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Search results for: eeg signal classification
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Ranking Speech Features for Their Usage in Singing Emotion Classification
PublicationThis paper aims to retrieve speech descriptors that may be useful for the classification of emotions in singing. For this purpose, Mel Frequency Cepstral Coefficients (MFCC) and selected Low-Level MPEG 7 descriptors were calculated based on the RAVDESS dataset. The database contains recordings of emotional speech and singing of professional actors presenting six different emotions. Employing the algorithm of Feature Selection based...
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The set of 22 sessions of 14-channel eeg signals recorded during watching pictures
Open Research DataThe data were collected in order to perform research on the possibility of controlling the content displayed on the monitor screen using human emotional states extracted from EEG signals. The dataset contains recordings of 14-channel EEG signals collected from 10 persons within 22 sessions, during which 45 different random photos taken from the ImageNet...
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Sequential classification.
PublicationOpisano uogólniony algorytm konstrukcji klasyfikatora sekwencyjnego. Uogólnienie polega na tym, że zbiór klas dzielimy na dwie grupy zamiast oddzielania po jednej klasie w każdym kroku uczenia klasyfikatora. Eksperymenty potwierdzały lepsze własności klasyfikatora.
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Detection of the First Component of the Received LTE Signal in the OTDoA Method
PublicationIn a modern world there is a growing demand for localization services of various kinds. Position estimation can be realized via cellular networks, especially in the currently widely deployed LTE (Long Term Evolution) networks. However, it is not an easy task in harsh propagation conditions which often occur in dense urban environments. Recently, time-methods of terminal localization within the network have been the focus of attention,...
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Accelerating Video Frames Classification With Metric Based Scene Segmentation
PublicationThis paper addresses the problem of the efficient classification of images in a video stream in cases, where all of the video has to be labeled. Realizing the similarity of consecutive frames, we introduce a set of simple metrics to measure that similarity. To use these observations for decreasing the number of necessary classifications, we propose a scene segmentation algorithm. Performed experiments have evaluated the acquired...
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Classification of Polish wines by application of ultra-fast gas chromatography
PublicationThe potential of ultra-fast gas chromatography (GC) combined with chemometric analysis for classification of wine originating from Poland according to the variety of grape used for production was investigated. A total of 44 Polish wine samples differing in the type of grape (and grape growth region) used for the production as well as parameters of the fermentation process, alcohol content, sweetness, and others which characterize...
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Multibeam Sonar Data Processing for Seafloor Classification
PublicationDespite many years of the development of methodology for sensing the seafloor by means of underwater acoustics, the currently used techniques are still not mature enough and not ready to be utilised in numerous different (i.e. with respect to a water region character, used equipment type etc.) tasks. Therefore the hydroacoustic methods, both utilising vertical observations (e.g. by singlebeam echosounders), as well as those relying...
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Selection of Features for Multimodal Vocalic Segments Classification
PublicationEnglish speech recognition experiments are presented employing both: audio signal and Facial Motion Capture (FMC) recordings. The principal aim of the study was to evaluate the influence of feature vector dimension reduction for the accuracy of vocalic segments classification employing neural networks. Several parameter reduction strategies were adopted, namely: Extremely Randomized Trees, Principal Component Analysis and Recursive...
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From Scores to Predictions in Multi-Label Classification: Neural Thresholding Strategies
PublicationIn this paper, we propose a novel approach for obtaining predictions from per-class scores to improve the accuracy of multi-label classification systems. In a multi-label classification task, the expected output is a set of predicted labels per each testing sample. Typically, these predictions are calculated by implicit or explicit thresholding of per-class real-valued scores: classes with scores exceeding a given threshold value...
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Simulation of signal acquisition from a rotary flowmeter
Open Research DataThe dataset contains results of simulation measuring the flow of homogeneous substances by rotational flow meter: a moment of impulse at the output of flow meter, time between successive pulses, number of pulses counted from standard generator and relative error of measurement.
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Digital signal processing applied to the modernization of Polish Navy sonars
PublicationThe article presents the equipment and digital signal processing methods used for modernizing the Polish Navy’s sonars. With the rapid advancement of electronic technologies and digital signal processing methods, electronic systems, including sonars, become obsolete very quickly. In the late 1990s a team of researchers of the Department of Marine Electronics Systems, Faculty of Electronics, Telecommunications and Informatics, Gdansk...
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Time variable gain for long range sonar with chirp sounding signal
PublicationThe main purpose of applaying Time Variable Gain (TVG) in active sonars with digital signal processing is to reduce dynamic range of echo signal and adapt it to the dynamic range of the analogue to digital conversion. With high transmission losses level, the dynamic range of the input signal in long range sonars can be very high and even exceed 200dB. When chirp sounding signals with matched filtration are used, sonars can raech...
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Application of passive acoustic radar to automatic localization, tracking and classification of sound sources
PublicationA concept, practical realization and applications of the passive acoustic radar to automatic localization, tracking and classification of sound sources were presented in the paper. The device consists of a new kind of multichannel miniature sound intensity sensors and a group of digital signal processing algorithms. Contrary to active radars, it does not emit the scanning beam but after receiving surrounding sounds it provides...
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A quasi-2D small-signal MOSFET model - main results
PublicationDynamic properties of the MOS transistor under small-signal excitation are determined by kinetic parameters of the carriers injected into the channel, i.e., the low-field mobility, velocity saturation, mobility at the quiescent-point (Q-point), longitudinal electric field in the channel, by dynamic properties of the channel, as well as by an electrical coupling between the perturbed carrier concentration in the channel and the...
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CLASSIFICATION OF RESTRAINTS IN THE OPTIMIZATION PROBLEM OF A COLD-FORMED PROFILE
PublicationThis work describes the restraints in the optimization problem. This is an important and complicated issue because it requires taking into account a vast range of information related to the design and production. In order to describe the relations of a specific optimization problem, it is essential to adopt appropriate criteria and to collect information on all kinds of restraints, i.e. boundary conditions. The following paper...
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Potential and Use of the Googlenet Ann for the Purposes of Inland Water Ships Classification
PublicationThis article presents an analysis of the possibilities of using the pre-degraded GoogLeNet artificial neural network to classify inland vessels. Inland water authorities monitor the intensity of the vessels via CCTV. Such classification seems to be an improvement in their statutory tasks. The automatic classification of the inland vessels from video recording is a one of the main objectives of the Automatic Ship Recognition and...
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Orken Mamyrbayev Professor
People1. Education: Higher. In 2001, graduated from the Abay Almaty State University (now Abay Kazakh National Pedagogical University), in the specialty: Computer science and computerization manager. 2. Academic degree: Ph.D. in the specialty "6D070300-Information systems". The dissertation was defended in 2014 on the topic: "Kazakh soileulerin tanudyn kupmodaldy zhuyesin kuru". Under my supervision, 16 masters, 1 dissertation...
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Comparative Analysis of Text Representation Methods Using Classification
PublicationIn our work, we review and empirically evaluate five different raw methods of text representation that allow automatic processing of Wikipedia articles. The main contribution of the article—evaluation of approaches to text representation for machine learning tasks—indicates that the text representation is fundamental for achieving good categorization results. The analysis of the representation methods creates a baseline that cannot...
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Reduction of the Velocity Impact on the Magnetic Flux Leakage Signal
PublicationThe velocity effect on the magnetic flux leakage (MFL) signal was investigated in this paper. Experiments were performed for velocity of the MFL tool within the range of 0–2 m/s. The velocity was not constant during each measurement to imitate real operational conditions of the MFL tool. Two components of the leakage were measured, i.e. the tangential to the motion direction (x) and the normal to the investigated surface (z). In...
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Classification of high-voltage varistors into groups of differentiated quality
PublicationThe research was aimed on defining a factor of quality for high-voltage varistors using Non-Destructive Testing (NDT) techniques, which could be applied during the production testing. The newly proposed parameter Q determined on the basis of the lowest resonant frequency fr measured within the preselected frequency range was taken into account. The parameter Q was defined for ZnO structures after firing, without metallized contacts....
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Design of novel microstrip directional coupler for differential signal decoupling
PublicationThis study describes a concept of a novel microstrip directional coupler for differential signal decoupling, which can be used to digital signal overhearing on printed-circuit-boards. The complete design method is proposed with rules given analytically. Considered methodology is suitable for synthesis of couplers with low coupling factors, which have negligible influence on the transmission in main line. Theoretical considerations...
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A Study on Audio Signal Processed by "Instant Mastering"
PublicationAn increasing amount of music produced in home- and project-studios results in development and growth of "automatic mastering services". The presented investigation explores changes introduced to audio signal by various online mastering platforms. A music set consisting of 10 songs produced in small facilities was processed by eight on-line automatic mastering services. Additionally, some laboratory-constructed signals were tested....
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A random signal generation method for microcontrollers with DACs
PublicationA new method of noise generation based on software implementation of a 7-bit LFSR based on a common polynomial PRBS7 using microcontrollers equipped with internal ADCs and DACs and a microcontroller noise generator structure are proposed in the paper. Two software applications implementing the method: written in ANSI C and based on the LUT technique and written in AVR Assembler are also proposed. In the method the ADC results are...
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Mask Detection and Classification in Thermal Face Images
PublicationFace masks are recommended to reduce the transmission of many viruses, especially SARS-CoV-2. Therefore, the automatic detection of whether there is a mask on the face, what type of mask is worn, and how it is worn is an important research topic. In this work, the use of thermal imaging was considered to analyze the possibility of detecting (localizing) a mask on the face, as well as to check whether it is possible to classify...
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TIME- AND FREQUENCY-DOMAIN QUASI-2D SMALL-SIGNAL MOSFET MODELS
PublicationA novel approach to small-signal MOSFET modeling is presented in this book. As a result, time- and frequency-domain physics-based quasi-2D NQS four-terminal small-signal MOSFET models are proposed. The time-domain model provides the background to a novel DIBL-included quasi‑2D NQS four-terminal frequency-domain small-signal MOSFET model. Parameters and electrical quantities of the frequency-domain model are described by explicit...
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A quasi-2D small-signal MOSFET model - main results
PublicationMain results stemming from a new quasi 2D non-quasi-static small-signal four-terminal model of the MOSFET are presented in this work. The model is experimentally verified up to 30 GHz.
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Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
PublicationBackground: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant)...
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Influence of sensor design and optical properties of tissue on the photoplethysmographic signal
PublicationPhotopletysmography and an associated technique called pulse oximetry are still explored due to the expectations that they give a lot of information about the state of the patient and, also, due to the fact that they are non invasive. Knowledge about the impact of various parameters on the measured signal leads to a faster and a more reliable way of analyzing measurement results and finding the dependencies between the involved...
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Improving css-KNN Classification Performance by Shifts in Training Data
PublicationThis paper presents a new approach to improve the performance of a css-k-NN classifier for categorization of text documents. The css-k-NN classifier (i.e., a threshold-based variation of a standard k-NN classifier we proposed in [1]) is a lazy-learning instance-based classifier. It does not have parameters associated with features and/or classes of objects, that would be optimized during off-line learning. In this paper we propose...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Identification, Assessment and Automated Classification of Requirements Engineering Techniques
PublicationSelection of suitable techniques to be used in requirements engineering or business analysis activities is not easy, especially considering the large number of new proposals that emerged in recent years. This paper provides a summary of techniques recommended by major sources recognized by the industry. A universal attribute structure for the description of techniques is proposed and used to describe 33 techniques most frequently...
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Classification of Music Genres Based on Music Separation into Harmonic and Drum Components . Klasyfikacja gatunków muzycznych wykorzystująca separację instrumentów muzycznych
PublicationThis article presents a study on music genre classification based on music separation into harmonic and drum components. For this purpose, audio signal separation is executed to extend the overall vector of parameters by new descriptors extracted from harmonic and/or drum music content. The study is performed using the ISMIS database of music files represented by vectors of parameters containing music features. The Support Vector...
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Problems in estimation of hand grip force based on EMG signal
PublicationThere has recently been a significant increase in the number of publications on and applications of bioelectric signals for diagnostic purposes. While the use of ECG (electrocardiography) is not surprising, the use of signals from registration of brain activity (EEG) and muscles activity (EMG) still finds new applications in various fields. The authors focus on the use of EMG signals for estimating hand grip force. Currently,...
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Effect of oxygenation time on signal of a sensor based on ionic liquids
PublicationThe paper presents an oxygen sensor based on ionic liquids and solid electrodes. The following ionic liquids have been employed: [BMIM][BF4], [HMIM][Cl], [BMIM][N(CN2)]. Minimum time of the sensor exposure to analyte, after which the signal (current intensity) was stable, has been evaluated. An impact of volumetric flow rate of analyte on the sensor exposure time and signal has been determined. A product of permeability coefficient...
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Signal propagation in electromagnetic media described by fractional-order models
PublicationIn this paper, signal propagation is analysed in electromagnetic media described by fractional-order (FO) models (FOMs). Maxwell’s equations with FO constitutive relations are introduced in the time domain. Then, their phasor representation is derived for one-dimensional case of the plane wave propagation. With the use of the Fourier transformation, the algorithm for simulation of the non-monochromatic wave propagation is introduced....
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Narrowband Transmission Quality in Presence of Modified IEEE 802.15.4a UWB Signal
PublicationThis paper presents results of measurement of narrowband transmission quality in presence of impulse radio UWB interference. In the first part of paper, unmodified IEEE 802.15.4a IR UWB signal is used. Then some modification of transmitted pulse sequence is proposed, which allow to reduce UWB power spectral density at frequency of narrowbandtransmission. Finally narrowband transmission quality in presence of modified ultrawideband...
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Signal conditioning for examination of shallow-water acoustic noise correlation properties
PublicationThe article describes the process of signal conditioning for examination of acoustic noise correlation properties in shallow water. Knowledge of these properties is very important for the design processes of passive and active hydroacoustic systems. This paper focuses on the above issue from the point of view of passive sonar. In sonar systems, signal processing algorithms operate on both useful acoustic signals, and accompanying...
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A study on signal processing methods applied to hearing aids
PublicationThis paper presents a short survey on current technology available in hearing aids with a focus on digital signal processing techniques used. First, factors influencing the hearing aid effectiveness are introduced. Then, examples of the present DSP methods and strategies are provided. Also, a description of current limitations of hearing aids and future trends of development are shown. Finally, the notion of computational auditory...
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Narrowband Transmission Quality in Presence of Modified IEEE 802.15.4a UWB Signal
PublicationThis paper presents results of measurement of narrowband transmission quality in presence of impulse radio UWB interference. In the first part of paper, unmodified IEEE 802.15.4a IR UWB signal is used. Then some modification of transmitted pulse sequence is proposed, which allow to reduce UWB power spectral density at frequency of narrowband transmission. Finally narrowband transmission quality in presence of modified ultrawideband...
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Research on methods for detecting respiratory rate from photoplethysmographic signal
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Wideband Signal Generation for Jamming Radio-Controlled Improvised Explosive Devices
PublicationThis paper focuses on modelling operation of a wideband jamming signal generator, considering the effects present in real device which influence the shape of transmitted signal’s spectrum. Introduction is followed by a brief overview of AEGIS project, aim of which is to develop a mobile generator of electromagnetic curtain. Next, simulation model is described which includes the factors...
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An automatic system for identification of random telegraph signal (RTS) noise in noise signals
PublicationIn the paper the automatic and universal system for identification of Random Telegraph Signal (RTS) noise as a non-Gaussian component of the inherent noise signal of semiconductor devices is presented. The system for data acquisition and processing is described. Histograms of the instantaneous values of the noise signals are calculated as the basis for analysis of the noise signal to determine the number of local maxima of histograms...
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublicationTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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A new multi-process collaborative architecture for time series classification
PublicationTime series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...
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Data Compression in Ultrasonic Network Communication via Sparse Signal Processing
PublicationThis document presents the approach of using compressed sensing in signal encoding and information transferring within a guided wave sensor network, comprised of specially designed frequency steerable acoustic transducers (FSATs). Wave propagation in a damaged plate was simulated using commercial FEM-based software COMSOL. Guided waves were excited by means of FSATs, characterized by the special shape of its electrodes, and modeled...
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Classification of Sea Going Vessels Properties Using SAR Satellite Images
PublicationThe aim of the project was to analyze the possibility of using machine learning and computer vision to identify (indicate the location) of all sea-going vessels located in the selected area of the open sea and to classify the main attributes of the vessel. The key elements of the project were to download data from the Sentinel-1 satellite [1], download data on the sea vessels [2], then automatically tag data and develop a detection...
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Dynamic Signal Strength Mapping and Analysis by Means of Mobile Geographic Information System
PublicationBluetooth beacons are becoming increasingly popular for various applications such as marketing or indoor navigation. However, designing a proper beacon installation requires knowledge of the possible sources of interference in the target environment. While theoretically beacon signal strength should decay linearly with log distance, on-site measurements usually reveal that noise from objects such as Wi-Fi networks operating in...
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Fast High-Impedance Spectroscopy Method Using SINC Signal Excitation
PublicationIn this paper the method of fast impedance spectroscopy of technical objects with high impedance (|Zx| > 1 Gohm) is evaluated by means of simulation and practical experiment. The method is based on excitation of an object with a sinc signal and sampling response signals proportional to current flowing through and voltage across the measured impedance. The object impedance spectrum is obtained with use of continuous Fourier transform...
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Towards Cancer Patients Classification Using Liquid Biopsy
PublicationLiquid biopsy is a useful, minimally invasive diagnostic and monitoring tool for cancer disease. Yet, developing accurate methods, given the potentially large number of input features, and usually small datasets size remains very challenging. Recently, a novel feature parameterization based on the RNA-sequenced platelet data which uses the biological knowledge from the Kyoto Encyclopedia of Genes and Genomes, combined with a classifier...
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Classification methods and criteria
PublicationKlasyfikacja akustyczna dna morskiego jest najnowszą metodologią zaprojektowaną w celu zdalnego wykrywania rozmaitych charakterystyk dna morskiego z informacji zawartych w echch od dna akustycznych impulsów transmitowanych z różnego typu sonarów. Poza szególnymi chrakterystykami sprzętowymi każdego systemu ASC, istotą każdej metody jest klasyfikacja modułu, który wyciąga serie cech z echa sygnału i przetwarza je aby posortować...