realizowanych projektów.
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E-learning course "International comparative studies on SMEs"
PublicationProjekt Leonardo da Vinci "International comparative studies and course development on SMEs" został zainspirowany poprzednim projektem LdV "A European Diploma in SME Management". Bazując na poprzednich doświadczeniach projektowych zaproponowano opracowanie struktur dla opisania narodowych systemów małych i średnich przedsiębiorstw (ang. SME Small Media Enterprises) przy wykorzystaniu dostępnych krajowych danych. Udowodniono, że...
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MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS
PublicationIn this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones - the healthy blood cells (erythrocytes) and the pathologic (echinocytes). The separated blood cells are analyzed in terms of their most important features by the eigenfaces method. The features are the...
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The use of machine learning for face regions detection in thermograms
PublicationThe aim of this study is to analyse the methods of detecting characteristic points of the face in thermographic images. As part of the implementation an extensive analysis of scientific publications covering similar issues both for the analysis of images made in visible light and thermographic images was carried out. On the basis of this analysis, 3 models were selected and then they were implemented and tested on the basis of...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublicationAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
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Prediction of flow boiling heat transfer data for R134a, R600a and R290 in minichannels
PublicationIn the paper presented is the analysis of the results of calculations using a model to predict flow boiling of refrigerants such as R134a, R600a and R290. The latter two fluids were not used in development of model semiempirical correction. For that reason the model was verified with present experimental data. The experimental research was conducted for a full range of quality variation and a relatively wide range of mass velocity....
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublicationThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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Formation of Protein Networks between Mucins: Molecular Dynamics Study Based on the Interaction Energy of the System
PublicationMolecular dynamics simulations have been performed for a model aqueous solution of mucin. As mucin is a central part of lubricin, a key component of synovial fluid, we investigate its ability to form cross-linked networks. Such network formation could be of major importance for the viscoelastic properties of the soft-matter system and crucial for understanding the lubrication mechanism in articular cartilage. Thus,the inter- and...
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Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublicationThis article introduces an innovative method for achieving low-cost and reliable multi-objective optimization (MO) of microwave passive circuits. The technique capitalizes on the attributes of surrogate models, specifically artificial neural networks (ANNs), and multi-resolution electromagnetic (EM) analysis. We integrate the search process into a machine learning (ML) framework, where each iteration produces multiple infill points...
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Lipid-protein interactions in membranes: a molecular modelling study
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Face with Mask Detection in Thermal Images Using Deep Neural Networks
PublicationAs the interest in facial detection grows, especially during a pandemic, solutions are sought that will be effective and bring more benefits. This is the case with the use of thermal imaging, which is resistant to environmental factors and makes it possible, for example, to determine the temperature based on the detected face, which brings new perspectives and opportunities to use such an approach for health control purposes. The...
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Modelling study of flow boiling heat transfer of perspective fluids for refrigeration technology
PublicationThere is a gap of knowledge on flow boiling at high saturation temperatures and higher values of reduced pressure. Thus far, the in-house developed semi-empirical model for flow boiling and flow condensation showed a satisfactory accuracy for calculations for various refrigeration fluids for a wide scope of reduced pressures. This study presents results of calculations of heat transfer coefficient of perspective refrigeration fluids,...
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Parametrization of Backbone−Electrostatic and Multibody Contributions to the UNRES Force Field for Protein-Structure Prediction from Ab Initio Energy Surfaces of Model Systems
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Structure of the register of immovable monuments under the primary function – comparison of 2017 and 2024
Open Research DataThis dataset compares the structure of the register of immovable monuments in Poland under the primary function of objects for 2017 and 2024. The statement included the following primary functions of the monuments: urbanism, sacral, defence, industrial, economic, residential, public utilities, communication, cemeteries, greenery, etc. The dataset has...
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Probabilistic assessment of SMRFs with infill masonry walls incorporating nonlinear soil-structure interaction
PublicationInfill Masonry Walls (IMWs) are used in the perimeter of a building to separate the inner and outer space. IMWs may affect the lateral behavior of buildings, while they are different from those partition walls that separate two inner spaces. This study focused on the seismic vulnerability assessment of Steel Moment-Resisting Frames (SMRFs) assuming different placement of IMWs incorporating nonlinear Soil-Structure Interaction (SSI)....
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Specific Binding of Cholesterol to the Amyloid Precursor Protein: Structure of the Complex and Driving Forces Characterized in Molecular Detail
PublicationC99 is the C-terminal membrane-bound fragment of the amyloid precursor protein that is cleaved by γ-secretase to release Aβ peptides, the hallmark of Alzheimer’s disease (AD). Specific interactions of C99 with cholesterol have been proposed to underlie the recognized role of cholesterol in promoting amyloidogenesis. By using molecular dynamics simulations, we studied cholesterol binding to C99 in a lipid bilayer. We determined...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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Silo music — Mechanism of dynamic flow and structure interaction
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Silo music - mechanism of dynamic flow and structure interaction
PublicationArtykuł omawia zjawisko muzyki silosowej. Wykonano pomiary dynamiczne przyspieszeń, częstotliwości i postaci drgań własnych. Zaproponowano nowa hipotezę powstawania efektów dynamicznych podczas przepływu silosowego.
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Silo music - mechanism of dynamic flow and structure interaction
PublicationArtykuł omawia zjawisko muzyki silosowe. Wykonano pomiary dynamiczne przyspieszeń, częstotliwości i postaci drgań własnych. Zaproponowano nowa hipotezę powstawania efektów dynamicznych podczas przepływu silosowego.
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Anita Maria Dąbrowicz-Tlałka dr
PeopleAnita Dąbrowicz-Tlałka graduated from the Faculty of Mathematics and Physics at the University of Gdańsk with an outstanding grade, having written her thesis in the field of geometric topology. She concurrently obtained a diploma in Postgraduate Studies in the Basics of Computer Science at the University of Gdańsk. In 2001 she received a Ph.D. degree in mathematical studies at the Poznań University of Technology after defending...
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PHYSICAL MODELLING OF GEOTECHNICAL STRUCTURES IN PORTS AND OFFSHORE
PublicationThe physical modelling of subsoil behaviour and soil-structure interaction is essential for the proper design of offshore structures and port infrastructure. A brief introduction to such modelling of geoengineering problems is presented and some methods and experimental devices are described. The relationships between modelling scales are given. Some examples of penetration testing results in centrifuge and calibration chamber...
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FE analysis of support-specimen interaction of compressive experimental test
PublicationThe objective of this work is to investigate the support-specimen interaction during the compressive experimental testing of stiffened plates. The interaction is analyzed employing the nonlinear Finite Element Method using the commercial software ANSYS. The connection between the stiffened plate and testing supports is modelled with the use of contact elements, where several possible interaction scenarios are investigated, and...
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublicationMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
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The function and structure of entrance examination on faculty of architecture in Poland.
PublicationArtykuł prezentuje zastosowanie aksonometrii do oceny wyobraźni przestrzennej i pośrednio do selekcji kandydatów na Wydział Architektury. Na przykładzie kilku oryginalnych zadań wskazuje się na potrzebę prowadzenia ciągłej kontroli jakości zadań testowych. Jakościowe i ilościowe procedury służące do oceny zadań bazują na teorii pomiaru dydaktycznego i koncentrują się potwierdzeniu odpowiedniego poziomu rzetelności, trafności i...
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Food microstructure systems modelling regarding interaction and contact phenomena.
PublicationPrzedstawiono wybrane fragmenty teorii modelowania w strukturach rozproszonych mikrostruktury żywności, w których zostały uwzględnione wzajemne oddziaływania cząstek oraz występujące zjawiska kontaktowe. Do oszacowania tych oddziaływań wykorzystano zmodyfikowany przez autora model Buczkowskiego i Kleibera.
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublicationThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...