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The improvement of axial bearing capacity of open-end pipe piles
PublikacjaZaproponowano sposób zwiększania nośności osiowej pali rurowych z otwartym dnem za pomocą wewnętrznych pierścieni. Przedstawiono wyniki badań w skali naturalnej i badań modelowych. Przeprowadzono analizę teoretyczną zjawiska metodą analityczną i numeryczną. Badania i analizy potwierdziły skuteczność proponowanego rozwiązania technicznego.
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The detection of Alternaria solani infection on tomatoes using ensemble learning
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Photophysical properties and photochemistry of a sulfanyl porphyrazine bearing isophthaloxybutyl substituents
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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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TEARING THE SPACE APART. RESPONSIBLE PARTICIPATION OR SELF-SERVING PARTICIPATION
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Becoming a Learning Organization Through Dynamic Business Process Management
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Real-time speech streching for supporting hearing impaired schoolchildren
PublikacjaA study of time scale modification algorithms applied to support hearing impaired schoolchildren is presented. Variety of algorithms are considered, namely: overlap-and add, two variations of synchronous overlapand- add, and the phase vocoder. Their effectiveness as well as real-time processing capabilities are examined.
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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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Determining the noise impact on hearing using psychoacoustical noise dosimeter
PublikacjaThis research study presents the designed noise dosimeter based on psychoacoustical properties of the human hearing system and, at the same time. evaluation of time and frequency characteristics of noise. The designed noise dosimeter enables assessing temporary threshold shift (TTS) in critical hands in real time. In this way it is possible monitoring the hearing threshold shift continuously for people who stay in the harmful noise...
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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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Influence of an applied bearing system on behaviour of multi-span footbridge
PublikacjaThe cycle overpass in Gdynia is a box structure over 300 metres long, 10-span. It was opened for bicycle traffic in the second half of 2013. At the end of its construction, there was failure due to excessive horizontal displacement of the system. A number of bearings exceeded the range of permissible transverse shifts thus it was necessary to temporarily protect the spans from slipping. The FEM analysis of the original solution...
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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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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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Experimental research on marine oil-lubricated stern tube bearing
PublikacjaBearings of propeller shafts are very crucial elements of the propulsion system of each of the ships. The safety of shipping depends on their durability and reliability. The new legal restrictions mean that today we are looking for environmentally friendly solutions. That is why water-lubricated bearings are becoming more and more popular. So, will oil-lubricated shaft bearings belong to the past? The bearing with a white metal...
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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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Stochastic contributions on the pressure in slide bearing gaps after impulse
PublikacjaTematem niniejszej pracy są parametry smarowania poprzecznych i poprzeczno-wzdłużnych łożysk ślizgowych olejem o własnościach lepkosprężystych. Wyprowadzono zmodyfikowane równania Reynoldsa do wyznaczania ciśnienia hydrodynamicznego ślizgowych łożysk o powierzchniach cylindrycznych, sferycznych, stożkowych i parabolicznych, przy jednoczesnym uwzględnieniu możliwości brania pod uwagę zmiennej lepkości oleju po grubości warstwy smarującej....
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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 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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Running performance of an aerodynamic journal bearing with squeeze film effect
PublikacjaResults of theoretical and experimental studies concerning the performance of an aerodynamic journal bearing of which running is assisted by squeeze film ultrasonic levitation (SFUL) are presented in this paper. The SFUL mechanism not only can separate journal from the bearing at the start and stop phases of operation but also can significantly contribute to the dynamic stability of the bearing when it runs at speed. Computer calculations...
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Methods of Improving Speech Intelligibility for Listeners with Hearing Resolution Deficit
PublikacjaMethods developed for real-time time scale modification (TSM) of speech signal are presented. They are based onthe non-uniform, speech rate depended SOLA algorithm (Synchronous Overlap and Add). Influence of theproposed method on the intelligibility of speech was investigated for two separate groups of listeners, i.e. hearingimpaired children and elderly listeners. It was shown that for the speech with average rate equal to or...
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Diagnosis of bearing damage in induction motors by instantaneous power analysis
PublikacjaResearch of the machine with simulated bearing damages has been carried out, where variable load torque, simulating bearing damage, was introduced. The results show that components which can be used for bearings diagnosis appear in the spectrum of the product of current and supply voltage instantaneous values. These components are easier to identify than the components of current spectrum, which have been used so far in diagnostic...
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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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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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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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Compliance tests of the polymer layers used as hydrodynamic bearing coatings
PublikacjaOperational experience and scientific investigations results showed that polymer lined hydrodynamic bearings can withstand more severe operating conditions compared than white metal bearings. PTFE and PEEK-based coatings are the most frequently used as Babbitt alternatives. Both polymers differ significantly from the each other in material properties. According to catalogue data compression modulus of PTFE, it is about an order...
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Design of poroelastic wearing course with the use of direct shear test
PublikacjaPoroelastic Road Surfaces (PERS) are characterized by porous structure with at least 20% of air void content and stiffness almost 10 times lower than typical asphalt course. Such properties enable noise reduction up to 12 dB in comparison to SMA 11 mixture. However, the main disadvantage of previously used poroelastic mixtures, based on resin type binders, was their low durability, which resulted in raveling and delamination from...
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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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Optimisation and field assessment of poroelastic wearing course bond quality
PublikacjaCompared to typical asphalt mixtures, poroelastic mixtures are characterised by high porosity and high flexibility, which are desirable for traffic noise reduction. However, the same properties increase the risk of debonding from the lower layer, which is a significant source of premature damage. The study investigates which of the factors – tack coat agent, type and texture of the lower layer – have the greatest impact on interlayer...
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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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Impact of Spatial Noise Correlation on Bearing Accuracy in DIFAR Systems
PublikacjaDIFAR type underwater passive systems are one of the more commonly used tools for detecting submarines. At the design stage, which usually uses computer simulations, it is necessary to generate acoustic noise of the sea. It has been shown that correlating noise significantly reduces these errors compared to the assumption that noise is uncorrelated. In addition, bearing errors have been shown to be the same in systems with a commonly...
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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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Equalization of pad loads in large tilting pad thtust bearing
PublikacjaW pracy przedstawiono przebieg projektowania zmodernizowanego łożyska wzdłużnego hydrogeneratora. Na podstawie eksploatacyjnych danych o zróżnicowaniu temperatury klocków łożyskowych, na drodze obliczeń elasto-termo-hydrodynamicznych, stwierdzono konieczność wyrównania rozkładu obciążenia na poszczególne klocki łożyska. Cel został osiągnięty poprzez wprowadzenie podatnego podparcia segmentów łożyska na sprężynach płytowych, których...
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Automatic assessment of the hearing aid dynamics based on fuzzy logic
PublikacjaPrzedstawiono podstawy koncepcyjne systemu dopasowania protez słuchu opartego na logice rozmytej. Przeprowadzono dyskusje na temat metody skalowania głośności. Następnie podano szczegóły procesu aproksymacji funkcji przynależności odzwierciedlające słuchowe wrażenia głośności. Załączono wnioski.
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Testing of performance properties of asphalt mixes for thin wearing courses.
PublikacjaPrzedstawiono wyniki badań następujących cech mieszanek mineralno asfaltowych: odporność na starzenie, oddziaływanie wody i mrozu, koleinowanie i oddziaływanie niskich temperatur. W badaniach zastosowano 2 typy mieszanek: beton asfaltowy o nieciągłym uziarnieniu i mastyks grysowy SMA. Wykorzystano 4 rodzaje asfaltów: 1 niemodyfikowany i 3 modyfikowane polimerami. Stwierdzono że wszystkie mieszanki są porównywalnie odporne na starzenie,...
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Nonlinear rate dependent model of high damping rubber bearing.
PublikacjaCelem artykułu jest analiza nieliniowego modelu łożyska wykonanego z wysokotłumiącej gumy, który symuluje pracę urządzenia pod zadanym obciążeniem. Parametry modelu dobrane są na podstawie wyników badań eksperymentalnych. Wyniki pracy pokazują, iż analizowany model umożliwia symulację zachowania się łożyska w szerokim zakresie odkształceń
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Application of neural networks for description of pressure distribution in slide bearing.
PublikacjaBadano rozkład ciśnienia hydrodynamicznego w łożysku ślizgowym dla wybranych wariantów łożyska. Wykazano, że zastosowanie sieci neuronowych umożliwia opis rozkładu ciśnienia hydrodynamicznego z uwzględnieniem zmian geometrycznych (bezwymiarowa długość - L) i mechanicznych (mimośrodowość względem H) łożyska.
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Identification of slide bearing main parameters using neural networks.
PublikacjaWykazano, że sieci neuronowe jak najbardziej nadają się do identyfikacji głównych parametrów geometrycznych i ruchowych hydrodynamicznych łożysk ślizgowych.
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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 strengths...