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Search results for: LOMBARD EFFECT, SPEECH DETECTION, NOISE SIGNAL, SELF-SIMILARITY MATRIX, CONVOLUTIONAL NEURAL NETWORK
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Ultra-Wideband Vivaldi Antenna with an Integrated Noise-Rejecting Parasitic Notch Filter for Online Partial Discharge Detection
PublicationPower transformers and gas-insulated switchgear (GIS) play crucial roles in electrical power grids. However, they may suffer from degradation of insulation material due to wear and tear, leading to their imminent failure. Partial discharges (PDs) are an initial sign of insulation materials degradation which emit signals spanning various physical domains, including electromagnetic. PDs are temporally narrow, high-frequency, stochastic...
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The Use of Wavelet Analysis to Denoising of Electrocardiography Signal
PublicationThe electrocardiography examination, due to its accessibility and simplicity, has an important role in diagnostics of the heart ailments. It enables quick detection of various heart defects, undetectable by other kinds of diagnostic tools, so it is very popular. Nevertheless, the measured signal is exposed to a different disturbances. Among them, the electromagnetic interferences, drift of reference electrode and high frequency...
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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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The Methods for RTS Noise Identification
PublicationIn the paper authors present two methods, which allows to identify the RTS noise in noise signal of semiconductor devices. The first one was elaborated to identify the RTS noise and also to estimate the number of its levels. The second one can be used to estimate all of the parameters of Gaussian and non-Gaussian components in the noise signal in a frequency domain.
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Designing of an effective structure of system for the maintenance of a technical object with the using information from an artificial neural network
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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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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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CMGNet: Context-aware middle-layer guidance network for salient object detection
PublicationSalient object detection (SOD) is a critical task in computer vision that involves accurately identifying and segmenting visually significant objects in an image. To address the challenges of gridding issues and feature...
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Performance analysis of an rfid-based 3d indoor positioning system combining scene analysis and neural network methods
PublicationThe main purpose of this research is to improve localization accuracy of an active Radio Frequency Identification, RFID tag, in 3D indoor space. The paper presents a new RFID based 3D Indoor Positioning System which shows performance improvement. The proposed positioning system combines two methods: the Scene Analysis technique and Artificial Neural Network. The results of both simulation using Log-Distance Path Loss Model and...
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FLUCTUATION AND NOISE LETTERS
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Biotrickling filtration of n-butanol vapors: process monitoring using electronic nose and artificial neural network
PublicationBiotrickling filtration is one of the techniques used to reduce odorants in the air. It is based on the aerobic degradation of pollutants by microorganisms located in the filter bed. The research presents the possibility of using the electronic nose prototype combined with artificial neural network for biofiltration process monitoring in terms of reduction in n-butanol concentration and odour intensity of treated air. The study...
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Corrupted speech intelligibility improvement using adaptive filter based algorithm
PublicationA technique for improving the quality of speech signals recorded in strong noise is presented. The proposed algorithmemploying adaptive filtration is described and additional possibilities of speech intelligibility improvement arediscussed. Results of the tests are presented.
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Self-Optimizing Adaptive Vibration Controller
PublicationThis paper presents a new approach to rejection of sinusoidal disturbances acting at the output of a discrete-time linear stable plant with unknown dynamics. It is assumed that the frequency of the sinusoidal disturbance is known, and that the output signal is contaminated with wideband measurement noise. The proposed controller, called SONIC (self-optimizing narrowband interference canceller), combines the coefficient fixing technique,...
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Improving signal quality of a speech codec using hybrid perceptual-parametric algorithm
PublicationW artykule zaprezentowano hybrydową architekturę parametryczno-perceptualną kodeka mowy. Jego podstawę stanowi kodek CELP, który wspomagany jest kodekiem perceptualnym. Celem zastosowania proponowanej metody jest uzyskanie poprawy jakości kodowania sygnału mowy. Badaniom poddano dwie architektury, z których w jednej dźwięczne części sygnału rezydualnego kodeka CELP kodowane są perceptualnie. Drugi z proponowanych kodeków dokonuje...
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The Method of a Two-Level Text-Meaning Similarity Approximation of the Customers’ Opinions
PublicationThe method of two-level text-meaning similarity approximation, consisting in the implementation of the classification of the stages of text opinions of customers and identifying their rank quality level was developed. Proposed and proved the significance of major hypotheses, put as the basis of the developed methodology, notably about the significance of suggestions about the existence of analogies between mathematical bases of...
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OOA-modified Bi-LSTM network: An effective intrusion detection framework for IoT systems
PublicationCurrently, the Internet of Things (IoT) generates a huge amount of traffic data in communication and information technology. The diversification and integration of IoT applications and terminals make IoT vulnerable to intrusion attacks. Therefore, it is necessary to develop an efficient Intrusion Detection System (IDS) that guarantees the reliability, integrity, and security of IoT systems. The detection of intrusion is considered...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublicationText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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Kamila Kokot-Kanikuła mgr
PeopleKamila Kokot-Kanikuła is a digital media senior librarian at Gdańsk University of Technology (GUT) Library. She works in Digital Archive and Multimedia Creation Department and her main areas of interests include early printed books, digital libraries, Open Access and Open Science. In the Pomeranian Digital Library (PDL) Project she is responsible for creating annual digital plans, transferring files on digital platform, and promoting...
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Neural-Network-Based Parameter Estimations of Induction Motors
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Cellular neural network application to moire pattern filtering
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Neural Network - Based Parameters Estimations Of Induction Motors
PublicationW artykule przedstwaiono algorytmy estymacji rezystancji wirnika i indukcyjności wzajemnej w zamkniętym układzie sterowania prędkości silnika indukcyjnego klatkowego. Do wyznaczenia rezystancji wykorzystano algorytm oparty na porównaniu modelu napięciowego i prądowego silnika. Do wyznaczania indukcyjności wykorzystano, znaną z literatury, zależność modelu multiskalarnego. Wyznaczane w stanie ustalonym parametry zapisywane są w...
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Neural network breast cancer relapse time prognosis
PublicationPrzedstawiono architekturę i wyniki testowania sztucznej sieci neuronowej w prognozowaniu czasu nawrotu choroby u kobiet chorych na raka piersi. Sieć neuronowa uczona była na danych zgromadzonych przez 20 lat. Dane opisują grupę 439 pacjentów za pomocą 40 parametrów. Spośród tych parametrów wybrano 6 najistotniejszych: liczbę przerzutowych węzłów chłonnych, wielkość guza, wiek, skalę według Blooma oraz stan receptorów estrogenowych...
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Comparative study of methods for artificial neural network training.
PublicationPrzedstawiono wyniki badań porównawczych następujących metod uczenia sieci neuronowych: propagacji wstecznej błędów, rekursywnej metody najmniejszych kwadratów, metody Zangwill'a i algorytmów ewolucyjnych. Badania dotyczyły projektowania adaptacyjnego regulatora neuronowego napięcia generatora synchronicznego.
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Detection of measurement noise in surface topography analysis
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Noise in biological Raman spectroscopy
PublicationRaman spectroscopy is a widely used method to investigate chemical molecules by analyzing their vibrational transitions. It utilizes inelastic scattering of the laser light irradiating the investigated object. The scattered light requires appropriate filtering to reduce dominant laser light and expose much weaker components having shifted wavelengths of a characteristic spectral pattern. These components are measured by dispersing...
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Comparison of pavement noise properties on selected road sections using different CPX measuring systems: self-powered vehicle and special test trailer
PublicationThe recently published ISO standard intended to measure the noise properties of road surfaces in a standardized method (ISO 11819-2:2017) precisely defines measurement procedure of the influence of road surface on traffic noise. According to it, two types of test vehicles may be utilized: a self-powered vehicle fitted with one or more test tyres and a trailer towed by a separate vehicle with one or more test tyres mounted on the...
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Examining Influence of Distance to Microphone on Accuracy of Speech Recognition
PublicationThe problem of controlling a machine by the distant-talking speaker without a necessity of handheld or body-worn equipment usage is considered. A laboratory setup is introduced for examination of performance of the developed automatic speech recognition system fed by direct and by distant speech acquired by microphones placed at three different distances from the speaker (0.5 m to 1.5 m). For feature extraction from the voice signal...
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Methods of Improving Speech Intelligibility for Listeners with Hearing Resolution Deficit
PublicationMethods developed for real-time time scale modification (TSM) of speech signal are presented. They are based onthe non-uniform, speech rate depended SOLA algorithm (Synchronous Overlap and Add). Influence of theproposed method on the intelligibility of speech was investigated for two separate groups of listeners, i.e. hearingimpaired children and elderly listeners. It was shown that for the speech with average rate equal to or...
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Distortion of speech signals in the listening area: its mechanism and measurements
PublicationThe paper deals with a problem of the influence of the number and distribution of loudspeakers in speech reinforcement systems on the quality of publicly addressed voice messages, namely on speech intelligibility in the listening area. Linear superposition of time-shifted broadband waves of a same form and slightly different magnitudes that reach a listener from numerous coherent sources, is accompanied by interference effects...
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Boron-doped carbon nanowalls for fast and direct detection of cytochrome C and ricin by matrix-free laser desorption/ionization mass spectrometry
PublicationDetecting proteins via surface assisted laser desorption/ionization mass spectrometry (SALDI-MS) method is still highly challenging, and only few examples of nanomaterials have been demonstrated to perform such detection so far. In this study, carbon nanowalls (CNWs), vertically aligned graphene sheet-based materials, presenting specific morphology, dimensions, and boron doping levels have shown improved performances for both qualitative...
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Material for Automatic Phonetic Transcription of Speech Recorded in Various Conditions
PublicationAutomatic speech recognition (ASR) is under constant development, especially in cases when speech is casually produced or it is acquired in various environment conditions, or in the presence of background noise. Phonetic transcription is an important step in the process of full speech recognition and is discussed in the presented work as the main focus in this process. ASR is widely implemented in mobile devices technology, but...
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Comparison of various speech time-scale modificartion methods
PublicationThe objective of this work is to investigate the influence of the different time-scale modification (TSM) methods on the quality of the speech stretched up using the designed non-uniform real-time speech time-scale modification algorithm (NU-RTSM). The algorithm provides a combination of the typical TSM algorithm with the vowels, consonants, stutter, transients and silence detectors. Based on the information about the content and...
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Neural network simulator's application to reference performance determination of turbine blading in the heat-flow diagnostics.
PublicationIn the paper, the possibility of application of artificial neural networks to perform the fluid flow calculations through both damaged and undamaged turbine blading was investigated. Preliminary results are presented and show the potentiality of further development of the method for the purpose of heat-flow diagnostics.
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Parametric impulsive noise detector for corrupted audio signals based on hidden Markow model
PublicationThe paper addresses the problem of impulsive noise detection for audio signals. A structure of threshold parameter detectors using modelingof signals was introduced. the algorithm of the noise detection, based on discrete-time hidden Markow model (HMM)of whitened audio signal is elaborated
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Creating neural models using an adaptive algorithm for optimal size of neural network and training set.
PublicationZaprezentowano adaptacyjny algorytm generujący modele neuronowe liniowych układów mikrofalowych, zdolny do oszacowania optymalnego rozmiaru zbiory uczącego i sieci neuronowej. Stworzono kilka modeli nieciągłości falowodowych i mokropaskowych, a następnie zweryfikowano ich poprawność porównując wyniki analiz metodą dopasowania rodzajów i metodą momentów filtrów pasmowo-przepustowych.
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Online urban acoustic noise monitoring system
PublicationConcepts and implementation of the Online Urban Noise Monitoring System are presented. Principles of proposed solution used for dynamic acoustical maps creating are discussed. The architecture of the system and the data acquisition scheme are described. The concept of noise mapping, based on noise source model and propagation simulations, was developed and employed in the system. Dynamic estimation of noise source parameters utilized...
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Lamb wave based structural damage detection using cointegration and fractal signal processing
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Rating by detection: an artifact detection protocol for rating EEG quality with average event duration
PublicationQuantitative evaluation protocols are critical for the development of algorithms that remove artifacts from real EEG optimally. However, visually inspecting the real EEG to select the top-performing artifact removal pipeline is infeasible while hand-crafted EEG data allow assessing artifact removal configurations only in a simulated environment. This study proposes a novel, principled approach for quantitatively evaluating algorithmically...
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Electrical and noise responses of graphene/AlGaN/GaN field-effect transistor for nitrogen dioxide, teatrahydrofuran, and acetone sensing
Open Research DataThis data set consists of raw and modified data concerning current-voltage characteristics and low-frequency noise spectra measured for graphene/AlGaN/GaN field-effect transistor in the ambiance of selected gases (laboratory air, dry and wet synthetic air, nitrogen dioxide, tetrahydrofuran, and acetone). The data show that sensor responses are enhanced...
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A Simplified Method of Trend Removal to Determine Noise Observed During a Supercapacitor’s Discharging
PublicationIn this paper, new method of trend removal is proposed. This is a simplified method based on Empirical Mode Decomposition (EMD). The method was applied for voltage time series observed during supercapacitor discharging process. It assured the determination of an additive noise component after subtracting the identified trend component. We analyzed voltage time series observed between the terminals of the supercapacitor when discharged...
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Deep neural networks for human pose estimation from a very low resolution depth image
PublicationThe work presented in the paper is dedicated to determining and evaluating the most efficient neural network architecture applied as a multiple regression network localizing human body joints in 3D space based on a single low resolution depth image. The main challenge was to deal with a noisy and coarse representation of the human body, as observed by a depth sensor from a large distance, and to achieve high localization precision....
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The Dominant Influence of Plastic Deformation Induced Residual Stress on the Barkhausen Effect Signal in Martensitic Steels
PublicationThe paper presents the results of investigation of the influence of plastic deformation on the magnetic properties of martensitic steel (P91 grade). The properties of the hysteresis loops as well as of the Barkhausen effect (BE) signal are analysed for both tensile and compressive loading up to ε = 10% of plastic deformation. The choice of the steel and of the deformation range is unique, since for such combination one can expect...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublicationRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
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Tensor Decomposition for Imagined Speech Discrimination in EEG
PublicationMost of the researches in Electroencephalogram(EEG)-based Brain-Computer Interfaces (BCI) are focused on the use of motor imagery. As an attempt to improve the control of these interfaces, the use of language instead of movement has been recently explored, in the form of imagined speech. This work aims for the discrimination of imagined words in electroencephalogram signals. For this purpose, the analysis of multiple variables...
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Noise sources in Raman spectroscopy of biological objects
PublicationWe present an overview of noise sources deteriorating the quality of the recorded biological Raman spectra and the ability to determine the specimen composition. The acquired Raman spectra exhibit intense additive noise components or drifts because of low intensity of the scattered light. Therefore we have to apply expensive or bulky measurement setups to limit their inherent noise or to apply additional signal processing to reduce...
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Analysis of noise properties of the optocoupler device
PublicationIn the paper the localization of a source of Random Telegraph Signal noise (RTS noise) in optocoupler devices type CNY 17 were defined. The equivalent noise circuit in low frequency noise for these type optocouplers was proposed.
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POSSIBILITY OF IDENTIFICATION OF TECHNICAL CONDITION OF BEARINGS FOR SELF-IGNITION ENGINES BY APPLICATION OF ACOUSTIC EMISSION AS A DIAGNOSTIC SIGNAL
PublicationThis paper presents the results of empirical studies where the acoustic emission (AE) method was applied to identify the technical condition of sliding surfaces of main and crank bearings for main diesel engines. The test results indicate that the measurements of the AE parameters allow the technical condition identification for bearings of this type. The results refer to the measurements of the parameters for AE generated in the...
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A new methof for identyfication of RTS noise
PublicationIn the paper a new method, called the Noise Scattering Pattern (NSP) method, for RTS noise identyfication in a noise signal is presented. Examples of patterns of the NSP method are included.
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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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Olgun Aydin dr
PeopleOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Principal Machine Learning Engineer in Nike, and works as Assistant Professor in Gdansk University of Technology in Poland. Dr. Aydin is part of editorial board of "Journal of Artificial Intelligence and Data Science" Dr. Aydin served as Vice-Chairman of Why R? Foundation and is member of Polish Artificial Intelligence Society. Olgun is...