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EN
The analysis of protein coding regions of DNA sequences is one of the most fundamental applications in bioinformatics. A number of model-independent approaches have been developed for differentiating between the protein-coding and non-protein-coding regions of DNA. However, these methods are often based on univariate analysis algorithms, which leads to the loss of joint information among four nucleotides of DNA. In this article, we introduce a method on basis of the noise-assisted multivariate empirical mode decomposition (NA-MEMD) and the modified Gabor-wavelet transform (MGWT). The NA-MEMD algorithm, as a multivariate analysis tool, is utilized to reconstruct the numerical analyzed sequence since it enables a matched-scale decomposition across all variables and eliminates the mode mixing. By virtues of NA-MEMD, the MGWT method achieves a stable improvement on the general identification performance. We compare our method with other Digital Signal Processing (DSP) methods on two representative DNA sequences and three benchmark datasets. The results reveal that our method can enhance the spectra of the analyzed sequences, and improve the robustness of MGWT to different DNA sequences, thus obtaining higher identification accuracies of protein coding regions over other applied methods. In addition, another comparative experiment with the model-dependent method (AUGUSTUS) on the recently proposed benchmark dataset G3PO verifies the superiority of model-independent methods (especially NA-MEMD-MGWT) for identifying coding regions of the poor-quality DNA sequences.
EN
This work is devoted to further research and improvement of the vibroacoustic condition monitoring of complex rotation system during operation. The low-frequency vibration and acoustic noise in the range 0-10 kHz is used as diagnostic information. We propose to use Bispectrum (BS) Analysis at the first level of signal processing, and Fractal Analysis of BS contour images at the second level of signal processing for the diagnosis of small imbalance of rotation system. The experimental studies of forced vibrations of the physical model (PM) of the rotation system are carried out under steady-state and non-steady-state rotation excitations. The results of the BS Analysis of vibroacoustical signals, which are emitted by a rotating PM during different excitation modes, are processed in order to determine fractal box-counting dimension (Minkowski dimension). The research shows that a small imbalance can be efficiently detected by the proposed multilevel signal processing in all modes of PM operation.
EN
The paper presents new approach to processing the Barkhausen Noise signal in order to detect and identify plastic deformations in carbon steel. A new automatic method of Barkhausen effect signal filtration was investigated. Apart from a classical measurement of Barkhausen effect signal, for which the RMS value is assumed, the signal waveform factor was also used in analyzes. The developed approach to processing the Barkhausen Noise signal has made it possible to obtain more useful diagnostic data than those obtained from the raw signal.
EN
In this paper, a problem of a perfect recovering cosinusoidal signal of any phase being sampled critically is considered. It is shown that there is no general solution to this problem. Its detailed analysis presented here shows that recovering both the original cosinusoidal signal amplitude and its phase is not possible at all. Only one of this quantities can be recovered under the assumption that the second one is known. And even then, performing some additional calculations is needed. As a byproduct, it is shown here that a transfer function of the recovering filter that must be used in the case of the critical sampling differs from the one which is used when a cosinusoidal signal is sampled with the use of a sampling frequency greater than the Nyquist rate. All the results achieved in this paper are soundly justified by thorough derivations.
EN
When the sampling of an analog signal uses the sampling rate equal to exactly twice the value of a maximal frequency occurring in the signal spectrum, it is called a critical one. As known from the literature, this kind of sampling can be ambiguous in the sense that the reconstructed signal from the samples obtained by criti-cal sampling is not unique. For example, such is the case of sampling of a cosinusoidal signal of any phase. In this paper, we explain in very detail the reasons of this behavior. Furthermore, it is also shown here that manipulating values of the coefficients of the transfer function of an ideal rectangular reconstruction filter at the transition edges from its zero to non-zero values, and vice versa, does not eliminate the ambiguity mentioned above.
6
Content available Secured wired BPL voice transmission system
EN
Designing a secured voice transmission system is not a trivial task. Wired media, thanks to their reliability and resistance to mechanical damage, seem an ideal solution. The BPL (Broadband over Power Line) cable is resistant to electricity stoppage and partial damage of phase conductors, ensuring continuity of transmission in case of an emergency. It seems an appropriate tool for delivering critical data, mostly clear and understandable voice messages. This paper describes such a system that was designed and evaluated in real-time operating conditions. It involved a two-way transmission of speech samples in American English and Polish. The efficiency of the designed solution was evaluated in the subjective study on a group of 15 people.
PL
Opracowanie bezpiecznego systemu transmisji mowy nie jest trywialnym zadaniem. Media przewodowe, z uwagi na niezawodność i odporność na uszkodzenia mechaniczne, zdają się być idealnym rozwiązaniem. Kabel BPL (Broadband over Power Line) jest odporny na przerwy w dostawie prądu i częściowe uszkodzenie przewodników fazowych, zapewniając ciągłość transmisji w przypadku awarii. Wydaje się odpowiednim narzędziem do dostarczania istotnych danych, w szczególności wyraźnych i zrozumiałych komunikatów głosowych. Artykuł ten opisuje taki system, który został opracowany oraz zbadany w rzeczywistych warunkach pracy. Obejmował on dwukierunkową transmisję próbek mowy w języku angielskim (amerykańskim) oraz polskim. Skuteczność zaprojektowanego rozwiązania została oceniona w badaniu subiektywnym na grupie 15 osób.
PL
W referacie zaproponowano metodę eliminacji wpływu efektu wielodrogowości poprzez analizę i filtrację odbieranego sygnału w cepstrum. Analiza taka, pozwala na wykrycie istnienia repliki (echa) sygnału nadawanego oraz odfiltrowanie tej repliki, co poprawia jakość realizowanej transmisji sygnału. W referacie zaprezentowano wyniki badan symulacyjnych.
EN
In paper a method of multipath propagation effect reduction based on analysis in cepstrum is presented. In this method signal in cepstrum is analysed, the signal replicas (echo) are detected and filtered, what leads to transmission quality improvement. In paper simulation results are presented.
PL
Tematyka pracy porusza zagadnienia dotyczące pozyskiwania informacji o ruchu drogowym z wykorzystaniem monitoringu akustycznego. Przybliżono podstawowe techniki nadzoru nad ruchem drogowym. Przedstawiono założenia akustycznego detektora ruchu i zbadano jego skuteczność na trzech płaszczyznach działania – zliczania pojazdów, klasyfikacji rodzajowej i klasyfikacji warunków pogodowych panujących na nawierzchni.
EN
The subject of the work is related to the acquisition of traffic information using acoustic monitoring. Baseline techniques of road traffic supervision are presented. The assumptions of the acoustic motion detector are introduced, and its effectiveness is examined at three levels of operation - vehicle counting, generic classification, and classification of weather conditions on the surface.
EN
The paper presents an algorithm for determining parameters of single sinusoidal components contained in the analyzed digital signal with the use of a small number of mathematical operations. The proposed algorithm can be applied, among others, in measuring devices to monitor basic parameters of electric energy quality as well as in devices used to determine the phasor in the power system. The proposed simplification of the algorithm for determining the sinusoidal components of the analyzed signal allows to use it in embedded devices with low computing power, which translates into lower cost of construction of devices of this type, while maintaining full functionality of the measuring system. The article contains a mathematical argument, which leads to the proposed algorithm, then the optimization of the number of performed mathematical operations is presented. The last part of the paper includes information about performed mathematical operations and presents exemplary times of execution of the algorithm for simple embedded devices.
EN
In this article is revealed the systems of a good delivery witch implement unmanned aerial vehicles during providing the service. the one channel systems of a goods delivery are a goal of this research work. the close analysing of their functional features, the classification, the types and parameters of different systems from this band are presented. in addition, the modelling of the different types of the one channel systems of goods delivery are has done.
EN
This paper presents exemplary exercise on the fundamentals of signal processing course which is offered for second year bachelor level students. Application of Field Programmable Analog Array (FPAA) for pulse amplitude modulation (PAM) exercise is described with signal processing laboratory. There are presented two methods for implementing PAM modulation and demodulation technique in FPAA module. Example configuration files are available form Authors’ web site.
EN
The article deals with an analysis of the properties of Norris gap derivatives. It discusses issues related to determining information from optical spectra measured with spectrometers. Impulse responses of differentiating filters were introduced using both Norris and Savitzky-Golay methods.The amplitude-frequency responses of the first and second order Norris differentiating filters were compared. The length impact of both segment and gaps on the frequency characteristics of filters was compared.The processing of exemplary gas spectra using the discussed technique was subsequently presented. The effect of first and second order derivatives on the spectra of carbon monoxide rotational lines for low resolution measurementsis investigated. The Norris method of derivatives arevery simple to implement and the calculation of theirparameters does not require the use of advanced numerical methods.
PL
Artykuł przedstawia analizę właściwości pochodnych według metody Norrisa. Omówiono w nim zagadnienia związane z wyznaczaniem informacji z widm optycznych mierzonychspektrometrami. Przedstawiono odpowiedzi impulsowe filtrów różniczkujących zarówno metodą Norrisa jak też Savitzky-Golay. Porównano odpowiedzi amplitudowo-częstotliwościowefiltrów różniczkujących Norrisa pierwszego i drugiego rzędu. Porównano wpływ zarówno długości segmentów jak i rozstępu (luk) na charakterystyki częstotliwościowe filtrów. Kolejno zaprezentowano przetwarzanieprzykładowych widm gazu z wykorzystaniem omawianej techniki. Przedstawiono także wpływ pochodnych pierwszego i drugiego rzędu na widma linii rotacyjnych tlenku węgla dla pomiarów o małej rozdzielczości. Metoda pochodnych według Norrisa jest bardzo prosta w implementacji a obliczanie jej parametrów nie wymaga stosowania zaawanasowanych metod numerycznych.
EN
Deep learning methods, used in machine vision challenges, often face the problem of the amount and quality of data. To address this issue, we investigate the transfer learning method. In this study, we briefly describe the idea and introduce two main strategies of transfer learning. We also present the widely-used neural network models, that in recent years performed best in ImageNet classification challenges. Furthermore, we shortly describe three different experiments from computer vision field, that confirm the developed algorithms ability to classify images with overall accuracy 87.2-95%. Achieved numbers are state-of-the-art results in melanoma thick- ness prediction, anomaly detection and Clostridium difficile cytotoxicity classification problems
EN
Entropy measurements are an accessible tool to perform irregularity and uncertainty measurements present in time series. Particularly in the area of signal processing, Multiscale Permutation Entropy (MPE) is presented as a characterization methodology capable of measuring randomness and non-linear dynamics present in non-stationary signals, such as mechanical vibrations. In this article, we present a robust methodology based on MPE for detection of Internal Combustion Engine (ICE) states. The MPE is combined with Principal Component Analysis (PCA) as a technique for visualization and feature selection and KNearest Neighbors (KNN) as a supervised classifier. The proposed methodology is validated by comparing accuracy and computation time with others presented in the literature. The results allow to appreciate a high effectiveness in the detection of failures in bearings (experiment 1) and ICE states (experiment 2) with a low computational consumption.
EN
In this study, a novel method to automatically detect Parkinson's disease (PD) using vowels is proposed. A combination of minimum average maximum (MAMa) tree and singular value decomposition (SVD) are used to extract the salient features from the voice signals. A novel feature signal is constructed from 3 levels of MAMa tree in the preprocessing phase. The SVD operator is applied to the constructed signal for feature extraction. Then 50 most distinctive features are selected using relief feature selection technique. Finally, k nearest neighborhood (KNN) with 10-fold cross validation is used for the classification. We have achieved the highest classification accuracy rate of 92.46% using vowels with KNN classifier. The dataset used consists of 3 vowels for each person. To obtain individual results, post processing step is performed and best result of 96.83% is obtained with KNN classifier. The proposed method is ready to be tested with huge database and can aid the neurologists in the diagnosis of PD using vowels.
EN
Electroencephalogram (EEG) measures the neuronal activities in the form of electric currents that are generated due to the synchronized activity by a group of specialized pyramidal cells inside the brain. The study presents a brief comparison of various functional neuroimaging techniques, revealing the excellent neuroimaging capabilities of EEG signals such as high temporal resolution, inexpensiveness, portability, and non-invasiveness as compared to the other techniques such as positron emission tomography, magnetoencephalogram, func-tional magnetic resonance imaging, and transcranial magnetic stimulation. Different types of frequency bands associated with the brain signals are also being summarized. The main purpose of this literature survey is to cover the maximum possible applications of EEG signals based on computer-aided technologies, ranging from the diagnosis of various neurological disorders such as epilepsy, major depressive disorder, alcohol use disorder, and dementia to the monitoring of other applications such as motor imagery, identity authentication, emotion recognition, sleep stage classification, eye state detection, and drowsiness monitoring. After reviewing them, the comparative analysis of the publicly available EEG datasets and other local data acquisition methods, preprocessing techniques, feature extraction methods, and the result analysis through the classification models and statistical tests has been presented. Then the research gaps and future directions in the present studies have been summarized with the aim to inspire the readers to explore more opportunities on the current topic. Finally, the survey has been completed with the brief description about the studies exploring the fusion of brain signals from multiple modalities.
EN
In the early days, consumption of multimedia content related with audio signals was only possible in a stationary manner. The music player was located at home, with a necessary physical drive. An alternative way for an individual was to attend a live performance at a concert hall or host a private concert at home. To sum up, audio-visual effects were only reserved for a narrow group of recipients. Today, thanks to portable players, vision and sound is at last available for everyone. Finally, thanks to multimedia streaming platforms, every music piece or video, e.g. from one’s favourite artist or band, can be viewed anytime and everywhere. The background or status of an individual is no longer an issue. Each person who is connected to the global network can have access to the same resources. This paper is focused on the consumption of multimedia content using mobile devices. It describes a year to year user case study carried out between 2015 and 2019, and describes the development of current trends related with the expectations of modern users. The goal of this study is to aid policymakers, as well as providers, when it comes to designing and evaluating systems and services.
EN
The development of software applications and the use of VR (Virtual Reality) techniques allow to improve the company’s financial result. The construction of models of robotic stations with robots using Virtual Robot technology allows to determine the time of the machining process. It allows its optimization through the selection of accelerations, tools, tooling strategies, and so on. Determining the time of a technological operation translates into savings. This allows you to decide on the purposefulness of the investment. In addition, modern software add-ons, for example, Signal Analyzer in RobotStudio, allow you to monitor the electricity consumption of a robotic station. The article presents a solution showing how, based on the construction of digital models and the use of VR, we can conclude about the profitability of the investment.
EN
The ability to correctly reproduce notes by the voice is one of the essential features of the singing task and called intonation. In combination with other parameters like timbre, formants, and sound attack, it affects the reception of listening impressions. In this paper, we present results of the examination concerning the automatic evaluation of intonation among the nonsingers, untrained and trained choral singers. We performed both pitch error during vocalization and pitch stability in crescendo task analysis among studied groups. We used Zero Band Filtering method to determine fundamental frequency from the singing signal. We noticed significant differences between singers with different skills and experience, and the possibility to classify the level of advancement of the singer by using intonation characteristic.
EN
The work considers the applicability of signals coming from rotor-mounted sensors in machine diagnostics. In the experiments, such sensors were implemented by piezoelectric patches bonded to the surface of a shaft. The laboratory stand also included more common sensors: laser sensors that measured the displacement of the central disc, as well as accelerometers mounted on the supports. The signals measured are analysed using the so-called full FFT method and the spectra are compared. The results show that the signals from piezoelectric sensors can be processed so that their spectral content is similar to typical spectra obtained using stator-mounted sensors.
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