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Wyniki wyszukiwania dla: LEARNING
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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 Modelling and Feature Engineering in Seismology Experiment
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Machine learning applied to bi-heterocyclic drugs recognition
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AGAR a Microbial Colony Dataset for Deep Learning Detection
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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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Personal bankruptcy prediction using machine learning techniques
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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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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–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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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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Raw data of AuAg nanoalloy plasmon resonances used for machine learning method
Dane BadawczeRaw data used for machine learning process. UV-vis measurements of AuAg alloyed nanostructures created from thin films. Plasmonic band position dependence on fabrication parameters. Small presentation reviewing achieved structures and their properties.
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Model of distributed learning objects repository for a heterogenic internet environment
PublikacjaW artykule wprowadzono pojęcie komponentu edukacyjnego jako rozszerzenie obiektu edukacyjnego o elementy zachowania (metody). Zaproponowane podejście jest zgodne z paradygmatem obiektowym. W oparciu o komponent edukacyjny zaprojektowano model budowy repozytorium materiałów edukacyjnych. Model ten jest oparty o usługi sieciowe i rejestry UDDI. Komponent edukacyjny oraz model repozytorium mogą znaleźć zastosowanie w konstrukcji zbiorów...
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Machine Learning in Multi-Agent Systems using Associative Arrays
PublikacjaIn 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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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublikacjaTo 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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Analysis of Learning Outcomes in Medical Education with the Use of Fuzzy Logic
PublikacjaThe 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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Employing Blended E-Learning to Improve Rate of Assignments Handing-In
PublikacjaIt has been observed that students hand in homework assignments at a notably low rate in introductory C programming course. A survey has revealed that the real issue was not student learning but instructor work organization. Based on survey results, the physical course has been complemented with an e-learning component to guide the homework process. Assignment handing-in rate significantly improved, as e-learning allowed the homework...
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Breast MRI segmentation by deep learning: key gaps and challenges
PublikacjaBreast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...
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Processes of enhancing the intelligence of Learning Organizations on the basis of Competence Centers
PublikacjaThe process of organizational learning and proper knowledge management became today one of the major challenges for the organization acting in the knowledge-based economy. According to the observations of the authors of this paper the demand for formalization of knowledge management processes and organizational learning is particularly evident in research institutions, established either by the universities, or the companies. The...
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Designing acoustic scattering elements using machine learning methods
PublikacjaIn 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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Data augmentation for improving deep learning in image classification problem
PublikacjaThese 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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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublikacjaThis 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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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublikacjaWe 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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Organizational Wisdom: The Impact of Organizational Learning on the Absorptive Capacity of an Enterprise
PublikacjaPurpose: 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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Divide and not forget: Ensemble of selectively trained experts in Continual Learning
PublikacjaClass-incremental learning is becoming more popular as it helps models widen their applicability while not forgetting what they already know. A trend in this area is to use a mixture-of-expert technique, where different models work together to solve the task. However, the experts are usually trained all at once using whole task data, which makes them all prone to forgetting and increasing computational burden. To address this limitation,...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe 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 applied to acoustic-based road traffic monitoring
PublikacjaThe 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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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublikacjaMusic 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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Antenna Optimization Using Machine Learning with Reduced-Dimensionality Surrogates
PublikacjaIn modern times, antenna design has become more demanding than ever. The escalating requirements for performance and functionality drive the development of intricately structured antennas, where parameters must be meticulously adjusted to achieve peak performance. Often, global adjustments to geometry are necessary for optimal results. However, direct manipulation of antenna responses evaluated with full-wave electromagnetic (EM)...
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Noise profiling for speech enhancement employing machine learning models
PublikacjaThis 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-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-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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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublikacjaLiquid 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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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-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...
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Deep learning-based waste detection in natural and urban environments
PublikacjaWaste 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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Playback detection using machine learning with spectrogram features approach
PublikacjaThis 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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Becoming a Learning Organization Through Dynamic Business Process Management
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Employing a biofeedback method based on hemispheric synchronization in effective learning
PublikacjaIn 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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Didaktische simulationsmodelle fur E-learning in der IK-ausbildung.
PublikacjaPrzedstawiono dydaktyczne modele symulacyjne wykorzystywane w zdalnym kształceniu z zakresu informatyki i technik komunikacyjnych. Pokazano na przykładach zbudowanych symulatorów, w jaki sposób zrealizować lub dostosować modele symulacyjne do zdalnego nauczania. Opisano doświadczenia autorów w wykorzystaniu modeli symulacyjnych w zdalnym nauczaniu.
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Agent-Based Population Learning Algorithm for RBF Network Tuning
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An A-Team Approach to Learning Classifiers from Distributed Data Sources
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An A-Team approach to learning classifiers from distributed data sources
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Beyond Traditional Learning: The LLM Revolution in BPM Education at University
PublikacjaLarge Language Models (LLMs) significantly impact higher education, requiring changes in educational processes, especially in Business Process Management (BPM) practical exercises. The research aims to evaluate the effectiveness of LLMs in BPM education to determine if LLMs can supplement educators. The study involved 33 master’s degree students. Students’ works were manually evaluated and compared to LLM-generated responses. Results...
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Digital competence learning in secondary adult education in Finland and Poland
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