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Search results for: MAGNETIC SIGNATURES, MEASUREMENT DEPTH, MODELING, NEURAL NETWORKS
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3rd International Workshop on Reliable Networks Design and Modeling (RNDM 2011)
Publicationartykuł sprawozdawczy z konferencji
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Fourth International Workshop on Reliable Networks Design and Modeling (RNDM 2012)
Publicationartykuł sprawozdawczy z konferencji
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Modelling changes in the energy efficiency of buildings using neural networks on the example of Zielona Góra
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Prediction of Early Childhood Caries Based on Single Nucleotide Polymorphisms Using Neural Networks
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The Effectiveness of Using a Pretrained Deep Learning Neural Networks for Object Classification in Underwater Video
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Application of artificial neural networks (ANN) as multiple degradation classifiers in thermal and flow diagnostics
PublicationPrzedyskutowano problem zwiększenia dokładności rozpoznawania wielokrotnych degradacji eksploatacyjnych urządzeń składowych dużych obiektów energetycznych. Zastosowani sieć neuronową (SSN) o skokowych funkcjach przejścia. Sprawdzono możliwości przyspieszenia treningu sieci neuronowych. Zastosowano modułową metodę budowy SSN, polegającą na dedykowaniu pojedynczej sieci do rozpoznawania tylko jednego typu degradacji.
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Accidental wow defect evaluation using sinusoidal analysis enhanced by artificial neural networks
PublicationArtykuł przedstawia metodę do wyznaczania charakterystyki pasożytniczych modulacji częstotliwości (kołysanie) obecnych w archiwalnych nagraniach dźwiękowych. Prezentowane podejście wykorzystuje śledzenie zmian sinusoidalnych komponentów dźwięku które odzwierciedlają przebieg kołysania. Analiza sinusoidalna wykorzystana jest do ekstrakcji składowych tonalnych ze zniekształconych nagrań dźwiękowych. Dodatkowo, w celu zwiększenia...
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Detecting Objects of Various Categories in Optical Remote Sensing Imagery Using Neural Networks
PublicationThe effective detection of objects in remote sensing images is of great research importance, so recent years have seen a significant progress in deep learning techniques in this field. However, despite much valuable research being conducted, many challenges still remain. A lot of research projects focus on detecting objects of a single category (class), while correctly detecting objects of different categories is much harder. The...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublicationRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
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Modeling saturation of main magnetic circuit of cage induction motors in presence of eccentricity
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<title>Modeling of noncontact temperature measurement system using multiwavelength pyrometry</title>
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Sławomir Jerzy Ambroziak dr hab. inż.
PeopleSławomir J. Ambroziak was born in Poland, in 1982. He received the M.Sc., Ph.D. and D.Sc. degrees in radio communication from Gdańsk University of Technology (Gdańsk Tech), Poland, in 2008, 2013, and 2020 respectively. Since 2008 he is with the Department of Radiocommunication Systems and Networks of the Gdańsk Tech: 2008-2013 as Research Assistant, 2013-2020 as Assistant Professor, and since 2020 as Associate Professor. He is...
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Determination of Odour Interactions in Gaseous Mixtures Using Electronic Nose Methods with Artificial Neural Networks
PublicationThis paper presents application of an electronic nose prototype comprised of eight sensors, five TGS-type sensors, two electrochemical sensors and one PID-type sensor, to identify odour interaction phenomenon in two-, three-, four- and five-component odorous mixtures. Typical chemical compounds, such as toluene, acetone, triethylamine, α-pinene and n-butanol, present near municipal landfills and sewage treatment plants were subjected...
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublicationABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Effects of FSW Tool Plunge Depth on Properties of an Al-Mg-Si Alloy T-Joint: Thermomechanical Modeling and Experimental Evaluation
PublicationOne of the main challenging issues in friction stir welding (FSW) of stiffened structures is maximizing skin and flange mixing. Among the various parameters in FSW that can affect the quality of mixing between skin and flange is tool plunge depth (TPD). In this research, the effects of TPD during FSW of an Al-Mg-Si alloy T-joint are investigated. The computational fluid dynamics (CFD) method can help understand TPD effects on FSW...
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Geospatial Modeling of the Tombolo Phenomenon in Sopot using Integrated Geodetic and Hydrographic Measurement Methods
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Modeling and Simulation for Exploring Power/Time Trade-off of Parallel Deep Neural Network Training
PublicationIn the paper we tackle bi-objective execution time and power consumption optimization problem concerning execution of parallel applications. We propose using a discrete-event simulation environment for exploring this power/time trade-off in the form of a Pareto front. The solution is verified by a case study based on a real deep neural network training application for automatic speech recognition. A simulation lasting over 2 hours...
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Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks
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Highlights from RNDM 2018 – 10th Anniversary Workshop on Resilient Networks Design and Modeling
PublicationArtykuł prezentujący relację z workshopu RNDM 2018
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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublicationObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
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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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Long Short-Term Memory (LSTM) neural networks in predicting fair price level in the road construction industry
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Application of neural networks for identification of forcedness having effect on magnitude of turbine rotor vibration using rotor trajectory.
PublicationW pracy dokonano analizy zastosowania sieci neuronowych do wyznaczenia wartości wymuszeń wpływających na wielkość drgań wirnika używając trajektorii jako parametr określający drgania. Badania przeprowadzono na powietrznej, jednostopniowej turbinie modelowej. Przemieszczenia poziome i pionowe wirnika turbiny mierzono przy pomocy systemu pomiarowego i rejestrowano na oscyloskopie cyfrowym. Przeprowadzono pomiary trajektorii ruchu...
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublicationAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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Study of Phase Transformation Processes Occurring in the Nanocrystalline Iron/Ammonia/Hydrogen System by the Magnetic Permeability Measurement Method
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The influence of a strong external magnetic field from a permanent magnet on a measurement accuracy of an inductive watt-hour meter
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A new analyzer based on pellistor sensor with neural network data postprocessing for measurement of hydrocarbons in lower explosive limit range
PublicationW pracy przedstawiono rezultaty pierwszego etapu badań nad nowym typem analizatora do oznaczania stężenia wodoru i lotnych węglowodorów w zakresie dolnej granicy wybuchowości. Analizator ten zbudowano w oparciu o pojedynczy czujnik pelistorowy z układem przetwarzania danych wykorzystującym sztuczną sieć neuronową.
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Artificial neural networks as a tool for selecting the parameters of prototypical under sleeper pads produced from recycled rubber granulate
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Two- and three-dimensional elastic networks with rigid junctions: modeling within the theory of micropolar shells and solids
PublicationFor two- and three-dimensional elastic structures made of families of flexible elastic fibers undergoing finite deformations, we propose homogenized models within the micropolar elasticity. Here we restrict ourselves to networks with rigid connections between fibers. In other words, we assume that the fibers keep their orthogonality during deformation. Starting from a fiber as the basic structured element modeled by the Cosserat...
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Three-dimensional visualization and measurement of conformal dose distributions using magnetic resonance imaging of bang polymer gel dosimeters
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Accurate Modeling of a Lossy Ferrite Circular Guide Section Magnetized Through a Rotary Four-Pole Magnetic Field
PublicationKorzystając z metody rodzajów sprzężonych opracowano model matematyczny umożliwiający określenie parametrów falowych i rozkładów pola em. fal występujących w ferrytowym falowodzie cylindrycznym magnesowanym czterobiegunowym polem magnetycznym. W oparciu o model określono macierz rozproszenia sekcji falowodu. Opracowane oprogramowanie pozwoliło na zbadanie charakterystyk częstotliwościowych sekcji ferrytowej i wskazanie możliwości...
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System pomiaru pola magnetycznego w procesie demagnetyzacji modeli okrętów =System for magnetic field measurement in degaussing process of ships
PublicationPrzedstawiono wybrane problemy związane z budową stanowiska badawczego oraz badaniami nowych metod demagnetyzacji okrętów prowadzonych na modelach. Przedstawiono zautomatyzowany system pomiarowy do badania pola magnetycznego modelu okrętu. Omówiono strukturę i funkcje układu pomiarowego oraz metodę ograniczania błędów wynikających z przemieszczania czujników pomiarowych względem pola magnetycznego. Podano przykładowe wyniki pomiarów.
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Bożena Kostek prof. dr hab. inż.
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Application of neural networks for identification of forcedness having effect on magnitude of turbine rotor vibration using pressure distribution in blade tip clearance.
PublicationW pracy sprawdzono, czy zastosowanie sieci neuronowych umożliwia identyfikację wymuszeń powstających w wyniku funkcjonowania maszyny jak i zależnych od jej stanu mechanicznego przy zastosowaniu rozkładu ciśnienia w uszczelnieniu nadbandażowym. Przeprowadzono pomiary rozkładu ciśnienia dla różnych warunków pracy, uwzględniając zmianę mimośrodu oraz zmianę skośnego ustawienia osi wirnika względem osi korpusu. Dokonano analiz przy...
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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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Prediction of Stress and Deformation Caused by Magnetic Attraction Force in Modulation Elements in a Magnetically Geared Machine Using Subdomain Modeling
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Particle swarm optimization–artificial neural network modeling and optimization of leachable zinc from flour samples by miniaturized homogenous liquid–liquid microextraction
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Synthesis and application of biomass-derived magnetic biochar catalyst for simultaneous esterification and trans-esterification of waste cooking oil into biodiesel: modeling and optimization
PublicationThis work created, characterized, and used a magnetic biochar catalyst that is both eco-friendly and very effective. Sugarcane bagasse was selected as primary raw material for catalyst preparation, because it is renewable and ecofriendly biomass. Cata- lyst created by doping sugarcane bagasse biochar with magnetic material in the form of (FeSO 4 ·7H 2 O). Thermogravimetric Analysis (TGA) and Fourier Transform Infrared spectroscopy...
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Modeling and Accuracy Assessment of Determining the Coastline Course Using Geodetic, Photogrammetric and Satellite Measurement Methods: Case Study in Gdynia Beach in Poland
PublicationThe coastal environment represents a resource from both a natural and economic point of view, but it is subject to continuous transformations due to climate change, human activities, and natural risks. Remote sensing techniques have enormous potential in monitoring coastal areas. However, one of the main tasks is accurately identifying the boundary between waterbodies such as oceans, seas, lakes or rivers, and the land surface....
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Michał Michna dr hab. inż.
PeopleMichal Michna received the M.Sc. and Ph.D. degrees in electrical engineering from the Gdansk University of Technology (GUT), Gdansk, Poland, in 1998 and 2005, respectively. Since 2004, he was employed at the Department of Power Electronics and Electrical Machines of the Gdańsk University of Technology (assistant, assistant professor, senior lecturer). In 2010-2015 he was a deputy of head of the Department of Power Electronics and...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublicationTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Mechanical properties of single V2O5 nanocrystal - nanoindentation measurement in control of the max-depth
Open Research DataThe DataSet contains the nanoindentation curves (indentation force Fn vs penetrationPd) for a single V2O5 nanocrystal supported on a substrate. The measurements were performed in control of the maximum depth of Berkovich indenter penetration: 60, 70, and 100 nm.
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ESCASA : Analytical estimation of atomic coordinates from coarse‐grained geometry for nuclear‐magnetic‐resonance ‐assisted protein structure modeling. I. Backbone and Hβ protons
PublicationA method for the estimation of coordinates of atoms in proteins from coarse-grained geometry by simple analytical formulas (ESCASA), for use in nuclear-magnetic-resonance (NMR) data-assisted coarse-grained simulations of proteins is proposed. In this paper, the formulas for the backbone Hα and amide (HN) protons, and the side-chain Hβ protons, given the Cα-trace, have been derived and parameterized, by using the interproton distances...
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Dagmara Nikulin dr
PeopleBio: Dagmara Nikulin Dagmara Nikulin has been employed at the Faculty of Management and Economics as a research and teaching assistant professor since 2014. Initially, she worked at the Department of Economic Sciences, and now at the Department of Statistics and Econometrics. She is a graduate of the Faculty of Economics at the Poznań University of Economics (2009) and the Faculty of Social Sciences of the Adam Mickiewicz University...
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Piotr Paradowski dr
PeopleDr Piotr Paradowski's areas of expertise in quantitative social science methods include truncated and censored models, quantile regressions, survival analysis, panel data models, discrete regressions and qualitative choice models, instrumental variable estimation, and hierarchical modeling. He is also an expert in statistical matching and statistical methods to handle missing data. In addition, he conducts research on income and...
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Jacek Stefański prof. dr hab. inż.
PeopleJJacek Stefański received M.Sc., Ph.D. and D.Sc. degrees in telecommunications engineering from Gdansk University of Technology (GUT), Poland, in 1993, 2000 and 2012, respectively. Awarded title of Professor by the President of Poland in 2020. Currently, he works as a professor at the Department of Radio Communication Systems and Networks (DRCSN) in GUT. From 2005 to 2009, he worked as an assistant professor in the National Institute...
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Applying of thin plate boundary condition in analysis of ship’s magnetic field
PublicationThis paper presents computer simulations of ship’s magnetic signatures using a new thin plate boundary condition implemented in the Opera-3d 18R2 program. The paper aims to check the magnetic signatures’ numerical calculations precision of objects using the thin plate boundary conditions and analysis of the magnetic signature of ship with a degaussing system and with and without inner devices.
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O zastosowaniu metody prądów wirowych do technicznego pomiaru własności elektrycznych i magnetycznych metali = About application of eddy current method for technical measurement of electric and magnetic properties of metals
PublicationOpisano wyniki badań nad wykorzystaniem efektu prądów wirowych do badania własności elektrycznych i magnetycznych metali. Badania wykonano za pomocą sondy różnicowej. Wyniki pomiarów zależności częstotliwościowej wykonane dla modelowych materiałów porównano z wynikami modelowania metodą elementów skończonych.
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Magnetic signature reproduction of ferromagnetic ships at arbitrary geographical position, direction and depth using a multi-dipole model – source and verification dataset with description
Open Research DataThe dataset include source synthetic magnetic data concerning the corvette-type ship numeric model. The data are for 6 locations around the World with different V1 ÷ V6 Earth magnetic field values. The attached data is in Matlab. MAT format, but the data can also be used in Octave software.
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An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublicationThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...