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Search results for: RESIDUAL NEURAL NETWORK
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Applying artificial neural networks for modelling ship speed and fuel consumption
PublicationThis paper deals with modelling ship speed and fuel consumption using artificial neural network (ANN) techniques. These tools allowed us to develop ANN models that can be used for predicting both the fuel consumption and the travel time to the destination for commanded outputs (the ship driveline shaft speed and the propeller pitch) selected by the ship operator. In these cases, due to variable environmental conditions, making...
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Microstructure and residual stresses in surface coatings with PTFE reservoirs
PublicationThe paper presents the results of experimental study into the microstructure and changes in residual stresses resulting from sliding and rolling/sliding loaded interaction between metallic surface coatings with embedded PTFE reservoirs and various counter faces. It was found that before testing surface coatings had compressive residual stresses. Molybdenum coating with all types of PTFE reservoirs displayed, as a result of testing,...
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Ship Resistance Prediction with Artificial Neural Networks
PublicationThe paper is dedicated to a new method of ship’s resistance prediction using Artificial Neural Network (ANN). In the initial stage selected ships parameters are prepared to be used as a training and validation sets. Next step is to verify several network structures and to determine parameters with the highest influence on the result resistance. Finally, other parameters expected to impact the resistance are proposed. The research utilizes...
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Comparative study of neural networks used in modeling and control of dynamic systems
PublicationIn this paper, a diagonal recurrent neural network that contains two recurrent weights in the hidden layer is proposed for the designing of a synchronous generator control system. To demonstrate the superiority of the proposed neural network, a comparative study of performances, with two other neural network (1_DRNN) and the proposed second-order diagonal recurrent neural network (2_DRNN). Moreover, to confirm the superiority...
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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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Neural Architecture Search for Skin Lesion Classification
PublicationDeep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture. This is a tedious and time-consuming process that requires expert knowledge. Different tasks need very different architectures to obtain satisfactory results. The group of methods called the neural architecture search (NAS) helps to find effective architecture...
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A survey of neural networks usage for intrusion detection systems
PublicationIn recent years, advancements in the field of the artificial intelligence (AI) gained a huge momentum due to the worldwide appliance of this technology by the industry. One of the crucial areas of AI are neural networks (NN), which enable commer‐ cial utilization of functionalities previously not accessible by usage of computers. Intrusion detection system (IDS) presents one of the domains in which neural networks are widely tested...
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Detection of high frequency current components by residual current devices
PublicationThe negative impact of current harmonics on the main components of residual current devices is presented. A solution for the improvement of the operation of residual current devices is proposed.
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Residual current devices in installations with PV energy sources
PublicationThe paper presents the principles of residual current devices (RCDs) application in photovoltaic (PV) installations. Provisions of standards in this regard are commented on, in particular, attention is drawn to the lack of obligation to use of RCDs in PV installations. The issue of the shape of the earth fault current and the level of leakage currents in such installations are discussed. These factors influence the selection of...
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Deep neural networks for data analysis
e-Learning CoursesThe aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...
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Adding Interpretability to Neural Knowledge DNA
PublicationThis 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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Tripping limitations of residual current devices in photovoltaic installations
PublicationIn electrical installations with photovoltaic sources of energy, earth fault current may comprise alternating current component and direct current component. The waveform shape of this earth fault current mainly depends on the point of the fault and the properties of a photovoltaic power electronics converter. The waveform shape of the current influences operation of protection devices, especially tripping threshold of residual...
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Residual current devices in electric vehicles charging installations
PublicationThe main requirements of national regulations and international standards regarding protection against electric shock in electric vehicle charging installations are presented. The principles of using residual current devices (RCDs) in such installations are discussed. It is pointed out that RCDs are mandatory equipment for safe charging of electric vehicles. It is noted that the standards require the use of RCDs having an appropriate...
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The effect of current delay angle on tripping of residual current devices
PublicationPower electronics converters applied in domestic or similar installations may utilize current delay (phase) angle control to change the level of transferred power. Due to application of such types of converters, earth fault current in the installation may be strongly distorted. The current distortion level depends on a value of current delay angle. This delay angle also influences the tripping threshold of residual current devices....
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A Novel Iterative Decoding for Iterated Codes Using Classical and Convolutional Neural Networks
PublicationForward 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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Tripping of F-type RCDs for High-Frequency Residual Currents
PublicationResidual current devices (RCDs) are apparatus commonly used for protection against electric shock in low-voltage electrical installations. They protect people in the case of an earth fault or even in the case of direct contact with the live parts. However, to be effective protective devices, RCDs have to detect residual currents of various waveform shapes which appear in modern electrical installations. For this purpose, RCDs...
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Tripping of F-type RCDs for high-frequency residual currents
PublicationResidual current devices (RCDs) are apparatus commonly used for protection against electric shock in low-voltage electrical installations. They protect people in the case of an earth fault or even in the case of direct contact with the live parts. However, to be effective protective devices, RCDs have to detect residual currents of various waveform shapes which appear in modern electrical installations. For this purpose, RCDs are...
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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublicationHandwriting 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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Requirements for Residual Current Devices Intended for Electric Vehicle Charging Systems
PublicationThe properties of residual current devices have been presented from the point of view of their ability to detect a specific shape of the residual current waveform. Moreover, the standard requirements relating to residual current protection used in electric vehicle charging installations have been pointed out. The operating characteristics of the IC-CPD and RDC-DD protections, which are intended for charging electric vehicles in...
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Improving sensitivity of residual current transformers to high frequency earth fault currents
PublicationFor protection against electric shock in low voltage systems residual current devices are commonly used. However, their proper operation can be interfered when high frequency earth fault current occurs. Serious hazard of electrocution exists then. In order to detect such a current, it is necessary to modify parameters of residual current devices, especially the operating point of their current transformer. The authors proposed...
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublicationThe 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
PublicationThis 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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Maritime Communications Network Development Using Virtualised Network Slicing of 5G Network
PublicationThe 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
PublicationA 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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Immunity of residual current devices to the impulse leakage current in circuits with variable speed drives
PublicationThis paper concerns reliability of supply in variable speed drive circuits with residual current devices. During normal operation of these circuits high value of leakage current causes unwanted tripping of residual current devices. Immunity of residual current devices to the impulse leakage current should be evaluated. The system for testing of residual current devices and results of the test are presented
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RCDs Tripping in the Range from DC to AC 50 kHz for Slowly Rising Residual Current
PublicationThe wide use of power electronic converters means that in many low-voltage systems earth fault currents containing components from DC to AC of various frequencies have to be taken into account. Due to the tendency to increase the modulation frequency in converters, components of higher frequencies may be in the order of several tens of kilohertz. Therefore, it is very important to verify the behavior of devices for protection against...
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An investigation on residual stress and fatigue life assessment of T-shape welded joints
PublicationThis paper aims to quantitatively evaluate the residual stress and fatigue life of T-type welded joints with a multi-pass weld in different direction. The main research objectives of the experimental test were to test the residual stress by changing direction along with multiple wielding passes and determine the fatigue life of the welded joints. The result shows that compressive residual stress increases in the sample gradually...
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Towards neural knowledge DNA
PublicationIn 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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Methods of Network Resource Provisioning for the Future Internet IIP Initiative
PublicationIn this paper, we present specification, design and implementation aspects of a network resource provisioning module introduced for the Polish Initiative of Future Internet called System IIP. In particular, we propose a set of novel LP optimization models of network resource provisioning designed to minimize the network resource consumption, either bandwidth or node’s computational power, as well as to maximize the residual capacity....
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Identification of residual force in static load tests on instrumented screw displacement piles
PublicationOccurrence of the so-called residual force of an unknown value significantly disturbs interpretation of static load tests performed on piles equipped with additional measuring instruments. Screw displacement piles are the piling technology in which the residual force phenomenon is very common. Its formation mechanism is closely related to the installation method of this type of piles, which initiates generation of negative pile...
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Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks
PublicationThe 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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Modification of the operating point of residual current transformers for high frequency earth fault currents detection
PublicationFor protection against electric shock in low voltage systems residual current devices are commonly used. However, their proper operation can be interfered when earth fault current with high frequency components occurs. Serious hazard of electrocution exists then. One of the most important element of residual current devices is a residual current transformer with iron core. Tripping characteristic of residual current devices strictly...
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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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Dynamically positioned ship steering making use of backstepping method and artificial neural networks
PublicationThe 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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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublicationThis 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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Behavior of residual current devices at frequencies up to 50 kHz
PublicationThe use of residual current devices (RCDs) is obligatory in many types of low-voltage circuits. They are devices that ensure protection against electric shock in the case of indirect contact and may ensure additional protection in the case of direct contact. For the latter purpose of protection, only RCDs of a rated residual operating current not exceeding 30 mA are suitable. Unfortunately, modem current-using equipment supplied...
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Verification of safety in low-voltage power systems without nuisance tripping of residual current devices
PublicationLow-voltage power systems require initial and periodical verification to check the effectiveness of protection against electric shock. As a protection in case of fault, automatic disconnection of supply is most often used. To verify such a protection measure, the earth fault loop impedance or resistance is measured. This measurement is easy to perform in circuits without residual current devices. When residual current devices are...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublicationIn 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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Marzena Starnawska dr
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Application of the neural networks for developing new parametrization of the Tersoff potential for carbon
PublicationPenta-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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Evaluation of applicability of classic methods of a fault loop impedance measurement to circuits with residual current devices
PublicationMeasurement of fault loop impedance in low voltage grids and systems is in most cases performed to verify the effectiveness of protection against electric shock by automatic disconnection of supply. For the sake of measurement accuracy, it is advisable to perform it using large current. Unfortunately, in circuits with residual current devices which are very widely used nowadays, a large measurement current may trigger those devices...
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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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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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Behavior of residual current devices at earth fault currents with DC component
PublicationLow-voltage electrical installations are increasingly saturated with power electronic converters. Due to very high popularity of photovoltaic (PV) installations and the spread of electric vehicles (EV) as well as their charging installations, DC–AC and AC–DC converters are often found in power systems. The transformerless coupling of AC and DC systems via power electronic converters means that an electrical installation containing...
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Neural Modelling of Steam Turbine Control Stage
PublicationThe 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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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublicationThe 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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Fatigue life improvement using low transformation temperature weld material with measurement of residual stress
PublicationWelding processes often produce high levels of tensile residual stress. Low transformation temperature (LTT) welding wires utilise phase transformation strains to overcome the thermal contraction of a cooling weld. In this paper, the residual stress within each weld was quantified using the milling/strain gauge method, being the strain change measured as the weldment was milled away. The fatigue tests were conducted under uniaxial...
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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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Experimental verification of a new method of loop resistance testing in low voltage systems with residual current devices
PublicationA periodical verification of the effectiveness of protection against electric shock shall be performed in low voltage systems. The scope of this verification includes loop impedance/resistance testing. If a residual current device is installed in a tested circuit, this testing is problematic. A residual current device trips out during the test, because of the high value of measurement current. This precludes the execution of the...
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