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The aim of this paper is to investigate the use of oculography signals for the recognition of experts in visual arts. We focused our attention on the number of sight transitions between characteristic image areas (ROIs). In the experiments we used oculographic data recorded at the Department of Experimental Psychology at the Catholic University of Lublin for 29 images and 34 users. The EM method was...
The article presents the use of genetic algorithm (GA) to select and classify ERD/ERS patterns. One hundred twenty eight channel EEG signal was used in the experiments. The signal was recorded for 40 people, during the process of imagining right and left hand movements. Feature extraction was performed using frequency analysis (FFT) with the resolution of 1Hz. So the features were spectral lines associated...
The article presents an analysis of the possibility of recognizing speaker's emotions from speech signal in Polish language. In order to perform experiments a database containing speech recordings with emotional content was created. On its basis, extraction of features from the speech signals was performed. The most important step was to determine which of the previously extracted features were the...
A new method of automatic SSVEP detection in the EEG signal based on Independent Components Analysis (A-ICA) is described in the article. For the presented method reduction of artifacts in EEG signal is not required. Besides, the method has low computational complexity. In order to select the best ICA decomposition, we conducted a comparative study of known ICA algorithms for the use in SSVEP detection...
In the article we present a new method of feature extraction from EEG signal for SSVEP recognition, called a simplified Matching Pursuit (sMP). The method has been tested on SSVEP for stimulation frequencies close to each other − 5, 6, 7, 8Hz. Its effectiveness has been verified and compared with commonly used for this purpose FFT method. sMP enables effective detection of SSVEP with an accuracy of...
This study was carried out to select EEG signal preprocessing methods to effectively detect and classify Steady State Visually Evoked Potentials (SSVEP). Algorithms, such as: Common Average Reference, Independent Component Analysis (in the task of electrooculography artifacts removing and SSVEP enhancement) and combinations of them were implemented and tested. The best classification accuracy improvement...
In the article the authors present their own method of designing spatial filters to use in brain-computer interface, based on steady state visually evoked potentials. The spatial filter is calculated by minimizing a specially created objective function. The developed method allows us to create a dedicated filter for each user, however it demands a calibration session. By using designed spatial filters...
The main task of brain-computer interface is to translate signals generated by neurons of the brain into commands. For the effective operation of BCI, efficient methods of feature selection of EEG signal are needed. In this article authors propose the use of correlation and t-statistics to feature selection.
This paper discusses an asynchronous system of brain-computer interface, operating in real time. In the proposed system, the processing, analysis and classification of EEG signal is implemented using the Matlab programming environment and the BCI2000 package.
Most of previous research on survivable networks has been focused on protecting the unicast traffic against random failures. In this paper we propose a new approach, called RA (resistant-to-attack), to provide protection of anycast and unicast communications against attacks on irregular (e.g. scale-free) networks. We use the single backup path approach to provide protection against a single node failure...
Most of previous research on survivable networks has been related to unicast communications. In this paper we propose a new approach to network survivability of anycast communications. To the best of our knowledge, anycast defined as one-to-one-of-many technique has not received much attention recently. To provide network survivability, we use the single backup path approach, i.e. each demand has...
Electric AC arc furnaces used in steelmaking are nonlinear loads of large power. Due to chaotic nature of the electric arc and the melting process, such devices cause significant power quality problems in a supply network, mainly harmonics, inter-harmonics, unbalance, voltage dips and flickers. Limitation of this negative influence and optimization of the cast process is an important issue. In the...
In this paper we evaluate the influence of the network topological characteristics on the extent of losses after attacks. For that purpose, we use the ATRF (attack-to-random failure) multiplier. Modeling results show that when using a standard metrics of distance in path computations, the number of connections broken due to attacks on irregular networks is significantly greater, compared to random...
In this paper we investigate the issue of preplanned end-to-end protection against multiple failures. In recent communications networks, such protection is provided by finding a set of k-disjoint paths for each demand. In particular, we analyze here the problem of calculating the set of k-disjoint paths of a demand in multi-cost networks, where each network arc an may be assigned k different costs...
The paper deals with analysis of electric power quality ratings in installation of an arc furnace with a battery of passive LC filters and a tracking static VAr compensation. On the basis of recorded waveforms of voltages and currents in individual circuits of an internal autonomous power network during cast process we evaluated waveforms of the electric power. Experiments were conducted for the on...
In this paper we propose a class-based protection algorithm providing fast service recovery in WDM networks in case of a simultaneous failure of two network elements. We focus on providing various levels of service survivability in order to correspond to differentiated requirements of end-users. We show that assuring the service survivability in case of a double failure requires up to 40% more total...
The powerpoint presentation discussed the issue of backup lightpath capacity sharing in optical WDM networks with limited wavelength conversion capability, the problem of the introduced a posteriori backup path sharing approach, the ILP model and the efficient heuristic algorithm, and the advantage of CPLEX modeling over FSR-SP-LWC algorithm that would achieved up to 50% values of recovery time compared...
In this paper we propose the class-based protection algorithm providing fast service recovery in optical networks using the new concept of fast protection cycles (f-cycles). We focus on service restoration time values and we show, that it is possible to decrease them, by reducing the size of active path protected area. We prove that it is also possible to reduce the ratio of link capacity utilization...
In this paper, a novel algorithm optimizing the utilization of backup path resources for survivable WDM mesh grooming networks, based on graph vertex-coloring approach, is proposed. This is the first optimization technique, dedicated to protection-at-connection level (PAC) in WDM grooming networks, such that does not increase the backup path length and thus provides fast service recovery. The concept...
The nearly avalanche expansion of the information and communication technology (ICT) strongly influenced many domains of our lives. From the viewpoint of an academic teacher specialized in the area of instrumentation and measurement (I&M) these influences alter both measurement techniques and didactic process. Distance learning based on the Internet technology is becoming more and more popular...
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