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Bulletin of Electrical Engineering and Informatics

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Published by Institute of Advanced Engineering and Science

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Core Subject : Science, Engineering,

Computer Science & IT Electrical & Electronics Engineering Engineering

Bulletin of Electrical Engineering and Informatics ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication, computer engineering, computer science, information technology and informatics from the global world. The journal publishes original papers in the field of electrical (power), electronics, instrumentation & control, telecommunication and computer engineering; computer science; information technology and informatics. Authors must strictly follow the guide for authors. Please read these instructions carefully and follow them strictly. In this way you will help ensure that the review and publication of your paper is as efficient and quick as possible. The editors reserve the right to reject manuscripts that are not in accordance with these instructions.

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Articles 45 Documents

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Search results for , issue "Vol 8, No 1: March 2019" : 45 Documents clear

Progress in neural network based techniques for signal integrity analysis–a survey Chan Hong Goay; Azniza Abd Aziz; Nur Syazreen Ahmad; Patrick Goh
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

With the increase in data rates, signal integrity analysis has become more time and memory intensive. Simulation tools such as 3D electromagnetic field solvers can be accurate but slow, whereas faster models such as design equations and equivalent circuit models lack accuracy. Artificial neural networks (ANNs) have recently gained popularity in the RF and microwave circuit modeling community as a new modeling tool. This has in turn spurred progress towards applications of neural networks in signal integrity. A neural network can learn from a set of data generated during the design process. It can then be used as a fast and accurate modeling tool to replace conventional approaches. This paper reviews the recent advancement of neural networks in the area of signal integrity modeling. Key advancements are considered, particularly those that assist the ability of the neural network to cope with an increasing number of inputs and handle large amounts of data.

Knots timber detection and classification with C-Support Vector Machine Fakhira Iwani Muhammad Redzuan; Marina Yusoff
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

Timber knots recognition is of prime importance to further determine the timber grade. The recognition is normally based on the human expert’s eyes in which can lead to some flaws based on human limitations and weaknesses. The use of X-ray can cause emits radiation and can be dangerous to the workers. This paper addresses the employment of computational methods for knot detection. A pre-processing and feature extraction methods include contrast stretching, median blur and thresholding, gray scale and local binary pattern were used. More than 400 datasets of knot images of the tropical timbers, namely Acacia and Hevea Brasiliensis have been tested using C-support vector machine as a knot classifier. The findings demonstrate different performances for three types of kernel. Linear kernel function outperformed both radial basis function and polynomial kernel functions for Acacia and Hevea Brasiliensis species. Both species classifications using linear kernel have managed to achieve a promising accuracy. Knots classification with the used of support vector machine has shown a promising result to improve the classifier and test with different types of tropical timbers.

Solving financial allocation problem in distribution system expansion planning Siti Hajar Mohd Tahar; Shamshul Bahar Yaakob; Ahmad Shukri Fazil Rahman; Amran Ahmed
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

This paper introduces a new technique to solve financial allocation in Distribution System Expansion Planning (DSEP) problem. The proposed technique will be formulated by using mean-variance analysis (MVA) approach in the form of mixed-integer programming (MIP) problem. It consist the hybridization of Hopfield Neural Network (HNN) and Boltzmann Machine (BM) in first and second phase respectively. During the execution at the first phase, this model will select the feasible units meanwhile the second phase will restructured until it finds the best solution from all the feasible solution. Due to this feature, the proposed model has a fast convergence and the accuracy of the obtained solution. This model can help planners in decision-making process since the solutions provide a better allocation of limited financial resources and offer the planners with the flexibility to apply different options to increase the profit.

Tooth segmentation using dynamic programming-gradient inverse coefficient of variation Anuar Mikdad Muad; Nur Sakinah Mohamed Bahaman; Aini Hussain; Mohd Yusmiaidil Putera Mohd Yusof
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

Teeth provide meaningful clues of an individual. The growth of the teeth is correlated with the individual age. This correlation is widely used to estimate age of an individual in applications like conducting forensic odontology, immigration, and differentiating juveniles and adolescents. Current forensic dentistry largely depends on laborious investigation process that is performed manually and can be influenced by human factors like fatigue and inconsistency. Digital panoramic radiograph dental images allow noninvasive and automatic investigation to be performed. This paper presents analyses on third molar tooth segmentation for the population in Malaysia, ranging from persons age of 5 years old to 23 years old. Two segmentation techniques: gradient inverse coefficient of variation with dynamic programming (DP-GICOV) and Chan-Vese (CV) were employed and compared. Results demonstrated that the accuracy of DP-GICOV and CV were 95.3%, and 81.6%, respectively.

Haze alarm visual map (HazeViz): an intelligent haze forecaster Mohd Said Syukri Morsid; Syeril Azira Jamaluddin; Nur Azmina Hood; Norshahida Shaadan; Yap Bee Wah; Muthukkaruppan Annamalai
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

The haze problem has intensified in recent years. The particulate matter of less than 10 microns in size, PM10 is the dominant air pollutant during haze. In this paper, we present the development of HazeViz, a Haze Alarm Visual Map forecaster, which is based on PM10. The intelligent web application allows users to visualize the pattern of PM10 in a region, forecasts PM10 value and alarms bad haze condition. HazeViz was developed using HTML, Java Script, PHP, MySQL, R Programming and Fusionex Giant. The SARIMA statistical forecasting models that underlie the application were developed using R. The PM10 trend analysis, and the consequential map and chart visualizations were implemented on the Fusionex GIANT Big Data Analytics platform. HazeViz was developed in the context of the Klang Valley, our case study. The dataset was obtained from Department of Environment Malaysia, which contains a total of 157,680 hourly PM10 data for six stations in Klang Valley, for the years 2013 to 2015. The SARIMA models were developed using maximum daily PM10 data for 2013 and 2014, and the 2015 data was used to validate the model. The fitting models were determined based on the Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). While the selected models were implemented in HazeViz and successfully deployed on the web, the results show that the selected models have MAPE ranging between 35 percent and 45 percent, which implies that the models are still far from robust. Future work can consider augmented SARIMA models that can yield improved results.

Evaluating users’ emotions for Kansei-based Malaysia higher learning institution website using Kansei checklist Punitha Turumogan; Aslina Baharum; Ismassabah Ismail; Nor Azida Mohamed Noh; Nur Shahida Ab Fatah; Noorsidi Aizuddin Mat Noor
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

Emotions play a crucial role in human-computer interaction. Emotion research in the field of human-computer interaction has only started recently and continuously evolving through the investigation and understanding of emotional effects. Thus, it forms an intelligent interaction between human and computer by responding effectively to the humans’ feelings. Emotional design generates remarkable user experiences for websites as the emotional experiences create an intense impression on our long-term memory. Recent scientific findings recommend emotional elements to be considered in designing websites as emotions influences one’s perception, conception and decision-making throughout the interaction with a website. A poorly designed user interface leads to bad user interaction while rising the users’ arousal and a displeasing user experience with a website elicits dissatisfaction emotion where consecutively results in avoidance and prevents revisit to the website. This proves the importance of emotional engagement in a website design. This research evaluated users’ emotions toward a Malaysian higher learning institution website which was designed in accordance with the standard Kansei-based web design guideline. The result justified the standard Kansei-based web design guideline for website of higher learning institutions in Malaysia.

Modeling and simulation of three phases cascaded H-bridge grid-tied PV inverter Swetapadma Panigrahi; Amarnath Thakur
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

In this paper a control scheme for three phase seven level cascaded H-bridge inverter for grid tied PV system is presented. As power generation from PV depends on varing environmental conditions, for extractraction of maximum power from PV array, fuzzy MPPT controller is incorporated with each PV array. It gives fast and accurate response. To maintain the grid current sinusoidal under varying conditions, a digital PI controller scheme is adopted. A MATLAB/Simulink model is developed for this purpose and results are presented. At last THD analysis is carried out in order to validate the performance of the overall system. As discussed, with this control strategy the balanced grid current is obtained keeping THD values with in the specified range of IEEE-519 standard.

Fabrication and studying the dielectric properties of (polystyrene-copper oxide) nanocomposites for piezoelectric application Dalal Hassan; Ahmed Hashim Ah-yasari
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

The preparation of (polystyrene-copper oxide) nanocomposites have been investigated for piezoelectric application. The copper oxide nanoparticles were added to polystyrene by different concentrations are (0, 4, 8 and 12) wt.%. The structural and A.C electrical properties of (PS-CuO) nanocomposites were studied.The results showed that the dielectric constant and dielectric loss of (PS-CuO) nanocomposites decrease with increase in frequency. The A.C electrical conductivity increases with increase in frequency. The dielectric constant, dielectric loss and A.C electrical conductivity of polystyrene increase with increase in copper oxide nanoparticles concentrations. The results of piezoelectric application showed that the electrical resistance of (PS-CuO) nanocomposites decreases with increase in pressure.

Simulation design of trajectory planning robot manipulator Wahyu S. Pambudi; Enggar Alfianto; Andy Rachman; Dian Puspita Hapsari
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

Robots can be mathematically modeled with computer programs where the results can be displayed visually, so it can be used to determine the input, gain, attenuate and error parameters of the control system. In addition to the robot motion control system, to achieve the target points should need a research to get the best trajectory, so the movement of robots can be more efficient. One method that can be used to get the best path is the SOM (Self Organizing Maps) neural network. This research proposes the usage of SOM in combination with PID and Fuzzy-PD control for finding an optimal path between source and destination. SOM Neural network process is able to guide the robot manipulator through the target points. The results presented emphasize that a satisfactory trajectory tracking precision and stability could be achieved using SOM Neural networking combination with PID and Fuzzy-PD controller.The obtained average error to reach the target point when using Fuzzy-PD=2.225% and when using PID=1.965%.

VMQ: an algorithm for measuring the Video Motion Quality Nawaf O. Alsrehin; Ahmad F. Klaib
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

This paper proposes a new full-reference algorithm, called Video Motion Quality (VMQ) that evaluates the relative motion quality of the distorted video generated from the reference video based on all the frames from both videos. VMQ uses any frame-based metric to compare frames from the original and distorted videos. It uses the time stamp for each frame to measure the intersection values. VMQ combines the comparison values with the intersection values in an aggregation function to produce the final result. To explore the efficiency of the VMQ, we used a set of raw, uncompressed videos to generate a new set of encoded videos. These encoded videos are then used to generate a new set of distorted videos which have the same video bit rate and frame size but with reduced frame rate. To evaluate the VMQ, we applied the VMQ by comparing the encoded videos with the distorted videos and recorded the results. The initial evaluation results showed compatible trends with most of subjective evaluation results.

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