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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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Investigation of overvoltage on square, rectangular and L-shaped ground grids of high voltage substations by ATP/EMTP Krung Luewattana; Paweena Rattanasena
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4689-4697

Abstract

Ground grid system is important for preventing the hazardous effects of overvoltage in high voltage substations due to fault current perhaps from lightning strike or device malfunction. Therefore, this study aimed to investigate the effects of overvoltage on square, rectangular and L-shaped ground grids with ground rods being distributed in mesh-pattern by using alternate transients program/electromagnetic transients program (ATP/EMTP) program. The models were simulated in the cases that 25 kA-fault current being injected into the center or one of the corners of ground grids. The results showed that the highest level of overvoltage (6.3349 kV) was detected at the corner of rectangular ground grid when the fault current was injected into its corner. However, the lowest level of overvoltage was found when the fault current was injected into the center of square ground grid. The results from this study indicated that ATP/EMTP program was useful for preliminary investigation of overvoltage on ground grids of different shapes. The obtained knowledge could be beneficial for further designing of ground grid systems of high voltage substations to receive the minimal damages due to fault current.
Small intestine bleeding detection using color threshold and morphological operation in WCE images A. Al Mamun; M. S. Hossain; P. P. Em; A. Tahabilder; R. Sultana; M. A. Islam
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp3040-3048

Abstract

Wireless capsule endoscopy (WCE) is a significant modern technique for observing the whole gastroenterological tract to diagnose various diseases like bleeding, ulcer, tumor, Crohn's disease, polyps etc in a non-invasive manner. However, it will make a substantial onus for physicians like human oversight errors with time consumption for manual checking of a vast amount of image frames. These problems motivate the researchers to employ a computer-aided system to classify the particular information from the image frames. Therefore, a computer-aided system based on the color threshold and morphological operation has been proposed in this research to recognize specified bleeding images from the WCE. Besides, A unique classifier, quadratic support vector machine (QSVM) has been employed for classifying the bleeding and non-bleeding images with the statistical feature vector in HSV color space. After extensive experiments on clinical data, 95.8% accuracy, 95% sensitivity, 97% specificity, 80% precision, 99% negative predicted value and 85% F1 score has been achieved, which outperforms some of the existing methods in this regard. It is expected that this methodology would bring a significant contribution to the WCE technology. 
Dielectric properties assessment of honey by using non-destructive dielectric spectroscopy Aslina Abu Bakar; Muhammad Aiman Najmi bin Rodzali; Rosfariza Radzali; Azlina Idris; Ahmad Rashidy Razali
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp189-200

Abstract

In this research the dielectric constant of three types of Malaysian honey has been investigated using a non-destructive measurement technique. The objective of this research is to assess the dielectric constant of the three types of honey in Malaysia using a non-destructive measurement technique known as an open-ended coaxial probe in the frequency range from 100 MHz to 10 GHz frequency. Analysis on the effect water concentration in honey on the dielectric constant and the effect of temperature on dielectric constant of honey has been conducted. The three types of honey that have been chosen to be investigated in this project are stingless bee honey, wild honey and commercial (organic) honey and together their water adulterated samples. For this research, the probe had been set up by setting a range of frequency from 100 MHz to 10 GHz and needs to be calibrated with three calibration methods namely open, short and reference water. From the result it was found that the higher the temperature of the honey and the higher percentage of water content in the honey, the dielectric constant is increased. The dielectric constants of all honeys decreased with increasing frequency in the measured frequency range and increased with increase percentage of water content and temperature.
Estimation of posture and prediction of the elderly getting out of bed using a body pressure sensor Atsushi Hagihara; Fumiko Harada; Hiromitsu Shimakawa
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp1208-1222

Abstract

We propose an IoT support system for estimating the posture of the care recipient on the bed from the body pressure of the care recipient measured by a sheet-type body pressure sensor, and detecting the posture related to leaving the bed in real time. In addition, we propose a method that predicts getting out of the bed before the care recipient takes a posture related to getting out of the bed by considering the state transition. Intervention experiment showed that using body pressure features as an explanatory variable and applying machine learning, 16 types of postures on the bed of care recipients with an F value of 0.7 or more could be identified. From the experiment without intervention, by applying the hidden Markov model, we calculated the transition probability to each hidden state when the care recipient getting out of the bed and the transition probability to each hidden state when the care recipient not getting out of the bed. As a result, there was a difference of about 0.1 in the transition probability of the state related to raising upper body.
Multipurpose medical assistant robot (Docto-Bot) based on internet of things Md. Anowar Hossain; Md Ebrahim Hossain; Mohammad Anisur Rahaman
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5558-5567

Abstract

The world's population is growing every day, and so is the number of patients. People's life expectancy is increasing due to technology's welfare, but the problem is that the health sector has always faced a shortage of inadequate doctors. This research main objective was to design and implement a biomedical-based medical assistant robot named "Docto-Bot" to deal with this problem. This research concerns this medical assistant robot's design and development for the disabled and the patients in need. Such a robot's prime utilization is to minimize person-to-person contact and ensure the cleaning, sterilization, and support in hospitals and similar facilities such as quarantine. This prototype robot consists of a medicine reminding and medicine providing system, Automatic hand sanitizer and IoT based physiological monitoring system (body temperature, pulse rate, ECG, Oxygen saturation level). A direct one-to-one server-based communication method and user-end android app maintaining system designed. It also included the controlling part, which control automatically and manually by users. Docto-Bot will play a very significant factor in bio-medical robot applications. Though the achievements described in the paper look fruitful and advanced, shortcomings still exist.
Spatial information of fuzzy clustering based mean best artificial bee colony algorithm for phantom brain image segmentation Waleed Alomoush; Ayat Alrosan; Ammar Almomani; Khalid Alissa; Osama A. Khashan; Ahmad Al-nawasrah
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4050-4058

Abstract

Fuzzy c-means algorithm (FCM) is among the most commonly used in the medical image segmentation process. Nevertheless, the traditional FCM clustering approach has been several weaknesses such as noise sensitivity and stuck in local optimum, due to FCM hasn’t able to consider the information of contextual. To solve FCM problems, this paper presented spatial information of fuzzy clustering-based mean best artificial bee colony algorithm, which is called SFCM-MeanABC. This proposed approach is used contextual information in the spatial fuzzy clustering algorithm to reduce sensitivity to noise and its used MeanABC capability of balancing between exploration and exploitation that is explore the positive and negative directions in search space to find the best solutions, which leads to avoiding stuck in a local optimum. The experiments are carried out on two kinds of brain images the Phantom MRI brain image with a different level of noise and simulated image. The performance of the SFCM-MeanABC approach shows promising results compared with SFCM-ABC and other stats of the arts.
AlertNet: Deep convolutional-recurrent neural network model for driving alertness detection P. C. Nissimagoudar; A. V. Nandi; Aakanksha Patil; Gireesha H. M.
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp3529-3538

Abstract

Drowsy driving is one of the major problems which has led to many road accidents. Electroencephalography (EEG) is one of the most reliable sources to detect sleep on-set while driving as there is the direct involvement of biological signals. The present work focuses on detecting driver’s alertness using the deep neural network architecture, which is built using ResNets and encoder-decoder based sequence to sequence models with attention decoder. The ResNets with the skip connections allow training the network deeper with a reduced loss function and training error. The model is built to reduce the complex computations required for feature extraction. The ResNets also help in retaining the features from the previous layer and do not require different filters for frequency and time-invariant features. The output of ResNets, the features are input to encoder-decoder based sequence to sequence models, built using Bi-directional long-short memories. Sequence to Sequence model learns the complex features of the signal and analyze the output of past and future states simultaneously for classification of drowsy/sleepstage-1 and alert stages. Also, to overcome the unequal distribution (class-imbalance) data problem present in the datasets, the proposed loss functions help in achieving the identical error for both majority and minority classes during the raining of the network for each sleep stage. The model provides an overall-accuracy of 87.92% and 87.05%, a macro-F1-core of 78.06%, and 79.66% and Cohen's-kappa score of 0.78 and 0.79 for the Sleep-EDF 2013 and 2018 data sets respectively.
IoT-based sound-level control for audio amplifiers: mosques as a case study Naeem Al-Oudat
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp859-867

Abstract

When using audio-amplifiers in the open, uneven distribution of sound makes people unpleasant because it is loud or unheared. This unfortunate situation arises because audio-amplifiers volumes are set according to the guess of sound technicians. Mosques, as an example, are distributed inside wide areas and fire Azan five times a day. Due to the relatively long distances between them, speed and direction of the wind impose setting sound levels prior to each Azan such that all the area is covered and the overlap is minimized. In this paper, we propose a system based on internet of things (IoT) model to control the sound level of each mosque in the community. An IoT device (one in a mosque) sets the level of sound fired by the audio-amplifier. To do that, a synchronized series of tones is fired from each node. Once a node hears these tones, the process of sound level control starts to indicate the distances to heared nodes. As the approximate distances between nodes are known, each node can calculate its suitable sound level. Results showed that the proposed system is effective in setting sound levels for mosques audio amplifiers.
A fault-tolerant photovoltaic integrated shunt active power filter with a 27-level inverter Kamel Saleh; Ameen Madi
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp1166-1177

Abstract

This paper introduces a fault-tolerant shunt active power filter (SAPF). The novility in of this work is that it poposes a solutions to increase the reliability of shunt active power filter to maintain its operation under a single-phase open-circuit fault in the SAPF. This will increase the reliability of the whole power system. The SAPF is composed of a 4-leg 27-level inverter based on asymmetric cascaded H-bridge topology. If an open-circuit fault is introduced to the operation of the SAPF, a special control technique will be implemented and the redundant leg of the SAPF will be activated. The fault-tolerant SAPF can do many tasks under healthy operating conditions and post and open circuit fault depending on the state of charge (SOC) of the batteries. It can mitigate harmonics in the power system, improve power factor in the system by injecting reactive power, and inject real power to the system. The proposed SAPF is tested and simulated in MATLAB/Simulink and the results have shown a significant improvement in total harmonics distortion (THD) of the source current from 13.9% to 3.9% under the normal operating condition and from 42% to 8.4% post and open circuit fault.
A new system to detect coronavirus social distance violation Marta Botella-Campos; José Luis Gacía-Navas; Albert Rego; Sandra Sendra; Jaime Lloret
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5034-5048

Abstract

In this paper, a novel solution to avoid new infections is presented. Instead of tracing users’ locations, the presence of individuals is detected by analysing the voices, and people’s faces are detected by the camera. To do this, two different Android applications were implemented. The first one uses the camera to detect people’s faces whenever the user answers or performs a phone call. Firebase Platform will be used to detect faces captured by the camera and determine its size and estimate their distance to the phone terminal. The second application uses voice biometrics to differentiate the users’ voice from unknown speakers and creates a neural network model based on 5 samples of the user’s voice. This feature will only be activated whenever the user is surfing the Internet or using other applications to prevent undesired contacts. Currently, the patient’s tracking is performed by geolocation or by using Bluetooth connection. Although face detection and voice recognition are existing methods, this paper aims to use them and integrate both in a single device. Our application cannot violate privacy since it does not save the data used to carry out the detection and does not associate this data to people.

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