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International Journal of Electrical and Computer Engineering
Published by Institute of Advanced Engineering and Science
ISSN : 20888708     EISSN : 27222578     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 111 Documents
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Search results for , issue "Vol 13, No 2: April 2023" : 111 Documents clear
Multi-modal palm-print and hand-vein biometric recognition at sensor level fusion Harbi Al-Mahafzah; Tamer AbuKhalil; Malek Alksasbeh; Bassam Alqaralleh
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1954-1963

Abstract

When it is important to authenticate a person based on his or her biometric qualities, most systems use a single modality (e.g. fingerprint or palm print) for further analysis at higher levels. Rather than using higher levels, this research recommends using two biometric features at the sensor level. The Log-Gabor filter is used to extract features and, as a result, recognize the pattern, because the data acquired from images is sampled at various spacing. Using the two fused modalities, the suggested system attained greater accuracy. Principal component analysis was performed to reduce the dimensionality of the data. To get the optimum performance between the two classifiers, fusion was performed at the sensor level utilizing different classifiers, including k-nearest neighbors and support vector machines. The technology collects palm prints and veins from sensors and combines them into consolidated images that take up less disk space. The amount of memory needed to store such photos has been lowered. The amount of memory is determined by the number of modalities fused.
Flexible handover solution for vehicular ad-hoc networks based on software defined networking and fog computing Muayad Khalil Murtadha; Baydaa Mohammad Mushgil
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1570-1579

Abstract

Vehicular ad-hoc networks (VANET) suffer from dynamic network environment and topological instability that caused by high mobility feature and varying vehicles density. Emerging 5G mobile technologies offer new opportunities to design improved VANET architecture for future intelligent transportation system. However, current software defined networking (SDN) based handover schemes face poor handover performance in VANET environment with notable issues in connection establishment and ongoing communication sessions. These poor connectivity and inflexibility challenges appear at high vehicles speed and high data rate services. Therefore, this paper proposes a flexible handover solution for VANET networks by integrating SDN and fog computing (FC) technologies. The SDN provides global knowledge, programmability and intelligence functions for simplified and efficient network operation and management. FC, on the other hand, alleviates the core network pressure by providing real time computation and transmission functionalities at edge network to maintain the demands of delay sensitive applications. The proposed solution overcomes frequent handover challenges and reduces the processing overhead at core network. Moreover, the simulation evaluation shows significant handover performance improvement of the proposed solution compared to current SDN based schemes, especially in terms of handover latency and packet loss ratio under various simulation environments.
Characterization of Arabic sibilant consonants Youssef Elfahm; Nesrine Abajaddi; Badia Mounir; Laila Elmaazouzi; Ilham Mounir; Abdelmajid Farchi
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1997-2008

Abstract

The aim of this study is to develop an automatic speech recognition system in order to classify sibilant Arabic consonants into two groups: alveolar consonants and post-alveolar consonants. The proposed method is based on the use of the energy distribution, in a consonant-vowel type syllable, as an acoustic cue. The application of this method on our own corpus reveals that the amount of energy included in a vocal signal is a very important parameter in the characterization of Arabic sibilant consonants. For consonants classifications, the accuracy achieved to identify consonants as alveolar or post-alveolar is 100%. For post-alveolar consonants, the rate is 96% and for alveolar consonants, the rate is over 94%. Our classification technique outperformed existing algorithms based on support vector machines and neural networks in terms of classification rate.
Design a cryptosystem using elliptic curves cryptography and Vigenère symmetry key Mai Manh Trung; Le Phe Do; Do Trung Tuan; Nguyen Van Tanh; Ngo Quang Tri
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1734-1743

Abstract

In this paper describes the basic idea of elliptic curve cryptography (ECC) as well as Vigenère symmetry key. Elliptic curve arithmetic can be used to develop elliptic curve coding schemes, including key exchange, encryption, and digital signature. The main attraction of elliptic curve cryptography compared to Rivest, Shamir, Adleman (RSA) is that it provides equivalent security for a smaller key size, which reduces processing costs. From the theorical basic, we proposed a cryptosystem using elliptic curves and Vigenère cryptography. We proposed and implemented our encryption algorithm in an integrated development environment named visual studio 2019 to design a safe, secure, and effective cryptosystem.
Secure cluster-based routing using multi objective-trust centric artificial algae algorithm for wireless sensor network Divyashree Habbanakuppe Balachandra; Puttamadappa Chaluve Gowda; Nandini Prasad Kanakapura Shivaprasad
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1618-1628

Abstract

Nowadays, wireless sensor network (WSN) is developed as a key technology to observe and track applications over a wide range. However, energy consumption and security are considered as important issues in the WSN. In this paper, the multi objective-trust centric artificial algae algorithm (M-TCAAA) is proposed to accomplish a secure broadcasting over the WSN. The proposed M-TCAAA is used to choose the secure cluster head (SCH) as well as routing path, based on the distinct fitness measures such as trust, communication cost, residual energy, and node degree. Hence, the M-TCAAA is used to ensure a secure data transmission while decreasing the energy consumed by the nodes. The performance of the M-TCAAA is analyzed by means of energy consumption, packet delivery ratio (PDR), throughput, end to end delay (EED), normalized routing load (NRL), and network lifetime. The existing researches namely energy aware trust and opportunity-based routing with mobile nodes (ETOR-MN), grey wolf updated whale optimization (GUWO), secure cluster-based routing protocol (SCBRP), secure routing protocol based on multi-objective ant-colony-optimization (SRPMA) and multi objective trust aware hybrid optimization (MOTAHO) are considered for evaluating the M-TCAAA. The PDR of the M-TCAAA for 100 nodes is 99.87%, which is larger than the ETOR-MN, GUWO, SRPMA and MOTAHO.
Tiny datablock in saving Hadoop distributed file system wasted memory Al-Masadeh, Mohammad Bahjat; Azmi, Mohad Sanusi; Syed Ahmad, Sharifah Sakinah
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1757-1772

Abstract

Hadoop distributed file system (HDFS) is the file system whereby Hadoop is use it to store all the upcoming data inside it. Since it been declared, HDFS is consuming a huge memory amount in order to serve a normal dataset. Nonetheless, the current file saving mechanism in HDFS save only one file in one datablock. Thus, a file with just 5 Mb in size will take up the whole datablock capacity causing the rest of the memory unavailable for other upcoming files, and this is considered a huge waste of memory in serving a normal size dataset. This paper proposed a method called tiny datablock-HDFS (TD-HDFS) to increase the usability of HDFS memory and increase the file hosting capabilities by reducing the datablock size to the minimum capacity, and then merging all the related datablocks into one master datablock. This master datablock consists of tiny virtual datablocks that contain the related small files together; will exploit the full memory of the master datablock. The result of this study is a running HDFS with a minimum amount of wasted memory with the same read/write data performance. The results were examined through a comparison between the standard HDFS file hosting and the proposed solution of this study.
Comparing machine learning and deep learning classifiers for enhancing agricultural productivity: case study in Larache Province, Northern Morocco Sara Belattar; Otman Abdoun; Haimoudi El Khatir
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1689-1697

Abstract

The agriculture sector in the Tangier-Tetouan-Al-Hoceima-Region (Northern Morocco) contributes a significant percentage to the national revenue. The Larache Province is at the regional forefront in agriculture terms due to its large irrigated areas. Golden-Gogi is a biological farm located in the Larache Province, and its objective is to produce organic crops. Besides climate change, this farm suffers from biotic factors such as snails and insects. These problems cause diseases in plants, resulting in massive crop production losses. Early detection of disease and biotic factors in plants is a difficult task for farmers, but it is now possible thanks to artificial intelligence. For that reason, we aim to contribute to this Province by comparing the well-known models in machine learning (ML) and deep learning (DL) used in early plant disease detection to specify the best-classifier in terms of detecting mint plant diseases. Mint plant is a major crop on the Golden-Gogi farm, and its dataset was collected from there. As per findings, DL classifiers outperform ML classifiers in disease detection. The best-classifier is DenseNet201, with high accuracy of 94.12%. Hence, the system using DenseNet201 offers a solution for farmers of this Province in making urgent decisions to avoid mint yield losses.
Enhanced two-terminal impedance-based fault location using sequence values Muhd Hafizi Idris; Mohd Rafi Adzman; Hazlie Mokhlis; Lilik Jamilatul Awalin; Mohammad Faridun Naim Tajuddin
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1291-1305

Abstract

Fault at transmission line system may lead to major impacts such as power quality problems and cascading failure in the grid system. Thus, it is very important to locate it fast so that suitable solution can be taken to ensure power system stability can be retained. The complexity of the transmission line however makes the fault point identification a challenging task. This paper proposes an enhanced fault detection and location method using positive and negative-sequence values of current and voltage, taken at both local and remote terminals. The fault detection is based on comparison between the total fault current with currents combination during the pre-fault time. While the fault location algorithm was developed using an impedance-based method and the estimated fault location was taken at two cycles after fault detection. Various fault types, fault resistances and fault locations have been tested in order to verify the performance of the proposed method. The developed algorithms have successfully detected all faults within high accuracy. Based on the obtained results, the estimated fault locations are not affected by fault resistance and line charging current. Furthermore, the proposed method able to detect fault location without the needs to know the fault type.
Fabrication and experimental study of transformer 400 V with a simple rectifier circuit design Fitri Puspasari; Sismanto Sismanto; Ahmad Ashari
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1320-1328

Abstract

The demand for increased voltage in renewable energy sources is relatively high. This study examines the rapid development of technology considering the use of voltage-increasing transformers. Voltage regulator circuits are generally used to stabilize the output voltage of the rectifier according to the amount of input from the transformer. However, components for high-voltage stabilizer circuits are rare, which becomes an obstacle to the stabilization of the rectifier output. This study aimed to determine the performance of the designed rectifier circuit against a non-center tap step-up direct current (DC) 400 V transformer and compare the measurement results to manual calculations. The research method is a direct comparison between the input and output voltage values of the transformer after going through a rectifier circuit. This experiment was conducted using the repeatability method three to five times for each voltage variation on the transformer. The voltage variations successfully created are 0 to 50, 0 to 100, 0 to 200, and 0 to 400 V. The output test results from the DC transformer and rectifier circuit show linear results and an increase in peak-to-peak voltage data between the transformer and rectifier outputs by 3.8%.
Alzheimer’s detection through neuro imaging and subsequent fusion for clinical diagnosis Bhavana Valsala; Krishnappa Honnamachanahalli Kariputtaiah
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1491-1498

Abstract

In recent years, vast improvement has been observed in the field of medical research. Alzheimer's is the most common cause for dementia. Alzheimer's disease (AD) is a chronic disease with no cure, and it continues to pose a threat to millions of lives worldwide. The main purpose of this study is to detect the presence of AD from magnetic resonance imaging (MRI) scans through neuro imaging and to perform fusion process of both MRI and positron emission tomography (PET) scans of the same patient to obtain a fused image with more detailed information. Detection of AD is done by calculating the gray matter and white matter volumes of the brain and subsequently, a ratio of calculated volume is taken which helps the doctors in deciding whether the patient is affected with or without the disease. Image fusion is carried out after preliminary detection of AD for MRI scan along with PET scan. The main objective is to combine these two images into a single image which contains all the possible information together. The proposed approach yields better results with a peak signal to noise ratio of 60.6 dB, mean square error of 0.0176, entropy of 4.6 and structural similarity index of 0.8.

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