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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 70 Documents
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Search results for , issue "Vol 21, No 1: January 2021" : 70 Documents clear
Fast and accurate primary user detection with machine learning techniques for cognitive radio networks G. A. Pethunachiyar; B. Sankaragomathi
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp472-478

Abstract

Spectrum decision is an important and crucial task for the secondary user to avail the unlicensed spectrum for transmission. Managing the spectrum is an efficient one for spectrum sensing. Determining the primary user presence in the spectrum is an essential work for using the licensed spectrum of primary user. The information which lacks in managing the spectrum are the information about the primary user presence, accuracy in determining the existence of user in the spectrum, the cost for computation and difficult in finding the user in low signal-to noise ratio (SNR) values. The proposed system overcomes the above limitations. In the proposed system, the various techniques of machine learning like decision tree, support vector machines, naive bayes, ensemble based trees, nearest neighbour’s and logistic regression are used for testing the algorithm. As a first step, the spectrum sensing is done in two stages with Orthogonal Frequency Division Multiplexing and Energy Detection algorithm at the various values of SNR. The results generated from the above algorithm is used for database generation. Next, the different machine learning techniques are trained and compared for the results produced by different algorithms with the characteristics like speed, time taken for training and accuracy in prediction. The accuracy and finding the presence of the user in the spectrum at low SNR values are achieved by all the algorithms. The computation cost of the algorithm differs from each other. Among the tested techniques, k-nearest neighbour (KNN) algorithm produces the better performance in a minimized time.
Supervision and control by SCADA of an automated fire system Omar Chamorro-Atalaya; Dora Arce-Santillan; Teodoro Diaz-Leyva; Martin Diaz-Choque
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp92-100

Abstract

The purpose of this article is to describe the development of a prototype of a monitoring and control system for a fire-fighting system, implemented through SCADA (supervisory control and data acquisition) for which the OPC (OLE for process control) is known. Known KepServerEX6 (single data source connectivity platform), with which the integration of the PLC (programmable logic controller), the human-machine interface (HMI) and the computer will be controlled, with the application of monitoring the operating parameters of a fire fighting system. These parameters are the pressure and flow of the electric pump, the values of the parameters are regularly controlled automatically by means of a frequency variator, according to the sprinkler actuation, the variator varies its operating frequency until achieving the optimal pressure and flow values. The level of correlation between the indicators to be monitored by the SCADA system is highly significant, equal to 0.977, 0.983 and 0.997 respectively. In addition, the dispersion model of the indicators monitored by the SCADA system will be determined, is the quadratic, with a determination factor of 0.999.
Reversible image authentication scheme based on prediction error expansion Thai-Son Nguyen; Phuoc-Hung Vo
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp253-262

Abstract

Reversible image authentication scheme is a technique that detects tampered areas in images and allows them to be reconstructed to their original version without any distortion. In this article, a new, reversible, image authentication scheme based on prediction error expansion is proposed for digital images. The proposed scheme classifies the host image into smooth blocks and complex blocks. Then, an authentication code that is created randomly with a seed is embedded adaptively into each image block. Experimental results showed that our proposed scheme achieves the high accuracy of tamper detection and preserved high image quality. Moreover, the proposed scheme achieved the reversibility, which is needed for some special applications, such as fine artwork, military images, and medical images. 
Arabic handwritten digits recognition based on convolutional neural networks with resnet-34 model Rasool Hasan Finjan; Ali Salim Rasheed; Ahmed Abdulsahib Hashim; Mustafa Murtdha
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp174-178

Abstract

Handwritten digits recognition has attracted the attention of researchers in pattern recognition fields, due to its importance in many applications in public real life, such as read bank checks and formal documents which is a continuous challenge in the last years. For this motivation, the researchers created several algorithms in recognition of different human languages, but the problem of the Arabic language is still widespread. Concerning its importance in many Arab and Islamic countries, because the people of these countries speak this language, However, there is still a little work to recognize patterns of letters and digits. In this paper, a new method is proposed that used pre-trained convolutional neural networks with resnet-34 model what is known as transfer learning for recognizing digits in the arabic language that provides us a high accuracy when this type of network is applied. This work uses a famous arabic handwritten digits dataset that called MADBase that contains 60000 training and 1000 testing samples that in later steps was converted to grayscale samples for convenient handling during the training process. This proposed method recorded the highest accuracy compared to previous methods, which is 99.6%.
An image enhancement method based on gabor filtering in wavelet domain and adaptive histogram equalization Jeevan K M; Anne Gowda A B; Padmaja Vijay Kumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp146-153

Abstract

The images are not always good enough to convey the proper information. The image may be very bright or very dark sometime or it may be low contrast or high contrast. Because of these reasons image enhancement plays important role in digital image processing. In this paper we proposed an image enhancement technique in which Gabor and median filtering is performed in wavelet domain and Adaptive Histogram Equalization is performed in spatial domain. Brightness and contrast are the two parameters used for analyzing the performance of the proposed method
Implementation of a bluetooth attack on controller area network (CAN) Zniti Asmae; El Ouazzani Nabih
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp321-327

Abstract

In this paper a general overview of the vulnerability of the CAN bus is presented and a practical short-range attack is proposed. There are more and more potential attacks on the CAN bus, which may cause leakage of information and thereby there may be danger for safe driving. The attack combines several techniques, such as how to update a node firmware using a Bluetooth module and inject a priority fake frame, in order to block the legitimate messages. 
Intelligent multimodal identification system based on local feature fusion between iris and finger vein Enas Abbas Abed; Rana Jassim Mohammed; Dhafer Taha Shihab
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp224-232

Abstract

Biometric identification systems, which use physical features to check a person's identity, ensure much higher security than password and number systems. Biometric features such as the face or a fingerprint can be stored on a microchip in a credit card, for example. A single modal biometric identification system fails to extract enough features for identification. Another disadvantage of using only one feature is not always readable. In this article, a smart multimodal biometric verification model for identifying and verifying a person's identity is recommended based on artificial intelligence methods. The proposed model is identified the iris and finger vein unique patterns each individual to overcome many challenges such as identity fraud, poor image quality, noise, and instability of the surrounding environment. Several experiments were performed on a dataset containing 50 people by using many matching methods. The results of the proposed model were provided a higher accuracy of 98%, with FAR and FRR of 0.0015% and 0.025%, respectively.
An accurate signature verification system based on proposed HSC approach and ANN architecture Mustafa S. Kadhm; Mamoun Jassim Mohammed; Hayder Ayad
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp215-223

Abstract

With the rapid development of technology in all life fields, and due to the huge daily needs for banking systems process, documents processing and other similar systems. The authentication became more required key for these systems. One of the successful system to verify the any person is the signature verification system. However, a reliable and accurate system is still needed. For this reason, the security challenge is take place via authentic signatures. However, a reliable and accurate system is still needed. For this reason, the security challenge is take place via authentic signatures. Therefore, this paper present a reliable signature verification system using proposed histogram of sparse codes (HSC) feature extraction approach and artificial neural networks (ANN) architecture for classification. The system achieved fast computing 0.09 ms and accurate verification results that is 99.7% using three different signature images datasets CEDAR, UTSig, and ICDAR.
Automation of the burner of a pirotubular boiler to improve the efficiency in the generation of steam Omar Chamorro-Atalaya; Diego Goicochea-Vilela; Dora Arce Santillan; Martin Diaz-Choque; Teodoro Diaz-Leyva
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp101-109

Abstract

The purpose of this article is to describe the automation developed by means of a programmable logic controller for the burner of a fire tube boiler, in order to improve the efficiency in the process of generating steam quantified through the percentage of oxygen generated. The implementation was developed under a control strategy based on the use of servomotors that allow to gradually open or close the solenoid valves that dose the amount of air and fuel; Considering that there are multiple elements, I limited the analysis to one of its main components, called the burner. After developing this automation, it was possible to demonstrate the decrease in the variability of the oxygen percentage in relation to the optimal or desired value in the boiler. The experimentally obtained data of the oxygen percentage, were subjected to a statistical analysis of dispersion, in which the value of the Pearson's correlation coefficient was determined, whose value was equal to 0.298; This result allowed to conclude that the degree of variability of the indicator in analysis with respect to time is very low, which means that the variable maintains a constant value, equal to the desired value, after automating the fire tube boiler.
Energy efficient hierarchical based fish eye state routing protocol for flying Ad-hoc networks Muhammad Abul Hassan; Syed Irfan Ullah; Abdus Salam; Arbab Wajid Ullah; Muhammad Imad; Farhat Ullah
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp465-471

Abstract

Flying Ad-hoc networks are emergent area in Ad-hoc networks evolved from MANETs and VANETs. Small unmanned aerial vehicles (UAVs) are used in FANETs applications and these small UAVs have limited resources while efficiently utilization of these resources is most critical task in real time monitoring of FANETs application. Network consumes its resources in path selection process and data routing from source to destination. Selecting of efficient routing protocol to utilize all available resources played vital role in extending network life time. In this article fisheye state routing (FSR) protocol is implemented in FANET and compare networks performance in term of channel utilization, link utilization vs throughput and packet delivery ratio (PDR) with distance sequence distance vector (DSDV), optimized link state routing (OLSR), adhoc on demand distance vector (AODV), dynamic source routing (DSR) and temperary ordered routing protocol (TORA). Experimental analysis slows that FSR is good in term of PDR (16438 packets delivered), channel utilization (89%) and link vs throughput from the rest of routing protocols after addressing of these problems UAVs resources are efficiently utilized (energy).

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