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Wyniki wyszukiwania dla: HEARING IMPAIRED
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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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Security of export transactions in the offer of leading banks on the Polish market
PublikacjaThe following article presents the so-called conditioned payment methods, i.e. instruments for securing export transactions, such as letter of credit, documentary collection, bank guarantees, factoring and forfaiting. The characteristics of each particular method are presented as well as the transactions using them are described. In the following paper, the author included also the leading Polish banks, which offer the above- mentioned...
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Becoming a Learning Organization Through Dynamic Business Process Management
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Sealing tax collection in Poland and the EU in the years 2008–2018
PublikacjaThe purpose of this study is to present issues related to sealing tax collection system in Poland and European Union countries as well as OECD members in 2008–2018. The article is divided into four parts, which include: introduction, origin of the problem, implemented solutions and conclusions. It presents the results of the conducted analysis including studies of the literature and empirical data (mainly from OECD, GUS—Polish...
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The detection of Alternaria solani infection on tomatoes using ensemble learning
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The Comparison of the Web GIS Applications Relevant for 4D Models Sharing
PublikacjaThe paper presents results of the project: Cultural Heritage Through Time (CHT 2, http://cht2-project.eu) realized accomplished within the framework of the “Joint Programming Initiative in Cultural Heritage” JPI-CH (http://www.jpi-culturalheritage.eu) by an international consortium: Politecnico di Milano (IT), Newcastle University (UK), Salamanca University (ES), and Stanislaw Staszic Scientific Association SSSA (a non-profit...
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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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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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Leasing i jego gospodarcze zastosowanie w warunkach zmian
PublikacjaArtykuł omawia prawne regulacje leasingu oraz wskazuje na zainteresowanie tą formą finansowania działalności polskich przesiębiorstw i jednostek samorządu terytorialnego. W jego tekście zawarte są także aspekty odzwierciedlające przebieg umowy leasingowej oraz odniesienie do podatkowych skutkow z nią związanych.
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The Tourism Sector’s Development and Popularization of Sharing Economy. The Impact on Cooperation
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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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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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Experimental Investigation of Prototype Water-Lubricated Compliant Foil Bearings
PublikacjaPraca zawiera wyniki badań doświadczalnych prototypowego łożyska foliowego smarowanego wodą. Łożyska tego typu mogą mieć zastosowanie w węzłach, od których wymaga się ekologicznego środka smarowego, np. pompy wodne czy turbiny wodne. W opracowaniu zademonstrowano wyniki badań trzech prototypowych poprzecznych łożysk foliowych. Opisano napotkane problemy badań oraz wprowadzonych do konstrukcji łożyska zmian, których celem była poprawa...
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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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Improving performance of large thrust bearings through modeling and experimentation
PublikacjaLarge thrust bearings are highly loaded machine elements and their failures cause serious losses. Start ups and stoppages of the bearing under load are specially critical regimes of operation. Load carrying capacity depends on the profile of the oil gap. In transient states this profile is also changing. In the design of large thrust bearings minimizing thermo-elastic deformations is an important goal, which can be accomplished...
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Behaviour of Asymmetric Structure with Base Isolation Made of Polymeric Bearings
PublikacjaEarthquake-induced ground motions are the most severe and unpredictable threats to the structures all around the world. Seismic excitations cause a lot of damage in a wide variety of ways, leaving thousands of casualties in their wake. Due to randomness of earthquake occurrence, lack of visible causes and their power of destructiveness, structural engineers need to develop new technical solutions and protection systems against...
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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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Behaviour of asymmetric structures with base isolation made of Polymeric Bearings
PublikacjaEarthquake-induced ground motions are the most severe and unpredictable threats to the structures all around the world. Seismic excitations cause a lot of damage in a wide variety of ways, leaving thousands of casualties in their wake. During the last few years alone, the world has witnessed many major earthquakes, five of which have caused far-reaching consequences of a national scale for Haiti (January 2010), Chile (February...
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Data Model Development for Security Information Sharing in Smart Grids
PublikacjaThe smart grid raises new security concerns which require novel solutions. It is commonly agreed that to protect the grid, the effective collaboration and information sharing between the relevant stakeholders is prerequisite. Developing a security information sharing platform for the smart grid is a new research direction which poses several challenges related to the highly distributed and heterogeneous character of the grid. In...
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Selected problems of experimental investigation of dynamically loaded journal bearings
PublikacjaIn the paper some problems concerning relations between external bearing loadings and critical lining stresses are described for test stand with rotating load vector. According to the standard ISO 7905/1 this type of test stand, for dynamically loaded slide bearing, is recommended as a basic research unit for material testing in a complete bearing unit. The lining stress calculation results occurred being dependent on applied calculation...
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Deep learning-based waste detection in natural and urban environments
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Trust, Tacit Knowledge Sharing, Project Performance and their Managerial Implications
PublikacjaTacit Knowledge Sharing is increasingly attracting the attention of scientists and managers intrigued by their potential application for creating innovative solutions. Project management as a set of methodologies and best practices need to be charged by knowledge. The research problem tackled in this article refers to a current managerial problem regarding tacit knowledge sharing execution in project based organizations. The objective...
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Company Culture, Knowledge Sharing and Organizational Performance. The Employee’s Perspective
PublikacjaKnowledge sharing, as a basic prerequisite for knowledge creation, is a dynamic social process characterized by profound human interactions. The process of knowledge sharing can be supported by organizational culture which is a set of values and norms giving identity to each enterprise. As a valuable element of intellectual capital, organizational culture contributes to achieving strategic business goals. The purpose of this article...
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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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Collaborative Delivery by Energy-Sharing Low-Power Mobile Robots
PublikacjaWe study two variants of delivery problems for mobile robots sharing energy. Each mobile robot can store at any given moment at most two units of energy, and whenever two robots are at the same location, they can transfer energy between each other, respecting the maximum capacity. The robots operate in a simple graph and initially each robot has two units of energy. A single edge traversal by an robot reduces its energy by one...
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Molecular dynamics-based model of VEGF-A and its heparin interactions
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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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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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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 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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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...
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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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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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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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DentalSegmentator: robust deep learning-based CBCT image segmentation
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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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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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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...