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Search results for: NEURON DYNAMICS
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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublicationThis work proposes a novel adaptive global surrogate modeling algorithm which uses two neural networks, one for prediction and the other for the model uncertainty. Specifically, the algorithm proceeds in cycles and adaptively enhances the neural network-based surrogate model by selecting the next sampling points guided by an auxiliary neural network approximation of the spatial error. The proposed algorithm is tested numerically...
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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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Automatic Breath Analysis System Using Convolutional Neural Networks
PublicationDiseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is common for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected as...
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Deep neural network architecture search using network morphism
PublicationThe paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...
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Automatic Breath Analysis System Using Convolutional Neural Networks
PublicationDiseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is not uncommon for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected...
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Categorization of emotions in dog behavior based on the deep neural network
PublicationThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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Optimization of multiple model neural tracking filter for marine targets
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Deep convolutional neural network for predicting kidney tumour malignancy
PublicationPurpose: According to the statistics, up to 15-20% of removed solid kidney tumors turn out to be benign in postoperative histopathological examination, despite having been identified as malignant by a radiologist. The aim of the research was to limit the number of unnecessary nephrectomies of benign tumors. Methods or Background: We propose a machine-aided diagnostic system for kidney...
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Energy-Efficient Neural Network Inference with Microcavity Exciton Polaritons
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Neural network approach to 2D Kalman filtering in image processing
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Neural networks based NARX models in nonlinear adaptive control
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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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Neural network modelling of the influence of channelopathies on reflex visual attention
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Automatic singing quality recognition employing artificial neural networks
PublicationCelem artykułu jest udowodnienie możliwości automatycznej oceny jakości technicznej głosów śpiewaczych. Pokrótce zaprezentowano w nim stworzoną bazę danych głosów śpiewaczych oraz zaimplementowane parametry. Przy pomocy sztucznych sieci neuronowych zaprojektowano system decyzyjny, który oceniono w pięciostopniowej skali jakość techniczną głosu. Przy pomocy metod statystycznych udowodniono, że wyniki generowane przez ten system...
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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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NIRCa: An artificial neural network-based insulin resistance calculator
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Verification of multiple model neural tracking filter with ship's radar
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Neural Graph Collaborative Filtering: Analysis of Possibilities on Diverse Datasets
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Sympathetic neural responses to coronary occlusion during balloon angioplasty
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Using neural networks to examine trending keywords in Inventory Control
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Prediction of antimicrobial activity of imidazole derivatives by artificial neural networks
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A MODEL FOR FORECASTING PM10 LEVELS WITH THE USE OF ARTIFICIAL NEURAL NETWORKS
PublicationThis work presents a method of forecasting the level of PM10 with the use of artificial neural networks. Current level of particulate matter and meteorological data was taken into account in the construction of the model (checked the correlation of each variable and the future level of PM10), and unidirectional networks were used to implement it due to their ease of learning. Then, the configuration of the network (built on the...
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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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Electromagnetic Modeling of Microstrip Elements Aided with Artificial Neural Network
PublicationThe electromagnetic modeling principle aided withartificial neural network to designing the microwave widebandelements/networks prepared in microstrip technology is proposedin the paper. It is assumed that the complete information is knownfor the prototype design which is prepared on certain substratewith certain thickness and electric permittivity. The longitudinaland transversal dimensions of new design...
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublicationDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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A Bayesian regularization-backpropagation neural network model for peeling computations
PublicationA Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...
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OBTAINING FLUID FLOW PATTERN FOR TURBINE STAGE WITH NEURAL MODEL.
PublicationIn the paper possibility of applying neural model to obtaining patterns of proper operation for fluid flow in turbine stage for fluid-flow diagnostics is discussed. Main differences between Computational Fluid Dynamics (CFD) solvers and neural model is given, also limitations and advantages of both are considered. Time of calculations of both methods was given, also possibilities of shortening that time with preserving the accuracy...
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The impact of the AC922 Architecture on Performance of Deep Neural Network Training
PublicationPractical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...
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Exploring Neural Networks for Musical Instrument Identification in Polyphonic Audio
PublicationThe purpose of this paper is to introduce neural network-based methods that surpass state-of-the-art (SOTA) models, either by training faster or having simpler architecture, while maintaining comparable effectiveness in musical instrument identification in polyphonic music. Several approaches are presented, including two authors’ proposals, i.e., spiking neural networks (SNN) and a modular deep learning model named FMCNN (Fully...
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USING ARTIFICIAL NEURAL NETWORKS FOR PREDICTING SHIP FUEL CONSUMPTION
PublicationIn marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types...
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Artificial neural network based sensorless control ofinduction motor.
PublicationW artykule przedstawiono bezczujnikowy układ sterowania silnikiem indukcyjnym wykorzystujący sztuczne sieci neuronowe (ANN). Sieć neuronową wykorzystano w regulatorze prędkości silnika. Zaprezentowano wyniki badań symulacyjnych.
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Neural Graph Collaborative Filtering: Analysis of Possibilities on Diverse Datasets
PublicationThis paper continues the work by Wang et al. [17]. Its goal is to verify the robustness of the NGCF (Neural Graph Collaborative Filtering) technique by assessing its ability to generalize across different datasets. To achieve this, we first replicated the experiments conducted by Wang et al. [17] to ensure that their replication package is functional. We received sligthly better results for ndcg@20 and somewhat poorer results for...
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Application of neural networks for description of pressure distribution in slide bearing.
PublicationBadano rozkład ciśnienia hydrodynamicznego w łożysku ślizgowym dla wybranych wariantów łożyska. Wykazano, że zastosowanie sieci neuronowych umożliwia opis rozkładu ciśnienia hydrodynamicznego z uwzględnieniem zmian geometrycznych (bezwymiarowa długość - L) i mechanicznych (mimośrodowość względem H) łożyska.
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Identification of slide bearing main parameters using neural networks.
PublicationWykazano, że sieci neuronowe jak najbardziej nadają się do identyfikacji głównych parametrów geometrycznych i ruchowych hydrodynamicznych łożysk ślizgowych.
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Application of a fuzzy neural network for river water quality prediction
PublicationMonitoring i modelowanie zmian w jakości wód powierzchniowych stanowią jeden z kluczowych elementów monitoringu i zarządzania ochroną środowiska na skalę globalną. Kontrolowanie tak złożonych i nieliniowych w swojej charakterystyce obiektów, jakimi są rzeki, jest trudnym zadaniem. Zazwyczaj do tego celu wykorzystuje się modele matematyczne, jednak czasem wymagają one bardzo dużej ilości danych, lub czas oczekiwania na odpowiedź...
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Estimation the rhythmic salience of sound with association rules and neural networks
PublicationW referacie przedstawiono eksperymenty mające na celu automatyczne wyszukiwanie wartości rytmicznych we frazie muzycznej. W tym celu wykorzystano metody data mining i sztuczne sieci neuronowe.
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The fuzzy neural network: application for trends in river pollution prediction
PublicationPraca przedstawia zastosowanie rozmytych sieci neuronowych do przygotowywania prognoz zmian w stężeniu zanieczyszczeń w rzekach. Opisane są pokrótce inne narzędzia stosowane w tym celu.
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Prognozirovanie svojstv betonov s pomoŝ'û iskusstvennyh nejronovyh setej
PublicationObserwacje mózgu ludzkiego oraz podstawowych komórek z jakich się składa (neuronów), doprowadziły do prób modelowania niedużych układów połączonych neuronów. Układy te, zwane w literaturze jako sieci neuronowe lub sieci neuropodobne (ang. neural network) wykazują pewne cechy zbliżone do cech mózgu. Są nimi np. zdolność uczenia i kojarzenia. Choć znany obecnie model matematyczny neuronu jest dość skomplikowany, to zachęcające wyniki...
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Wybrane uwagi o analizie dynamicznej ciała sztywnego i powłok sprężystych. Problemy dynamiki konstrukcji. Zbiór prac XI Międzynarodowego Sympozjum Dynamiki Konstrukcji.
PublicationPraca podejmuje tematykę ruchu kulistego bryły sztywnej i metod jej wyznaczania. Zastosowane procedury numeryczne testowane dla przypadku bryły sztywnej są stosowane do analizy dynamicznej powłok sprężystych na podstawie analogii równań dynamiki.
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Oxygen release from BaLnMn2O6 (Ln: Pr, Nd, Y) under reducing conditions as studied by neutron diffraction
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Long range molecular dynamics study of interactions of the eukaryotic glucosamine-6-phosphate synthase with fructose-6-phosphate and UDP-GlcNAc
PublicationGlucosamine-6-phosphate synthase (EC 2.6.1.16) is responsible for catalysis of the first and practically irreversible step in hexosamine metabolism. The final product of this pathway, uridine 5 diphospho Nacetyl- d-glucosamine (UDP-GlcNAc), is an essential substrate for assembly of bacterial and fungal cell walls. Moreover, the enzyme is involved in phenomenon of hexosamine induced insulin resistance in type II diabetes, which...
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Experimental and Computational Fluid Dynamics Studies on Straight and U-Bend Double Tube Heat Exchangers with Active and Passive Enhancement Methods
PublicationIn this work, the authors wanted to demonstrate the possibility to increase the heat transfer efficiency by using simple wire coil inserts to create turbulent flow in the boundary layer as well as air blowing into the annulus of the pipe. Experimental investigations were carried out for four heat exchanger constructions, i.e., plain double tube, turbulized double tube, plain U-bend double tube, U-tube with turbulator, plain double...
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Dynamics of hepatitis B virus quasispecies heterogeneity in association with nucleos(t)ide analogue treatment determined by MALDI-TOF MS
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Interval estimator for chlorine monitoring in drinking water distribution systems under uncertain system dynamics, inputs and state measurement errors
PublicationThe design of interval observer for estimation of unmeasured state variables for application to drinking water distribution systems is described in this paper. In particular, it considers the design of such observer for estimation of water quality described by free chlorine concentration. An interval observer is derived to produce robust interval bounds on the estimated water quality state variables. The stability and robustness...
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Phonon confinement and interface lattice dynamics of ultrathin high-k rare earth sesquioxide films: the case of Eu2O3 on YSZ(001)
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Arginine-, d-arginine-vasopressin, and their inverso analogues in micellar and liposomic models of cell membrane: CD, NMR, and molecular dynamics studies
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Ergodicity and model quality in template-restrained canonical and temperature/Hamiltonian replica exchange coarse-grained molecular dynamics simulations of proteins
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Structural elucidation of transmembrane transporter protein bilitranslocase: Conformational analysis of the second transmembrane region TM2 by molecular dynamics and NMR spectroscopy
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Tackling Air Pollution in Cities with Modelling and Simulation: Remote Group Model Building as an Educational Tool Supporting System Dynamics Modelling
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Toward mechanosynthesis of diamondoid sructures: viii. quantum-chemical molecular dynamics simulations of hexagonal silicon-iv structure synthesis with stm
Publicationw tej publikacji badano metodami kwantowo-chemicznymi różne strategie mechanosyntezy heksagonalnego krzemu iv. określono przybliżone warunki mechanosyntezy krzemu w formie lonsdaleitu za pomocą uhv-spm.