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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 6,301 Documents
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A simple design and fabrication of polarization reconfigurable antenna for industrial scientific and medical-band applications Md. Azad Hossain; Muhammad Asad Rahman; Abu Hena Murshed; Eisuke Nishiyama; Ichihiko Toyoda
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.pp1580-1587

Abstract

This paper proposes a simple microstrip patch antenna (MPA) that can reconfigure its polarization states from linear to circular polarization in real-time by means of a PIN diode. An antenna is fed by a 50 Ω coaxial cable through the substrate of Teflon with relative permittivity of 2.15. The proposed antenna possesses a simple patch with a one-sided corner truncated to achieve polarization reconfigurability. A PIN diode is loaded to connect the main patch with a truncated corner and further maintain dual polarization states such as linear polarization (LP) and circular polarization (CP). Advanced design system (ADS) was used as a simulator to simulate the antenna, and a good understanding was obtained between simulated and measured results. Measured results showed a good agreement with simulated results at all working frequencies of interest. It shows minimum reflection coefficient gain with -10 dB scattering bandwidth 100 MHz for LP states and 170 MHz for CP states. It also shows an axial ratio of 1.56 dB for CP, and the cross-polarization level is also in a satisfying range.
Determination of location and capacity of distributed generations with reconfiguration in distribution systems for power quality improvement Ontoseno Penangsang; Muhammad Daffa Cahyonoputra; Dimas Fajar Uman Putra; Muhira Dzar Faraby; Sofyan Sofyan; Akhyar Muchtar
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp28-38

Abstract

The use of non-linear loads and the integration of renewable energy in electricity network can cause power quality problems, especially harmonic distortion. It is a challenge in the operation and design of the radial distribution system. This can happen because harmonics that exceed the limit can cause interference to equipment and systems. This study will discuss the determination of the optimal location and capacity of distributed generation (DG) and network reconfiguration in the radial distribution system to improve the quality of electric power, especially the suppression of harmonic distribution. This study combines the optimal location and capacity of DG and network reconfiguration using the particle swarm optimization method. In addition, this research method is implemented in the distribution system of Bandar Lampung City by considering the effect of using nonlinear loads to improve power quality, especially harmonic distortion. The inverter-based DG type used considers the value of harmonic source when placed. The combination of the proposed methods provides an optimal solution. Increased efficiency in reducing power losses up to 81.17% and %total harmonic distortion voltage (THDv) is below the allowable limit.
Network selection based on chi-square distance and reputation for internet of things Said Radouche; Cherkaoui Leghris
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp823-832

Abstract

The internet of things (IoT) has become one of the most important technologies of the 21st century. The IoT environment is composed of heterogeneous IoT communication networks. These technologies are complementary and need to be integrated to meet the requirements of different types of IoT applications that require the mobility of the IoT device under different IoT communication networks. In this paper, the vertical handover decision method is considered to select the appropriate network among different IoT technologies. So, IoT devices, equipped with several radio technologies, can select the most suitable network based on several criteria like quality of service (QoS), cost, power, and security. In this work, a multi-attribute decision-making algorithm (MADM) based on techniques for order preference by similarity to an ideal solution (TOPSIS) that uses chi-square distance instead of Euclidean distance is proposed. The network reputation is added to reduce the average number of handoffs. The proposed algorithm was implemented to select the best technology depending on the requirements of the different IoT traffic classes. The obtained results showed that our proposition outperforms the traditional MADM algorithms.
Enhancing the stability of the deep neural network using a non-constant learning rate for data stream Hussein Abdul Ameer Abbas Al-Khamees; Nabeel Al-A'araji; Eman Salih Al-Shamery
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.pp2123-2130

Abstract

The data stream is considered the backbone of many real-world applications. These applications are most effective when using modern techniques of machine learning like deep neural networks (DNNs). DNNs are very sensitive to set parameters, the most prominent one is the learning rate. Choosing an appropriate learning rate value is critical because it is able to control the overall network performance. This paper presents a new developing DNN model using a multi-layer perceptron (MLP) structure that includes network training based on the optimal learning rate. Thereupon, this model consists of three hidden layers and does not adopt the stability of the learning rate but has a non-constant value (varying over time) to obtain the optimal learning rate which is able to reduce the error in each iteration and increase the model accuracy. This is done by deriving a new parameter that is added to and subtracted from the learning rate. The proposed model is evaluated by three streaming datasets: electricity, network security layer-knowledge discovery in database (NSL-KDD), and human gait database (HuGaDB) datasets. The results proved that the proposed model achieves better results than the constant model and outperforms previous models in terms of accuracy, where it achieved 88.16%, 98.67%, and 97.63% respectively.
A low complexity distributed differential scheme based on orthogonal space time block coding for decode-and-forward wireless relay networks Samer Alabed; Nour Mostafa; Wael Hosny Fouad Aly; Mohammad Al-Rabayah
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp1180-1188

Abstract

This work proposes a new differential cooperative diversity scheme with high data rate and low decoding complexity using the decode-and-forward protocol. The proposed model does not require either differential encoding or channel state information at the source node, relay nodes, or destination node where the data sequence is directly transmitted and the differential detection method is applied at the relay nodes and the destination node. The proposed technique enjoys a low encoding and decoding complexity at the source node, the relay nodes, and the destination node. Furthermore, the performance of the proposed strategy is analyzed by computer simulations in quasi-static Rayleigh fading channel and using the decode-and-forward protocol. The simulation results show that the proposed differential technique outperforms the corresponding reference strategies.
A secure sharing control framework supporting elastic mobile cloud computing Aws Hamed Hamad; Adnan Yousif Dawod; Mohammed Fakhrulddin Abdulqader; Israa Al_Barazanchi; Hassan Muwafaq Gheni
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.pp2270-2277

Abstract

In elastic mobile cloud computing (EMCC), mobile devices migrate some computing tasks to the cloud for execution according to current needs and seamlessly and transparently use cloud resources to enhance their functions. First, based on the summary of existing EMCC schemes, a generic EMCC framework is abstracted; it is pointed out that the migration of sensitive modules in the EMCC program can bring security risks such as privacy leakage and information flow hijacking to EMCC; then, a generic framework of elastic mobile cloud computing that incorporates risk management is designed, which regards security risks as a cost of EMCC and ensures that the use of EMCC is. Finally, it is pointed out that the difficulty of risk management lies in risk quantification and sensitive module labeling. In this regard, risk quantification algorithms are designed, an automatic annotation tool for sensitive modules of Android programs is implemented, and the accuracy of the automatic annotation is demonstrated through experiments.
Smart ports: towards a high performance, increased productivity, and a better environment Hayder Ali Al-Fatlawi; Hassan Jassim Motlak
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.pp1472-1482

Abstract

Ports are currently competing fiercely for capital and global investments in order to improve revenues, mostly by improving performance and lowering labor costs. Smart ports are a fantastic approach to realize these elements since they integrate information and communication technologies within smart applications, ultimately contributing to port management improvement. This leads to greater performance and lower operational expenses. As a result, several ports in Europe, Asia, Australia, and North America have gone smart. However, there are a lot of critical factors to consider when automating port operations, such as greenhouse gas emissions, which have reached alarming proportions. The purpose of this study is to define the most essential tasks conducted by smart ports, such as the smart ship industry, smart gantry and quayside container cranes, transport automation, smart containers, and energy efficiency. Furthermore, it gives a model of the smart port concept and highlights the critical current technologies on which the ports are based. Each technology’s most significant contributions to its development are noted. This technology is compared to more traditional technologies. It is hoped that this effort would pique the curiosity of fresh researchers in this sector.
A novel application of artificial neural network for classifying agarwood essential oil quality Noratikah Zawani Mahabob; Zakiah Mohd Yusoff; Aqib Fawwaz Mohd Amidon; Nurlaila Ismail; Mohd Nasir Taib
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp6645-6652

Abstract

This work studies the agarwood oil classification into high and low quality by using two different techniques. Initially, the Forest Research Institute Malaysia (FRIM) and Universiti Malaysia Pahang (UMP) are where the sample preparation and compound extraction of agarwood oil is collected. The data collections were done from the previous researcher consists of 96 samples from seven significant agarwood oil compounds. The artificial neural network (ANN) and the proposed stepwise regression technique were used in this study. The stepwise regression was done the feature selection and successfully reduced agarwood oil compounds from seven to four. Then, the ANN technique was used to classify agarwood oil into high and low using input from seven and four compounds separately. The performance of ANN with different inputs is compared (ANN with seven inputs compared with ANN with four inputs). All the experimental work was performed using the MATLAB R2017b using the “patternet” implemented Levenberg Marquardt algorithm and ten hidden neurons. It was found that the ANN technique using seven compounds obtained the best performance according to high accuracy and lower mean square error (MSE) value. Finally, 1 hidden neuron in ANN with seven inputs selected as the best neuron for grading the agarwood oil compounds.
A novel frequency reconfigurable antenna for smart grid applications in TV white space band Sanjeev Kumar; Neela Rayavarapu; Praveen Vummadisetty Naidu
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp611-618

Abstract

This paper presents the design and analysis of a frequency reconfigurable, aperture coupled rectangular patch antenna for use in smart grid applications in TV white space bands. The proposed antenna model has been realized on multi-substrate layers of Polylactic acid (PLA) material (εr=2.65, tanδ=0.003) with a ground plane sandwiched in between them. An aperture has been made in the ground plane for coupling energy to the patch. The overall system dimensions are 270×270 mm. The feature of frequency reconfigurability has been achieved by incorporating a switch and varying the reactance of the feed line on the bottom substrate. A rectangular slot on the long feed line improves impedance matching. The ON and OFF states of the switch provide two operating frequency bands namely 630.13 to 636.7 MHz and 619.16 to 625.3 MHz respectively. The proposed aperture coupled reconfigurable system operates with a maximum gain of 6.4 dB and average efficiency of 78.5% in both bands. The measured results are satisfactory and the proposed antenna will be suitable for operation in the smart grid environment.
AgroSupportAnalytics: big data recommender system for agricultural farmer complaints in Egypt Esraa Rslan; Mohamed H. Khafagy; Mostafa Ali; Kamran Munir; Rasha M. Badry
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp746-755

Abstract

The world’s agricultural needs are growing with the pace of increase in its population. Agricultural farmers play a vital role in our society by helping us in fulfilling our basic food needs. So, we need to support farmers to keep up their great work, even in difficult times such as the coronavirus disease (COVID-19) outbreak, which causes hard regulations like lockdowns, curfews, and social distancing procedures. In this article, we propose the development of a recommender system that assists in giving advice, support, and solutions for the farmers’ agricultural related complaints (or queries). The proposed system is based on the latent semantic analysis (LSA) approach to find the key semantic features of words used in agricultural complaints and their solutions. Further, it proposes to use the support vector machine (SVM) algorithm with Hadoop to classify the large agriculture dataset over Map/Reduce framework. The results show that a semantic-based classification system and filtering methods can improve the recommender system. Our proposed system outperformed the existing interest recommendation models with an accuracy of 87%.

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