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Wyniki wyszukiwania dla: NEURON MODELS
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Chosen aspects of skeletal system modeling: Numerical solid and shell models of femur part
PublikacjaThe purpose of this paper is to present a new method of femur part modeling by using the finite element method. This method treats a femur part as a system composed of cortical and trabecular bone. For the purpose of determining a proper shape of femur part model there were created three models: a) the first one describes a femur part as a solid structure; b) the second one describes a femur part as a connection of cortical bone...
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Macro models of casualties in road transport. Modelowanie strat osobowych w transporcie drogowym.
PublikacjaW referacie przedstawiono propozycję makro modelu strat osobowych ponoszonych w wypadkach drogowych. Zaproponowano modele liczby ofiar śmiertelnych wypadków drogowych zbudowanych na bazie danych z kilkudziesięciu krajów całego świata. Przedstawione koncepcje budowy modeli mogą posłużyć do opracowania modeli czynnikowych opisujących strategiczne ryzyko społeczne na sieci dróg wybranych krajów z całego świata. jedną z koncepcji...
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Fast EM-driven optimization using variable-fidelity EM models and adjoint sensitivities
PublikacjaA robust and computationally efficient technique for microwave design optimization is presented. Our approach exploits variable-fidelity electromagnetic (EM) simulation models and adjoint sensitivities. The low-fidelity EM model correction is realized by means of space mapping (SM). In the optimization process, the SM parameters are optimized together with the design itself, which allows us to keep the number...
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Optimal shape design of multi-element trawl-doors using local surrogate models
PublikacjaTrawl-doors have a large influence on the fuel consumption of fishing vessels. Design and optimiza-tion of trawl-doors using computational models are a key factor in minimizing the fuel consump-tion. This paper presents an optimization algorithm for the shape design of trawl-door shapes using computational fluid dynamic (CFD) models. Accurate CFD models are computationally expensive. Therefore, the direct use of traditional optimization...
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Efficient knowledge-based optimization of expensive computational models using adaptive response correction
PublikacjaComputer simulation has become an indispensable tool in engineering design as they allow an accurate evaluation of the system performance. This is critical in order to carry out the design process in a reliable manner without costly prototyping and physical measurements. However, high-fidelity computer simulations are computationally expensive. This turns to be a fundamental bottleneck when it comes to design automation using numerical...
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Parameters’ Identification of Perzyna and Chaboche Viscoplastic Models for Aluminum Alloy at Temperature of 120◦C
PublikacjaThe main purpose of this paper is the parameters identification of the Perzyna and the Chaboche models for the aluminum alloy at elevated temperature. The additional purpose is comparison of the results for these viscoplastic models. The results have been verified by the numerical simulation of the laboratory tests. The material parameters have been calculated on the basis of the uniaxial tension test. The determination of the...
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Rapid design optimization of antennas using variable-fidelity EM models and adjoint sensitivities
PublikacjaPurpose – Development of techniques for expedited design optimization of complex and numerically expensive electromagnetic (EM) simulation models of antenna structures validated both numerically and experimentally. The paper aims to discuss these issues. Design/methodology/approach – The optimization task is performed using a technique that combines gradient search with adjoint sensitivities, trust region framework, as well as...
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Integration and Visualization of the Results of Hydrodynamic Models in the Maritime Network-Centric GIS of Gulf of Gdansk
PublikacjaEnsuring of security in the coastal area makes on a seaside countries research in the field of infrastructure spatial information of environmental data. The paper presents the results of work on the construction of this infrastructure by integrating electronic navigational chart with ortophotomaps of coastal areas as well as numerical data from weather and hydrodynamic models. Paper focuses on a problems associated with creating...
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Expedited two-objective dimension scaling of compact microwave passives using surrogate models
PublikacjaGeometry scaling of compact microwave structures is a challenging problem because of complex relationships between the physical dimensions and electrical characteristics, mostly caused by considerable cross-couplings in densely arranged layouts. Here, a procedure for expedited dimension scaling of compact microwave couplers with respect to two independent criteria has been presented. Our approach involves inverse surrogate models...
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Correlation–polarization effects in electron/positron scattering from acetylene: A comparison of computational models
PublikacjaDifferent computational methods are employed to evaluate elastic (rotationally summed) integral and differential cross sections for low energy (below about 10 eV) positron scattering off gas-phase C2H2 molecules. The computations are carried out at the static and static-plus-polarization levels for describing the interaction forces and the correlation–polarization contributions are found to be an essential component for the correct...
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Selection of AHI + SC Hybrid Storage Based on Mathematical Models and Load Variation Characteristics
PublikacjaThe article deals with the design of a hybrid storage consisting of Aqueous Hybrid Ion battery (AHI) and supercapacitor (SC) modules. The selection of components is based on the knowledge of the load profile of the storage and the AHI battery and supercapacitor models. The paper presents the method of selecting components of the storage made of AHI batteries and supercapacitor modules The article includes an example of the hybrid...
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Application of Diffusion Models in the Analysis of Financial Markets: Evidence on Exchange Traded Funds in Europe
PublikacjaExchange traded funds (ETFs) are financial innovations that may be considered as a part of the index financial instruments category, together with stock index derivatives. The aim of this paper is to explore the trajectories and formulates predictions regarding the spread of ETFs on the financial markets in six European countries. It demonstrates ETFs’ development trajectories with regard to stock index futures and options that...
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Fast Multi-Objective Aerodynamic Optimization Using Sequential Domain Patching and Multifidelity Models
PublikacjaExploration of design tradeoffs for aerodynamic surfaces requires solving of multi-objective optimization (MOO) problems. The major bottleneck here is the time-consuming evaluations of the computational fluid dynamics (CFD) model used to capture the nonlinear physics involved in designing aerodynamic surfaces. This, in conjunction with a large number of simulations necessary to yield a set of designs representing the best possible...
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The Effect of the Selection of Three-Dimensional Random Numerical Soil Models on Strip Foundation Settlements
PublikacjaThis paper delivers a probabilistic attempt to prove that the selection of a random three-dimensional finite element (FE) model of a subsoil affects the computed settlements. Parametricanalysis of a random soil block is conducted, assuming a variable subsoil Young’s modulus inparticular finite elements. The modulus is represented by a random field or different-sized setsof random variables; in both cases, the same truncated...
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Equivalent Single Layer Models in Free Vibration Analysis of Laminated Multi-Layered Plates
PublikacjaThe performance of selected equivalent single-layer (ESL) models is evaluated within several classical benchmark tests for small amplitude free vibration analysis of multi-layered plates. The authors elaborated their own Finite Element software based on the first-order shear deformation (FOSD) theory with some modifications incorporated including a correction of the transverse shear stiffness and an application of zigzag type functions....
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Experimental study on models of cylindrical steel tanks under mining tremors and moderate earthquakes
PublikacjaThe aim of the study is to show the results of complex shaking table experimental investigation focused on the response of two models of cylindrical steel tanks under mining tremors and moderate earthquakes, including the aspects of diagnosis of structural damage. Firstly, the impact and the sweep-sine tests have been carried out, so as to determine the dynamic properties of models filled with different levels of liquid. Then,...
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Macro Models of Casualties in Road Transport / Modelowanie Strat Osobowych W Transporcie Drogowym
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Predicting the impact of traffic–induced vibrations on buildings using artificial neural networks
PublikacjaTraffic–induced vibrations may constitute a considerable load to a building, cause cracking of plaster, cracks in load–bearing elements or even a global structural collapse of the whole structure [1-4]. Vibrations measurements of real structures are costly and laborious, not justified in all cases. The aim of the paper is to create an original algorithm, to predict the negative dynamic impact on the examined residential building...
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THE CONCEPT OF MODELING OF SNOW IMPACT ON THE STRUCTURE OF THE SUSPENDED TAURON ARENA ROOF IN CRACOW
PublikacjaThe article presents studies and numerical simulations on modeling snow influence on TAURON ARENA suspended roof structure in Cracow. The scope of work includes experimental tests, functions solutions taking into account various cases of snow impact according to PN and EC, as well as numerical simulations for the sport and entertainment arena in the Czyzyny district. The FEM roof structure model developed in the SOFISITK software...
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Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network
PublikacjaThe goal of this research is to find a way of highlighting the acoustic differences between consonant phonemes of the Polish and Lithuanian languages. For this purpose, similarity matrices are employed based on speech acoustic parameters combined with a convolutional neural network (CNN). In the first experiment, we compare the effectiveness of the similarity matrices applied to discerning acoustic differences between consonant...
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Diagnosing wind turbine condition employing a neural network to the analysis of vibroacoustic signals
PublikacjaIt is important from the economic point of view to detect damage early in the wind turbines before failures occur. For this purpose, a monitoring device was built that analyzes both acoustic signals acquired from the built-in non-contact acoustic intensity probe, as well as from the accelerometers, mounted on the internal devices in the nacelle. The signals collected in this way are used for long-term training of the autoencoder...
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Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening
PublikacjaBeta-glucosidase inhibitors play important medical and biological roles. In this study, simple two-variable artificial neural network (ANN) classification models were developed for beta-glucosidase inhibitors screening. All bioassay data were obtained from the ChEMBL database. The classifiers were generated using 2D molecular descriptors and the data miner tool available in the STATISTICA package (STATISTICA Automated Neural...
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Neuronal Nitric Oxide Synthase Induction in the Antitumorigenic and Neurotoxic Effects of 2-Methoxyestradiol
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Aerodynamic excitations generated in turbine shroud clearance determined bymeans of neural networks
PublikacjaSiły aerodynamiczne generowane w uszczelnieniach turbinowych z reguły opisywane są modelem liniowym. Przy dużych drganiach wirnika sposób ten daje niezbyt dokładne wyniki. Zaproponowano wykorzystanie sieci neuronowych do określania sił ciśnieniowych powstających w uszczelnieniu. Wyniki porównano z badaniami eksperymentalnymi.
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Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks
PublikacjaThe presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods....
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublikacjaThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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Adaptive Hyperparameter Tuning within Neural Network-based Efficient Global Optimization
PublikacjaIn this paper, adaptive hyperparameter optimization (HPO) strategies within the efficient global optimization (EGO) with neural network (NN)-based prediction and uncertainty (EGONN) algorithm are proposed. These strategies utilize Bayesian optimization and multiarmed bandit optimization to tune HPs during the sequential sampling process either every iteration (HPO-1itr) or every five iterations (HPO-5itr). Through experiments using...
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Application of fuzzy neural network for supporting measurements and control in a wastewater treatment plant
PublikacjaOczyszczanie ścieków jest jednym z ważniejszych aspektów ochrony środowiska. Nowoczesne systemy kontroli w oczyszczalniach ścieków pozwalają na poprawę jakości procesu oczyszczania redukując jednocześnie koszty. Systemy kontroli i optymalizacji jakie odkilku lat opracowuje się dla oczyszczalni ścieków, bazują zazwyczaj na skomplikowanych modelach matematycznych. Kluczowym problemem w zastosowaniu tych systemów jest duża liczba...
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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublikacjaA 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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Distinct hippocampal-prefrontal neural assemblies coordinate memory encoding, maintenance, and recall
PublikacjaShort-term memory enables incorporation of recent experience into subsequent decision-making. This processing recruits both the prefrontal cortex and hippocampus, where neurons encode task cues, rules, and outcomes. However, precisely which information is carried when, and by which neurons, remains unclear. Using population decoding of activity in rat medial prefrontal cortex (mPFC) and dorsal hippocampal CA1, we confirm that mPFC...
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Artificial Neural Networks in Classification of Steel Grades Based on Non-Destructive Tests
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Designing the Composition of Cement Stabilized Rammed Earth Using Artificial Neural Networks
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The Influence of Input Data Standardization Method on Prediction Accuracy of Artificial Neural Networks
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Leveraging Training Strategies of Artificial Neural Network for Classification of Multiday Electromyography Signals
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Adsorption chiller in a combined heating and cooling system: simulation and optimization by neural networks
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Self-organizing Artificial Neural Networks into Hydrographic Big Data Reduction Process
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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublikacjaThis paper contains research results of the diagnostics of induction motor bearings based on measurement of the supply current with usage of artificial neural networks. Bearing failure amount is greater than 40% of all engine failures, which makes their damage-free operation crucial. Tests were performed on motors with intentionally made bearings defects. Chapter 2 introduces the concept of artificial neural networks. It presents...
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Application of spatial neural simulators of turbine blade rows to fluid flow diagnostics
PublikacjaThis chapter presents the results of neural modelling of fluid flow in steam turbine row. In modelling working conditions of the flow channel varied, thus the aim of the work was to reconstruct the reference state - distributions of velocity, pressure, and losses in flow channel - with high accuracy for fluid flow diagnostics.
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Multi-Camera Vehicle Tracking Using Local Image Features and Neural Networks
PublikacjaA method for tracking moving objects crossing fields of view of multiple cameras is presented. The algorithm utilizes Artificial Neural Networks (ANNs). Each ANN is trained to recognize images of one moving object acquired by a single camera. Local image features calculated in the vicinity of automatically detected interest points are used as object image parameters. Next, ANNs are employed to identify the same objects captured...
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The application of neural networks in forecasting the influence of traffic-induced vibrations on residential buildings
PublikacjaTraffic-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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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublikacjaIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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System for monitoring road slippery based on CCTV cameras and convolutional neural networks
PublikacjaThe slipperiness of the surface is essential for road safety. The growing number of CCTV cameras opens the possibility of using them to automatically detect the slippery surface and inform road users about it. This paper presents a system of developed intelligent road signs, including a detector based on convolutional neural networks (CNNs) and the transferlearning method employed to the processing of images acquired with video...
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Physics-guided neural networks (PGNNs) to solve differential equations for spatial analysis
PublikacjaNumerous examples of physically unjustified neural networks, despite satisfactory performance, generate contradictions with logic and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage involves extending...
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Neural Oscillation During Mental Imagery in Sport: An Olympic Sailor Case Study
PublikacjaThe purpose of the current study was to examine the cortical correlates of imagery depending on instructional modality (guided vs. self-produced) using various sports-related scripts. According to the expert-performance approach, we took an idiosyncratic perspective analyzing the mental imagery of an experienced two-time Olympic athlete to verify whether different instructional modalities of imagery (i.e., guided vs. self-produced)...
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Development of a tropical disease diagnosis system using artificial neural network and GIS
PublikacjaExpert systems for diagnosis of tropical diseases have been developed and implemented for over a decade with varying degrees of success. While the recent introduction of artificial neural networks has helped to improve the diagnosis accuracy of such systems, this aspect is still negatively affected by the number of supported diseases. A large number of supported diseases usually corresponds to a high number of overlapping symptoms,...
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Heavy duty vehicle fuel consumption modelling using artificial neural networks
PublikacjaIn 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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EURO Journal on Decision Processes
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EURO Journal on Transportation and Logistics
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EURO Journal on Computational Optimization
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Objectivity in the non-Markovian spin-boson model
PublikacjaObjectivity constitutes one of the main features of the macroscopic classical world. An important aspect of the quantum-to-classical transition issue is to explain how such a property arises from the microscopic quantum theory. Recently, within the framework of open quantum systems, there has been proposed such a mechanism in terms of the so-called spectrum broadcast structures. These are multipartite quantum states of the system...