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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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Design and analysis of wide and multi-bands multi-input multi-output antenna for 5G communications Karrar Shakir Muttair; Ali Zuhair Ghazi Zahid; Oras Ahmed Shareef; Raed Hameed Chyad Alfilh; Ahmed Mohammed Qasim Kamil; Mahmood Farhan Mosleh
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp903-914

Abstract

A good antenna design has played an essential role in the design of wireless communication systems, international companies are looking for the best design that suits their products in terms of size, bandwidth, gain, cost, and performance. In this paper, three antenna models are designed for fifth-generation (5G) communications, the first model is a single antenna, the second model is a two-ports multi-input multi-output (MIMO) antenna, and the third model is a four-ports MIMO antenna. The geometric dimensions of a single antenna are 20×37×1.6 mm3, the two-ports antenna dimensions are 44×37×1.6 mm3, while the four-ports antenna dimensions are 74×44×1.6 mm3. The design of these antennas was based on the latest strategies in terms of their small sizes and operating from 13.5 to 20 GHz in wide and multiple bands to be compatible with all advanced communication devices. Based on the results that emerged, it was noted that the reflection coefficient (S11) < -10 dB and has better isolation between the ports is < -26 dB. While the envelope correlation coefficient (ECC) value is < 1.036×10-9, and the diversity gain (DG) value is 10 dB. All antennas proposed operate in ultra-wideband (UWB) which is very necessary for 5G communications devices.
Sentiment analysis system for COVID-19 vaccinations using data of Twitter Eman Thabet Khalid; Entesar B. Talal; Methaq K. Khamees; Ali A. Yassin
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp1156-1164

Abstract

COVID-19 vaccination topic has been a hot topic of discussions on social media platforms wondering its effectiveness against the SARS-COV-2 virus. Twitter is one of the social media platforms that people widely lunched to express and share their thoughts about different issues touching their daily life. Though many studies have been undertaken for COVID-19 vaccine sentiment analysis, they are still limited and need to be updated constantly. This paper conducts a system for COVID-19 vaccine sentiment analysis based on data extracted from Twitter platform for the time interval from 1st of January till the 3rd of Sep. 2021, and by using deep learning techniques. The introduced system proposes to develop a model architecture based on a deep bidirectional long short-term memory (LSTM) neural network, to analyze tweets data in the form of positive, neutral, and negative. As a result, the overall accuracy of the developed model based on validation data is 74.92%. The obtained outcomes from the sentiment analysis system on collected tweets-data of COVID-19 vaccine revealed that neutral is the prominent sentiment with a rate of 69.5%, and negative sentiment has less rate of tweets reached 20.75% while the positive sentiment has a lesser rate of tweets reached of 9.67%.
Using resource allocation for seamless service provisioning in cloud computing Mustafa Mahmood Akawee; Munef Abdullah Ahmed; Raed Abdulkareem Hasan
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp854-858

Abstract

A Resources allocation is one of the most important things in cloud computing because the environment in which work depends is heterogeneous environment and there are many who request the same service at the same time. Two criteria are used to be considered. First, the time for completing all the required tasks on the available resources and secondly the energy consumed and is extracted from the number of processes that used to complete those tasks. While uploading an application to the Cloud, load balancer allocates the appealed instances for physical computers to balance the computational load of several applications through physical computers. this paper presents some resource allocation problems and issues that can solve with help of load balancing techniques and algorithms. In addition, the performance of the algorithm was measured on seven mathematical functions, and the best results were for the algorithm pyogenes.
Combination of narrow bipolar pulses and attempted leaders in Melaka, Malaysia Isa, Nur Asyiqin Binti Mohd; Baharudin, Zikri Abadi; Daud, Izdihartun Najihah Binti Ahmad; Zainuddin, Hidayat
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.pp1825-1830

Abstract

This paper presents the characteristic of the positive attempted leaders preceded by positive narrow bipolar pulses (NPBPs). Attempted leaders are the preliminary breakdown process with no subsequent event (return stroke). On the other hand, narrow bipolar pulse is the lightning event commonly isolated and produces a strong electromagnetic field (in a short period). Attempted leaders hardly occurred in the tropics, and the preceding of the NBP (the combination) should be considered unique. In this present study, we found four samples in which the arithmetic means of duration of NPBPs pulse was 32.19 µs, with separation between the positive attempted leader was 1.86 ms apart. For the positive attempted leader, the arithmetic means of the whole pulse train, individual pulse and interval pulse of positive attempted leaders were 3.47 ms, 29.66 µs and 486.53 µs, respectively. The pulse train in this study seems to fade out fast compared to the isolated positive attempted leader pulse train. Next, the NPBP's pulse duration in this study shows well in agreement with the type of isolated NPBPs indicates that the association does not affect its pulse duration characteristic already present in the title.
Output power control of nuclear reactor using ant lion optimization-based controller Tarek A. Boghdady; Mostafa Mahmoud Ibrahim; Essam Aboul Zahab; Mahmoud Sayed
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1299-1305

Abstract

Power level control is a critical issue in nuclear power stations due to its nonlinear dynamics. One of the most commonly used controllers is fractional order proportional–integral–derivative (FOPID). The FOPID is an enhanced and modern controlling system that has two additional added parameters. In this paper, comparison between particle swarm, gray wolf and ant lion optimization techniques is performed to determine the FOPID controller parameters. The nuclear reactor is a pressurized water reactor which is a fifth order nonlinear reactor model and is simulated using MATLAB software based on the point kinetic model. The integral square error (ISE) performance index is used to evaluate the performance of the three optimization techniques. The simulation results show that ant lion optimization for tuning the FOPID controller parameters gives the best performance and integral square error index better than the two other optimization techniques.
Delay-power efficient VLSI architecture design for robust proportionate adaptive filter Gangadharaiah Soralamavu Lakshmaiah; Chikkajala Krishnappa Narayanappa; Divya Muddenahalli Narasimhaiah; Munivenkatappa Nagabhushanam; Nuthan Prasad Venkatesh; Bhanu Darshan Srinivas Shobhavathi
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i1.pp67-74

Abstract

This paper proposes the robust proportionate adaptive filtering algorithms and their respective efficient very large-scale integration (VLSI) architectures for sparse system identification under impulsive noise, several types of algorithms are combined to obtain optimum results. Here, we rendered a relative analysis on these algorithms and the algorithms are mapped on to the hardware to show that the improvement is obtained with respect to convergence rate and hardware complexity of VLSI architectures and has negligible hardware overhead with improved robustness. Good performance and convergence rate is obtained by combining the delayed μ-law proportionate (DMP) and least mean logarithmic square (LMLS) algorithms i.e. delayed µ-law proportionate least mean logarithmic square (DMP LMLS). Robust proportionate adaptive filter is coded in system verilog and synthesized using cadence genus compiler with 90 nm technology library.
Cancerous brain tumor detection using hybrid deep learning framework Sonali Kothari; Shwetambari Chiwhane; Shruti Jain; Malti Baghel
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1651-1661

Abstract

Computational models based on deep learning (DL) algorithms have multiple processing layers representing data at multiple levels of abstraction. Deep learning has exploded in popularity in recent years, particularly in medical image processing, medical image analysis, and bioinformatics. As a result, deep learning has effectively modified and strengthened the means of identification, prediction, and diagnosis in several healthcare fields, including pathology, brain tumours, lung cancer, the abdomen, cardiac, and retina. In general, brain tumours are among the most common and aggressive malignant tumour diseases, with a limited life span if diagnosed at a higher grade. After identifying the tumour, brain tumour grading is a crucial step in evaluating a successful treatment strategy. This research aims to propose a cancerous brain tumor detection and classification using deep learning. In this paper, numerous soft computing techniques and a deep learning model to summarise the pathophysiology of brain cancer, imaging modalities for brain cancer, and automated computer-assisted methods for brain cancer characterization is used. In the sense of machine learning and the deep learning model, paper has highlighted the association between brain cancer and other brain disorders such as epilepsy, stroke, Alzheimer's, Parkinson's, and Wilson's disease, leukoaraiosis, and other neurological disorders.
A microcontroller based microfluidic biochip for calcium percentage detection in blood Zaid H. Al-Sawwaff; Zahraa M. Rashid; Mohammed Faeik Ruzaij Al-Okby; Fatma Kandemirli
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i1.pp135-142

Abstract

Apheresis is an essential step in clinical diagnostic. Searching for a safe and fast way was necessary to avoid wasting time and obtain the desired results efficiently. This research includes two stages: First, a microfluidic biochip with the properties of fast processing response, automation capability, and low-cost was designed having a tiny mesh-type channel that filters pure plasma from the blood components and a straight channel to deliver the pure plasma to a tank. Second, an automated system was designed to detect blood calcium levels using a microcontroller and a colors-detection sensor TCS3200-DB. The device is designed to take a 0.15 to 2.15 mg/dL, 10-160 µm blood sample, which is considered small compared to the samples taken for the blood apheresis process used in laboratories where a substantial quantity of pure plasma is obtained naturally. Pure plasma is mixed with calcium detectors R1 and R2 to get a violet-colored solution with a wavelength between 390 nm to 440 nm. The results of the proposed device were compared with the traditional methods used spectroscopy method using concentrations of 10 different blood samples, and the results proved that there is a slight error between the two processes.
Performance comparison of TOPAS chirped fiber Bragg grating sensor with Tanh and Gaussian apodization Dedi Irawan; Khaikal Ramadhan; Saktioto Saktioto; Azwir Marwin
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1477-1485

Abstract

In this work we carried out a numerical simulation with software Optigrating for Apodization chirped fiber Bragg grating (CFBG) with TOPAS material to improve sensitivity sensor, it was found that CFBG with a grating length of 50 mm has advantages in terms of ripple factor, side lobe left (SLL), and side lobe right (SLR) with values of -0,998 and -10,5264 dB, respectively. While the 10 mm CFBG has a narrower full-width half maximum (FWHM) with a value of 0.4528 nm. Tanh and Gaussian apodization were arranged in the CFBG design, it was found that the Tanh linear-CFBG had a narrow FWHM but for the ripple factor and the main lobe and side lobes were not good enough compared to the Tanh Cubicroot-CFBG, and the same pattern was also obtained in the Gaussian apodization. The narrow FWHM indicates the accuracy in detecting temperature, as well as the suppression of SLL and SLR. for the effect of apodization on CFBG it was found that The Tanh Linear-CFBG design with TOPAS material has the highest sensitivity which is -51.76 pm/oC compared to other designs.
Employing light fidelity technology in health monitoring system Marwan Al-Dabbagh; Awos Kh. Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp989-997

Abstract

Light Fidelity (Li-Fi) is an emerging technology that has been in transferring data packets in Internet of Things (IoT) applications. During the COVID-19 pandemic, healthcare institutes try to manage the rapid increase of patients’ numbers. The healthcare team may not have the ability to monitor patients’ stats around the clock with the conventional techniques. In this paper, a healthcare monitoring framework to exchange health data between biosensors and terminals employing Li-Fi technology is proposed. It exploits Li-Fi to transmit data towards a terminal then to a cloud platform. It is intended for use in highly dense healthcare institutes where the number of patients is high. Exploiting Li-Fi to establish connection to cut high cost of other transmission technologies including Wi-Fi and provides less complexity and shorter latency. We evaluate the framework in a real-life environment using biosensors and Li-Fi communication model (for network infrastructure), these two components are connected to a computing terminal to help health staff monitor patients. The computing terminal is connected to a cloud platform to provide remote monitoring and computing resilience. The framework shows superior performance in real-world scenarios compared to Wi-Fi. A comprehensive analysis has been conducted to show the differences between Li-Fi and Wi-Fi.

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