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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 9,174 Documents
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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.
Offline Signature Recognition using Back Propagation Neural Network Asyrofa Rahmi; Vivi Nur Wijayaningrum; Wayan Firdaus Mahmudy; Andi Maulidinnawati A. K. Parewe
Indonesian Journal of Electrical Engineering and Computer Science Vol 4, No 3: December 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v4.i3.pp678-683

Abstract

The signature recognition is a difficult process as it requires several phases. A failure in a phase will significantly reduce the recognition accuracy. Artificial Neural Network (ANN) believed to be used to assist in the recognition or classification of the signature. In this study, the ANN algorithm used is Back Propagation. A mechanism to adaptively adjust the learning rate is developed to improve the system accuracy. The purpose of this study is to conduct the recognition of a number of signatures so that can be known whether the recognition which is done by using the Back Propagation is appropriate or not. The testing results performed by using learning rate of 0.64, the number of iterations is 100, and produces an accuracy value of 63%.
Video Quality Assessment through PSNR Estimation for Different Compression Standards Renuka Girish Deshpande; Lata L Ragha; Satyendra Kumar Sharma
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp918-924

Abstract

Abstract           There is a threefold increase in video traffic over internet. Due to this video compression has become important. Compression of video signals is quiet an interesting task but comes at the cost of video quality. After compression, two methods are scientifically applied to evaluate the quality of video; Subjective and objective analysis. In subjective approach the compressed video is shown to a group of viewers and their feedback is recorded Objective approach aims to set up a mathematical model which can approximate the results of subjective analysis. One such approach is based on the measurement of PSNR. When a signal is applied to the encoder for compression, too much of compression results in a signal with a smaller size but at the same time quality of the signal degrades. In this paper we will compare the quality of compressed video signals produced by H.264, Mpeg2 and Mpeg4 encoder based on the values of MSE and PSNR. Lower the value of MSE, higher will be the PSNR. Comparative plots of MSE, PSNR, SSIM and images for subjective analysis have been added at the end of this paper. 
Comparison of microarray breast cancer classification using support vector machine and logistic regression with LASSO and boruta feature selection Nursabillilah Mohd Ali; Nor Azlina Ab Aziz; Rosli Besar
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 2: November 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i2.pp712-719

Abstract

Breast cancer is the most frequent cancer diagnosis amongst women worldwide. Despite the advancement of medical diagnostic and prognostic tools for early detection and treatment of breast cancer patients, research on development of better and more reliable tools is still actively conducted globally. The breast cancer classification is significantly important in ensuring reliable diagnostic system. Preliminary research on the usage of machine learning classifier and feature selection method for breast cancer classification is conducted here. Two feature selection methods namely Boruta and LASSO and SVM and LR classifier are studied. A breast cancer dataset from GEO web is adopted in this study. The findings show that LASSO with LR gives the best accuracy using this dataset.
Performance analysis of supercapacitors for transportation industry Vinoth Jonathan Nagarajah; Hui Jing Lee; King Guan Tan; Nathawat Khunprasit
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 3: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i3.pp1031-1038

Abstract

Monitoring device is essential to ensure a reliable and a healthy lifespan of the energy storage system. Hence, a monitoring device is needed to monitor the state of health and state of charge of a Supercapacitor. This project aims to demonstrate a method to monitor Supercapacitors using a microcontroller in both hardware and software approaches. The data was successfully collected by an online platform called ThingSpeak.
The Application of Modified Least Trimmed Squares with Genetic Algorithms Method in Face Recognition Nur Azimah Abdul Rahim; Nor Azura Md. Ghani; Norazan Mohamed; Hishamuddin Hashim; Ismail Musirin
Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 1: October 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v8.i1.pp154-158

Abstract

Severely occluded face images are the main problem in low performance of face recognition algorithms. In this paper, we apply a new algorithm, a modified version of the least trimmed squares (LTS) with a genetic algorithms introduce by [1]. We focused on the application of modified LTS with genetic algorithm method for face image recognition. This algorithm uses genetic algorithms to construct a basic subset rather than selecting the basic subset randomly. The modification in this method lessens the number of trials to obtain the minimum of the LTS objective function. This method was then applied to two benchmark datasets with clean and occluded query images. The performance of this method was measured by recognition rates. The AT&T dataset and Yale Dataset with different image pixel sizes were used to assess the method in performing face recognition. The query images were contaminated with salt and pepper noise. The modified LTS with GAs method is applied in face recognition framework by using the contaminated images as query image in the context of linear regression. By the end of this study, we can determine this either this method can perform well in dealing with occluded images or vice versa.
SWARM BASED CROSS LAYER OPTIMIZATION PROTOCOL FOR WMSN Adhyapak, Deepali Parag; Bhavani, Sridharan; Laturkar, Aparna Pradeep
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 3: June 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i3.pp1296-1302

Abstract

Wireless Multimedia Sensor Network (WMSN) is comprised of tiny, low cost multimedia devices such as video cameras and microphones. These networks can transfer scalar as well as multimedia data into real time as well as non-real time applications. However addition of such devices exposes additional challenges on both QoS assurance and energy efficiency for efficient use of resources.  This paper presents cross layer based AntSenseNet protocol to meet various QoS requirements such as throughput, jitter, lifetime and packet delivery ratio in order to improve network lifetime. Cross layer routing protocol utilizes scheduling algorithm and AntSenseNet protocol builds hierarchical structure and able to use multipath routing protocol.  Simulation results shows Cross layer based AntSenseNet protocol outperforms Ant Sense routing protocol and cross layer routing protocol in terms of throughput and packet delivery ratio.
A New Approach to Linear Estimation Problem in Multi-user Massive MIMO Systems Muhammad Ali Raza Anjum
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

A novel approach for solving linear estimation problem in multi-user massive MIMO systems is proposed. In this approach, the difficulty of matrix inversion is attributed to the incomplete definition of the dot product. The general definition of dot product implies that the columns of channel matrix are always orthogonal whereas, in practice, they may be not. If the latter information can be incorporated into dot product, then the unknowns can be directly computed from projections without inverting the channel matrix. By doing so, the proposed method is able to achieve an exact solution with a 25% reduction in computational complexity as compared to the QR method. Proposed method is stable, offers an extra flexibility of computing any single unknown, and can be implemented in just twelve lines of code. DOI:  http://dx.doi.org/10.11591/telkomnika.v13i2.7003 
Recognition of handwritten Arabic (Indian) numerals using skeleton matching Bassam Alqaralleh; Malek Zakarya Alksasbeh; Tamer Abukhalil; Harbi Almahafzah; Tawfiq Al Rawashdeh
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1461-1468

Abstract

This paper brings into discussion the problem of recognizing Arabic numbers using a monocular camera as the only sensor. When a digital image is presented in this application, optical character recognition (OCR) can be exploited to comprehend numerical data. However, there has been a limited success when applied to the handwritten Arabic (Indian) numbers. This paper aims to overcome this limitation and introduces optical character recognition system based on skeleton matching. The proposed approach is used for handwritten Arabic numbers only. The experimental results indicate the effectiveness of the proposed optical character recognition system even for numbers written in worst case. The right system achieves a recognition rate of 99.3 %.
QoS Performance of Integrated Hybrid Optical Network in Mobile Fronthual Networks Dawit Hadush Hailu
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp189-204

Abstract

Cloud Radio Access Network (C-RAN) has emerged as a promising solution to meet the ever-growing capacity demand and reduce the cost of mobile network components. In such network, the mobile operator’s Remote Radio Head (RRH) and Base Band Unit (BBU) are often separated and the connection between them has very tight timing and latency requirements. To employ packet-based network for C-RAN fronthaul, the carried fronthaul traffic are needed to achieve the requirements of fronthaul streams. For this reason, the aim of this paper is focused on investigating and evaluating the feasibility of Integrated Hybrid Optical Network (IHON) networks for mobile fronthaul. TransPacket AS (www.transpacket.com) develops a fusion switching that efficiently serves both Guaranteed Service Transport (GST) traffic with absolute priority and packet switched Statistical Multiplexing (SM) best effort traffic. We verified how the leftover capacity of fusion node can be used to carry the low priority packets and how the GST traffic can have deterministic characteristics on a single wavelength by delaying it with Fixed Delay Line (FDL). For example, for L1GE SM =0.3 the added SM traffic increases the 10GE wavelength utilization up to 89% without any losses and with SM PLR=1E-03 up to 92% utilization. The simulated results and numerical analysis confirm that the PDV and PLR of GST traffic in Ethernet network meet the requirements of mobile fronthaul using CPRI. For Ethernet network, the number of nodes in the network limits the maximum separation distance between BBU and RRH (link length); for increasing the number of nodes, the link length decreases. Consequently, Radio over Ethernet (RoE) traffic should receive the priority and Quality of Service (QoS) HP can provide. On the other hand, Low Priority (LP) classes are not sensitive to QoS metrics and should be used for transporting time insensitive applications and services.

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