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Search results for: e-learing
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Improving the accuracy of bearing in active sonar with cylindrical array using spectrum estimation.
PublicationThe articles presents a method for improving the accuracy of bearing in multibeam sonar with a cylindrical array. Based on a known spatial spectrum estimation technique, the method has been successfully used in linear array systems. Its accuracy of bearing is satisfactory and ensures a relatively low computational effort. The article discusses certain simplifications and assumptions to adapt the spatial spectrum estimation technique...
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AUTOMATIC LEARNING OF STRATEGY AND RULES IN CARD GAMES USING IMAGE FROM CAMERA
PublicationBelow work tries to answer a question: if it is possible to replace real human with computer system in social games. As a subject for experiments, card games were chosen, because they require a lot of player interaction (playing and taking cards), while their rules are easy to present in form of clear list of statements. Such a system, should allow real players to play without constant worrying about guiding or helping computer...
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Common-Mode Voltage and Bearing Currents in PWM Inverters: Causes, Effects and Prevention
PublicationIn modern induction motor drives an increase of transistors' switching frequency and a decrease of switching times are the sources of some serious problems. The high dv/dt and the common mode voltage generated by the inverter PWM control results in the appearances of bearing currents, shaft voltages, motor terminal overvoltages, the decrease of motor efficiency, and electromagnetic interference. The aspects of common mode (CM)...
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Continuous learning as a method of raising qualifications – the perspective of workers, employers and training organizations
PublicationContinuous learning is discussed in strategic documents of Poland and the European Union. In Poland, the idea of continuous learning is not very popular. However, in the context of strong competition in the labour market and the progressive globalization processes, the skills issue takes on new meaning — both for employees and employers. In order to adapt skills to labour market needs it is necessary to conduct adequate studies...
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Enhancing diaphragmatic defect repair and regeneration: How biomaterials leading the way to progress?
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Fuzzy reasoning system design and assessment of load-bearing endoprostheses and their fabrication processes
PublicationZaproponowano piec zastosowan podejscia rozumowania rozmytego do rozwiazania problemów w dziedzinie biomechanikioraz inzynierii biomateriałów. Obejmuja one: (A) oszacowanie maksymalnych naprezen kontaktowych działajacych naendoproteze, (B) zaprojektowanie procesu spiekania dla otrzymania porowatego implantu, (C) opracowanie planu utleniania wcelu otrzymania struktury nanorurkowej na stopach Ti, (D) oraz (E) zaprojektowanie osadzania...
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Running characteristics of aerodynamic bearing with self-lifting capability at low rotational speed
PublicationAn aerodynamic journal bearing that is capable of self-generating squeeze-film pressure is presented and its dynamic characteristics investigated numerically and experimentally. A numerical method based on a time marching static model was applied to assess the orbit trajectory path of the rotor upon a perturbation. Experimental results were obtained to validate the effect of the self- generated squeeze-film pressure on the stability...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublicationThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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THE SYNCHROSQUEEZING METHOD IN BEARING ESTIMATION OF STATIONARY SIGNALS FOR PASSIVE SONAR WITH TOWED ARRAY
PublicationIn this paper, a novel method of bearing estimation in a passive sonar system with a towed array is introduced. The classical approach of bearing estimation based on the spatial spectrum [1] is extended by using the synchrosqeezing method that is a part of the reassignment method introduced by Kodera et al. [2]. Using this method leads to a precise bearing estimation. The proposed method requires a relatively small amount of computation,...
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The influence of time of hearing aid use on auditory perception in various acoustic situations
PublicationThe assessment of sound perception in hearing aids, especially in the context of benefits that a prosthesis can bring, is a complex issue. The objective parameters of the hearing aids can easily be determined. These parameters, however, do not always have a direct and decisive influence on the subjective assessment of quality of the patient’s hearing while using a hearing aid. The paper presents the development of a method for...
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Ecological bearing systems for water turbines – research and development at Gdansk University of Technology
PublicationIncreasing requirements for environmental protection make it necessary to introduce new materials and designs. Hydroelectric power plants operating in direct contact with water reservoirs and rivers are potentially endangering water cleanliness, hence they should also be modernized in the way minimizing the environmental hazards. A lot of progress in this field has been achieved in last decades, but still there is much work to...
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New Generation of Water lubricated Foil bearing - Numerical Models and Experimental Verification
PublicationIn the paper a new idea of foil water lubricated bearing and methodology of hydrodynamic characteristics calculations is presented. To assesses the theoretical characteristics of these bearings two different computer models were built. First is structural model coupled with fluid model. It takes into account: fluid flow in the deformed fluid gap, specific design of bearing support and friction in bearing support. The second is...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublicationComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublicationThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublicationTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
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Combined thrust radial bearing of a submarine main shaft – Design and analysis of failure
PublicationThis paper presents an analysis of the combined thrust radial bearing of a submarine propulsion shaft. The lubrication system of the bearing is based on a fixed ring. The efficiency of the lubrication system depends on the shaft speed and temperature, which affects oil viscosity. In turn, the thrust bearing load also depends on the rotational speed of the shaft, because as the speed increases, the drag of the ship increases simultaneously,...
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Water-lubricated stern tube bearing - experimental and theoretical investigations of thermal effects
PublicationThe paper presents research results of thermal phenomena accompanying operation of a water-lubricated stern tube bearing with axial grooves. Experimental tests revealed, that intensity of forced axial flow has strong influence on bush temperature. Numerical simulations focused on investigation of the thermal phenomena under operation of water-lubricated journal bearing showed, that restricted axial flow promotes backflow of the...
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Field Tests on Hydrodynamic and Hybrid Operation of a Bidirectional Thrust Bearing of a Pump-Turbine
PublicationIn vertical shaft pump turbines operating in pumped storage power plants an important role is played by a thrust bearing. Due to the bidirectional character of operation, thrust bearing tilting pads have to be supported symmetrically, which is known to be unfavourable from the point of view of their performance. Large thrust bearings have to be carefully designed so as to minimise excessive thermo-elastic pad deformations. The...
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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The effects of relational and psychological capital on work engagement: the mediation of learning goal orientation
PublicationPurpose – This paper proposes a research model in which learning goal orientation (LGO) mediates the impacts of relational capital and psychological capital (PsyCap) on work engagement. Design/methodology/approach – Data obtained from 475 managers and employees in the manufacturing and service industries in Poland were utilized to assess the linkages given above. Common method variance was controlled by the unmeasured latent method...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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On the use of leading safety indicators in maritime and their feasibility for Maritime Autonomous Surface Ships
PublicationAlthough the safety of prospective Maritime Autonomous Surface Ships will largely depend on their ability to detect potential hazards and react to them, the contemporary scientific literature lacks the analysis of how to achieve this. This could be achieved through an application of leading safety indicators. The aim of the performed study was to identify the research directions of leading safety indicators in three safety-critical...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublicationEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Machine learning approach to packaging compatibility testing in the new product development process
PublicationThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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DESIGN AND THEORETICAL ANALYSIS OF A PROTOTYPE TILTING-PAD RADIAL BEARING WITH ADJUSTABLE CLEARANCE
PublicationThe article introduces a design and analysis results of a prototype ORC (organic Rankine cycle) turbo generator rotor assembly of 300kW power, supported by tilting-pad bearings of original design. The calculations were performed for a prototype turbo generator rotor. The shaft of this machine is supported with two radial bearings, lubricated with an unusual lubricant – a low-boiling-point agent. The main objective of the presented...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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A comparative performance assessment of a hydrodynamic journal bearing lubricated with oil and magnetorheological fluid
PublicationThis work presents the investigation results of a journal bearing lubricated with magnetorheological fluid that is activated by a local constant magnetic field to vary both the local flow resistance and pressure. The bearing performance is assessed via Finite Element Modelling (FEM) and results are corroborated by experiments. The FEM model uses the Bingham model to describe the fluid film. A dedicated test rig is used to assess...
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Effect of manufacturing errors of the pad sliding surface on the performance of the hydrodynamic thrust bearing
PublicationIn the present study, investigation of the effect of manufacturing errors on the performance of large tilting pad thrust bearings has been performed, following a CFD-based Thermohydrodynamic analysis of a single pad. A 3D model has been generated, including the pad, the lubricant film and the corresponding part of the collar. The pad has been assumed to be deformed about the pivot point, due to thrust loading. Manufacturing errors...
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublicationThis work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...
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Iron(III)-selective materials based on a catechol-bearing amide for optical sensing
PublicationThe synthesis and ion-binding properties of a new amide L derived from 3,4-dihydroxybenzoic acid are described. Due to the presence of a catechol unit, the compound interacts selectively with iron(III) in organic solvent (dimethyl sulfoxide, DMSO) to produce a color change from pale yellow to green. The incorporation of the ligand L into polymeric matrices or its encapsulation into surfactant-based spheres enables analyte detection...
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Supervised-learning-based development of multi-bit RCS-reduced coding metasurfaces
PublicationCoding metasurfaces have been introduced as efficient tools allowing meticulous control over the electromagnetic (EM) scattering. One of their relevant application areas is radar cross section (RCS) reduction, which principally relies on the diffusion of impinging EM waves. Despite its significance, careful control of the scattering properties poses a serious challenge at the level of practical realization. This article is concerned...
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Wisdom from Experience Paradox: Organizational Learning, Mistakes, Hierarchy and Maturity Issues
PublicationOrganizations often perceive mistakes as negligence and low-performance indicators, yet they can be a precious learning resource. However, organizations cannot learn from mistakes if they have not accepted them. This study aimed to explore how organizational hierarchy and maturity levels influence the relationship between mistakes acceptance and the ability to change. A sample composed of 380 Polish employees working in knowledge-driven...
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublicationWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublicationHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublicationIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublicationBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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Modeling of bearing capacity of footings on sand within stochastic micro-polar hypoplasticity.
PublicationAnalizowano numerycznie efekt wstępnego rozkładu wskaźnika porowatości na wytrzymałość i strefy ścinania w problemach fundamentów na piasku w skali modelowej. Obliczenia wykonano przy zastosowaniu stochastycznej metody elementów skończonych i mikropolarnego modelu hipoplastycznego. Wskaźnik porowatości miał formę skorelowanych pól stochastycznych. Dodatkowo obliczono efekt skali dla 3 różnych szerokości fundamentów.
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The State and Critical Assessment of the Sharing Economy in Europe
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The Sharing Economy in Europe: From Idea to Reality
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Acoustic heating in a weakly dispersive fluid flow
PublicationZbadano specyficzną rolę dyspersyjnych własności płynu w generacji ogrzewania przez straty energii fali akustycznej. Przedstawiono ilustracje zaistniałego ogrzewania powstającego na skutek przejścia dwoch typów fal - impulsowej i stacjonarnej.
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Molecular Biology of Meniscal Healing: A Narrative Review
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Modelling of acoustic backscattering by southern Baltic herring
PublicationAssessment of Baltic herring abundance can be carried out using acoustic techniques. Analysis of the relationship between the Baltic herring individual target strength, TS, and the total fish length, L, important for the acoustic assessment, showed the relationship to be dependent on the location of the study area. This finding motivated a detailed analysis of the relationship for the herring occurring in the southern Baltic...
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Temperature measurements in monitoring of large thrust bearings
PublicationW pracy przedstwiono krytyczną analizę aktualnych metod diagnostyki dużych hydrodnamicznych łożysk wzdłużnych hydrozespołów elektrowni wodnych. Wykazano niedostatki i zagrożenia płynące ze stosowania diagnostyki opartej na jednopunktowym pomiarze temperatury. Zaprezentowano wstępna koncepcję nowej metody diagnostycznej opartej na odwrotnym zagadnieniu przepływu ciepła (IPHC).
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Utulization of biomass for heating purposes in pomeranian region
PublicationW publikacji przedstawiono analizę potencjału użycia odnawialnych źródeł energii do produkcji ciepła w regionie pomorskim. Każde miasto regionu zostało oszacowane pod względem potencjału użycia odnawialnych źródeł energii. Dwa obszary miejskie cechują się tym, że mają potencjał pokrycia swojego zapotrzebowania na ciepło tylko ze słomy, czyli możemy rozpatrywać produkcję ciepła z kotłów opalanych słomą jako 100% potencjalne zapotrzebowanie...
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Institutionalization of knowledge sharing in a software development organization
PublicationZaproponowano podejście modelowe do problemu wymiany wiedzy. Omówiono implementację modelu na przykładzie instytucji zajmującej się produkcja oprogramowania komputerowego.
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The Resistance of Polyethersulfone Membranes on the Alkaline Cleaning Solutions
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Membrane cleaning and pretreatments in membrane distillation – a review
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