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Wyniki wyszukiwania dla: MULTILAYER NEURAL NETWORK
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Survivability issues in multilayer networks
PublikacjaW artykule rozważa się zagadnienia zabezpieczenia i odtwarzania w wielowarstwowych architekturach sieciowych w celu osiągnięcia określonego poziomu przeżywalności po awarii węzła lub łącza. Problem optymalizacji polega na znalezieniu dla każdej optycznej ścieżki aktywnej, przenoszącej dany strumień IP, węzłowo-rozłącznej optycznej ścieżki zabezpieczającej w taki sposób, by awaria pojedyńczego węzła lub łącza spowodowana atakiem...
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Adding Interpretability to Neural Knowledge DNA
PublikacjaThis paper proposes a novel approach that adds the interpretability to Neural Knowledge DNA (NK-DNA) via generating a decision tree. The NK-DNA is a promising knowledge representation approach for acquiring, storing, sharing, and reusing knowledge among machines and computing systems. We introduce the decision tree-based generative method for knowledge extraction and representation to make the NK-DNA more explainable. We examine...
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A Novel Iterative Decoding for Iterated Codes Using Classical and Convolutional Neural Networks
PublikacjaForward error correction is crucial for communication, enabling error rate or required SNR reduction. Longer codes improve correction ratio. Iterated codes offer a solution for constructing long codeswith a simple coder and decoder. However, a basic iterative code decoder cannot fully exploit the code’s potential, as some error patterns within its correction capacity remain uncorrected.We propose two neural network-assisted decoders:...
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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublikacjaHandwriting biometrics applications in e-Security and e-Health are addressed in the course of the conducted research. An automated graphomotor analysis method for the dynamic electronic representation of the handwritten signature authentication was researched. The developed algorithms are based on dynamic analysis of electronically handwritten signatures employing neural networks. The signatures were acquired with the use of the...
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublikacjaThe paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...
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A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublikacjaThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
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Generalized access control in hierarchical computer network
PublikacjaThe paper presents the design of the security layer for a distributed system located in the multizone hierarchical computer network. Depending on the zone from which a client’s request comes to the system and the type of the request, it will be either authorized or rejected. There is one common layer for the access to all the business services and interactions between them. Unlike the commonly used RBAC model, this system enforces...
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Maritime Communications Network Development Using Virtualised Network Slicing of 5G Network
PublikacjaThe paper presents the review on perspectives of maritime systems development at the context of 5G systems implementation and their main properties. Firstly, 5G systems requirements and principles are discussed, which can be important for maritime applications. Secondly, the problems of network softwarisation, virtualisation and slicing, and possible types of services for potential implementation in 5G marine applications are described....
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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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Resonance Frequency Calculation of a Multilayer and Multipatch Spherical Microstrip Structure Using a Hybrid Technique
PublikacjaThis communication offers a rigorous analysis of the resonance frequency problem of a spherical microstrip structure mounted on a multilayer, dielectric-coated metallic sphere, with an electrically small radius. The structure consists of single or multiple metallic patches with arbitrary shapes. A full-wave analysis is employed with the use of proposed hybrid approach, combining the finite-difference technique with a spectral domain...
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Iterative Algorithms for Multilayer Optimizing Control
PublikacjaMonografia przedstawia struktury, koncepcje i algorytmy dla wielowarstwowego sterowania optymalizującego procesami przemysłowymi będące w przeważającym stopniu wynikiem badań prowadzonych przez jej autorów. Metodologie i algorytmy sterowania są starannie ilustrowane wynikami symulacji dla wybranych przykładowych systemów. Oprócz tego przedstawione są zastosowania do realnych obiektów przemysłowych: kolumny destylacyjnej etyliny,...
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Towards neural knowledge DNA
PublikacjaIn this paper, we propose the Neural Knowledge DNA, a framework that tailors the ideas underlying the success of neural networks to the scope of knowledge representation. Knowledge representation is a fundamental field that dedicates to representing information about the world in a form that computer systems can utilize to solve complex tasks. The proposed Neural Knowledge DNA is designed to support discovering, storing, reusing,...
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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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A MODEL FOR FORECASTING PM10 LEVELS WITH THE USE OF ARTIFICIAL NEURAL NETWORKS
PublikacjaThis 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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Dynamically positioned ship steering making use of backstepping method and artificial neural networks
PublikacjaThe article discusses the issue of designing a dynamic ship positioning system making use of the adaptive vectorial backstepping method and RBF type arti cial neural networks. In the article, the backstepping controller is used to determine control laws and neural network weight adaptation laws. e arti cial neural network is applied at each time instant to approximate nonlinear functions containing parametric uncertainties....
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublikacjaIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Adsorption-assisted transport of water vapour in super-hydrophobic membranes filled with multilayer graphene platelets
PublikacjaThe effects of confinement of multilayer graphene platelets in hydrophobic microporous polymeric membranes are here examined. Intermolecular interactions between water vapour molecules and nanocomposite membranes are envisaged to originate assisted transport of water vapour in membrane distillation processes when a suitable filler-polymer ratio is reached. Mass transport coefficients are estimated under different working conditions,...
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Application of the neural networks for developing new parametrization of the Tersoff potential for carbon
PublikacjaPenta-graphene (PG) is a 2D carbon allotrope composed of a layer of pentagons having sp2- and sp3-bonded carbon atoms. A study carried out in 2018 has shown that the parameterization of the Tersoff potential proposed in 2005 by Ehrhart and Able (T05 potential) performs better than other potentials available for carbon, being able to reproduce structural and mechanical properties of the PG. In this work, we tried to improve the...
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Automatic Breath Analysis System Using Convolutional Neural Networks
PublikacjaDiseases 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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Automatic Breath Analysis System Using Convolutional Neural Networks
PublikacjaDiseases 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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Neural Modelling of Steam Turbine Control Stage
PublikacjaThe paper describes possibility of steam turbine control stage neural model creation. It is of great importance because wider application of green energy causes severe conditions for control of energy generation systems operation Results of chosen steam turbine of 200 MW power measurements are applied as an example showing way of neural model creation. They serve as training and testing data of such neural model. Relatively simple...
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Analysis of Asymmetrical Rolling Process of Multilayer Plates
PublikacjaW niniejszej pracy przedstawiono wyniki badań numerycznych asymetrycznego procesu walcowania blach wielowarstwowych M1E-Al99,8-AlMg5. Modelowanie numeryczne procesu walcowania blach wielowarstwowych przeprowadzono w programie Forge 2D, którego obliczenia bazują na metodzie elementów skończonych. Przedstawione w pracy wyniki umożliwiły przeprowadzenie analizy procesu walcowania blach wielowarstwowych.
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Multilayer thermal model of healty and burned skin
PublikacjaW pracy przedstawiono spójny model cieplny skóry wraz z tkankami podskórnymi, na podstawie pomiarów "in vitro" na świni domowej. Model uwzględnia rozkład temperatury, przewodności cieplnej oraz efuzyjności i dyfuzyjności cieplnej w funkcji głębokości, zarówno dla skóry zdrowej jak i oparzonej.
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Integrated protection/restoration in survivable multilayer architectures
PublikacjaArtykuł przedstawia nową koncepcję projektowania wielowarstwowych architektur sieci przeżywalnych, wykorzystującą informację międzywarstwową do zabezpieczania odtwarzania na wypadek pojedyńczej awarii węzła lub łącza w sposob zapobiegający propagacji awarii. Oryginalne zadanie optymalizacji całej zintegrowanej architektury przeżywalnej sformułowano jako zadanie programowania całkowitego. Jest ono NP-zupełne i zaproponowano algorytm...
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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublikacjaThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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Clothes Detection and Classification Using Convolutional Neural Networks
PublikacjaIn this paper we describe development of a computer vision system for accurate detection and classification of clothes for e-commerce images. We present a set of experiments on well established architectures of convolutional neural networks, including Residual networks, SqueezeNet and Single Shot MultiBox Detector (SSD). The clothes detection network was trained and tested on DeepFashion dataset, which contains box annotations...
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Automatic singing quality recognition employing artificial neural networks
PublikacjaCelem 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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Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks
PublikacjaIn 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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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublikacjaIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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Hybrid of Neural Networks and Hidden Markov Models as a modern approach to speech recognition systems
PublikacjaThe aim of this paper is to present a hybrid algorithm that combines the advantages ofartificial neural networks and hidden Markov models in speech recognition for control purpos-es. The scope of the paper includes review of currently used solutions, description and analysis of implementation of selected artificial neural network (NN) structures and hidden Markov mod-els (HMM). The main part of the paper consists of a description...
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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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Application of Numerical Simulations on 10GN2MFA Steel Multilayer Welding
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Numerical Simulations of X22CrMoV12-1 Steel Multilayer Welding
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Algorithms of fast service restoration in survivable multilayer networks
PublikacjaGłównym celem rozprawy jest zaproponowanie nowych modeli/algorytmów doboru tras zapewniających przeżywalność usług w sieciach IP-MPLS/WDM poprzez zastosowanie wyznaczonych zawczasu ścieżek zabezpieczających. Zakres pracy obejmuje: dokonanie przeglądu mechanizmów transmisji informacji w warstwowych sieciach teleinformatycznych IP-MPLS/WDM; szczegółowy opis sposobów zapewniania przeżywalności usług; zaproponowanie nowych metod doboru...
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Blood Pressure Estimation Based on Blood Flow, ECG and Respiratory Signals Using Recurrent Neural Networks
PublikacjaThe 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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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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Architectural Modifications to Enhance Steganalysis with Convolutional Neural Networks
PublikacjaThis paper investigates the impact of various modifications introduced to current state-of-the-art Convolutional Neural Network (CNN) architectures specifically designed for the steganalysis of digital images. Usage of deep learning methods has consistently demonstrated improved results in this field over the past few years, primarily due to the development of newer architectures with higher classification accuracy compared to...
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OBTAINING FLUID FLOW PATTERN FOR TURBINE STAGE WITH NEURAL MODEL.
PublikacjaIn 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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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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Collision-Free Network Exploration
PublikacjaA set of mobile agents is placed at different nodes of a n-node network. The agents synchronously move along the network edges in a collision-free way, i.e., in no round may two agents occupy the same node. In each round, an agent may choose to stay at its currently occupied node or to move to one of its neighbors. An agent has no knowledge of the number and initial positions of other agents. We are looking for the shortest possible...
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Collision-free network exploration
PublikacjaMobile agents start at different nodes of an n-node network. The agents synchronously move along the network edges in a collision-free way, i.e., in no round two agents may occupy the same node. An agent has no knowledge of the number and initial positions of other agents. We are looking for the shortest time required to reach a configuration in which each agent has visited all nodes and returned to its starting location. In...
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Bees Detection on Images: Study of Different Color Models for Neural Networks
PublikacjaThis paper presents an approach to bee detection in video streams using a neural network classifier. We describe the motivation for our research and the methodology of data acquisition. The main contribution to this work is a comparison of different color models used as an input format for a feedforward convolutional architecture applied to bee detection. The detection process has is based on a neural binary classifier that classifies...
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Adding Intelligence to Cars Using the Neural Knowledge DNA
PublikacjaIn this paper we propose a Neural Knowledge DNA based framework that is capable of learning from the car’s daily operation. The Neural Knowledge DNA is a novel knowledge representation and reasoning approach designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing devices. We examine our framework for drivers' classification based on their driving behaviour. The experimental...
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APPLICATION OF NUMERICAL SIMULATIONS ON X10CRWMOVNB9-2 STEEL MULTILAYER WELDING
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New Approach to the Designing of Curtains – Decorative Multilayer Woven Structures
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Investigation of multilayer three-strip coplanar lines with the ferrite material
PublikacjaW artykule opisano wyniki badań przeprowadzonych nad wielowarstwową linią koplanarną zawierającą trzy paski umieszczone na podłużnie magnesowanym ferrycie. Analiza opiera się o metodę rodzajów sprzężonych. Uzyskane rezultaty zostały zweryfikowane eksperymentalnie.
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An Analysis of Elliptical-Rectangular Patch Structure on Multilayer Elliptic Cylinders
PublikacjaThe resonance frequency problem of an ellipticalrectangular patch mounted on multilayered dielectric coated elliptic conducting cylinder, is investigated in this paper. A fullwave analysis and a moment-method calculation are employed. The analysis is carried out considering the expansion of the field as a series of Mathieu functions. An additional theorem for Mathieu functions is utilized to investigate the non-confocal ellipse...
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EMULACJA ŚRODOWISKA DLA ZASTOSOWANIA PROTOKOŁU IN-BAND NETWORK TELEMETRY
PublikacjaOkreślenie jakości obsługi strumieni pakietów w sieci przełączników wymaga odpowiedniego środowiska badawczego w którym prowadzi się doświadczenia i pomiary wybranych wielkości. Protokół In-band Network Telemetry jest jednym z narzędzi, które można wykorzystać do realizacji tych zadań. W pracy zaproponowano zwirtualizowane środowisko badawcze w którym można emulować sieć przełączników programowalnych w języku P4 wraz z implementacją...
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Toward Intelligent Recommendations Using the Neural Knowledge DNA
PublikacjaIn this paper we propose a novel recommendation approach using past news click data and the Neural Knowledge DNA (NK-DNA). The Neural Knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for news recommendation tasks on the MIND benchmark dataset. By taking advantages of NK-DNA, deep...
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Diagnosis of damages in family buildings using neural networks
PublikacjaThe article concerns a problem of damages in family buildings, which result from traffic-induced vibrations. These vibrations arise from various causes and their size is influenced by many factors. The most important is the type of a road, type and weight of vehicles that run on the road, type and condition of the road surface, the distance from the house to the source of vibrations and many others which should be taken into account....