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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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Application of Artificial Neural Networks in Investigations of Steam Turbine Cascades
PublicationZaprezentowano wyniki badań numerycznych zastosowania sieci neuronowych przy obliczeniach przepływów w palisadach turbin parowych. Na podstawie uzyskanych wyników wykazano, że sieci neuronowe mogą być używane do szacowania przestrzennego rozkładu parametrów przepływu, takich jak entalpia, entropia, ciśnienie czy prędkość czynnika w kanale przepływowym. Omówiono również zastosowania tego typu metod przy projektowaniu palisad, stopni...
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Forecasting of currency exchange rates using artificial neural networks
PublicationW rozdziale tym autor przedstawił wyniki swoich badań nad wykorzystaniem sztucznych sieci neuronowych do prognozowania kursu walut (na przykładzie pary walutowej PLN-USD).Głównym celem badań było porównanie skuteczności przewidywania kursu złotówki w latach 1997 - 2005 przy pomocy różnych rodzajów sieci neuronowych.
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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublicationA problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...
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Towards Scalable Simulation of Federated Learning
PublicationFederated learning (FL) allows to train models on decentralized data while maintaining data privacy, which unlocks the availability of large and diverse datasets for many practical applications. The ongoing development of aggregation algorithms, distribution architectures and software implementations aims for enabling federated setups employing thousands of distributed devices, selected from millions. Since the availability of...
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Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublicationCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
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Reliable renewable energy – application of electrochemical capacitors for electrical energy storage
PublicationThis paper presents electrical energy storage devices such as electrochemical capacitors, their principle of operation and electrode materials most commonly used in their manufacturing technology. Moreover, our research on development of new nanocomposite materials based on multi-walled carbon nanotubes and conducting polymer is shown. Additionally, the possibility and advantages of application of supercapacitors for accumulation...
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Energy-Aware Scheduling for High-Performance Computing Systems: A Survey
PublicationHigh-performance computing (HPC), according to its name, is traditionally oriented toward performance, especially the execution time and scalability of the computations. However, due to the high cost and environmental issues, energy consumption has already become a very important factor that needs to be considered. The paper presents a survey of energy-aware scheduling methods used in a modern HPC environment, starting with the...
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Internet photogrammetry as a tool for e-learning
PublicationAlong with Internet development, there were interactive applications which allow for remote sensing and photogrammetric analysis. An example of an application that can provide Earth images and make it possible to measure distances in these images is Google Earth. The authors, who have experience from 2001-2015 argue that it is possible and it is important to create more advanced photogrammetric network applications. In this there...
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An A-Team Approach to Learning Classifiers from Distributed Data Sources
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Degradation of electrical performance of a crystalline photovoltaic module due to dust deposition in northern Poland
PublicationThe reduction in power output caused by the accumulation of dust on the photovoltaic module surface is an important problem and should receive much more attention in the literature. This study was an evaluation of the performance degradation of crystalline photovoltaic modules due to natural and simulated dust deposition. Dust is created from powdered grains of sand and particles of different bodies. Dust originates from different...
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NEURAL NETWORKS
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Gross final energy demand from RES, broken down by type of energy
Open Research DataAccording to the forecasts of the Ministry of Economy, taking into account the macroeconomic situation and legal conditions (including the EU Program "20x20x20", the Act on Renewable Energy Sources and the Energy Efficiency Act), power plants producing energy based on renewable energy will gain in importance in the coming years. energy sources.
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Testing motional accuracy of a manufacturing machine - a task imposed on modern maintenance
PublicationArtykuł dotyczy zagadnień utrzymania ruchu maszyn w powiązaniu z problemami parametryzacji zautomatyzowanych napędów. Przedstawiono krótki przegląd i kierunki rozwoju wspomagania komputerowego w ramach zakładowych systemów utrzymania ruchu. Zwrócono uwagę na pomijanie w popularnie publikowanych graficznych modelach systemów informatycznych CIM, ich podsystemów dedykowanych dla wspomagania utrzymania ruchu maszyn, podczas gdy takie...
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Selected Problems of Machine Dynamics
e-Learning CoursesThe following set of lectures is performed: 1. LECTURE No.1 - INTRODUCTION TO SELECTED PROBLEMS OF MACHINE DYNAMICS. STRUCTURES and MACHINES 2. LECTURE No.2 - ENVIRONMENT, LOADS ON STRUCTURES and MACHINES 3. LECTURE No.3 - DYNAMICS of STRUCTURES and MACHINES 4. LECTURE No.4 - STRENGTH of STRUCTURES and MACHINES 5. LECTURE No.5 - SPECIAL PROBLEMS ASSOCIATED with DYNAMICS and STRENGTH of STRUCTURES and MACHINES
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TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK
PublicationThe need for precise detection of toxic gases drives development of new gas sensors structures and methods of processing the output signals from the sensors. In literature, artificial neural networks are considered as one of the most effective tool for the analysis of gas sensors or sensors arrays responses. In this paper a method of toxic gas components identification using a electrocatalytic gas sensor as a detector and an artificial...
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Half-Order Modeling of Saturated Synchronous Machine
PublicationNoninteger order systems are used to model diffusion in conductive parts of electrical machines as they lead to more compact and knowledge models but also to improve their precision. In this paper a linear half-order impedance model of a ferromagnetic sheet deduced from the diffusion of magnetic field is briefly introduced. Then, from physical considerations and finite elements simulation, the nonlinear half-order impedance model...
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublicationAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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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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RENEWABLE & SUSTAINABLE ENERGY REVIEWS
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Calculation of self and mutual inductances of the switched reluctance machine mathematical model.
PublicationA mathematical model of the switched reluctance machine (SRM) in a drive system obtained using Lagrange's energy method and a method of calculation of self and mutual inductances of the SRM are presented in the paper. The self and mutual inductances are elements of Lagrange's function in generalised coordinates and have been calculated using the finite element method (FEM). Selected calculation results for the particular machine...
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Alternative Energy: Photovoltaic Solar Cells
PublicationSolar radiation is a fuel for photovoltaic cells and modules, which are a source of electric energy. Viable solar technologies that have been developed in the past are starting to be adopted on a broader and more meaningful global scale across different sectors with ever-increasing market penetration. In this entry, a brief overview of the material properties relevant to solar cell operation, the structure of the solar cell, and electrical...
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Examples of renewable and waste energy sources utilisation in municipal sewage treatment plants.
PublicationTematem pracy jest problem zaopatrzenia miejskich oczysczalni ścieków w energię elektryczną i cieplną. przedstawiono dwie polskie oczyszczalnie scieków: w Żywcu i Grudziądzu jako przykłądy zastosowania odnawialnych i odpadowych źródeł energii. Zamieszczone zostały informacje na temat ilości produkowanego biogazu, źródeł energii, systemów zaopatrzenia w ciepło, w tym agregatów kogeneracyjnych i pomp ciepła. Sformułowano wnioski...
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Comprehensive modernization of local heating system using cogeneration and renewable energy sources
PublicationPrzedstawiono przeprowadzoną kompleksową modernizację lokalnego systemu grzewczego z wprowadzeniem gospodarki cieplno-elektrycznej opartej na paliwie gazowym LNG, oraz z zastosowaniem odnawialnych źródeł energii w posatci energii słónecznej i geotermicznej.
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Application of renewable energy sources to drive organic Rankine cycle micro CHP
PublicationOdnawialne źródła energii rzadko znajdują zastosowanie przy stawianych obecnie wymaganiach przez nowoczesne ciepłownie. Pojawiła się unikalna okazja pomocy przy wprowadzeniu na rynek elektrowni zoptymalizowanej dla tych nieużywanych i pomijanych źródeł ciepła. Organiczny obieg Rankine'a jest podobny do konwencjonalnych turbin parowych, wyjątkiem jest płyn napędzający turbinę, którym jest płyn roboczy o dużej masie cząsteczkowej....
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Renewable Energy Sources in the Lubusz Voivodship (Poland). The Present Conditions and Perspectives for Development
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Non-linear circuit model of a single doubly-fed induction machine formulated in natural axes for drive systems simulation purposes
PublicationMathematical modelling and a circuit model formulated in natural axes of a single doubly-fed induction machine, with the account of magnetic circuit nonlinearity are presented in the paper. Derivation of the model differential equations was based on Lagrange's energy method. State functions of magnetic elements in the model are non-linear and depend on all currents flowing in the machine windings and on the angle of rotor position....
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Agnieszka Landowska dr hab. inż.
PeopleAgnieszka Landowska works for Gdansk University of Technology, FETI, Department of Software Engineering. Her research concentrates on usability, accessibility and technology adoption, as well as affective computing methods. She initiated Emotions in HCI Research Group and conducts resarch on User eXperiene evaluation of applications and other technologies.
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublicationHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Voltage profiles improvement in a power network with PV energy sources – results of a voltage regulator implementation
PublicationThe constant increase in the number of photovoltaic (PV) energy sources in distribution networks is the cause of serious voltage problems. The networks built at least a dozen years ago are not provided for the installation of a large number of micro-sources. It happens that the previously properly functioning power networks are not able to provide to consumers power with the required parameters, after installing many PV sources....
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EMPIRICAL ASSESMENT OF THE MAIN DRIVING SYSTEM OF THE CIRCULAR SAWING MACHINE
PublicationThe producers of panel saws tend to improve sawing accuracy and minimise a level of vibrations, to increase their competitiveness at the market. Mechanical vibrations in the main saw driving system, which level depend on a plethora independent factors, may really affect sawing accuracy and general machine tool vibrations. The objective of the research was to explore vibrations signals of the main spindle system, and to extract...
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Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublicationThe Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...
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ALTERNATIVE ENERGY SOURCES
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Multi-criteria Differential Evolution for Optimization of Virtual Machine Resources in Smart City Cloud
PublicationIn a smart city, artificial intelligence tools support citizens and urban services. From the user point of view, smart applications should bring computing to the edge of the cloud, closer to citizens with short latency. However, from the cloud designer point of view, the trade-off between cost, energy and time criteria requires the Pareto solutions. Therefore, the proposed multi-criteria differential evolution can optimize virtual...
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The application of neural networks in forecasting the influence of traffic-induced vibrations on residential buildings
PublicationTraffic-induced vibrations may cause the cracking of plaster, damage to structural elements and, in extreme cases, may even lead to the structural collapse of residential buildings. The aim of this article is to analyse the effectiveness of a method of forecasting the impact of vibrations on residential buildings using the concept of artificial intelligence. The article presents several alternative forecasting systems for which...
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Comparison of Two Nonlinear Predictive Control Algorithms for Dissolved Oxygen Tracking Problem at WWTP
PublicationThe wastewater treatment plant is classified as a complex system, due to its nonlinear dynamics, large uncertainty of disturbance inputs, multiple time scales in the internal process dynamics, and multivariable structure. The aeration process, in turn, is an important and expensive part of wastewater treatment plant operation. All operating parameters of the aeration in biological processes are to be precisely controlled to provide...
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublicationThis work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...
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A review on application of artificial neural network (ANN) for performance and emission characteristics of diesel engine fueled with biodiesel-based fuels
PublicationBiodiesel has been emerging as a potential and promising biofuel for the strategy of reducing toxic emissions and improving engine performance. Computational methods aiming to offer numerical solutions were inevitable as a study methodology which was sometimes considered the only practical method. Artificial neural networks (ANN) were data-processing systems, which were used to tackle many issues in engineering and science, especially...
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Software Factory project for enhancement of student experiential learning
PublicationProviding opportunities for students to work on real-world software development projects for real customers is critical to prepare students for the IT industry. Such projects help students to understand what they will face in the industry and experience real customer interaction and challenges in collaborative work. To provide this opportunity in an academic environment and enhance the learning and multicultural teamwork experience,...
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Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Comparison of effectiveness of musical sound separation algorithms employing neural networks.
PublicationNiniejszy referat przedstawia kilka algorytmów służących do separacji dźwięków instrumentów muzycznych. Zaproponowane podejście do dekompozycji miksów dźwiękowych opiera się na założeniu, że wysokość dźwięków w miksie jest znana, tzn. wejściem dla algorytmów jest przebieg zmian wysokości dźwięków składowych miksu. Proces estymacji fazy i amplitudy składowych harmonicznych wykorzystuje dopasowywanie zespolonych przebiegów harmonicznych...
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The concept of application of artificial neural networks for cultivation controlof cartilages in bioreactors.
PublicationNowym elementem niniejszej pracy jest omówienie problemów związanych z możliwością sterowania parametrami hydrodynamicznymi hodowanej w bioreaktorze chrząstki stawowej przy wykorzystaniu sztucznych sieci neuronowych. Przedstawiona została architektura strategii sterowania hodowlą tkanki z zastosowaniem tych sieci.
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Processing of musical data employing rough sets and artificial neural networks
PublicationArtykuł opisuje założenia systemu automatycznej identyfikacji muzyki i dźwięków muzycznych. Dokonano przeglądu standardu MPEG-7, ze szczególnym naciskiem na parametry opisowe dźwięku. Przedyskutowano problemy analizy danych audio, związane z zastosowaniami wykorzystującymi MPEG-7. W oparciu o eksperymenty przedstawiono efektywność deskryptorów niskiego poziomu w automatycznym rozpoznawaniu dźwięków instrumentów muzycznych. Przedyskutowano...
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Processing of musical data employing rough sets and artificial neural networks
PublicationArtykuł opisuje założenia systemu automatycznej identyfikacji muzyki i dźwięków muzycznych. Dokonano przeglądu standardu MPEG-7, ze szczególnym naciskiem na parametry opisowe dźwięku. Przedyskutowano problemy analizy danych audio, związane z zastosowaniami wykorzystującymi MPEG-7. W oparciu o eksperymenty przedstawiono efektywność deskryptorów niskiego poziomu w automatycznym rozpoznawaniu dźwięków instrumentów muzycznych. Przedyskutowano...
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Analysis of electrical patterns activity in artificial multi-stable neural networks
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Artificial Neural Networks for Prediction of Antibacterial Activity in Series of Imidazole Derivatives
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Analysis of pedestrian activity before and during COVID-19 lockdown, using webcam time-lapse from Cracow and machine learning
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Determinants of anxiety levels among young males in a threat of experiencing military conflict–Applying a machine-learning algorithm in a psychosociological study
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The Neural Knowledge DNA Based Smart Internet of Things
PublicationABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...
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Induction machine behavioral modeling for prediction of EMI propagation.
PublicationThis paper presents the results of wideband behavioral modeling of an induction machine (IM). The proposed solution enables modeling the IM differential- and common-mode impedance for a frequency range from 1 kHz to 10 MHz. Methods of parameter extraction are derived from the measured IM impedances. The developed models of 1.5 kW and 7.5 kW induction machines are designed using the Saber Sketch scheme editor and simulated in the...
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Model of distributed learning objects repository for a heterogenic internet environment
PublicationW 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...