Zaiton Sharif

Analysis and classification of heart sounds and murmurs based on the instantaneous energy and frequency estimations

This paper proposes the use of the instantaneous energy and the frequency estimation in the classification of the heart sounds and murmurs for common heart diseases. It has been known that the present of the heart murmurs in ones heart sound indicates that there is a potential heart problem. Thus, the goal of this work is to develop a technique for detecting and classifying murmurs. Such a technique can be used as part of a heart diagnostic system. The analysis is performed based on a set of 102 data for various heart sounds. To discriminate the various heart sounds, the instantaneous energy and frequency estimation is used to estimate the features of heart sound. The techniques used to estimate the instantaneous frequency are the central finite difference frequency estimation (CFDFE) and zero crossing frequency estimation (ZCFE). From the instantaneous energy and frequency estimate, the energy and frequencies of the heart sounds are defined as the features of the heart sounds that can uniquely discriminate the various heart sounds.

Classification and quantification of palm oil adulteration via portable NIR spectroscopy

Short wave near infrared spectroscopy (NIR) method was used to detect the presence of lard adulteration in palm oil. MicroNIR was set up in two different scan modes to study the effect of path length to the performance of spectral measurement. Pure and adulterated palm oil sample were classified using soft independent modeling class analogy (SIMCA) algorithm with model accuracy more than 0.95 reported for both transflectance and transmission modes. Additionally, by employing partial least square (PLS) regression, the coefficient of determination (R2) of transflectance and transmission were 0.9987 and 0.9994 with root mean square error of calibration (RMSEC) of 0.5931 and 0.6703 respectively. In order to remove the uninformative variables, variable selection using cumulative adaptive reweighted sampling (CARS) has been performed. The result of R2 and RMSEC after variable selection for transflectance and transmission were improved significantly. Based on the result of classification and quantification analysis, the transmission mode has yield better prediction model compared to the transflectance mode to distinguish the pure and adulterated palm oil.

The Application of Cross Correlation Technique for Estimating Impulse Response and Frequency Response of Wireless Communication Channel

Cross correlation technique is one of the most commonly used methods to estimate the channel impulse response such as a wireless communication channel. This paper looks at the use of two different types of signals that is applied in the cross correlation technique. The signals are phase shift keying (PSK) and linear FM signals (Chirps). Pseudo random sequence (PRS) is used in the generation of the PSK signals. The parameters of the PRS are varied according to the sequence lengths, sampling frequency and bit rate. From the cross correlation functions and the cross spectrum, the channel impulse response and channel frequency response are respectively estimated. Besides PSK signals, linear FM signal is also used as an input to estimate the channel impulse response. Both PSK and linear FM signals are chosen due to their auto correlation properties that are similar to an impulse function. Thus, the channel impulse response can be estimated based on the cross correlation between the output and the input signals. The desired and the estimated channel impulse responses and channel frequency response are respectively estimated and compared based on the mean squared error (MSE).

An expert system approach for classification of heart sounds and murmurs

The various types of heart valvular problems can be classified from the auscultation of heart sounds and murmurs that only requires the use of the stethoscope. To discriminate the various heart sounds and murmurs, the signal parameters are estimated using the instantaneous energy and frequency estimation (IEFE) technique. The parameters are then used as inputs to an expert system classifier to classify the heart sounds and murmurs based on the rule-based method.

Detection and analysis of power quality disturbances using Bilinear Time-Frequency Distribution

This paper presents a Bilinear Time Frequency Distribution (BTFD) for recognition and detection of power quality (PQ) disturbances with power related analysis. BTFD have been intensively used to characterize and analyze non stationary signals. The bilinear TFDs offer a good time and frequency resolution and are successfully applied to various reallife problems such as radar, sonar, seismic data analysis, biomedical engineering, and automatic emission [4]. The method used in this paper is Wigner Ville Distribution. This paper will characterize the pattern for the tested power quality disturbances signals such as voltage sag, harmonics, and voltage swell in Time-frequency representation. This proposed BTFDs Time-Frequency Representation has a better insight and time resolution compared to the time domain representation or frequency domain representation alone.

Estimation of the Doppler spread and time delay spread for the wireless communication channel

The performance of the wireless communication channel including HF channel is strongly affected by the short term variations. It is due to the multipath fading which introduces time and frequency selective fading. By characterizing the wireless channel, the information can be used to increase the performance of the wireless communication. Doppler spread and time delay spread are parameters to be investigated where they can be used to characterize the wireless channel. Scattering function via the ambiguity function estimator is adopted in this work. PSK signal with two signal lengths (1 second and 2 seconds) are used in the analysis. The analysis is performed in the absent of the white Gaussian noise. The Doppler spread is estimated from the spread of the scattering plot at the peak of each path while the time delay spread is estimated from the time lag marginal of the scattering function derivation. BPSK having duration of more than 1 second can be used to estimate the Doppler spread and the time delay in the multipath environment. The information on the number of path and their attenuations can also be obtained. Besides, it can give information on the frequency selective fading and the multipath fading condition of the channel.

Characterization of wireless communication channel based on scattering function

Almost all communication channels introduce dispersive or multiplicative disturbances which give rise to dispersive effects known as time selective fading and frequency selective fading. Scattering function can be used to characterize this channel in terms of time delay profile and Doppler spread. Doppler spread gives a measure in frequency variation where it introduces time selective fading. Frequency selective fading on the other hand is the effect of time delay spread in frequency domain where certain frequency components in the received signal spectrum have greater gains than the others. Channel scattering function is determined based on the ambiguity function and it is derived based on the Fourier transform relationship of the cross bilinear. Based on periodogram of the scattering function, time delay spread and Doppler spread can be determined. PSK and QPSK signals having duration of 0.512 sec are used for this purpose.

FT-NIR, MicroNIR and LED-MicroNIR for detection of adulteration in palm oil via PLS and LDA

Chemometrics analysis was performed to compare the performance of FT-NIR, MicroNIR and LED-NIR for detection of adulteration in palm oil. FT-NIR has a high spectral resolution and signal-to-noise ratio, but MicroNIR is more light weight and suitable for on-site application. The feasibility of LED to replace the conventional halogen tungsten light source in MicroNIR has been discussed in this paper. The wavelength of LEDs was based on the variable selection method, CARS, and the results were in good agreement with the C–H and O–H bond interaction displayed in the observed NIR spectrum. The advantages of using LED instead of a halogen tungsten light source are cost effectiveness, low power consumption and reduced number of variables. Different pretreatment approaches has been applied to the spectral data acquired to investigate the performance of preprocess to the result of chemometrics. Quantitative analysis was performed using partial least square (PLS) algorithms with the linear regression method. The best correlation coefficient, (R2), reported using FT-NIR was 0.99 with RMSEC and RMSEP values less than 1, indicating that the spread of calibration and prediction data was small. The LDA result showed that LED-NIR outperforms FT-NIR and MicroNIR with a sensitivity of 1.00 and a specificity of 0.9333.

Application of K-Means clustering in hot spot detection for thermal infrared images

K-Means Clustering is one of the method for image segmentation which will subtract the interest area from background. By using K-Means Clustering, thermal image is divided into 2 layers which separates the hotter region from the background image. This will ease the hot spot detection on thermal infrared images. This paper presents work on the implementation of K-Means Clustering onto thermal images. The algorithm for thermal infrared image segmentation using K-Means Clustering was developed and executed using MATLAB R2015a software. It was proven that K-Means Clustering ease the hot spot detection from the thermal images.

The comparison between listening to Surah Al-Mulk and Surah Al-Hasyr using EEG

The Quran is a script consisting of 114 Surah. The Quran is known to have positive effects on human, aids the stress healing process. Each Surah is provided for a different understanding and meaning of its own. This paper investigates the subjects reaction towards listening to two different Surahs. The electroencephalogram (EEG) machine was used to observe and record the subject brain activity. By using the EEG, brain signals of the subject taken with 2 sessions. The first session the subject listens Surah Al-Mulk, while second session the subject listens Surah Al-Hasyr. Results indicate that on average the subjects are more relax while listening to Surah Al-Hasyr compared to Surah Al-Mulk. In addition, the subjects brain induced alpha right brainwaves the both of Surahs.