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Search results for: PHOTOVOLTAIC SYSTEMS , RENEWABLE ENERGY SOURCES , ACCURACY , MACHINE LEARNING ALGORITHMS , MACHINE LEARNING , ARTIFICIAL NEURAL NETWORKS , PREDICTIVE MODELS
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THE ONLINE APPLICATION AND E-LEARNING IN THE COMPETENCE-BASED MANAGEMENT IN PUBLIC ADMINISTRATION ORGANIZATIONS
PublicationThe integration of effective management of work-related processes and utilization of human resources potential leads to the development of organization. The purpose of this paper was to examine how the principles of competences-based management can be introduced to enhance organization’s effectiveness in human resources management. A model of assessment and development of competences-based management, embracing an online application...
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A review on analytical models of brushless permanent magnet machines
PublicationThis study provides an in-depth investigation of the use of analytical and numerical methods in analyzing electrical machines. Although numerical models such as the finite-element method (FEM) can handle complex geometries and saturation effects, they have significant computational burdens, are time-consuming, and are inflexible when it comes to changing machine geometries or input values. Analytical models based on magnetic equivalent...
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Comparative studies of manufacturing strategies within multi-machine production systems using simulation
PublicationZaprezentowano metodykę budowy struktur przestrzennych systemów produkcji typu gniazdowego wg zasad technologii grupowej, wykorzystując zaproponowane modele i algorytmy analizy zbiorów/relacji rozmytych. Generowane, z wykorzystaniem tych algorytmów, przebiegi procesów porównywano z przebiegami procesów w strukturach przestrzennych typu hybrydowego, tj. o wspólnych zasobach. Odnosząc się do zdefiniowanego studium przypadku, wykazano...
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Directions of Energy Transition of Uzbekistan
PublicationThe aim of the paper is to present the changes in the Uzbekistan energy market over the past few years. Uzbekistan is self-sufficient in terms of energy resources, the exploitation of which will last for many years. In 2019, the government adopted the "Concept Note ensuring electricity supply in Uzbekistan in 2020-2030" strategy, which announced the modernization of gas and coal power plants and the construction of new energy facilities,...
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Tripping limitations of residual current devices in photovoltaic installations
PublicationIn electrical installations with photovoltaic sources of energy, earth fault current may comprise alternating current component and direct current component. The waveform shape of this earth fault current mainly depends on the point of the fault and the properties of a photovoltaic power electronics converter. The waveform shape of the current influences operation of protection devices, especially tripping threshold of residual...
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Gas Detection Using Resistive Gas Sensors And Radial Basis Function Neural Networks
PublicationWe present a use of Radial Basis Function (RBF) neural networks and Fluctuation Enhanced Sensing (FES) method in gas detection system utilizing a prototype resistive WO3 gas sensing layer with gold nanoparticles. We investigated accuracy of gas detection for three different preprocessing methods: no preprocessing, Principal Component Analysis (PCA) and wavelet transformation. Low frequency noise voltage observed in resistive gas...
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Design of Microstrip UWB Balun Using Quasi-TEM Approach Aided by the Artificial Neural Network
PublicationThe design procedure for UWB balun realized in the microstrip technology is proposed in the paper. The procedure applies Artificial Neural Network which corrects the dimensions of the approximate design found by appropriate scaling of the dimensions of the prototype. The scale coefficients for longitudinal and transverse dimensions of microstrip lines are determined from electromagnetic modeling based on transmission line equations....
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Jerzy Balicki dr hab. inż.
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Residual current devices in installations with PV energy sources
PublicationThe paper presents the principles of residual current devices (RCDs) application in photovoltaic (PV) installations. Provisions of standards in this regard are commented on, in particular, attention is drawn to the lack of obligation to use of RCDs in PV installations. The issue of the shape of the earth fault current and the level of leakage currents in such installations are discussed. These factors influence the selection of...
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Reducing Air Pollutant Emissions from the Residential Sector by Switching to Alternative Energy Sources in Single-Family Homes
PublicationThe paper discusses a scenario for adapting residential buildings to the requirements of the EU climate and energy package. It analyzes the option of reducing pollutant emissions to ambient air by switching to alternative energy sources in a typical single-family residential building. The most common sources of energy in central heating and ventilation systems and water heating systems were compared, and the analyzed energy carriers...
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Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems
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Renewable Energy Focus
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Differential models versus neural models in optimisation
PublicationW pracy porównano zastosowanie modeli różniczkowych i modeli neuronowych dla celów optymalizacji.
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Open source solution LMS for supporting e-learning/blended learning engineers
PublicationW artykule zaprezentowano darmowe systemy zarządzania kształceniem na odległość wspomagające e-learningowe/mieszane nauczanie inżynierów. Pierwszy system TeleCAD został opracowany w ramach projektu Leonardo da Vinci (1998-2001). System TeleCAD był propozycją w projekcie V Ramowy CURE (2003-2006). W roku 2003 dzięki projektowi Leonardo da Vinci EMDEL (2001-2005) Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej wybrało system...
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Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks
PublicationIn this paper, the optical linear sensor, a representative of low-resolution sensors, was investigated in the multiclass recognition of near-field hand gestures. The recurrent neural network (RNN) with a gated recurrent unit (GRU) memory cell was utilized as a gestures classifier. A set of 27 gestures was collected from a group of volunteers. The 27 000 sequences obtained were divided into training, validation, and test subsets....
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Application of sliding switching functions in backstepping based speed observer of induction machine
PublicationThe paper presents an analysis of the speed observer which is based on the backstepping and sliding mode approach. The speed observer structure is based on the extended mathematical model of an induction machine. The observer structure is based on the measured phase stator currents and transformed to ( αβ ) coordinate system. The stator voltage vector components are treated as known values. Additionally, such an observer structure...
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Prototype design and development of low-load-roof photovoltaic modules for applications in on-grid systems
PublicationFour prototypes of lightweight photovoltaic modules for applications in on-grid systems have been designed, developed, manufactured and tested for compliance with relevant IEC standards. Selected, commercially available materials characterized by thermogravimetry, differential scanning calorimetry, dilatometry, scanning electron microscopy and nanoindentation technique were used in frameless, adhesively-bonded sandwich-structures...
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Distance learning trends: introducing new solutions to data analysis courses
PublicationNowadays data analysis of any kind becomes a piece of art. The same happens with the teaching processes of statistics, econometrics and other related courses. This is not only because we are facing (and are forced to) teach online or in a hybrid mode. Students expect to see not only the theoretical part of the study and solve some practical examples together with the instructor. They are waiting to see a variety of tools, tutorials,...
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Modelling relation between oxidation resistance and tribological properties of non-toxic lubricants with the use of artificial neural networks
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublicationWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations
PublicationAlthough making mistakes is a crucial part of learning, it is still often being avoided in companies as it is considered as a shameful incident. This goes hand in hand with a mindset of a boss who dominantly believes that mistakes usually have negative consequences and therefore avoids them by only accepting simple tasks. Thus, there is no mechanism to learn from mistakes. Employees working for and being influenced by such a boss...
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Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublicationThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...
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Air-cooled photovoltaic roof tile as an example of the BIPVT system – An experimental study on the energy and exergy performance
PublicationThe air-cooled photovoltaic tile is a subject of presented investigations, which focused on improving the overall system efficiency of PV tiles with heat recovery. The operational efficiency of a PV roof tile, together with the construction optimising the air cooling efficiency, were the main points of plans realized at this research stage. The article describes the experimental research consisting of the assessment of electrical,...
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Parallel implementation of background subtraction algorithms for real-time video processing on a supercomputer platform
PublicationResults of evaluation of the background subtraction algorithms implemented on a supercomputer platform in a parallel manner are presented in the paper. The aim of the work is to chose an algorithm, a number of threads and a task scheduling method, that together provide satisfactory accuracy and efficiency of a real-time processing of high resolution camera images, maintaining the cost of resources usage at a reasonable level. Two...
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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublicationIn this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model has been used. The task is to predict simultaneously and independent of each characteristic parameters of a buried object of several radii at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable...
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Transfer learning in imagined speech EEG-based BCIs
PublicationThe Brain–Computer Interfaces (BCI) based on electroencephalograms (EEG) are systems which aim is to provide a communication channel to any person with a computer, initially it was proposed to aid people with disabilities, but actually wider applications have been proposed. These devices allow to send messages or to control devices using the brain signals. There are different neuro-paradigms which evoke brain signals of interest...
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Scheduling with Complete Multipartite Incompatibility Graph on Parallel Machines: Complexity and Algorithms
PublicationIn this paper, the problem of scheduling on parallel machines with a presence of incompatibilities between jobs is considered. The incompatibility relation can be modeled as a complete multipartite graph in which each edge denotes a pair of jobs that cannot be scheduled on the same machine. The paper provides several results concerning schedules, optimal or approximate with respect to the two most popular criteria of optimality:...
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Patryk Ziółkowski dr inż.
PeoplePatryk Ziolkowski is a graduate of the Faculty of Civil and Environmental Engineering at the Gdansk University of Technology, specializing in Building and Engineering Structures. He works as an Assistant Professor at the Department of Engineering Structures. He participated in international projects, including projects for the Ministry of Transportation of the State of Alabama (2015), he is also the winner of a grant from the Kosciuszko...
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ANALYSIS AND OPTIMIZATION OF ELECTRIC VEHICLE CHARGING PROCESSES IN TRANSACTIVE ENERGY SYSTEMS
PublicationThe implementation of smart charging of electric vehicles allows operators of local power networks and electricity suppliers to implement new business models for the interaction of electric vehicles with the network. In addition to the optimal selection of Microgrid capacities when charging electric vehicles, it is also important to use different charging methods. To satisfy the interests of all participants of local systems from...
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Recycling of raw materials, silicon wafers and complete solar cells from photovoltaic modules
PublicationPhotovoltaic modules (PVs) are an attractive way of generating electricity in reliable and maintenance-free systems with the use of solar energy. The average lifetime of photovoltaic modules is 25 to 30 years. To offset the negative impact of photovoltaic modules on the environment, it is necessary to introduce a long-term strategy that includes a complete lifecycle of all system components from the production phase through installation...
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Modeling of small molecule's affinity to phospholipids using IAM-HPLC and QSRR approach enhanced by similarity-based machine algorithms
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Towards neural knowledge DNA
PublicationIn this paper, we propose the Neural Knowledge DNA, a framework that tailors the ideas underlying the success of neural networks to the scope of knowledge representation. Knowledge representation is a fundamental field that dedicates to representing information about the world in a form that computer systems can utilize to solve complex tasks. The proposed Neural Knowledge DNA is designed to support discovering, storing, reusing,...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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Application of the neural networks for developing new parametrization of the Tersoff potential for carbon
PublicationPenta-graphene (PG) is a 2D carbon allotrope composed of a layer of pentagons having sp2- and sp3-bonded carbon atoms. A study carried out in 2018 has shown that the parameterization of the Tersoff potential proposed in 2005 by Ehrhart and Able (T05 potential) performs better than other potentials available for carbon, being able to reproduce structural and mechanical properties of the PG. In this work, we tried to improve the...
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Bożena Kostek prof. dr hab. inż.
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Deep learning for recommending subscription-limited documents
PublicationDocuments recommendation for a commercial, subscription-based online platform is important due to the difficulty in navigation through a large volume and diversity of content available to clients. However, this is also a challenging task due to the number of new documents added every day and decreasing relevance of older contents. To solve this problem, we propose deep neural network architecture that combines autoencoder with...
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Adam Dąbrowski dr inż.
PeopleAdam Dabrowski has obtained a PhD in mechanical engineering from Gdańsk University of Technology and MSc. degree in mechatronics from Technische Universität Hamburg. He has an industry experience in Institute of Aviation Engineering Design Center (Warsaw, Poland) and SICK AG (Hamburg, Germany). Additionally, as an assistant at Gdansk University of Technology he teaught courses on mechanics, space mechanisms and dynamics of space...
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Metaheuristic algorithms for optimization of resilient overlay computing systems
PublicationThe idea of distributed computing systems has been gaining much interest in recent years owing to the growing amount of data to be processed for both industrial and academic purposes. However, similar to other systems, also distributed computing systems are vulnerable to failures. Due to strict QoS requirements, survivability guarantees are necessary for provisioning of uninterrupted service. In this article, we focus on reliability...
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International Journal of Neural Networks
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IEEE TRANSACTIONS ON NEURAL NETWORKS
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The methodology of design of axial clearances compensation unit in hydraulic satellite displacement machine and their experimental verification
PublicationA new methodology of calculating the dimensions of the axial clearance compensation unit in the hydraulic satellite displacement machine is described in this paper. The methods of shaping the compensation unit were also proposed and described. These methods were used to calculate the geometrical dimensions of the compensation field in an innovative prototype of a satellite hydraulic motor. This motor is characterized by the fact...
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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublicationThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublicationThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
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Autoencoder application for anomaly detection in power consumption of lighting systems
PublicationDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
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Analysis of electricity generation variability in 2019 with special consideration of electrical energy generation from wind sources.
PublicationThis article presents issues related to the broadly understood development of wind energy. The state of the art of wind energy in the world has been discussed. This paper also shows issues related to factors affecting the development of renewable energy sources and their impact on the natural environment on the basis of available research. The focus is, however, on the critical analysis of phenomena in the data of the Transmission...
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Experimental verification of MWO bearing machine
PublicationPrzedstawiono wyniki weryfikacji doświadczalnej nowego stanowiska przeznaczonego do badań wytrzymałości zmęczeniowej warstwy powierzchniowej łożysk ślizgowych. Badano dwu- i trójwarstwowe cienkościenne panwie ślizgowe. Warstwa nośna wykonana była ze stopu CuPb30. W wariancie trójwarstwowym występowała powłoka ze stopu PbSnCu. Przedstawiono przykłady zaobserwowanych pęknięć zmęczeniowych. Maszyna MWO okazała się w pełni przydatna...
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Simulations CAE of wood pellet machine
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublicationThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader's behavior must align for the best learning effects....
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublicationThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning effects....
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Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublicationThe rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...