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Open access

George Tambouratzis and Marina Vassiliou

Abstract

The present article describes a novel phrasing model which can be used for segmenting sentences of unconstrained text into syntactically-defined phrases. This model is based on the notion of attraction and repulsion forces between adjacent words. Each of these forces is weighed appropriately by system parameters, the values of which are optimised via particle swarm optimisation. This approach is designed to be language-independent and is tested here for different languages.

The phrasing model’s performance is assessed per se, by calculating the segmentation accuracy against a golden segmentation. Operational testing also involves integrating the model to a phrase-based Machine Translation (MT) system and measuring the translation quality when the phrasing model is used to segment input text into phrases. Experiments show that the performance of this approach is comparable to other leading segmentation methods and that it exceeds that of baseline systems.

Open access

Yang Cao, R. Samidurai and R. Sriraman

Abstract

This paper studies the global asymptotic stability and dissipativity problem for a class of neutral type stochastic Markovian Jump Static Neural Networks (NTSMJSNNs) with time-varying delays. By constructing an appropriate Lyapunov-Krasovskii Functional (LKF) with some augmented delay-dependent terms and by using integral inequalities to bound the derivative of the integral terms, some new sufficient conditions have been obtained, which ensure that the global asymptotic stability in the mean square. The results obtained in this paper are expressed in terms of Strict Linear Matrix Inequalities (LMIs), whose feasible solutions can be verified by effective MATLAB LMI control toolbox. Finally, examples and simulations are given to show the validity and advantages of the proposed results.

Open access

Amnah Nasim, Laura Burattini, Muhammad Faisal Fateh and Aneela Zameer

Abstract

Cases where the derivative of a boundary value problem does not exist or is constantly changing, traditional derivative can easily get stuck in the local optima or does not factually represent a constantly changing solution. Hence the need for evolutionary algorithms becomes evident. However, evolutionary algorithms are compute-intensive since they scan the entire solution space for an optimal solution. Larger populations and smaller step sizes allow for improved quality solution but results in an increase in the complexity of the optimization process. In this research a population-distributed implementation for differential evolution algorithm is presented for solving systems of 2nd-order, 2-point boundary value problems (BVPs). In this technique, the system is formulated as an optimization problem by the direct minimization of the overall individual residual error subject to the given constraint boundary conditions and is then solved using differential evolution in the sense that each of the derivatives is replaced by an appropriate difference quotient approximation. Four benchmark BVPs are solved using the proposed parallel framework for differential evolution to observe the speedup in the execution time. Meanwhile, the statistical analysis is provided to discover the effect of parametric changes such as an increase in population individuals and nodes representing features on the quality and behavior of the solutions found by differential evolution. The numerical results demonstrate that the algorithm is quite accurate and efficient for solving 2nd-order, 2-point BVPs.

Open access

Md Wasiur Rahman, Fatema Tuz Zohra and Marina L. Gavrilova

Abstract

Computational intelligence firmly made its way into the areas of consumer applications, banking, education, social networks, and security. Among all the applications, biometric systems play a significant role in ensuring an uncompromised and secure access to resources and facilities. This article presents a first multimodal biometric system that combines KINECT gait modality with KINECT face modality utilizing the rank level and the score level fusion. For the KINECT gait modality, a new approach is proposed based on the skeletal information processing. The gait cycle is calculated using three consecutive local minima computed for the distance between left and right ankles. The feature distance vectors are calculated for each person’s gait cycle, which allows extracting the biometric features such as the mean and the variance of the feature distance vector. For Kinect face recognition, a novel method based on HOG features has been developed. Then, K-nearest neighbors feature matching algorithm is applied as feature classification for both gait and face biometrics. Two fusion algorithms are implemented. The combination of Borda count and logistic regression approaches are used in the rank level fusion. The weighted sum method is used for score level fusion. The recognition accuracy obtained for multi-modal biometric recognition system tested on KINECT Gait and KINECT Eurocom Face datasets is 93.33% for Borda count rank level fusion, 96.67% for logistic regression rank-level fusion and 96.6% for score level fusion.

Open access

Simone A. Ludwig

Abstract

An intrusion detection system (IDS) is an important feature to employ in order to protect a system against network attacks. An IDS monitors the activity within a network of connected computers as to analyze the activity of intrusive patterns. In the event of an ‘attack’, the system has to respond appropriately. Different machine learning techniques have been applied in the past. These techniques fall either into the clustering or the classification category. In this paper, the classification method is used whereby a neural network ensemble method is employed to classify the different types of attacks. The neural network ensemble method consists of an autoencoder, a deep belief neural network, a deep neural network, and an extreme learning machine. The data used for the investigation is the NSL-KDD data set. In particular, the detection rate and false alarm rate among other measures (confusion matrix, classification accuracy, and AUC) of the implemented neural network ensemble are evaluated.

Open access

Mingke Cheng, Feng Gao and Yan Li

Abstract

The spindle vibrations of the high-speed grinding motorized spindle largely determine the machining quality and precision. In order to accurately predict the spindle vibrations of the PMSM high-speed grinding motorized spindle, the vibration causes are explored and analyzed. The radial vibration, inclined vibration, and axial vibration model are established. The experimental modal analysis method is proposed to analyze the dynamic response of the spindle and to identify the modal parameters of the spindle structure. Thereafter, the frequency response function (FRF) is calculated by self-power spectrum and cross-power spectrum. It is transformed into the vibration spectrum analysis of the spindle. The least-square method is used to fit the radial trajectory of the spindle. This paper aims to propose double standard spheres for 5- DOF spindle vibrations used to detect the spindle vibrations. In the experiment, the method proposed in this paper can effectively and accurately determine the causes of the spindle vibrations. The spectrum analysis and the trajectory are common tools in the spindle vibration detection.

Open access

Boris Širaiy, Roman Trobec and Vladimir Ilić

Abstract

The aim of this study was to evaluate the quality of the ECG signal, obtained from a telemetric body-sensor device during a maximum stress test on an ergometer. Twenty-three subjects, 13 males, were included in the study (20.56±1.19 years). Two different sensor positions were verified on each subject by the concurrent use of two ECG sensors. Each subject participated in four exercise stress tests: two on a treadmill and two on a cycle ergometer. In the first test, both sensors were attached to self-adhesive skin electrodes on the body, while in the second test the sensors were additionally fixed with self-adhesive tapes. The measurements were compared on both ergometers, in terms of the ECG sensors’ positions and the methods used for the sensors’ fixation. The results showed a significant difference in the running speed that provides an assessable ECG signal between the non-fixed and the fixed sensors at position left inferior (p = 0.000), as well as between the positions left inferior and left superior in the first (p = 0.019), and in the second test (p = 0.000) on the treadmill. On the cycle ergometer the differences were significant between the positions left inferior and left superior in the first (p = 0.000), and the second test (p = 0.003), and between the tests with fixed and non-fixed sensors in the position left superior (p = 0.011). The study confirms that ECG sensors could be used for maximal exercise stress tests in laboratories, especially on a cycle ergometer, and that they present a great potential for future use of ECG sensors during physical activity.

Open access

Tomas Tankeliun, Oleg Zaytsev and Vytautas Urbanavicius

Abstract

In this paper, a hybrid time-base (HTB) device for the coherent sampling oscilloscope is presented. The HTB device makes it possible to reduce the uncertainty of determining the time position of the sample in the horizontal channel of the sampling oscilloscope. For its functioning, the proposed HTB device requires that the system-under-test, in addition to the test signal, also has a synchronous reference clock – harmonic oscillation. It should be noted that both the test signal and the harmonic reference clock are sampled simultaneously. The harmonic reference clock is connected to one of the oscilloscope channels and a special algorithm processes the clock samples and adjusts the coherent sampling mode. Two techniques of determining the position of the sample on the time axis are combined in the HTB device – the “trigonometric”, when the position is calculated by the arccosine or arcsine formula of the reference clock sampling value, and the interpolation method, according to which the time position of the sample is found by averaging the positions of two adjacent samples, obtained using said “trigonometric” technique. Primary experimental studies have shown that using the HTB device can reduce jitter of the sampling oscilloscope by several times and the drift with constant time distortion components is practically absent in this device.

Open access

Matej Kucera, Miroslav Gutten, Milan Simko, Milan Sebok, Daniel Korenciak, Roman Jarina and Martin Pitonak

Abstract

The article presents a theoretical analysis of electromagnetic compatibility (EMC) and experimental measurement of effects of radiation and acoustic emission of high-voltage transformers for electronic equipment and working personnel in a control room. Electromagnetic compatibility and safety of equipment are not considered as two distinct areas of study in electric and electronic safety. Economic criteria cannot compromise safety but at the same time immunity levels must be relevant in order to establish a “Functional Safety”. Introducing Special Immunity Levels in the level of equipment testing allows us to combine the two areas of EMC and safety. The measurement was carried out in high-current of very high-voltage distribution station. A real-life analysis of effects of electric and electromagnetic field was carried out. FFT was used for mathematical processing of data which were later presented in a graphical form of a spectrally analyzed area. In the last part of the paper we discuss the suitability of acoustic camera to perform contactless monitoring of the health and operation conditions of the power transformer by analyzing acoustic field generated by the transformer core and windings in near control room.

Open access

Rokas Kvedaras, Vygaudas Kvedaras, Tomas Ustinavičius and Ričardas Masiulionis

Abstract

The paper presents the developed complex Digital Signal Processing algorithm for the reduction of white and 1/f noise and processing of the measurement signals of the Settling Time Measurement of the Digital-to-Analog Converters. The results show that the proposed DSP algorithm ensures 100-fold suppression of the white noise and 1/f noise. It was shown that it is possible to measure settling times of highspeed DACs (up to 16-17 Bits) with readout levels of ± 0.5 LSB while measurement errors do no exceed ± 1.4 ns.