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Search results for: THERMOELECTRIC GENERATOR (TEG) MAXIMUM POWER POINT TRACKING (MPPT) SWARM INTELLIGENCE (SI) FEED-FORWARD NEURAL NETWORK (FFNN)
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Comparison of single best artificial neural network and neural network ensemble in modeling of palladium microextraction
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High-efficiency hybrid PV-TEG system with intelligent control to harvest maximum energy under various non-static operating conditions
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Neural network based algorithm for hand gesture detection in a low-cost microprocessor applications
PublicationIn this paper the simple architecture of neural network for hand gesture classification was presented. The network classifies the previously calculated parameters of EMG signals. The main goal of this project was to develop simple solution that is not computationally complex and can be implemented on microprocessors in low-cost 3D printed prosthetic arms. As the part of conducted research the data set EMG signals corresponding...
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Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublicationLine heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the...
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International Journal of Swarm Intelligence Research
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Development of a tropical disease diagnosis system using artificial neural network and GIS
PublicationExpert 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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The measurement of input power of power supply in network disturbed by low frequency distortions
PublicationIn the paper authors present results of observation of input power changes versus harmonics amplitude in supply voltage of low-power power supply device. In the study, the electrical measurements supported with thermal imaging were used. The input circuit elements of studied device responsible for input power increase are pointed
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Analysis of mixing rules for the Stillinger-Weber potential: a case study of Ge-Si interactions in the liquid phase
PublicationCiekły stop Ge_{0.25}Si_{0.75} symulowano metodą dynamiki molekularnej, przy użyciu potencjału Stillingera-Webera. Badano wpływ parametryzacji członu potencjału odpowiedzialnego za oddziaływania trójciałowe w trójkach nieidentycznych atomów na strukturę symulowanego stopu. Wpływ ten okazał się być znaczący.Zmiany w parametrach rzędu kilku procent skutkowały istotnymi różnicami w parowych funkcjach rozkładu, kątowych funkcjach rozkładu...
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Optical Sensor Based Gestures Inference Using Recurrent Neural Network in Mobile Conditions
PublicationIn this paper the implementation of recurrent neural network models for hand gesture recognition on edge devices was performed. The models were trained with 27 hand gestures recorded with the use of a linear optical sensor consisting of 8 photodiodes and 4 LEDs. Different models, trained off-line, were tested in terms of different network topologies (different number of neurons and layers) and different effective sampling frequency...
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New Two-center Ellipsoidal Basis Function Neural Network for Fault Diagnosis of Analog Electronic Circuits
PublicationIn the paper a new fault diagnosis-oriented neural network and a diagnostic method for localization of parametric faults in Analog Electronic Circuits (AECs) with tolerances is presented. The method belongs to the class of dictionary Simulation Before Test (SBT) methods. It utilizes dictionary fault signatures as a family of identification curves dispersed around nominal positions by component tolerances of the Circuit Under Test...
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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublicationIn 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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Testing Situation Awareness Network for the Electrical Power Infrastructure
PublicationThe contemporary electrical power infrastructure is exposed to new types of threats. The cause of such threats is related to the large number of new vulnerabilities and architectural weaknesses introduced by the extensive use of Information and Communication Technologies (ICT) in such complex critical systems. The power grid interconnection with the Internet exposes the grid to new types of attacks, such as Advanced Persistent...
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Artificial neural network prophecy of ion exchange process for Cu (II) eradication from acid mine drainage
PublicationThe removal of heavy metal ions from wastewater was found to be significant when the cation exchange procedure was used effectively. The model of the cation exchange process was built using an artificial neural network (ANN). The acid mine drainage waste’s Cu(II) ion was removed using Indion 730 cation exchange resin. Experimental data from 252 cycles were recorded. In a column study, 252 experimental observations validated the...
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Situational Awareness Network for the Electric Power System: the Architecture and Testing Metrics
PublicationThe contemporary electric power system is highly dependent on Information and Communication Technologies which results in its exposure to new types of threats, such as Advanced Persistent Threats (APT) or Distributed-Denial-of-Service (DDoS) attacks. The most exposed components are Industrial Control Systems in substations and Distributed Control Systems in power plants. Therefore, it is necessary to ensure the cyber security of...
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Voltage and frequency regulation of a standalone induction generator by reduced-rating power electronic compensators - comparative evaluation
PublicationIn this paper are considered two fundamental topologies of power electronic compensators for voltage and frequency control of a standalone self-excited induction generator (IG) system. These are voltage and current source inverter based shunt compensators with energy storage. The aim of this study is to assess main features of both topologies in dynamic and steady-state IG operation. The whole system is modelled with the aid of...
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Modelling of the High Speed Multi-Pole Synchronous Generator for Application in More Electric Aircraft Power Systems
PublicationIn this paper different models of the synchronous generator are presented. The simulation results compared with the measurements are shown. Certain physical phenomena are included in described models for the porpoise of adequate analysis of the more electric aircraft power system. For different modelling levels, such as functional level or behavioural level, different physical phenomena have been included. Simulation results for...
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An application of the TCRBF neural network in multi-node fault diagnosis method
PublicationPrzedstawiono nową metodę samo-testowania części analogowej w systemach elektronicznych sterowanych mikrokontrolerami. Układ badany pobudzany jest przebiegiem sinusoidalnym przez generator zamontowany w systemie, a jego odpowiedź jest próbkowana w wybranych węzłach przez wewnętrzny przetwornik A/C mikrokontrolera. Detekcja i lokalizacja uszkodzenia jest dokontwana przez sieć neuronową typu TCRBF. Procedurę diagnostyczną zaimplementowano...
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Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network
PublicationThe 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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Comparison of the Ability of Neural Network Model and Humans to Detect a Cloned Voice
PublicationThe vulnerability of the speaker identity verification system to attacks using voice cloning was examined. The research project assumed creating a model for verifying the speaker’s identity based on voice biometrics and then testing its resistance to potential attacks using voice cloning. The Deep Speaker Neural Speaker Embedding System was trained, and the Real-Time Voice Cloning system was employed based on the SV2TTS, Tacotron,...
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Design of Microstrip UWB Balun Using Quasi-TEM Approach Aided by the Artificial Neural Network
PublicationThe design procedure for UWB balun realized in the microstrip technology is proposed in the paper. The procedure applies Artificial Neural Network which corrects the dimensions of the approximate design found by appropriate scaling of the dimensions of the prototype. The scale coefficients for longitudinal and transverse dimensions of microstrip lines are determined from electromagnetic modeling based on transmission line equations....
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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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Optimal Power Flow Problem Using Particle Swarm Optimization Algorithm
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Swarm Algorithms in Modern Engineering Optimization Problems
PublicationComplexity of today engineering problems is constantly increasing. Scientists no longer are facing issues, for which simple, mathematical programming methods are sufficient. Issues like autonomic vehicle navigation or classification are considered to be challenging, and although there exist valid means to solve them, in some cases there still is some place for improvement. With emergence of a new type of optimization techniques...
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BP-EVD: Forward Block-Output Propagation for Efficient Video Denoising
PublicationDenoising videos in real-time is critical in many applications, including robotics and medicine, where varying light conditions, miniaturized sensors, and optics can substantially compromise image quality. This work proposes the first video denoising method based on a deep neural network that achieves state-of-the-art performance on dynamic scenes while running in real-time on VGA video resolution with no frame latency. The backbone...
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Analysis of application of feed-water injector heaters to steam power plants
PublicationStrumienice parowo-wodne to urządzenia, w których zachodzi wymiana masy, pędu i energii między dwoma płynami, pozostającymi w bezpośrednim kontakcie. Mogą one pracować jako pompy, mieszalniki bądź bezprzeponowe wymienniki ciepła. W tym ostatnim aspekcie są one bardzo interesujące do użycia jako regeneracyjne podgrzewacze wody w obiegu cieplnym Rankina stosowanym w siłowniach parowych na lądzie oraz na morzu (statki i okręty). W...
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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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Review of Methods for Diagnosing the Degradation Process in Power Units Cooperating with Renewable Energy Sources Using Artificial Intelligence
PublicationThis work is based on a literature review (191). It mainly refers to two diagnostic methods based on artificial intelligence. This review presents new possibilities for using genetic algorithms (GAs) for diagnostic purposes in power plants transitioning to cooperation with renewable energy sources (RESs). The genetic method is rarely used directly in the modeling of thermal-flow analysis. However, this assignment proves that the...
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Adaptive Hyperparameter Tuning within Neural Network-based Efficient Global Optimization
PublicationIn 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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The impact of the distribution network reconfiguration on active power losses: Selected issues of UPGRID project realization
PublicationThe dynamic development of smart grids allows the use of remote controllable switches to change the configuration of the distribution network. The paper discusses the impact of the distribution system reconfiguration on active power losses, taking into account the typical daily load profiles. Based on modified IEEE 33-bus test distribution system the article presents the method of selection the appropriate sensitivity factor and...
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Optimization of multiple model neural tracking filter for marine targets
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Verification of multiple model neural tracking filter with ship's radar
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Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublicationWith the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...
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Neural simulator of steam power unit.
PublicationZbadano możliwości zbudowania neuronowego symulatora turbinowego bloku energetycznego. Zamodelowano ten obieg i sprawdzono konfiguracje sztucznych sieci neuronowych (SSN) zapewniające dużą dokładność symulatora neuronowego. Zwrócono uwagę na problemy dotyczące węzłów siłowni, w których następuje mieszanie się strumieni czynnika o zróżnicowanych parametrach cieplno-przepływowych. Wskazano na zastosowanie takiego symulatora w diagnostyce.
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Combined operation of 900MW power plant with the ORC through the bleed steam extraction point and CO2 recovery system
PublicationThe work presented here is aimed at utylisation of waste heat in the reference supercritical power plant in the manner to produce electricity in ORC installation. The waste heat is available in the form of a stream of hot water at 90 C, recovered from the exhaust gases in the amount of 200MW. Such low enthalpy heat source is rather insufficient to produce a good quality vapour to feed the ORC turbine. Therefore an original approach...
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APPLICATION OF STATISTICAL FEATURES AND MULTILAYER NEURAL NETWORK TO AUTOMATIC DIAGNOSIS OF ARRHYTHMIA BY ECG SIGNALS
PublicationAbnormal electrical activity of heart can produce a cardiac arrhythmia. The electrocardiogram (ECG) is a non-invasive technique which is used as a diagnostic tool for cardiac diseases. Non-stationarity and irregu- larity of heartbeat signal imposes many difficulties to clinicians (e.g., in the case of myocardial infarction arrhythmia). Fortunately, signal processing algorithms can expose hidden information within ECG signal contaminated...
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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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Artificial Neural Network for Multiprocessor Tasks Scheduling
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Approximation task decomposition for artificial neural network.
PublicationW pracy przedstawiono wpływ dekompozycji zadania na czasochłonność projektowania oraz dokładność i szybkość obliczeń sztucznej sieci neuronowej wykorzystanej do rozwiązania rzeczywistego problemu technicznego, którego matematyczny model był znany. Celem obliczeń prowadzonych przez sieć neuronową było określenie wartości współczynnika przepływu m na podstawie znajomości wartości: przewodności dźwiękowej C i średnicy przewodu d (a...
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Selection of optimal location and rated power of capacitor banks in distribution network using genetic algorithm
PublicationIn this paper, the problem of placement and rated power of capacitor banks in the Distribution Network (DN) is considered. We try to suggest the best places for installing capacitor banks and define their reactive power. The considered formulation requires the optimization of the cost of two different objectives. Therefore the use of properly multiobjective heuristic optimization methods is desirable. To solve this problem we use...
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Self-Organising map neural network in the analysis of electromyography data of muscles acting at temporomandibular joint.
PublicationThe temporomandibular joint (TMJ) is the joint that via muscle action and jaw motion allows for necessary physiological performances such as mastication. Whereas mandible translates and rotates [1]. Estimation of activity of muscles acting at the TMJ provides a knowledge of activation pattern solely of a specific patient that an electromyography (EMG) examination was carried out [2]. In this work, a Self-Organising Maps (SOMs)...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublicationForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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Comparative Evaluation of Multicoil Inductive Power Transfer Approaches Based on Z-source Network
PublicationThis paper describes comparative evaluation between wireless power transfer topologies with utilization of Z-source network. Paper describes components calculation method. List of open-loop, close-loop simulations were conducted to compare both topologies. Spectrum of signals is also researched.
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Cost-Effective Piggyback Forward dc-dc Converter
PublicationThe novel piggyback dc-dc converter as a cost-effective solution is presented in this work. It provides a wide input voltage range of regulation with a low component count. The novel solution is an advanced forward dc-dc converter with an additional clamp output capacitor. The idea of such a type of converter is to transfer magnetizing energy of transformer to the output side, instead of using input clamp circuit. The design guidelines...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublicationMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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Voltage profiles improvement in a power network with PV energy sources – results of a voltage regulator implementation
PublicationThe constant increase in the number of photovoltaic (PV) energy sources in distribution networks is the cause of serious voltage problems. The networks built at least a dozen years ago are not provided for the installation of a large number of micro-sources. It happens that the previously properly functioning power networks are not able to provide to consumers power with the required parameters, after installing many PV sources....
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Design of synchronous generator two inputs regulator based on hinf control theory.
PublicationThe power system is highly nonlinear system, its dynamics depends on system network configuration, system loading… etc. To overcome the above mentioned difficulties and fulfill the performance requirements the different control methods are considered and tested for design of synchronous generator control system. Application of the H optimization method to synchronous generator regulator based on measurement of generator voltage...
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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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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublicationArtificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained...
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Swarm-Assisted Investment Planning of a Bioethanol Plant
PublicationBioethanol is a liquid fuel for which a significant increase in the share of energy sources has been observed in the economies of many countries. The most significant factor in popularizing bioethanol is the profitability of investments in construction of facilities producing this energy source, as well as the profitability of its supply chain. With the market filled with a large amount of equipment used in the bioethanol production...
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Identification of the Contamination Source Location in the Drinking Water Distribution System Based on the Neural Network Classifier
PublicationThe contamination ingression to the Water Distribution System (WDS) may have a major impact on the drinking water consumers health. In the case of the WDS contamination the data from the water quality sensors may be efficiently used for the appropriate disaster management. In this paper the methodology based on the Learning Vector Quantization (LVQ) neural network classifier for the identification of the contamination source location...