Waree Kongprawechnon

A framework for automatic heart sound analysis without segmentation

BackgroundA new framework for heart sound analysis is proposed. One of the most difficult processes in heart sound analysis is segmentation, due to interference form murmurs.MethodEqual number of cardiac cycles were extracted from heart sounds with different heart rates using information from envelopes of autocorrelation functions without the need to label individual fundamental heart sounds (FHS). The complete method consists of envelope detection, calculation of cardiac cycle lengths using auto-correlation of envelope signals, features extraction using discrete wavelet transform, principal component analysis, and classification using neural network bagging predictors.ResultThe proposed method was tested on a set of heart sounds obtained from several on-line databases and recorded with an electronic stethoscope. Geometric mean was used as performance index. Average classification performance using ten-fold cross-validation was 0.92 for noise free case, 0.90 under white noise with 10 dB signal-to-noise ratio (SNR), and 0.90 under impulse noise up to 0.3 s duration.ConclusionThe proposed method showed promising results and high noise robustness to a wide range of heart sounds. However, more tests are needed to address any bias that may have been introduced by different sources of heart sounds in the current training set, and to concretely validate the method. Further work include building a new training set recorded from actual patients, then further evaluate the method based on this new training set.

A robust controller design of SSSC for stabilization of frequency oscillations in interconnected power systems

Abstract As an AC interconnected power system is subjected to a large load with rapid change, system frequency may be severely disturbed and becomes oscillatory. To stabilize the frequency oscillations, the dynamic power flow control of the Static Synchronous Series Compensator (SSSC) located in series with the tie line between interconnected power systems, is employed. By regarding the system interconnection as the control channel, the power flow control by an SSSC via the interconnection creates a sophisticated method of frequency stabilization. To implement this concept, the robust design method of the lead/lag controller equipped with the SSSC is proposed. In the design process, not only the attenuation performance of system disturbances, but also the robust stability against system uncertainties are taken into consideration. The optimal parameters of the lead/lag controller are obtained by using the tabu search algorithm (TSA), so that both performance and robustness are satisfied. In addition, the technique of overlapping decompositions is applied to reduce the order of the study power system, meanwhile the physical characteristic is still preserved. Simulation study exhibits the significant effect of designed controller on the study four-area interconnected power system under different load disturbances and variation of system parameters.

Improved gradient-based methods for motion estimation in image sequences

This paper shows that two conventional gradient-based motion estimation techniques can be significantly improved by using unit gradient vectors instead of image intensities. Since unit gradient vectors are insensitive to changing image intensities, the proposed motion estimation techniques are far more robust to irregular lighting conditions than the conventional techniques. In addition, the proposed techniques demonstrate much better motion estimation performance where image gradients are close to one-directional because the proposed methods utilize the measure of the varieties of local gradient directions as a weighting factor in the computation of motion estimates.

Test system for defect detection in construction materials with ultrasonic waves by support vector machine and neural network

This paper introduces a newly developed test system for structure inspection and evaluation of cement-based products by applying ultrasonic test with support vector machine (SVM) classifier. In other words, this paper represents a novel method based on SVM for defect detection, classification of number of defects, and identification of defect materials. With the system, pattern of ultrasonic waves for each case of specimen can be obtained from direct and indirect measurements. Machine learning algorithm called support vector machine and artificial neural network (ANN) are employed for classification and verification of the wave patterns obtained from different samples. By applying the system, the presence or absence of a defect in mortar can be identified. Moreover, the system can also classify the number of defects and identify the defect materials being inside the mortar. For classification, input features are extracted in different ways and the numbers of training sets are varied. Base on the results from SVM, the signals extracted in frequency domain gives better performance than time domain. Using a larger training set can give more satisfactory results. In this article, the methodology is explained and the classification results are discussed. The effectiveness of the developed test system is evaluated. Comparison of the classification results that obtained by between SVM and ANN classifiers is also demonstrated. This study shows that this technique based on pattern recognition has a high potential for practical inspection of concrete structure.

Discrete-Time Feedback Error Learning for Unknown Nonlinear Systems

In this study, the technique of discrete-time feedback error learning for nonlinear systems(DTFELN) is extended to control unknown nonlinear systems. First, the relationship between DTFEL and nonlinear discrete-time adaptive control with adaptive feedback linearization is discussed. It shows that DTFEL can be interpreted as a form of nonlinear adaptive control. Second, Lyapunov analysis of the controlled system is presented. It suggests that the condition of strictly positive realness (s.p.r.) associated with the tracking error dynamics is a sufficient condition for asymptotic stability of the closed-loop dynamics. Then, radial basis function is used to characterize as an approximation of the unknown basis function. Finally, numerical simulations is presented to illustrate the tracking performance of DTFELN.

Adaptive neural network based backstepping control design for MIMO nonlinear systems with actuator nonlinearities

Purpose – The purpose of the proposed research methodology is to control the trajectory tracking of EDRM and also to cancel out the effect of no-smooth nonlinearities, which affect the system performance badly. Design/methodology/approach – Robust adaptive neural network (RANN)-based backstepping control design methodology is presented in this paper. The proposed design methodology improves the trajectory tracking and running mean error. Findings – The running mean error results show that the convergence of the proposed RANN-based backstepping technique is very fast as compare to the conventional PD control and due to this proposed control technique, the EDRM follows its desired trajectory perfectly. Practical implications – The EDRM trajectory tracking performance increases which leads to a better working position of EDRM. Originality/value – The originality of this research article is 93 per cent.

Automatic screening of narrow anterior chamber angle and angle-closure glaucoma based on slit-lamp image analysis by using support vector machine

At present, Van Hericks method is a standard technique used to screen a Narrow Anterior Chamber Angle (NACA) and Angle-Closure Glaucoma (ACG). It can identify a patient who suffers from NACA and ACG by considering the width of peripheral anterior chamber depth (PACD) and corneal thickness. However, the screening result of this method often varies among ophthalmologists. So, an automatic screening of NACA and ACG based on slit-lamp image analysis by using Support Vector Machine (SVM) is proposed. SVM can automatically generate the classification model, which is used to classify the result as an angle-closure likely or an angle-closure unlikely. It shows that it can improve the accuracy of the screening result. To develop the classification model, the width of PACD and corneal thickness from many positions are measured and selected to be features. A statistic analysis is also used in the PACD and corneal thickness estimation in order to reduce the error from reflection on the cornea. In this study, it is found that the generated models are evaluated by using 5-fold cross validation and give a better result than the result classified by Van Hericks method.

Fuzzy controller and image enhancement for slit lamp microscopy

Because of lacking of Ophthalmologists in rural areas, Eye-Teleanalyzer is developed. Further, it is improved to have the function of an auto focus system and eye tracking system during focusing process. In this study, two processes are proposed to improve the performance of the system. The first process is use to deal not only with blinking image but also to control the motor of auto focus system. It aims to increase the speed and reduce the error. The study shows the improvement of the accuracy, reliability, and robustness of the system. Since the image obtained from the Eye Teleanalyzer provides only narrow vision image which is not an entire sharp image, the second process is applied to solve the problem. The proposed method used for image improvement is called dasiaImage Merging Techniquepsila. The technique is adopted to improve the quality and extend the vision of the image used in Eye-Teleanalyzer.

Design of Robust Frequency Stabilizers of Superconducting Magnetic Energy Storages

When large load disturbances occur in a power system, a system frequency may be heavily perturbed and oscillatory. To stabilize frequency oscillations, the active power controlled by superconducting magnetic energy storage (SMES) can be applied. In this paper, a new robust design of a frequency stabilizer equipped with SMES is presented. The frequency stabilizer is based on a second-order lead/lag compensator. To enhance the robust stability of the controlled system against uncertainties such as system parameters variations, various load changes etc., the multiplicative uncertainty is included in system modeling. As a result, the robust stability can be easily guaranteed in terms of the multiplicative stability margin (MSM). Control parameters of the frequency stabilizer are tuned by a tabu search, so that the desired damping ratio of the target inter-area mode and the best MSM are obtained. Simulation studies confirm the high robustness of the frequency stabilizer against system uncertainties

J-Lossless Conjugation for Discrete-Time Systems and its Sequential Structure

J-lossless conjugation is a powerful tool for carrying out the J-lossless factorization which is a crucial part of solving H ∞ control problem. In this paper, a necessary and sufficient condition for the existence of J-lossless conjugation is obtained which is represented in terms of a Riccati equation. Its sequential structure is exploited which is closely related to the celebrated factorization theory of J-lossless systems.