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Wyniki wyszukiwania dla: blended e-learning
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e-Commerce Websites and the Phenomenon of Dropshipping: Evaluation Criteria and Model
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Edu Inspiracje WZiE: Dlaczego porzucamy kursy e-learningowe?
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Higginsianins D and E, Cytotoxic Diterpenoids Produced by Colletotrichum higginsianum
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Problemy społeczeństwa informacyjnego w Polsce a program e-Europe+.
PublikacjaProblemy społeczeństwa informacyjnego w Polsce wiążą się ze słabą infrastrukturą teleinformatyczną, drogim i ograniczonym dostępem do Internetu oraz niewystarczająca wiedzą naszego społeczeństwa. Obszary wiejskie i małych miasteczek są permanentnie zaniedbywane w tworzeniu nowoczesnej infrastruktury teleinformatycznej.
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E-studium szansą dla MSP (małych , średnich przedsiębiorstw)
PublikacjaPodyplomowe studia jedno i dwusemestralne spelniają kryteria stawiane dla tego typu kształcenia menedzerów małych i średnich przedsiębiorstw (MSP).
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Problematyka zarządzania wiedzą w systemach typu e-health.
PublikacjaW rozdziale przedstawiono koncepcję systemu zarządzania wiedzą w ogólnodostępnym, wielofunkcyjnym systemie ukierunkowanym na różnorodne zastosowania związane z ochroną zdrowia. Koncepcja ta jest realizowana w zintegrowanym projekcie objętym 6. Programem Ramowym Unii Europejskiej. Zaprezentowano: miejsce zarządzania wiedzą w stosunku do innych części systemu, architekturę podsystemu zarządzania wiedzą oraz szczegółowo omówiono funkcje...
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Elementy analizy RAMS i cyklu życia napędów nowej generacji w układzie e-transformatora realizowanych w technologii SiC do elektrycznych zespołów trakcyjnych
PublikacjaTransport kolejowy podlega ciągłej presji, aby zwiększać dostępność połączeń i obniżać koszty przejazdów. Konstruktorzy pociągów i przewoźnicy, w odpowiedzi na stawiane oczekiwania, starają się wdrażać pojawiające się na rynku nowe innowacyjne rozwiązania. Europejski program Shift2Rail stawia ambitne cele w stosunku do kluczowych wskaźników wydajności (z ang. KPI - Key Performance Indicators) systemu kolejowego obejmującego infrastrukturę,...
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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublikacjaRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
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Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublikacjaThe Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublikacjaThis 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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IEEE 802.11 LAN capacity: incentives and incentive learning
PublikacjaMotywację 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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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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Learning from the often-forgotten Jan Heweliusz disaster
PublikacjaPrzedstawiono 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
PublikacjaArtykuł 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
PublikacjaPrzedstawiono 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
PublikacjaThe 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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Machine Learning Modelling and Feature Engineering in Seismology Experiment
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AGAR a Microbial Colony Dataset for Deep Learning Detection
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Scent emitting multimodal computer interface for learning enhancement
PublikacjaKomputerowy 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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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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Personal bankruptcy prediction using machine learning techniques
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Data Reduction Algorithm for Machine Learning and Data Mining
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Musical Instrument Identification Using Deep Learning Approach
PublikacjaThe work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related to musical instrument identification. It focuses on tasks performed, input type, algorithms employed, and metrics used. The paper starts with the background presentation, i.e., metadata...
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INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublikacjaThe 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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Transfer learning in imagined speech EEG-based BCIs
PublikacjaThe Brain–Computer Interfaces (BCI) based on electroencephalograms (EEG) are systems which aim is to provide a communication channel to any person with a computer, initially it was proposed to aid people with disabilities, but actually wider applications have been proposed. These devices allow to send messages or to control devices using the brain signals. There are different neuro-paradigms which evoke brain signals of interest...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublikacjaAutomatic 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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MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS
PublikacjaIn 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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Classifying Emotions in Film Music - A Deep Learning Approach
PublikacjaThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
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The use of machine learning for face regions detection in thermograms
PublikacjaThe 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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Endoscopy images classification with kernel based learning algorithms.
PublikacjaPrzedstawiono 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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Machine learning system for estimating the rhythmic salience of sounds.
PublikacjaW 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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In-situ Cu-doped MnCo-spinel coatings for solid oxide cell interconnects processed by electrophoretic deposition
PublikacjaThe Cu doping of the Mn–Co spinel is obtained “in-situ” by electrophoretic co-deposition of CuO and Mn1.5Co1.5O4 powders and subsequent two-step reactive sintering. Cu-doped Mn1.5Co1.5O4 coatings on Crofer22APU processed by electrophoretic co-deposition method are tested in terms of long term oxidation resistance and area specific resistance tests up to 3600 h. The introduction of Cu in the spinel lead to higher level of densification...
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Recent advances on spinel-based protective coatings for solid oxide cell metallic interconnects produced by electrophoretic deposition
PublikacjaThe application of ceramic protective coatings to the metallic interconnects in solid oxide cells (SOCs) is a viable and effective method to limit interconnect degradation issues. This featured letter provides a critical overview of the main outcomes of current research on the use of the electrophoretic deposition (EPD) technique to produce protective coatings for SOC metallic interconnects, specifically focusing on different approaches...
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Electrophoretic co-deposition of Fe2O3 and Mn1,5Co1,5O4: Processing and oxidation performance of Fe-doped Mn-Co coatings for solid oxide cell interconnects
PublikacjaThe “in-situ” Fe-doping of the manganese cobalt spinel was achieved by electrophoretic co-deposition of Mn1,5Co1,5O4 and Fe2O3 powders followed by a two-step reactive sintering treatment. The effects on the coating properties of two different Fe-doping levels (5 and 10 wt.% respectively) and two different temperatures of the reducing treatment (900 and 1000 °C) are discussed. Samples with Fe-doped coatings demonstrated a lower...
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Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublikacjaThis 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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Bending and buckling formulation of graphene sheets based on nonlocal simple first-order shear deformation theory
PublikacjaThis paper presents a formulation based on simple first-order shear deformation theory (S-FSDT) for large deflection and buckling of orthotropic single-layered graphene sheets (SLGSs). The S-FSDT has many advantages compared to the classical plate theory (CPT) and conventional FSDT such as needless of shear correction factor, containing less number of unknowns than the existing FSDT and strong similarities with the CPT. Governing...
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Effect of Chitosan Solution on Low-Cohesive Soil’s Shear Modulus G Determined through Resonant Column and Torsional Shearing Tests
PublikacjaIn this study the effect of using a biopolymer soil stabilizer on soil stiffness characteristics was investigated. Chitosan is a bio-waste material that is obtained by chemical treatment of chitin (a chemical component of fungi or crustaceans’ shells). Using chitosan solution as a soil stabilizer is based on the assumption that the biopolymer forms temporary bonds with soil particles. What is important is that these bonds are biodegradable,...
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Investigation of Wood Flour Size, Aspect Ratios, and Injection Molding Temperature on Mechanical Properties of Wood Flour/Polyethylene Composites
PublikacjaIn the present research, wood flour reinforced polyethylene polymer composites with a coupling agent were prepared by injection molding. The effects of wood flour size, aspect ratios, and mold injection temperature on the composites’ mechanical properties were investigated. For the preparation of the polymer composites, five different formulations were created. The mechanical properties including tensile strength and the modulus,...
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Unexpected Z/E isomerism of N-methyl-O-phosphothioyl benzohydroxamic acids, their oxyphilic reactivity and inertness to amines
PublikacjaThiophosphinoylation of N-methyl p-substituted benzohydroxamic acids using disulfanes (method A) or diphenylphosphinothioyl chloride (method B) provides only one conformer of the respective O-phosphothioyl derivative (Xray and NMR analysis). Undergoing the P-transamidoxylation reaction is an evidence of the reversibility of thiophosphinoylation. Only those products containing strong EWG substituents in the aroyl residue or bulky...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublikacjaDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublikacjaDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublikacjaMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublikacjaPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublikacjaSatellite 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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How does the Relationship Between the Mistakes Acceptance Component of Learning Culture and Tacit Knowledge-Sharing Drive Organizational Agility? Risk as a Moderator
PublikacjaChanges in the business context create the need to adjust organizational knowledge to new contexts to enable the organizational agile responses to secure competitiveness. Tacit knowledge is strongly contextual. This study is based on the assumption that business context determines tacit knowledge creation and acquisition, and thanks to this, the tacit knowledge-sharing processes support agility. Therefore, this study aims to expose...
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Magnetic anisotropy and structural flexibility in the f ield-induced single ion magnets [Co{(OPPh2) (EPPh2)N}2], E = S, Se, explored by experimental and computational methods
PublikacjaDuring the last few years, a large number of mononuclear Co(II) complexes of various coordination geometries have been explored as potential single ion magnets (SIMs). In the work presented herein, the Co(II) S = 3/2 tetrahedral [Co{(OPPh2)(EPPh2)N}2], E = S, Se, complexes (abbreviated as CoO2E2), bearing chalcogenated mixed donor-atom imidodiphosphinato ligands, were studied by both experimental and computational techniques. Specifically,...
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Structure redetermination, transport and thermal properties of the YNi3Al9 compound
PublikacjaSingle crystals of completely ordered variant of the YNi3Al9 compound were grown by self-flux method with excess of aluminum. The crystal structure of the title compound was redetermined from single crystal X-ray diffraction data. The structure adopts ErNi3Al9 type, space group R32, parameters of the unit cell a = 7.2838(2) Å, c = 27.4004(8) Å. The growth of relatively large single crystals of the YNi3Al9 compound, having completely...
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublikacjaPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...