Salina Abd. Samad

Development of a DSP-Based Power Quality Monitoring Instrumentfor Real-Time Detection of Power Disturbances

Current trends of power quality monitoring instruments are based on digital signal processors (DSP), which are used to record waveforms and harmonics and comes with software for collecting data and viewing monitoring results. The variations in the DSP based instruments are in the way algorithms that are developed for processing the real-time power quality waveforms. At present, all of the available power quality monitoring instruments are not capable of troubleshooting and diagnosing power quality problems. Therefore, a DSP-based power quality monitoring instrument is proposed for real-time disturbance recognition and source detection. The proposed instrument uses the Texas Instruments TMS320C6711DSP starter kit with a TI ADS8364EVM analog digital converter mounted on the daughter card. The instrument architecture and the software implementation are discussed in the paper. Preliminary experimental results displaying the fast Fourier transform analysis of the real-time voltage signals are included

Analysis of the Sound of the Kompang for Computer Music Synthesis

This paper presents an analysis of the properties and the characteristics of sound made by a kompang for computer music synthesis. The kompang is a Malay traditional musical instrument with a circular membrane made from goatskin. It is classified as a membranophone. The sound samples used for analysis are the sound produced by the kompang as the instrument is played traditionally, by striking it with the palm near the centre of the membrane and striking it with the fingers near the boundary of the membrane. The sound samples are analyzed using time and frequency domain analysis. Time domain analysis uses waveform examination and amplitude envelope detection, while frequency domain analysis uses the fast Fourier transform analysis and the short time Fourier transform analysis. The sample waveforms, frequency content, and spectrogram are obtained. The results show that when the kompang is struck at the centre of the membrane, the sound has a longer attack and decay period and a larger amount of frequency content than when it is struck near the edge of the membrane. Like most membranophones, sound produced by the kompang does not have a pitch since the normal modes of the excited kompang do not have frequencies that are integral multiples of a number.

Software defined radio for RFID signal in Rayleigh fading channel

Software Defined Radio (SDR) based tools of identification may increase with the diffusion of frequency agnostic modes of radio frequency identification (RFID). Similarly, fixed frequency readers may be replaced with interrogators that can operate in any frequency. SDR is a feasible solution for RFID signal, which can perform different functions at different times on the same hardware. Pilot Symbol Assisted Modulation (PSAM) is a good method to compensate for the channel fading effect in wireless mobile communications. In this paper, we first build up a SDR simulation including coding, modulation, Rayleigh fading, decoding and demodulation with match filter. Then, we test the effect of channel model to the RFID signal in receiver with constellation and BER (bit error rate) plots under PSAM.

Human activity classification for smart home: A multiagent approach

Smart home research requires study of psychological characteristics of home user. People follow some specific patterns in their life style. Inhabitant activity classification plays a vital role to predict smart home events. The paper proposed a multiagent system to track the user for task isolation. The system is composed of cooperative agents which works by sharing local views of individual agents. An algorithm is derived based on opposite entity state extraction for activity classification. The algorithm clusters the smart home events by isolating opposite status of home appliance. Result shows that the proposed algorithm can successfully identify inhabitant activities of various lengths.

A non linear face recognition system using Support Vector Machine

A face recognition system uses face to verify individuals using computing capability. However, its performances often degrade due to high dimensional data and large feature appearance of the face image. This paper present a face recognition system based on non linear feature extraction technique to reduce the dimensionality of the face image, called Locally Linear Embedding. This method considers the hidden layer of face manifold to be the input of a SVM multiclass classifier. The performance is evaluated using the ORL database and achieved better recognition rates than the Principal Component Analysis.

The Efficiency of Data Hiding by Manipulating the DPCM Macroblocks in Compressed Video

Steganography is the idea of embedding a secret data in different media and has become an important regulation of methods of data integration. Although the still images are generally applied in the past, is very popular in recent years for the video. The techniques of video data hiding in recent year’s emphasis on the features generated by the video compression standard, a safer method for steganography uses MPEG-4/H.264 Bit Plane Complexity Segmentation (BPCS) algorithm is proposed in this approach. The reason for choosing such a video coverage is the enormous amount of data that can be hidden in each frame of MPEG-4 video. In other words, MPEG-4 has three types of images: I-frame, B, and P frames. Unlike other techniques used to hide data, such as the LSB algorithm, PBCS can achieve better results in both mathematics expression and human vision. In this paper, data is embedded in the videos of the I-frame until the BPCS can reach high levels of integration with low distortion based on the theory that regions of low noise-levels as in a picture can be replaced by noise without a significant loss of image quality. This approach invents data hidden in high-security environments. Experimental results show the success of hidden data in the selected and extracted data from the sequence of frames and also indicate the effectiveness of the implementation plan of steganography compressed video with high security features.

New Approach of Encrypting Embedded Data in H.264 Compressed Video

Digital video steganography has attracted a great deal of research interest in the recent few years in applications. In this paper, we propose a method to embed and encrypt messages into video sequences by using steganography technique Based on the H.264 video coding standard. The system implemented in this work provides robust H.264 video compression constant, without significantly affecting the overall bit rate and quality of the video stream. The results indicate that the algorithm can be implemented steganography fast and efficiently and effect vision and peak signal to noise ratio (PSNR) of video sequences are almost unaffected after decoding.

Investigation on Different Pre-processing Approaches for Face Recognition System

One of the challenges in face recognition system is to deal with inhomogeneous intensity problem that occur with different lighting conditions. In this paper, comparisons are made on several pre-processing methods i.e. histogram equalization, local binary pattern, wavelet transform and multiscale retinex. First, the input image is pre-processed with the illumination correction method before the classification task is done. The results are evaluated using the Yale, ORL and our own UKM database. These databases include images with various illumination conditions and expressions. Using PCA as the feature extraction and Euclidean Distance as the classification purposed, our experiments shows that multiscale retinex achieved the lowest equal error rates with 5.03% followed by local binary pattern (7.52%), wavelet transform (12.53%) and histogram equalization (12.97%) on average for all three databases.

TPMS for Intelligent Vehicle Safety Application

The vehicles being operated without tire pressure monitoring system (TPMS) is posing a significant safety problem. To solve the problems, number researches have been widely investigated. However, factors of limitation described in introduction are still the major concern. Hence, the appropriate systems of TPMS are still being investigated. This paper deals with development of TPMS that contributes significantly towards the enhancement of the intelligent vehicle safety application. A detailed overview on tire pressure monitor (TPM) and receiver modules development such as data acquisition, communication protocol, Manchester encoding algorithm and interface programme are demonstrated. The performance evaluation of the experimental results of the TPMS shows that data acquisition, complete messages of pressure and temperature and real-time monitoring are unique and advance. Thus, the experimental result is therefore ensures the data monitoring and provides warning to validate the usefulness of the TPMS system in maintaining and enhancing vehicle performance.