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Wyniki wyszukiwania dla: KNOWLEDGE CULTURE, KNOWLEDGE SHARING, KNOWLEDGE HIDING, LEARNING CULTURE, MISTAKES ACCEPTANCE, LEARNING CLIMATE, HUMAN CAPITAL
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TEACHING AND LEARNING IN MEDICINE
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublikacjaDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
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Baltic Sea climate fever. Creative solutions for waterfront cities in the context of climate change
PublikacjaThe goal of the research is to recognize climate change impact on Baltic Sea cities and description of strengths and weaknesses of cities strategies and activities. The range of research has been limited to 3 cities in the Baltic Sea (Copenhagen, Gothenburg, Tallinn) and Tricity as an area for which recommendations will be proposed actions in the field of adaptation to climate change. Recommendations for Tricity as a unique group...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublikacjaAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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A learning community model: the Center for Innovative Education supporting academic didactics at Gdańsk University of Technology, Poland
PublikacjaThe current digital transformation requires academics to apply their pedagogical and technological skills to their teaching and professional development to address the newly emerging needs of the digital era. This study aims to analyse the operating model of the Center for Innovative Education (CIE) at Gdańsk University of Technology (Gdańsk Tech), Poland, as an incubator for professional development of academic staff at Gdańsk...
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Adapting education to a changing climate: preparing architecture students for climate-resilient design
PublikacjaIn this article, the authors explore the connection between climate change and the fields of architecture and urban planning. With the increasing frequency of flooding and extreme weather events, the built environment is confronting challenges in terms of sustainability and resilience. To meet these problems, it is necessary to prepare various specialists to assume responsibility for making future decisions. The authors of this...
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Venture capital w finansowaniu rozwoju przedsiębiorstwa
PublikacjaW różnych fazach rozwoju, przedsiębiorstwa korzystają z wielu rodzajów źródeł finansowania. Wybór konkretnej formy finansowania, kapitału własnego czy obcego, źródła długo lub krótkoterminowego, zależy od wielu istotnych dla przedsiębiorstwa czynników. Korzystanie z venture capital związane jest często z brakiem możliwości pozyskania kapitału z innego źródła. Opracowanie omawia proces inwestycyjny w funduszach venture capital,...
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Artemisia abrotanum L. (Southern Wormwood)—History, Current Knowledge on the Chemistry, Biological Activity, Traditional Use and Possible New Pharmaceutical and Cosmetological Applications
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Oral Health-Related Knowledge, Attitudes and Behaviours of Arab Dental Students: Multi-National Cross-Sectional Study and Literature Analysis 2000–2020
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Crossroad between current knowledge and new perspective of diagnostic and therapy of late-onset schizophrenia and very late-onset schizophrenia-like psychosis: An update
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An Adversarial Machine Learning Approach on Securing Large Language Model with Vigil, an Open-Source Initiative
PublikacjaSeveral security concerns and efforts to breach system security and prompt safety concerns have been brought to light as a result of the expanding use of LLMs. These vulnerabilities are evident and LLM models have been showing many signs of hallucination, repetitive content generation, and biases, which makes them vulnerable to malicious prompts that raise substantial concerns in regard to the dependability and efficiency of such...
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Iterative learning approach to active noise control of highly autocorrelated signals with applications to machinery noise
PublikacjaThis paper discusses the design and application of iterative learning control (ILC) and repetitive control (RC) for high modal density systems. Typical examples of these systems are structural and acoustical systems considered in active structural acoustic control (ASAC) and active noise control (ANC) applications. The application of traditional ILC and RC design techniques, which are based on a parametric system model, on systems...
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Fluctuation-enhanced sensing of organic solvent vapors mixture by machine learning
Dane BadawczeThe data set consists of exemplary results of the product of voltage noise power spectral density S(f) multiplied by frequency f and normalized to squared DC voltage U^2 recorded in the graphene back-gated Field Effect Transistor under UV light assistance (275 nm) in the selected ambient atmospheres (Figure 3) and the results of gas detection by SVM...
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A Case Study of Electric Vehicles Load Forecasting in Residential Sector Using Machine Learning Techniques
PublikacjaElectric vehicles (EVs) have been widely adopted to prevent global warming in recent years. The higher installation of Level-1 and Level-2 chargers in residential areas soon poses challenges to the distributed network. However, such challenges can be mitigated through the adoption of smart charging or controlled charging schemes. To facilitate the implementation of smart charging, accurate forecasting of EV charging demand in residential...
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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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Reversible Data Hiding in Encrypted DICOM Images Using Cyclic Binary Golay (23, 12) Code
PublikacjaIn this paper, a novel reversible data hiding method for encrypted images (RDHEI) is proposed. An efficient coding scheme based on cyclic binary Golay (23, 12) code is designed to embed additional data into the least significant bits (LSBs) of the encrypted image. The most significant bits (MSBs) are used to ensure the reversibility of the embedding process. The proposed scheme is lossless, and based on the receiver’s privileges,...
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Olgun Aydin dr
OsobyOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Principal Machine Learning Engineer in Nike, and works as Assistant Professor in Gdansk University of Technology in Poland. Dr. Aydin is part of editorial board of "Journal of Artificial Intelligence and Data Science" Dr. Aydin served as Vice-Chairman of Why R? Foundation and is member of Polish Artificial Intelligence Society. Olgun is...
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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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Determination of cytotoxic activity of new bisacridines IKE18, IKE19, IKE21 and IE10 against human kidney HEK-293 (ATCC® CRL-1573™) and liver cells HEPG2 (ATCC® HB-8065™)
Dane BadawczeThe datasets contain the results of determining in vitro cytotoxic activity of compounds using human cell lines assessed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, a method that evaluates cell viability by measuring cellular oxidoreductase activity. Initially, cells were seeded in 96-well culture plates and allowed...
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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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Machine learning applied to bi-heterocyclic drugs recognition
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Personal bankruptcy prediction using machine learning techniques
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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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Data Reduction Algorithm for Machine Learning and Data Mining
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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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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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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 Modelling and Feature Engineering in Seismology Experiment
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AGAR a Microbial Colony Dataset for Deep Learning Detection
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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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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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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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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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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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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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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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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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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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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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E-learning w małych i średnich przedsiębiorstwach
PublikacjaW rozdziale przedstawiono podstawowych zagadnienia e-learningu w małych i średnich przedsiębiorstwach oraz przykłady realizowanych projektów.
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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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E-learning course "International comparative studies on SMEs"
PublikacjaProjekt 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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Precise Identification of Different Cervical Intraepithelial Neoplasia (CIN) Stages, Using Biomedical Engineering Combined with Data Mining and Machine Learning
PublikacjaCervical cancer (CC) is one of the most common female cancers worldwide. It remains a significant global health challenge, particularly affecting women in diverse regions. The pivotal role of human papillomavirus (HPV) infection in cervical carcinogenesis underscores the critical importance of diagnostic strategies targeting both HPV infection and cervical...
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A novel experimental approach for studying life-history traits of phytophagous arthropods utilizing an artificial culture medium
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The Co-Culture of Staphylococcal Biofilm and Fibroblast Cell Line: The Correlation of Biological Phenomena with Metabolic NMR1 Footprint
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267: Mesenchymal cells regulate growth of intestinal crypts by a Wnt independent mechanism in 3D culture system
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Comparison of 2D and 3D culture models in the studies of the biological response induced by unsymmetrical bisacridines in cancer cells
PublikacjaMulticellular tumor spheroids are a good tool for testing new anticancer drugs, including those that may target cancer stem cells (CSCs), responsible for cancer progression, metastasis, and recurrence. Therefore, following the initial evaluation of the impact of antitumor unsymmetrical bisacridines (UAs) on lung and colon cancer cells using traditional monolayer cultures, I extended my investigations and applied the spherical model....