Search results for: human learning
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Deep learning-based waste detection in natural and urban environments
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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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The detection of Alternaria solani infection on tomatoes using ensemble learning
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Scheduling Repetitive Construction Processes Using the Learning-Forgetting Theory
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Generation of microbial colonies dataset with deep learning style transfer
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Meta-Design and the Triple Learning Organization in Architectural Design Process
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Didaktische simulationsmodelle fur E-learning in der IK-ausbildung.
PublicationPrzedstawiono 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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Processes of enhancing the intelligence of Learning Organizations on the basis of Competence Centers
PublicationThe 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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Divide and not forget: Ensemble of selectively trained experts in Continual Learning
PublicationClass-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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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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Breast MRI segmentation by deep learning: key gaps and challenges
PublicationBreast 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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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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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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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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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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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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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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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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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublicationRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Leadership, culture, intellectual capital and knowledge processes for organizational innovativeness across industries: the case of Poland
PublicationPurpose – This study aims to present the overview of intellectual capital creation micro-mechanisms concerning formal and informal knowledge processes. The organizational culture, transformational leadership and innovativeness are also included in the investigation as ascendants and consequences of the focal relation of intellectual capital and knowledge processes. Design/methodology/approach – Based on a sample of 1,418 Polish...
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Jacek Rumiński prof. dr hab. inż.
PeopleWykształcenie i kariera zawodowa 2022 2016 2002 1995 1991-1995 Tytuł profesora Habilitacja Doktor nauk technicznych Magister inżynier Prezydent RP, dziedzina nauk inżynieryjno-technicznych, dyscyplina: inzyniera biomedyczna Politechnika Gdańska, Biocybernetyka i inżyniera biomedyczna, tematyka: „Metody wyodrębniania sygnałów i parametrów z różnomodalnych sekwencji obrazów dla potrzeb diagnostyki i wspomagania...
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A Prototype of Educational Agent in Distance Learning Environment - Virtual Student Assistant
PublicationW zdalnym nauczaniu pojawia się wiele systemów wspierających, z których niezwykle ciekawym przykładem są agenty edukacyjne. Wśród wielu rodzajów agentów edukacyjnych wyróżnia się osobistych asystentów, których rolą jest organizacyjna pomoc osobie zdobywającej wiedzę. Artykuł jest poświęcony zaimplementowanemu na Wydziale ETI Politechniki Gdańskiej prototypowi agenta edukacyjnego o nazwie WAS (Wirtualny Asystent Studenta). Pokazana...
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Modular machine learning system for training object detection algorithms on a supercomputer
PublicationW pracy zaprezentowano architekturę systemu służącego do tworzenia algorytmów wykorzystujących metodę AdaBoost i służących do wykrywania obiektów (np. twarzy) na obrazach. System został podzielony na wyspecjalizowane moduły w celu umożliwienia łatwej rozbudowy i efektywnego zrównoleglenia implementacji przeznaczonej dla superkomputera. Na przykład, system może być rozszerzony o nowe cechy i algorytmy ich ekstrakcji bez konieczności...
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Reward Learning Requires Activity of Matrix Metalloproteinase-9 in the Central Amygdala
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Efficient sampling of high-energy states by machine learning force fields
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Beesybees-Agent-Based, Adaptive & Learning Workflow Execution Module for BeesyCluster
PublicationPrezentujemy projekt oraz implementację adaptacyjnego i uczącego się modułu przeznaczonego dowykonywania scenariuszy w środowisku BeesyCluster. BeesyCluster pozwala na modelowaniescenariuszy w formie acyklicznego grafu skierowanego, w którym wierzchołki oznaczają zadania,a krawędzie określają zależności między nimi. Przedstawiamy także kooperatywne wykonaniescenariusza przez grupę agentów zdolnych do zbierania, składowania i korzystania...
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Stacking and rotation-based technique for machine learning classification with data reduction
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Designing RBF Networks Using the Agent-Based Population Learning Algorithm
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POPULATION-BASED MULTI-AGENT APPROACH TO SOLVING MACHINE LEARNING PROBLEMS
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Learning from Imbalanced Data Using Over-Sampling and the Firefly Algorithm
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Deep learning approach for delamination identification using animation of Lamb waves
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Deep learning super-resolution for the reconstruction of full wavefield of Lamb waves
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OmicSelector: automatic feature selection and deep learning modeling for omic experiments
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Measurement of the Development of a Learning IT Organization Supported by a Model of Knowledge Acquisition and Processing
PublicationThe paper presents a model of knowledge acquisition and processing for the development of learning organizations. The theory of a learning organization provides neither metrics nor tools to measure its development The authors' studies in this field are based on their experience gathered after projects realized in real IT organizations. The authors have described the construction of the model and the methods of its verification...
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Loosely-Tied Distributed Architecture for Highly Scalable E-Learning System
PublicationVast majority of modern e-learning products are based on client-server architecture and utilization of web-based technologies (WBT). Such approach permits easy creation of e-learning systems that do not require a complex, operating system dependant client software. Unfortunately there are also drawbacks of such solution. Because of the majority of mechanisms are located on the server, its usage levels trend to build up quickly...
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E-learning - prawdziwa czy fikcyjna koncepcja edukacyjnego rozwoju uczelni
PublicationNie można zaprzeczyć, że wykorzystanie narzędzi multimedialnych oraz Internetu pozwala na dodanie istotnych, z punku widzenia dydaktyki, komponentów edukacyjnych tworzących kompetencje i umiejętności zawodowe, a także te czysto akademickie. Trzeba rozważyć, czy wszystkie strony procesu dydaktycznego na uczelni są przygotowane do e−learningu. Oczywistym wymogiem jest posiadanie odpowiedniej bazy sprzętowej i przygotowanej kadry...
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Limitations of Emotion Recognition from Facial Expressions in e-Learning Context
PublicationThe paper concerns technology of automatic emotion recognition applied in e-learning environment. During a study of e-learning process the authors applied facial expressions observation via multiple video cameras. Preliminary analysis of the facial expressions using automatic emotion recognition tools revealed several unexpected results, including unavailability of recognition due to face coverage and significant inconsistency...
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Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publicationconvolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...
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IT support for OKNO broadband Internet-based distant learning system at WUT
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Analysis of network infrastructure and QoS requirements for modern remote learning systems.
PublicationW referacie przedstawiono różne modele zdalnego nauczania. Podjęto próbę oceny wymagań nakładanych na infrastrukturę sieci. Ponadto przedstawiono mechanizmy QoS spotykane w sieciach teleinformatycznych oraz dokonano oceny możliwości ich współpracy w systemach edukacji zdalnej
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Developing ICT-rich lifelong learning opportunities trough EU-projects.
PublicationArtykuł opisuje doświadczenia Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej od 1997 roku we wdrażaniu kształcenia na odległość. Głównym zadaniem CEN PG jest tworzenie dostępu do materiałów, skryptów, kursów i środowiska internetowego w sieciach LAN i WAN. Udostępniane moduły kursowe zostały opracowane głównie w międzynarodowych zespołach projektowych w wyniku realizowanych unijnych programów Leonardo da Vinci, Socrates...
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Bimodal deep learning model for subjectively enhanced emotion classification in films
PublicationThis research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....
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Modeling lignin extraction with ionic liquids using machine learning approach
PublicationLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublicationThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublicationIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublicationThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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A Note on Knowledge Management Education: Towards Implementing Active Learning Methods
PublicationKnowledge Management as an area of education is still a big challenge for teachers and practitioners. Nevertheless, there are several useful teaching methods in active education, especially oriented towards courses where innovation and delivering dynamic knowledge are critical. The goal of the paper is to present and discuss criteria relevant in the selection of active educational methods supporting knowledge management courses....