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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 :
Arjuna Subject : -
Articles 63 Documents
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Search results for , issue "Vol 14, No 1: April 2019" : 63 Documents clear
Collision-aware cooperative MAC protocol design for mobile ad-hoc networks Y. Neeraja; V. Sumalatha
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i1.pp455-461

Abstract

Mobile ad hoc networks are designed to maintain communication among the independent nodes without a server or base station. High efficient MAC protocol takes a major role to maintain collision free, bandwidth efficient communication among the networked nodes. Collisions among the nodes provide considerable reduction in the performance of the network. The objective of the work is to provide collision aware cooperative MAC protocol design by modifying the backoff to a specific range. It improves the throughput and reduces delay with less collision rate. It minimizes the complexity of the problem arising in memory and processing.
A computer vision based image processing system for depression detection among students for counseling Sandhya Parameswaran Namboodiri; Venkataraman D
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i1.pp503-512

Abstract

Psychological problems in college students like depression, pessimism, eccentricity, anxiety etc. are caused principally due to the neglect of continuous monitoring of students’ psychological well-being. Identification of depression at college level is desirable so that it can be controlled by giving better counseling at the starting stage itself. The disturbed mental state of a student suffering from depression would be clearly evident in the student’s facial expressions.Identification of depression in large group of college students becomes a tedious task for an individual. But advances in the Image-Processing field have led to the development of effective systems, which prove capable of detecting emotions from facial images, in a much simpler way. Thus, we need an automated system that captures facial images of students and analyze them, for effective detection of depression. In the proposed system, an attempt is being made to make use of the Image processing techniques, to study the frontal face features of college students and predict depression. This automated system will be trained with facial features of positive and negative facial emotions. To predict depression, a video of the student is captured, from which the face of the student is extracted. Then using Gabor filters, the facial features are extracted. Classification of these facial features is done using SVM classifier. The level of depression is identified by calculating the amount of negative emotions present in the entire video. Based on the level of depression, notification is send to the class advisor, department counselor or university counselor, indicating the student’s disturbed mental state. The present system works with an accuracy of 64.38%. The paper concludes with the description of an extended architecture for depression detection as future work.
Edge enhancement of IBP reconstruction by using sharp infinite symmetrical exponential filter A.R. A Nazren; Ngadiran R.; S. N. Yaakob
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i1.pp258-266

Abstract

This study contributes to provide an enhancement technique for improving the Iterative Back Projection (IBP) Super Resolution technique by using the Sharp Infinite Symmetrical Filter (SISEF). Theoretically, the IBP technique operates as minimizer the error reconstruction iteratively until it refined the High Resolution (HR) image. However, due to iterative manner and lack of edge guidance during the back projection operation, this technique has suffered from produced the ringing artefact on the HR image appearances. Additionally, the IBP reconstruction also demands for large number iteration for accomplishing the prediction HR image. This problem arose when the IBP estimator tended to oscillate at the same solution frequently. In order to overcome these constraints, the SISEF is deployed as regulator to improve the IBP estimator with provides an accurate edge information for enhancing the edge image and reduce the ringing artefacts. Fortunately, highly precision of edge information provided by SISEF capable to reduce amount of estimation process repetition.
Hybrid backpropagation neural network-particle swarm optimization for seismic damage building prediction Marina Yusoff; Faris Mohd Najib; Rozaina Ismail
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i1.pp360-367

Abstract

The evaluation of the vulnerability of buildings to earthquakes is of prime importance to ensure a good plan can be generated for the disaster preparedness to civilians. Most of the attempts are directed in calculating the damage index of buildings to determine and predict the vulnerability to certain scales of earthquakes. Most of the solutions used are traditional methods which are time consuming and complex. Some of initiatives have proven that the artificial neural network methods have the potential in solving earthquakes prediction problems. However, these methods have limitations in terms of suffering from local optima, premature convergence and overfitting. To overcome this challenging issue, this paper introduces a new solution to the prediction on the seismic damage index of buildings with the application of hybrid back propagation neural network and particle swarm optimization (BPNN-PSO) method. The prediction was based on damage indices of 35 buildings around Malaysia. The BPNN-PSO demonstrated a better result of 89% accuracy compared to the traditional backpropagation neural network with only 84%. The capability of PSO supports fast convergence method has shown good effort to improve the processing time and accuracy of the results.
Reservoir water level forecasting using normalization and multiple regression Siti Rafidah M-Dawam; Ku Ruhana Ku-Mahamud
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i1.pp443-449

Abstract

Many non-parametric techniques such as Neural Network (NN) are used to forecast current reservoir water level (RWLt). However, modelling using these techniques can be established without knowledge of the mathematical relationship between the inputs and the corresponding outputs. Another important issue to be considered which is related to forecasting is the preprocessing stage where most non-parametric techniques normalize data into discretized data. Data normalization can influence the the results of forecasting. This paper presents reservoir water level (RWL) forecasting using normalization and multiple regression. In this study, continuous data of rainfall (RF) and changes of reservoir water level (WC) are normalized using two different normalization methods, Min-Max and Z-Score techniques. Its comparative studies and forecasting process are carried out using multiple regression. Three input scenarios for multiple regression were designed which comprise of temporal patterns of WC and RF, in which the sliding window technique has been applied. The experimental results showed that the best input scenario for forecasting the RWLt employs both the RF and the WC, in which the best predictors are three day’s delay of WC and two days’ delay of RF. The findings also suggested that the performance of the RWL forecasting model using multiple regression was dependent on the normalization methods.
A symmetry based anomaly detection in brain using cellular automata for computer aided diagnosis Nisha V M; L Jeganathan
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i1.pp471-477

Abstract

Computer aided diagnosis (CAD) is an advancing technology in medical imaging. CAD acts as an additional computing power for doctors to interpret the medical images which leads to a more accurate diagnosis of the disease.CAD system increases the chances of detection of brain lesions by assisting the physicians in decreasing the observational oversight in the early stage of diseases.This paper focuses on the development of a cellular automata based model to find the anomaly prone areas in human brains.Because of the bilateral symmetric nature of human brain, a symmetry based cellular automata model is proposed.An algorithm is designed based on the proposed model to detect the anomaly prone areas in brain images. The proposed model can be a standalone model or it can be incorporated to a sophisticated computer aided diagnosis system. By incorporating asymmetry information into a computer aided diagnosis system, enhances its performance in identifying the anomalies exists in bilaterally symmetrical brain images.
A novel approach of multiplier design based on BCD decoder Salah Alkurwy
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i1.pp38-43

Abstract

A novel approach of multiplier design is presented in this paper. The design idea is implemented based on binary coded decimal (BCD) decoder to seven segment display, by computing all the probability of multiplying 3 3 binary digits bits and grouping in table rows. The obtaining of the combinational logic functions is achieved by simplified the generated columns of [A5: A0], using a Karnaugh map. Then, the 3 3-bits multiplier circuit is used to implement the 6x6- and 12x 12-bit multipliers. Comparing with a conventional multiplier, the proposed design outperformed in terms of the time delay by a 32% and 41.8% respectively. It is also reduced the combinational adaptive look-up-tables (ALUTs) by 24.6%, and 46% for both multipliers. Both overmentioned advantages make the proposed multipliers more attractive and suitable for high-speed digital systems      
Comparison of different configuration space representations for path planning under combinatorial method Sanjoy Kumar Debnath; Rosli Omar; Nor Badariyah Abdul Latip
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i1.pp1-8

Abstract

The use of autonomous vehicle/robot has been adopted widely to replace human beings in performing dangerous missions in adverse environments. Keeping this in mind, path planning ensures that the autonomous vehicle must safely arrive to its destination with required criteria like lower computation time, shortest travelled path and completeness. There are few kinds of path planning strategies, such as combinatorial method, sampling based method and bio-inspired method. Among them, combinatorial method can accomplish couple of criteria without further adjustment in conventional algorithm. Configuration space provides detailed information about the position of all points in the system and it is the space for all configurations. Therefore, C-space denotes the actual free space zone for the movement of robot and guarantees that the vehicle or robot must not collide with the obstacle. This paper analyses different C-Space representation techniques under combinatorial method based on the past researches and their findings with different criteria such as optimality, completeness, safety, memory uses, real time and computational time etc. Visibility Graph has optimality which is a unique from other
BER analysis of concatenated levels of encoding in GFDM system using labview Nagarjuna Telagam; S Lakshmi; K Nehru
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i1.pp77-87

Abstract

All the devices are interconnected each other in digital form, for different applications the input data is encoded for error correcting and detecting purpose. The paper describes the transmission of QAM signals with two level encoded stages, i.e. convolutional and hamming coded GFDM system with 256-point IFFT at transmitter and FFT at the receiver using LABVIEW software. GFDM is a non-orthogonal, digital multicarrier transmission scheme which digitally implements the classical filter bank approach. GFDM transmits a block of frame composed by M time slots with K subcarriers. The higher order QAM is used because of transmitting more data but is less reliable when compared to lower order QAM. Based on GFDM specifications for the IEEE 802.11, latest 5G physical layer standards, the coding is provided by ½ rate encoder at the input side, and Maximum Likelihood decoder at the receiver side is used. The standard convolution code (7, [171, 133]), is used as encoder for the GFDM system. The GFDM complex values are displayed in the front panel, along with FFT and power spectrum is plotted for GFDM signal. The array of input bits and output bits are shown with green colour LED’s. The van de Beek algorithm is used at the receiver for maximum likelihood detection acts as convolutional decoder of GFDM signal. Next the signal is subjected to remove cyclic prefix and zero padding and applied to channel estimation algorithm. The un-equalized data and equalized data graph is shown in the front panel, before and after channel estimation VI. With BER VI available in the LABVIEW the data is normalized and its response is plotted with respect to SNR. BER values for different levels of encoders have shown in table for SNR values. This paper concludes the 32.91% improvement in BER for two levels of concatenated codes.Thus the GFDM signal outperforms the OFDM signal interms of BER for series levels of coding using labVIEW software.
Spectral coding performance under free space optical medium A.K Rahman; N Julai; M. Jusoh; C.B.M Rashidi; S.A Aljunid; Anuar M.S; M.F Talib; Nurdiani Zamhari; S.K Sahari; K.F. Tamrin; Rudiyanto P. Jong; D.N.A Zaidel; N.A.A Mohtadzar; M.R.M Sharip; Y.S Samat
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i1.pp290-294

Abstract

 This paper focus on performance of code Zero Correlation-Correlation (ZCC) in free space optical communication. The ZCC code has a superior characteristic which eliminate the overlapping code between any users. Due to this high class characteristic, the code improves the performance of the conventional code in free space optical environment. In this paper the analysis performance of bit error rate is considering the avalanche (APD) noise, thermal noise and multiuser interference. The result shows that ZCC code improve the performance of conventional code in term of number of users, power received and data bit rate.

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