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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
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Articles 49 Documents
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Search results for , issue "Vol 10, No 1: April 2018" : 49 Documents clear
Adopting Hardware-In-the-Loop for Testing Vehicle Instrument Panel using Economical Approach Wan Shahmisufi Wan Jamaludin; Tan Wei Ren; Bakhtiar Affendi Rosdi; Dahaman Ishak; Noor Hafizi Hanafi; Muhammad Nasiruddin Mahyuddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp50-58

Abstract

An economical approach for testing Vehicle Instrument Panel is proposed in this paper due to high expenditure of purchasing the available Commercial Off-The-Shelf Hardware-In-The-Loop. Vehicle Instrument Panel is designated as the Device-Under-Test in this paper. The Hardware-In-The-Loop, designated as the test equipment, will simulate the assigned input signals controllable via designed Graphical User Interface. The resulting display is shown on the Graphical User Interface and the Device-Under-Test. The speedometer gauge measurement showed the highest disparity of 4 km/h which is within the tolerance of the pre-determined specification of the Device-Under-Test.
Classification of Leaf Disease from Image Processing Technique Mahanijah Md Kamal; Ahmad Nor Ikhwan Masazhar; Farah Abdul Rahman
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp191-200

Abstract

Disease in palm oil sector is one of the major concerns because it affects the production and economy losses to Malaysia. Diseases appear as spots on the leaf and if not treated on time, cause the growth of the palm oil tree. This work presents the use of digital image processing technique for classification oil palm leaf disease sympthoms. Chimaera and Anthracnose is the most common symtoms infected the oil palm leaf in nursery stage. Here, support vector machine (SVM) acts as a classifier where there are four stages involved. The stages are image acquisition, image enhancement, clustering and classification. The classification shows that SVM achieves accuracy of 97% for Chimaera and 95% for Anthracnose.
Multi-Level of Feature Extraction and Classification for X-Ray Medical Image Mohammed Muayad Abdulrazzaq; Imad FT Yaseen; SA Noah; Moayad A. Fadhil
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp154-167

Abstract

There has been a rise in demand for digitized medical images over the last two decades. Medical images' pivotal role in surgical planning is also an essential source of information for diseases and as medical reference as well as for the purpose of research and training. Therefore, effective techniques for medical image retrieval and classification are required to provide accurate search through substantial amount of images in a timely manner. Given the amount of images that are required to deal with, it is a non-viable practice to manually annotate these medical images. Additionally, retrieving and indexing them with image visual feature cannot capture high level of semantic concepts, which are necessary for accurate retrieval and effective classification of medical images. Therefore, an automatic mechanism is required to address these limitations. Addressing this, this study formulated an effective classification for X-ray medical images using different feature extractions and classification techniques. Specifically, this study proposed pertinent feature extraction algorithm for X-ray medical images and determined machine learning methods for automatic X-ray medical image classification. This study also evaluated different image features (chiefly global, local, and combined) and classifiers. Consequently, the obtained results from this study improved results obtained from previous related studies.
A Real Time Vein Detection System Kazi Istiaque Ahmed; Mohamed Hadi Habaebi; Md Rafiqul Islam
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp129-137

Abstract

Blood veins detection process can be cumbersome for nurses and medical practioners when it comes to special overweight type of patients.This simple routine procedure can lead the process into an extreme calamity for these patients. In this paper, we emphasized on a process for the detection of the vein in real time using the consecrations of Matlab to prevent or at least reduce the number of inescapable calamity for patients during the infusion of a needle by phlebotomy or doctor in everyday lives. Hemoglobin of the blood tissues engrossed the Near Infrared (NIR) illuminated light and Night vision camera is used to capture the scene and enhance the vein pattern clearly using Contrast Limited Adaptive Histogram Equalization (CLAHE) method. This simple approach can successfully also lead to localizing bleeding spots, clots from stroke …etc among other things.
Verification of Quartz Crystal Microbalance Array using Vector Network Analyzer and OpenQCM Ahmad Anwar Zainuddin; Anis Nurashikin Nordin; Rosminazuin Ab. Rahim; Aliza Aini Md. Ralib; Sheroz Khan; Cyril Guines; Matthieu Chatras; Arnaud Pothier
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp84-93

Abstract

Quartz Crystal Microbalance (QCM) is a device that allows non-destructive measurements of r in situ reaction activities. In this article, an array comprising of six 3MHz QCM sensors in an array were characterized using a vector network analyzer and OpenQCM, a portable measuring instrument that measures change in resonance frequency. Measurements of S21 transmission characteristics using the vector network analyzer provides the resonance frequency and can also be used to derive the RLC equivalent electrical circuit values of a resonant two-port network based on the Butterworth-Van Dyke model. In this work, Rm, Lm, Cm and Co were obtained via curve-fitting of the measurement results to the simulated results. Measurements were done in triplicates to verify reproducibility for all 6 sensors. For comparison, measurements were also done using a portable, open-source instrument, OpenQCM. The OpenQCM instrument directly measures changes in resonance frequencies, making it ideal for biosensing experiments, which correlate changes in mass with changes in resonance frequencies. Comparison between resonance frequency measurements using VNA and OpenQCM exhibit low percentage difference 0.2%.  This QCM sensor array has the potential of conducting real-time, point-of-care analyses for detection of biological molecules. 
Modified 128-EEA2 Algorithm by Using HISEC Lightweight Block Cipher Algorithm with Improving the Security and Cost Factors Alyaa Ghanim Sulaiman; Sufyan Salim Mahmood AlDabbagh
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp337-342

Abstract

128-EEA2 (Evolved Packet System Encryption Algorithm 2) is a confidentiality algorithm which is used to encrypt and decrypt block of data based on confidentiality key. This confidentiality algorithm 128-EEA2 is based on the AES-128 which is the block cipher algorithm of 128 bit in CTR mode. In this paper, we are going to replace the AES-128 block cipher algorithm by HISEC block cipher algorithm for two reasons such as reducing cost and ameliorate security factor.
Anomaly Detection in Log Records Poonam Ghuli
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp343-347

Abstract

Complex software systems are continuously generating application and server logs for the events which had occurred in the past. These logs generated and can be utilized for anomaly and intrusion detection. These log files can be used for anomaly or outlier detection. Certain types of abnormalities or exceptions such as spikes in HTTP requests, number of exceptions raised in logs, etc. All these events are logged into the log files for further analysis. These types of events are generally used for predicting the anomalies in future. The developed prototype assumes that the user inputs log records in a standard apache log format. At first the user uploads the log file for outlier detection. Next, a prototype is developed to get the number of HTTP requests for outlier detection. Then anomalies in number of HTTP requests are detected using three techniques namely InterQuartileRange method, Moving averages and Median Absolute deviation. Once the outliers are detected, these outliers are removed from the current dataset. This output is given as input to the Multilayer Perceptron model to predict the number of HTTP requests at the next timestamp 
Comparison of Entropy Coding mechanism on IEEE1857.2 Lossless Audio Compression Standard Fathiah Abdul Muin; Teddy Surya Gunawan; Mira Kartiwi; Elsheikh M.A. Elsheikh
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp176-183

Abstract

This paper has two objectives. First, we aim to review and analyze the performance of the IEEE 1857.2 standard, focusing is on the Golomb-Rice and Arithmetic entropy algorithms as well as the effect of the pre-processing block on these entropy blocks. The pre-processing block normalizes the error residue of the Linear Predictive encoder, which then is passed to Entropy block, where the selector chooses the entropy encoder to use. The second objective is to present results from experimenting different existing algorithms available to benchmark it’. The results are discussed, and comparisons are made to identify the effect on compression ratio and encoding speed of the lossless encoder. As well as this, comparison is made to analyze effects of enabling and disabling the pre-processing output to the Entropy Coding block. We concluded that pre-processing block works well to flatten the output at lower predictor order for all the sound types, but works best at improving the residual output for music sound type.
Wavelet-Based Weighted Median Filter For Image Denoising Of MRI Brain Images N. Rajalakshmi; K. Narayanan; P. Amudhavalli
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp201-206

Abstract

Preliminary diagnosing of MRI images from the hospital cannot be relied on because of the chances of occurrence of artifacts resulting in degraded quality of image, while others may be confused with pathology. Obtained MRI image usually contains limited artifacts. It becomes complex one for doctors in analyzing them. By increasing the contrast of an image, it will be easy to analyze. In order to find the tumor part efficiently MRI brain image should be enhanced properly. The image enhancement methods mainly improve the visual appearance of MRI images. The goal of denoising is to remove the noise, which may corrupt an image during its acquisition or transmission, while retaining its quality. In this paper effectiveness of seven denoising algorithms viz. median filter, wiener filter, wavelet filter, wavelet based wiener, NLM, wavelet based NLM, proposed wavelet based weighted median filter(WMF) using MRI images in the presence of additive white Gaussian noise is compared. The experimental results are analyzed in terms of various image quality metrics.

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