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Search results for: STANDA RD OF LIVING, NEURAL NETWORKS, K OHONEN SELF - ORG ANIZING MAPS, REGIONAL ANALYSIS
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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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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublicationIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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Minimization of the number of periodic points for smooth self-maps of closed simply-connected 4-manifolds
PublicationLet M be a smooth closed simply-connected 4-dimensional manifold, f be a smooth self-map of M with fast grow of Lefschetz numbers and r be a product of different primes. The authors calculate the invariant equal to the minimal number of r-periodic points in the smooth homotopy class of f.
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Blood Pressure Estimation Based on Blood Flow, ECG and Respiratory Signals Using Recurrent Neural Networks
PublicationThe estimation of systolic and diastolic blood pressure using artificial neural network is considered in the paper. The blood pressure values are estimated using pulse arrival time, and additionally RR intervals of ECG signal together with respiration signal. A single layer recurrent neural network with hyperbolic tangent activation function was used. The average blood pressure estimation error for the data obtained from 21 subjects...
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Efficient uncertainty quantification using sequential sampling-based neural networks
PublicationUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
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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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Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening
PublicationFamilial hypercholesterolemia (FH) is a highly undiagnosed disease. Among FH patients, the onset of premature coronary artery disease is 13 times higher than in the general population. Early diagnosis and treatment is essential to prevent cardiovascular diseases and their complications, and to prolong life. One of the clinical criteria of FH is the occurrence of a corneal arcus (CA) among patients, especially those under 45 years...
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NETWORKS
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Towards bees detection on images: study of different color models for neural networks
PublicationThis paper presents an approach to bee detection in videostreams using a neural network classifier. We describe the motivationfor our research and the methodology of data acquisition. The maincontribution to this work is a comparison of different color models usedas an input format for a feedforward convolutional architecture appliedto bee detection. The detection process has is based on a neural...
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Computer Networks-laboratories - 2023
e-Learning CoursesAcquiring the skills to design, build and configure computer networks. Demonstration of skills to identify and analyze selected protocols and mechanisms of LAN and WAN networks.
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Computer Networks laboratories 2024
e-Learning CoursesAcquiring the skills to design, build and configure computer networks. Demonstration of skills to identify and analyze selected protocols and mechanisms of LAN and WAN networks.
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Activation maps of convolutional neural networks as a tool for brain degeneration tracking in early diagnosis of dementia in Parkinson's disease based on magnetic resonance imaging
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Chlorinated solvents in a petrochemical wastewater treatment plant: Anassessment of their removal using self-organising maps
PublicationThe self-organising map approach was used to assess the efficiency of chlorinated solvent removal frompetrochemical wastewater in a refinery wastewater treatment plant. Chlorinated solvents and inorganicanions (11 variables) were determined in 72 wastewater samples, collected from three different purificationstreams. The classification of variables identified technical solvents, brine from oil desalting andrunoff sulphates as pollution...
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Neural Networks Based on Ultrafast Time-Delayed Effects in Exciton Polaritons
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublicationThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublicationThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
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Neural Network-Based Sequential Global Sensitivity Analysis Algorithm
PublicationPerforming global sensitivity analysis (GSA) can be challenging due to the combined effect of the high computational cost, but it is also essential for engineering decision making. To reduce this cost, surrogate modeling such as neural networks (NNs) are used to replace the expensive simulation model in the GSA process, which introduces the additional challenge of finding the minimum number of training data samples required to...
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Deep neural networks for human pose estimation from a very low resolution depth image
PublicationThe work presented in the paper is dedicated to determining and evaluating the most efficient neural network architecture applied as a multiple regression network localizing human body joints in 3D space based on a single low resolution depth image. The main challenge was to deal with a noisy and coarse representation of the human body, as observed by a depth sensor from a large distance, and to achieve high localization precision....
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublicationEstimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...
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Safety Assessment of the Regional Warmia and Mazury Road Network Using Time-Series Analysis
PublicationWarmia and Mazury still belongs to the areas with the smallest transport accessibility in Europe. Unsatisfactory state of road infrastructure is a major barrier to the development of the regional economy, impacting negatively on the life conditions of the population. Also in terms of road safety Warmia and Mazury is one of the most endangered regions in Poland. The Police statistics show that beside a high pedestrian risk observed...
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Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks
PublicationA method developed for parametrization of EEG signals gathered from participants with acquired brain injuries is shown. Signals were recorded during therapeutic session consisting of a series of computer assisted exercises. Data acquisition was performed in a neurorehabilitation center located in Poland. The presented method may be used for comparing the performance of subjects with acquired brain injuries (ABI) who are involved...
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Andrzej Chybicki dr inż.
PeopleA graduate of the Faculty of Electronics, Telecommunications and Informatics at the Gdańsk University of Technology, PhD in technical sciences in the field of IT specializing in distributed data processing in IT . Aimed at exploiting the achievements and knowledge in the field of industrial research. He cooperated with a number of companies including OpeGieka Elbląg, Reson Inc., Powel Sp. z o. o., Wasat, Better Solutions, the European...
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Heavy duty vehicle fuel consumption modelling using artificial neural networks
PublicationIn this paper an artificial neural network (ANN) approach to modelling fuel consumption of heavy duty vehicles is presented. The proposed method uses easy accessible data collected via CAN bus of the truck. As a benchmark a conventional method, which is based on polynomial regression model, is used. The fuel consumption is measured in two different tests, performed by using a unique test bench to apply the load to the engine. Firstly,...
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On the growth of the number of periodic points for smooth self maps of a compact manifold
PublicationDla ciągłego przekształcenia jednospójnej rozmaitości wymiaru co najmniej 3 w siebie, wykazujemy, że wzrost liczby punktów r-periodycznych w klasie homotopii może być nie szybszy niż liniowy, dla dowolnego, ustalonego r.
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Algebraic periods of self-maps of a rational exterior space of rank 2
PublicationArtykuł stanowi kompletny opis okresów algebraicznych dla odwzorowań wymiernej przestrzeni zewnętrznej rangi 2 w siebie.
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Minimal number of periodic points for smooth self-maps of S^3
PublicationW pracy wyznaczona została najmniejsza liczba punktów periodycznych w gładkiej klasie homotopii odwzorowania sfery trójwymiarowej w siebie.
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Ecotoxicity and chemical sediment data classification by the useof self-organising maps
PublicationArtykuł dotyczy przedstawiania nowej interpretacji szacowania jakości osadów. To oryginalne podejście bada powiązania między parametrami ekotoksyczności (ostrej i chronicznej) i składnikami chemicznymi (zanieczyszczenia takie jak polichlorowane bifenyle, pestycydy, wielopierścieniowe węglowodory aromatyczne, metale ciężkie) próbek osadów Jeziora Turawskiego (Polska) poprzez zastosowanie samoorganizujących się map (SOM) wobec badanego...
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Minimal number of periodic points for smooth self-maps of RP^3
PublicationNiech f będzie gładkim odwzorowaniem 3-wymiarowej rzeczywistej przestrzeni rzutowej w siebie, r będzie ustaloną liczbą naturalną. W artykule wyznaczona została minimalna liczba punktów r-periodycznych w gładkiej klasie homotopii odwzorowania f.
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Modelling of wastewater treatment plant for monitoring and control purposes by state - space wavelet networks
PublicationMost of industrial processes are nonlinear, not stationary, and dynamical with at least few different time scales in their internal dynamics and hardly measured states. A biological wastewater treatment plant falls into this category. The paper considers modelling such processes for monitorning and control purposes by using State - Space Wavelet Neural Networks (SSWN). The modelling method is illustrated based on bioreactors of...
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Constrained aerodynamic shape optimization using neural networks and sequential sampling
PublicationAerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...
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Józef Woźniak prof. dr hab. inż.
PeopleProfessor Józef Woźniak received his M.Sc., Ph.D. and D.Sc. degrees in electronics and telecommunications from the Faculty of Electronics, Gdańsk University of Technology (GUT), Poland, in 1971, 1976 and 1991, respectively. In January 2002 he became a full professor. In 1993 he was elected Associate Dean of the Faculty of Electronics and in 1994 he was he was appointed a Professor at GUT. Simultaneously, from October 1994 till...
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Combinatorial scheme of finding minimal number of periodic points for smooth self-maps of simply connected manifolds
PublicationLet M be a closed smooth connected and simply connected manifold of dimension m at least 3, and let r be a fixed natural number. The topological invariant D^m_r [f], defined by the authors in [Forum Math. 21 (2009), 491-509], is equal to the minimal number of r-periodic points in the smooth homotopy class of f, a given self-map of M. In this paper, we present a general combinatorial scheme of computing D^m_r [f] for arbitrary dimension...
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Exploiting multi-interface networks: Connectivity and Cheapest Paths
PublicationLet G = (V,E) be a graph which models a set of wireless devices (nodes V) that can communicate by means of multiple radio interfaces, according to proximity and common interfaces (edges E). The problem of switching on (activating) the minimum cost set of interfaces at the nodes in order to guarantee the coverage of G was recently studied. A connection is covered (activated) when the endpoints of the corresponding edge share at...
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Minimal number of periodic points for smooth self-maps of two-holed 3-dimensional closed ball
PublicationDla ciągłego odwzorowania f przestrzeni określonej w tytule w siebie, które posiada rzeczywiste wartości własne na drugiej grupie homologii, wyznaczona została minimalna liczba punktów r-periodycznych w klasie wszystkich gładkich odwzorowań homotopijnych z f.
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An algorithmic approach to estimating the minimal number of periodic points for smooth self-maps of simply-connected manifolds
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General construction of noiseless networks detecting entanglement with the help of linear maps
PublicationW pracy zaprezentowano ogólny schemat konstrukcji bezszumowych sieci pozwalających wykrywać splątanie przy pomocy odwzorowań liniowych. Pokazano jak zastosować metodę do detekcji splątania nieznanego stanu bez jego wcześniejszej rekonstrukcji. W szczególności pokazano, że zawsze istnieje bezszumowa sieć pozwalająca wykrywać splątanie przy użyciu dodatnich, ale nie kompletnie dodatnich odwzorowań. Zaprezentowano także uogólnienie...
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Computer Networks EN 2022
e-Learning CoursesThe student becomes familiar with the network layered logical architectures, classifies the basic problems of network communication and identifies and analyzes selected protocols and mechanisms of LAN and WAN (IP) networks.
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Computer Networks EN 2023
e-Learning CoursesThe student becomes familiar with the network layered logical architectures, classifies the basic problems of network communication and identifies and analyzes selected protocols and mechanisms of LAN and WAN (IP) networks.
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The Use of Artificial Neural Networks and Decision Trees to Predict the Degree of Odor Nuisance of Post-Digestion Sludge in the Sewage Treatment Plant Process
PublicationThis paper presents the application of artificial neural networks and decision trees for the prediction of odor properties of post-fermentation sludge from a biological-mechanical wastewater treatment plant. The input parameters were concentrations of popular compounds present in the sludge, such as toluene, p-xylene, and p-cresol, and process parameters including the concentration of volatile fatty acids, pH, and alkalinity in...
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Journal of Maps
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The regional energy transformation in the context of renewable energy sources potential
PublicationThe topics addressed in the article concern the problem of exploiting the potential of renewable energy sources (RES) at the regional level and the problem of the course of regional energy transition processes. Throughout the world, energy transition proceeds in a specific way for each country, due to the different potential of the selected RES and political, institutional and socio-economic conditions. Energy transition processes...
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Artificial Neural Networks in Microwave Components and Circuits Modeling
PublicationArtykuł dotyczy wykorzystania sztucznych sieci neuronowych (SNN) w projektowaniu i optymalizacji układów mikrofalowych.Zaprezentowano podstawowe zasady i założenia modelowania z użyciem SNN. Możliwości opisywanej metody opisano wykorzystując przykładowyprojekt anteny łatowej. Przedstawiono różne strategie modelowania układów, które wykorzystują możliwości opisywanej metody w połączeniu zwiedzą mikrofalową. Porównano również dokładność...
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Neural networks in the diagnostics of induction motor rotor cages.
PublicationW środowisku Lab VIEW została stworzona aplikacja służąca do pomiaru, prezentacji i zapisu przebiegów widma prądu stojana z uwzględnieniem potrzeb pomiarowych występujących podczas badania wirników silników indukcyjnych przy użyciu sieci neuronowych. Utworzona na bazie zbioru uczącego sieć Kohonena z powodzeniem rozwiązała stawiany przed nią problem klasyfikacji widm prądu stojana, a co za tym idzie również diagnozy stanu...
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Applications of neural networks and perceptual masking to audio restoration
PublicationOmówiono zastosowania algorytmów uczących się w dziedzinie rekonstruowania nagrań fonicznych. Szczególną uwagę zwrócono na zastosowanie sztucznych sieci neuronowych do usuwania zakłócających impulsów. Ponadto opisano zastosowanie inteligentnego algorytmu decyzyjnego do sterowania maskowaniem perceptualnym w celu redukowania szumu.
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Application of neural networks for turbine rotor trajectory investigation.
PublicationW pracy przedstawiono rezultaty badań sieci neuronowych przewidujących trajektorię wirnika turbinowego uzyskanych ze stanowiska turbiny modelowej. Badania wykazały, iż sieci neuronowe wydają się być z powodzeniem zastosowane do przewidywania trajektorii ruchu wirnika turbiny. Najważniejszym zadaniem wydaje się poprawne określenie wektorów sygnałów wejściowych oraz wyjściowych jak również prawidłowe stworzenie sieci neuronowej....
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Co-Living or a “Sandpit” for Future Entrepreneurs. First Experience from Poland.
PublicationNowadays, the Western world seems saturated with the myriad of enhancements for entrepreneurship development. Also, in Eastern European countries we observe a growing number of initiatives at different organizational levels, aiming at accompanying potential future entrepreneurs in their efforts. Meanwhile, there is one novelty, never before offered on the Polish market – the first co- -living space, launched in Gdañsk. Therefore,...
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Software for calculation of noise maps implemented on the supercomputer
PublicationThis paper presents investigation results relevant to the implementation of the algorithms for the calculation of noise maps. The aim of the implementation of the algorithms on the computer cluster is explained. Selected implementation details of the software called the noise propagation model are described. The interaction of the software with the data acquisition system is presented. Noise maps obtained by exploitation of the...
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A Review of Traffic Analysis Attacks and Countermeasures in Mobile Agents' Networks
PublicationFor traditional, message-based communication, traffic analysis has been already studied for over three decades and during that time various attacks have been recognised. As far as mobile agents’ networks are concerned only a few, specific-scope studies have been conducted. This leaves a gap that needs to be addressed as nowadays, in the era of Big Data, the Internet of Things, Smart Infrastructures and growing concerns for privacy,...
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublicationThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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