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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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Third harmonic current minimization using third harmonic blocking transformer Vishnuprasada Vittal Bhat; Pinto Pius
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 2: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i2.pp697-709

Abstract

Zero sequence blocking transformers (ZSBTs) are used to suppress third harmonic currents in 3-phase systems. Three-phase systems where single-phase loading is present, there is every chance that the load is not balanced. If there is zero-sequence current due to unequal load current, then the ZSBT will impose high impedance and the supply voltage at the load end will be varied which is not desired. This paper presents Third harmonic blocking transformer (THBT) which suppresses only higher harmonic zero sequences. The constructional features using all windings in single-core and construction using three single-phase transformers explained. The paper discusses the constructional features, full details of circuit usage, design considerations, and simulation results for different supply and load conditions. A comparison of THBT with ZSBT is made with simulation results by considering four different cases.
LTE network performance evaluation based on effects of various parameters on the cell range and MAPL Asaad. S. Daghal; Haider Mohammed Turki Al-Hilfi
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i3.pp1770-1776

Abstract

These days long term evaluation (LTE) is considered the common mobile technology around the world and there is a need to maximize the network performance to satisfy the increased demand in terms of the cell capacity and coverage. These are many parameters in the network configuration and in the surrounded environment, which have great effects on the network performance. Examples of parameters are the system overhead rations, the required capacity of the network, neighbor cell load, and link budget parameters. The determination of the optimum configuration parameters, which achieve the best network performance, is a main step in the planning process in addition to it is continuous step in network optimization phase. In this study, the effects of some parameters will be investigating to get the best parameters that achieve the best network performance in terms of capacity of the cells and coverage area. The study will start by discussing introduction about LTE network components and protocols, and then the main parameters of the protocols will be revising. The study will display the results of changing many parameters related to LTE protocols and surrounding environment parameters on the LTE network performance.
Efficient resampling features and convolution neural network model for image forgery detection Manjunatha S; Malini M. Patil
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 1: January 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i1.pp183-190

Abstract

The extended utilization of picture-enhancing or manipulating tools has led to ease of manipulating multimedia data which includes digital images. These manipulations will disturb the truthfulness and lawfulness of images, resulting in misapprehension, and might disturb social security. The image forensic approach has been employed for detecting whether or not an image has been manipulated with the usage of positive attacks which includes splicing, and copy-move. This paper provides a competent tampering detection technique using resampling features and convolution neural network (CNN). In this model range spatial filtering (RSF)-CNN, throughout preprocessing the image is divided into consistent patches. Then, within every patch, the resampling features are extracted by utilizing affine transformation and the Laplacian operator. Then, the extracted features are accumulated for creating descriptors by using CNN. A wide-ranging analysis is performed for assessing tampering detection and tampered region segmentation accuracies of proposed RSF-CNN based tampering detection procedures considering various falsifications and post-processing attacks which include joint photographic expert group (JPEG) compression, scaling, rotations, noise additions, and more than one manipulation. From the achieved results, it can be visible the RSF-CNN primarily based tampering detection with adequately higher accurateness than existing tampering detection methodologies.
Public key cryptosystem based on multiple chaotic maps for image encryption Yousif S. Najaf; Maher K. Mahmood Al-Azawi
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i3.pp1457-1466

Abstract

Image is one of the most important forms of information. In this paper, two public key encryption systems are proposed to protect images from various attacks. Both systems depend on generating a chaotic matrix (I) using multiple chaotic maps. The parameters for these maps are taken from the shared secret keys generated from Chebyshev map using public keys for Alice and secret key for Bob or vice versa. The second system has the feature of deceiving the third party for searching for fake keys. Analysis and tests showed that the two proposed systems resist various attacks and have very large key space. The results are compared with other chaos based systems to show the superiority of these two proposed systems.
A composite controller based on nonlinear H_∞ and nonlinear disturbance observer for attitude stabilization of a flying robot Vahid Razmavar; Heidar Ali Talebi; Farzaneh Abdollahi
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp270-276

Abstract

In this article a novel composite control technique is introduced. We added a nonlinear disturbance observer to a nonlinear H_∞ control to form this composite controller. The quadrotor kinematics and dynamics is formulated using euler angles and parameters. After that, this nonlinear robust controller is developed for this flying robot attitude control for the outdoor conditions. Because under these conditions the flying robot, experiences both external disturbance and parametric uncertainty. Stability analysis is also presented to show the global asymptotical stability using a Lyapunov function. The simulation results showed that the suggested composite controller had a better performance in comparison with a nonlinear H_∞ control scheme.
A performance enhancement of physical layer at Wi-MAX system with RLDPC code Sandeep Bawage; Manjula S; A. M. Bhavikatti
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i3.pp1557-1566

Abstract

In present wireless communication network, the error correction codes plays the major role for efficient data transmission in noisy environments. To get minimum BER and PAPR has been the main aim towards the field in forward error control coding. Majority of the researchers has considered turbo codes at specific SNR over AWGN channel but have complexity issues with the iterative output decoder and causes degradation in the Wi-Max network system. In this paper, the author presents and evaluates WiMAX physical layer performance with using MIMO technologies, where a Robust-LDPC technique of coding and decoding in OFDM based WiMAX system is consider. The decoding method of RLDPC has processed by Belief Propagation at the logarithmic domain in an iterative manner, the proposed methodology shows good decoding outcome for RLDPC codes at Rician and Rayleigh channel. Moreover, the applicability of our proposed model channel codes is defined under IEEE Wi-MAX standard and the results analysis is done under different code-rate and modulation schemes.
Transfer learning with Resnet-50 for detecting COVID-19 in chest X-ray images Hamlili, Fatima-Zohra; Beladgham, Mohammed; Khelifi, Mustapha; Bouida, Ahmed
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 3: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i3.pp1458-1468

Abstract

The novel coronavirus, also known as COVID-19, initially appeared in Wuhan, China, in December 2019 and has since spread around the world. The purpose of this paper is to use deep convolutional neural networks (DCCN) to improve the detection of COVID-19 from X-ray images. In this study, we create a DCNN based on a residual network (Resnet-50) that can identify COVID-19 from two other classes (pneumonia and normal) in chest X-ray images. DCNN was evaluated using two classification methods: binary (BC-1: COVID-19 vs. normal, BC-2: COVID-19 vs. pneumonia) and multi-class (pneumonia vs. normal vs. COVID-19). In all experiments, four fold cross-validation was used to train and test the model. This architecture's average accuracy is 99.9% for BC-1, 99.8% for BC-2, and 97.3% for multi-class cases. The experimental findings demonstrated that the suggested system detects COVID-19 with an average precision and sensitivity of 95% and 95.1% for multi-class classification, respectively. According to our findings, the proposed DCNN may help health professionals in confirming their first evaluation of COVID-19 patients.
Temporal analysis of air pollutants in the most affected monsoon region Omar Kairan; Nur Nasehah Zainudin; Nurul Hasya Mohd Hanafiah; Nur Emylia Arissa Mohd Jafri; Fukayhah Fatiha @Suhami; Mohd Firdaus Mustapha
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp229-236

Abstract

Air pollution has become an issue at all rates in the world. In Malaysia, there is a system is known as air quality index (API) used to indicate the overall air quality in the country where the air pollutants include or the new ambient air quality standard are sulphur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3) and particulate matter with size less than 10 (PM10). The concentration levels of the air pollutants were said to be affected by the monsoon changes. Therefore, this study is conducted to examine the existence of temporal variations of each air pollutant then identify the differences of each air pollutants concentration in temporal variations. This study uses secondary data where data that has been retrieved from the Department of Environment (DOE) where it is data of air pollution specifically for Kota Bharu, kelantan records. Hierarchical agglomerative cluster analysis was conducted to group monthly air quality. As a conclusion, the study can conclude that the five air pollutants grouped into several different monthly clusters mostly representing the two main monsoon seasons. Mostly air pollutant varied accordingly towards the monsoon season. During the southwestern monsoon, air pollutant concentration tends to higher compare to the northeastern monsoon with mostly due to meteorological factors.
Design secure multi-level communication system based on duffing chaotic map and steganography Aliaa Sadoon Abd; Ehab Abdul Razzaq Hussein
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 1: January 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i1.pp238-246

Abstract

Cryptography and steganography are among the most important sciences that have been properly used to keep confidential data from potential spies and hackers. They can be used separately or together. Encryption involves the basic principle of instantaneous conversion of valuable information into a specific form that unauthorized persons will not understand to decrypt it. While steganography is the science of embedding confidential data inside a cover, in a way that cannot be recognized or seen by the human eye. This paper presents a high-resolution chaotic approach applied to images that hide information. A more secure and reliable system is designed to properly include confidential data transmitted through transmission channels. This is done by working the use of encryption and steganography together. This work proposed a new method that achieves a very high level of hidden information based on non-uniform systems by generating a random index vector (RIV) for hidden data within least significant bit (LSB) image pixels. This method prevents the reduction of image quality. The simulation results also show that the peak signal to noise ratio (PSNR) is up to 74.87 dB and the mean square error (MSE) values is up to 0.0828, which sufficiently indicates the effectiveness of the proposed algorithm.
Optimal integration of wind energy with a shunt-FACTS controller for reductions in electrical power loss I Made Wartana; Ni Putu Agustini; Sasidharan Sreedharan
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp41-53

Abstract

The integration of distributed generators (DGs) with flexible alternating current transmission systems (FACTS) can improve the performance of the grid system. In this study, we determine the location and optimal size of one type of DG, based on wind energy, with a shunt-FACTS control device called a static var compensator (SVC). The voltage profile is increase and the power loss reduced due to an improvement in performance from the maximizing load bus system scenario. Newton-Raphson power flow with a wind turbine generator (WTG) and SVC are formulated as a multi-objective problem called MLB system and minimizing system power loss (Ploss) by satisfying various system constraints, namely the loading limits, generation limits, voltage limits, and the small-signal stability. A variant of the genetic algorithm, called the non-dominated sorting genetic algorithm II (NSGA-II), is used to solve these conflicting multi-objective optimization problems. Modifications to the IEEE 14-bus standard and practical test system integrated to the WTG and SVC in the PSAT software are used as a test system. The simulation results indicate that the optimal allocation of the WTG and SVC, determined using the proposed technique, results in improved system performance, since all the specified constraints are met.

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