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Wyniki wyszukiwania dla: AFFECTIVE LEARNING
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Psychometric properties of the polish version of the job-related affective well-being scale
PublikacjaObjectives: The aim of this study was to verify psychometric properties of the Polish version of the Job-related Affective Well-being Scale (JAWS). Specifically, theoretical 4-factor structure (based on the dimensions of pleasure and arousal) and reliability of the original – 20-item JAWS (van Katwyk et al., 2000) and the shortened – 12-item (Schaufeli and Van Rhenen, 2006) versions were tested. Material and Methods: Two independent...
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Evaluation of affective intervention process in development of affect-aware educational video games
PublikacjaIn this paper initial experiences are presented on implementing specific methodology of affective intervention design (AFFINT) for development of affect-aware educational video games. In the described experiment, 10 student teams are to develop affect-aware educational video games using AFFINT to formalize the whole process. Although all projects are still in progress, first observations and conclusions may already be presented.
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Analysis of the instantaneous power signal for bearing diagnostics -bearing damaged
Dane BadawczeThe attached dataset contains the measurement results of the instantaneous values of current and voltage, recorded during the diagnostics of a damaged bearing. Bearing diagnostics can be carried out based on the method, which relies on the measurement and analysis of the variability of the signal instantaneous power, defined as the product of instantaneous...
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Analysis of the instantaneous power signal for bearing diagnostics - bearing undamaged
Dane BadawczeThe attached dataset contains the measurement results of the instantaneous values of current and voltage, recorded during the diagnostics of an undamaged bearing. Bearing diagnostics can be carried out based on the method, which relies on the measurement and analysis of the variability of the signal instantaneous power, defined as the product of instantaneous...
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Factors Affecting the Rheological Properties of Foods
PublikacjaIn this chapter, engineering aspects concerning real body mechanics and the impact of respective food ingredients on said properties are presented together. Food is a complex matrix and each of macro and micro ingredients plays its role in the formation of rheologic properties, and minor changes in the basic ingredient structure may affect the change of these properties significantly. Basic analytic techniques are presented for...
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Factors affecting the quality of bottled water
PublikacjaThe ever-increasing popularity of bottled water means that it is important to analyze not only its mineral content but also, above all,its content of possible contaminants, especially the organic ones. In this respect, bottled waters are a special case, because apartfrom organic chemical contaminants derived from the well from which they were acquired, their secondary contamination is alwayspossible, during treatment or storage...
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Applicability of phenolic acids as effective enhancers of cocrystals solubility of methylxanthines
PublikacjaApplicability of phenolic acids as potential cocrystal formers for methylxanthine derivatives was analyzed both in terms of cocrystallization probabilities and solubility advantage. The cocrystal formation abilities were evaluated using mixing enthalpy estimated within the conductor like screening model for real solvents (COSMO-RS) framework. The solubility improvement of potential cocrystals was estimated by formulation of the...
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Effective Drug Concentration and Selectivity Depends on Fraction of Primitive Cells
PublikacjaPoor efficiency of chemotherapeutics in the eradication of Cancer Stem Cells (CSCs) has been driving the search for more active and specific compounds. In this work, we show how cell density-dependent stage culture profiles can be used in drug development workflows to achieve more robust drug activity (IC50 and EC50) results. Using flow cytometry and light microscopy, we characterized the cytological stage profiles of the HL-60-,...
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Analysis and evaluation of grouping methods for effective cutting tool operation
PublikacjaThis article presents the possibilities for using cluster analysis in the assignment of machine tools in automated manufacturing systems. Based on the similarity of manufacturing processes in the system, cutting tools have been grouped. The objective was to obtain groups of similar objects, which could potentially ensure the reduction of the frequency and time of setups, optimizing the maintenance of tool resources and improving...
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W-SBA-15 as an Effective Catalyst for the Epoxidation of 1,5,9-Cyclododecatriene
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On effective properties of beam-lattice structures made of flexoelectric materials
PublikacjaThe e-Workshop Advances in ELAstoDYNamics of architected materials and BIOmaterials International Research Project (IRP) Coss&Vita of the CNRS
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THE COST-EFFECTIVE AND GEOTECHNIC SAFELY BUILDINGS ON THE AREAS WITH MINE EXPLOITATION
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Chitosan-Based Nanoparticles as Effective Drug Delivery Systems—A review
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The Effect of Effective Microorganisms on the Quality of Potato Chips and French Fries
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Effective and environmental friendly propulsion system for small fishing cutter
PublikacjaW pracy przedstawiono opis systemu napędowego małego kutra rybackiego oraz układ napędu i sterowania hydraulicznego wszystkich istotnych jego urządzeń. Zaprezentowany system stosunkowo nowoczesny i efektywny, a przy tym ekologiczny został zainstalowany na małym kutrze rybackim zaprojektowanym na Wydziale Oceanotechniki i Okrętownictwa Politechniki Gdańskiej. We wrześniu 2002 roku kuter rozpoczął regularne połowy na Bałtyku i jak...
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Applicability of an effective conductivity approach in modeling thoracic impedance changes
PublikacjaThis paper describes numerical simulations of the influence of conductivity changes inside a volume conductor on impedance changes measured on its surface. A simple model based on the finite element method has been developed to estimate an applicability of the effective conductivity theory in human chest modeling. The model consisted of a cylinder with two concentric spheres inside. Simulations were performed for two cases: first...
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Proposal of a method for effective tasks distribution in the execution of compolex problems
PublikacjaAn access to a great number of various services allows for decomposition of complex problems into smaller and less complex tasks. Those tasks can be presented in a form of a dependency graph. This paper shows an idea of executing such a problem using cooperating autonomous agents. Main focus of this work is cooperation covering effective tasks distribution among executors. This paper presents an algorithm for dynamic executor selection...
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Cost Effective Corrosion and Fatigue Monitoring for Marine Transport Products
PublikacjaW artykule omówiono genezę i główne założenia projektu badawczego "Cost Effective Corrosion and Fatigue Monitoring for Transport Products'' o kryptonimie CORFAT, realizowanego w ramach VII Programu Ramowego Unii Europejskiej. Przedstawiono cele i metodykę badań, zalety nowej nowej metodyki monitorowania statków, zadania projektu, zalety i ograniczenia metody Emisji Akustycznej (EA), opis innych metod badań nieniszczących (NNDT)....
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Vident-real: an intra-oral video dataset for multi-task learning
Dane BadawczeWe introduce Vident-real, a large dataset of 100 video sequences of intra-oral scenes from real conservative dental treatments performed at the Medical University of Gdańsk, Poland. The dataset can be used for multi-task learning methods including:
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Effect of the 5-HTTLPR polymorphism on affective temperament, depression and body mass index in obesity
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Becoming a Learning Organization Through Dynamic Business Process Management
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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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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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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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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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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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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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Digital competence learning in secondary adult education in Finland and Poland
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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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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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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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Deep learning-based waste detection in natural and urban environments
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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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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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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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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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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 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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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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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...