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Wyniki wyszukiwania dla: FEDERATED LEARNING
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Social Learning in Cluster Organizations and Accumulation of Technological Capability
PublikacjaThe purpose of the paper is to present how members of cluster organizations perceive their role in the accumulation of technological capability through social learning. The paper presents the results of a qualitative study of four cluster organizations. The theoretical foundation of the study are the communities of practice and the organizational inertia theories. The study indicates that the dynamics of technological capability...
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Training of Deep Learning Models Using Synthetic Datasets
PublikacjaIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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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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Detecting Lombard Speech Using Deep Learning Approach
PublikacjaRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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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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An application of blended and collaborative learning in spatial planning course
PublikacjaSpatial Planning is a master course for graduate students of Environmental Engineering. The course is based on assumptions that students’ future work will be connected with spatial planning, and spatial issues will have an influence on their everyday lives. To familiarize students with environmental issues in planning, the teams of students get an assignment to design an urban space, waterfront along a stream. The whole project...
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How Machine Learning Contributes to Solve Acoustical Problems
PublikacjaMachine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task...
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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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Learning from Mistakes. A Study on Maturity and Adaptability to Change
PublikacjaLearning culture matters; company culture must support continuous improvement. Organizational learning is a process of identifying and modifying mistakes that result from interactions between co-workers. The article aims to explore the learning power via errors, using the level of organizational maturity as a moderator. Companies need to know how organizational maturity may moderate the adaptability to change via the acceptance...
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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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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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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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Balance error generated by numerical diffusion in the solution of Muskingum equation
PublikacjaIn the paper the conservative properties of the lumped hydrological models with variable parameters are discussed. It is shown that in the case of the non-linear Muskingum equation the mass balance is not satisfied. The study indicates that the mass balance errors are caused by the improper form of equation and by the numerical diffusion which is generated in the solution. It has been shown that the classical way of derivation...
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The Method of reduction of aerodynamic forces generated in turbine blade seals
PublikacjaThe distibution of pressure in the seal gaps does not only affect the so called '' leakage losses'' and the turbine stage overall efficiency but also plays an important role in the generation of aerodynamic forces which may cause self-excited rotor vibrations. The paper describes a chamber seal applied for the reduction of the aerodynamic forces created in shroud seals. This kind of turbine seal was patented and tested.
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The Method of Reduction of Aerodynamic Forces Generated in Turbine Blade Seals
PublikacjaOpisano metodę zmniejszania sił wymuszających drgania aerodynamiczne poprzez zastosowanie nowego uszczelnienia nadbandażowego typu komorowego. Efektywność stosowania uszczelnienia komorowego potwierdzono obliczeniami numerycznymi i badaniami eksperymentalnymi.
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Some aspects of noise generated by a small ship in the shallow sea
PublikacjaThe passing and underwater moving objects produce the noises of variable intensity, which significantly increase the overall level of noise in the sea. This applies to both the sonic and ultrasonic range. The excessive levels of underwater noise adversely affects the so-called underwater acoustic climate and is the reason why this phenomenon is intensively investigated from the number of years. The results of experimental work...
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Energy Yield Generated by a Small Building Integrated Photovoltaic Installation
PublikacjaIn the recent years photovoltaic (PV) industry has experienced a major growth, caused by the ever present annual decrease in module production prices and the expanding awareness of the general public in terms of renewable energy. There are numerous ways to implement PV modules as an additional energy source for a building, be it mounted on the rooftop, or building integrated (BIPV). An analysis of BIPV consisting of 8 modules with...
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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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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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Becoming a Learning Organization Through Dynamic Business Process Management
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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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Digital competence learning in secondary adult education in Finland and Poland
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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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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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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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Deep learning-based waste detection in natural and urban environments
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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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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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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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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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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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Building the Learning Environment for Sustainable Development: a Co-creation approach
PublikacjaEducation for sustainable development supports the improvement of knowledge, skills, attitudes and behaviors related to global challenges such as climate change, global warming and environmental degradation, among others. It is increasingly taking place through projects based on information and communication technologies. The effectiveness of the actions taken depends not only on the quality of the project activities or the...
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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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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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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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The detection of Alternaria solani infection on tomatoes using ensemble learning
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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 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-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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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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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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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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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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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...