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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 112 Documents
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Search results for , issue "Vol 12, No 5: October 2022" : 112 Documents clear
Predicting the mental health of rural Bangladeshi children in coronavirus disease 2019 Nazmun Nessa Moon; Refath Ara Hossain; Israt Jahan; Shahriar Shakil; Shihab Uddin; Mahmudul Hassan; Fernaz Narin Nur
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5501-5510

Abstract

The novel coronavirus disease 2019 (COVID-19) current pandemic is a worldwide health emergency like no other. It is not the only COVID-19 infection in infants, children, and adolescents that is causing concern among their families and professionals; there are also other serious issues that must be carefully detected and addressed. Major things are identified due to COVID-19, some elements are affecting children’s healthcare in direct or indirect ways, affecting them not just from a medical standpoint but also from social, psychological, economic, and educational perspectives. All these factors may have affected children’s mental development, particularly in rural settings. As Bangladesh faces a major challenge such as a lack of public mental health facilities, especially in rural areas. So, we discovered a method to predict the mental development condition of rural children that they are facing at this time of COVID-19 using machine learning technology. This research work can predict whether a rural child is mentally developed or mentally hampered in Bangladesh and this prediction gives nice feedback.
Learning trends in customer churn with rule-based and kernel methods Nahier Aldhafferi; Abdullah Alqahtani; Fatema Sabeen Shaikh; Sunday Olusanya Olatunji; Abdullah Almurayh; Fahad A. Alghamdi; Ghalib H. Alshammri; Amani K. Samha; Mutasem Khalil Alsmadi; Hayat Alfagham; Abderrazak Ben Salah
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5364-5374

Abstract

In the present article an attempt has been made to predict the occurrences of customers leaving or ‘churning’ a business enterprise and explain the possible causes for the customer churning. Three different algorithms are used to predict churn, viz. decision tree, support vector machine and rough set theory. While two are rule-based learning methods which lead to more interpretable results that might help the marketing division to retain or hasten cross-sell of customers, one of them is a kernel-based classification that separates the customers on a feature hyperplane. The nature of predictions and rules obtained from them are able to provide a choice between a more focused or more extensive program the company may wish to implement as part of its customer retention program.
A new three-term conjugate gradient method with application to regression analysis Nur Idalisa; Mohd Rivaie; Nur Hidayah Mohd Noh; Mohd Agos Salim Nasir; Nurul Hafawati Fadhilah; Norma Alias
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5248-5259

Abstract

Conjugate gradient (CG) method is well-known for its ability to solve unconstrained optimization (UO.) problems. This article presenting a new CG method with sufficient descent conditions which improves the former method developed by Rvaie, Mustafa, Ismail and Leong (RMIL). The efficacy of the proposed method has been demonstrated through simulations on the Kijang Emas pricing regression problem. The daily data between January 2021 to May 2021 were obtained from Malaysian Ministry of Health and Bank Negara Malaysia. The dependent variable for this study was the Kijang Emas price, and the independent variables were the coronavirus disease (COVID-19) measures (i.e., new cases, R-naught, death cases, new recovered). Data collected were analyzed on its correlation and coefficient determinant, and the influences of COVID-19 on Kijang Emas price was examined through multiple linear regression model. Findings revealed that the suggested technique outperformed the existing CG algorithms in terms of computing efficiency.
Gender detection in children’s speech utterances for human-robot interaction Ameer Abdul-Baqi Badr; Alia Karim Abdul-Hassan
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5049-5054

Abstract

The human voice speech essentially includes paralinguistic information used in many real-time applications. Detecting the children’s gender is considered a challenging task compared to the adult’s gender. In this study, a system for human-robot interaction (HRI) is proposed to detect the gender in children’s speech utterances without depending on the text. The robot's perception includes three phases: Feature’s extraction phase where four formants are measured at each glottal pulse and then a median is calculated across these measurements. After that, three types of features are measured which are formant average (AF), formant dispersion (DF), and formant position (PF). Feature’s standardization phase where the measured feature dimensions are standardized using the z-score method. The semantic understanding phase is where the children’s gender is detected accurately using the logistic regression classifier. At the same time, the action of the robot is specified via a speech response using the text to speech (TTS) technique. Experiments are conducted on the Carnegie Mellon University (CMU) Kids dataset to measure the suggested system’s performance. In the suggested system, the overall accuracy is 98%. The results show a relatively clear improvement in terms of accuracy of up to 13% compared to related works that utilized the CMU Kids dataset.
Design and analysis of dual-mode numerically controlled oscillators based controlled oscillator frequency modulation Ramana Reddy Gujjula; Chitra Perumal; Prakash Kodali; Bodapati Venkata Rajanna
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4935-4943

Abstract

In this paper, the design and analysis of dual-mode numerically controlled oscillators (NCO) based controlled oscillator frequency Modulation is implemented. Initially, input is given to the analog to digital (ADC) converter. This will change the input from analog to digital converter. After that, the pulse skipping mode (PSM) logic and proportional integral (PI) are applied to the converted data. After applying PSM logic, data is directly transferred to the connection block. The proportional and integral block will transfer the data will be decoded using the decoder. After decoding the values, it is saved using a modulo accumulator. After that, it is converted from one hot residue (OHR) to binary converter. The converted data is saved in the register. Now both data will pass through the gate driver circuit and output will be obtained finally. From simulation results, it can observe that the usage of metal oxide semiconductor field effect transistors (MOSFETs) and total nodes are very less in dual-mode NCO-based controlled oscillator frequency modulation.
Classification of plasmodium falciparum based on textural and morphological features Doni Setyawan; Retantyo Wardoyo; Moh Edi Wibowo; E. Elsa Herdiana Murhandarwati
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5036-5048

Abstract

Malaria is a disease caused by plasmodium parasites transmitted through the bites of female anopheles-mosquito that infect the human red blood cell (RBC). The standard malaria diagnosis is based on manual examination of a thick and thin blood smear, which heavily depends on the microscopist experience. This study proposed a system that can identify the life stages of plasmodium falciparum in human RBC. The image preprocessing process was done by illumination correction using gray world assumption, contrast enhancement using shadow correction, extraction of saturation component, and noise filtering. The segmentation process was applied using Otsuthresholding and morphological operation. The test results showed that the use of artificial neural network (ANN) using a combination of texture and morphological features gives better results when compared to the use of only texture or morphology features. The results showed that the proposed feature achieved an accuracy of 82.67%, a sensitivity of 82.18%, and a specificity of 94.17%, thus improving decision-making for malaria diagnosis.
Korean-popular Facebook fan page analytics in Thailand Wirapong Chansanam; Kulthida Tuamsuk; Kanyarat Kwiecien; Sam Gyun Oh
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5291-5303

Abstract

The purpose of this study was to gather, analyze, and elaborate big data on Facebook’s essential information, with a specific focus on the information obtained from Korean-popular (K-Pop) fan pages on the social networking site. For this analysis, a total of 3,531,736 comments by Korean-pop fans were gathered from various K-pop Facebook pages. In order to interpret how 11 extremely popular Facebook pages shape Thai fans’ enthusiasm for the South Korean music industry, descriptive statistics and visualization analysis were employed. Finally, data analytics and correlation analysis were used to evaluate the essential understanding of the Facebook pages. The research revealed three key findings: i) K-pop fan pages provide more opportunities for Thai fans to express their support for K-pop artists and advocate for causes, ii) K-pop fan pages provide more opportunities for Thai fans to communicate with K-pop artists, and iii) K-pop fan pages build opportunities for Thai fans to establish a more glamorous online presence despite limitations concerning financial resources, foreign language skills, and opportunities. In the future, the research outcomes may be valuable for academic studies and practice.
Automated prediction of sudden cardiac death using statistically extracted features from electrocardiogram signals Karna Viswavardhan Reddy; Navin Kumar
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4960-4969

Abstract

Sudden cardiac death (SCD) is becoming a severe problem despite significant advancements in the usage of the information and communication technology (ICT) in the health industry. Predicting an unexpected SCD of a person is of high importance. It might increase the survival rate. In this work, we have developed an automated method for predicting SCD utilizing statistical measures. We extracted the intrinsic attributes of the electrocardiogram (ECG) signals using Hilbert-Huang and wavelet transforms. Then utilizing machine learning (ML) classifier, we are using these traits to automatically classify regular and SCD existing risks. Support vector machine (SVM), decision tree (DT), naive Bayes (NB), discriminate k-nearest neighbors (KNN), analysis (Disc.), as well as an ensemble of classifiers also utilized (Ens.). The efficiency and practicality of the proposed methods are evaluated using a standard database and measured ECG data obtained from 18 ECG records of SCD cases and 18 ECG records of normal cases. For the automated scheme, the set of features can predict SCD very fast that is, half an hour before the occurrence of SCD with an average accuracy of 100.0% (KNN), 99.9% (SVM), 98.5% (NB), 99.4% (DT), 99.5% (Disc.), and 100.0% (Ens.)
Particle swarm optimization and Taguchi algorithm-based power system stabilizer-effect of light loading condition Kumara Kalegowda; Amruthur Doreswamy Iyengar Srinivasan; Nagaraj Chinnamadha
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4672-4679

Abstract

A robust design of particle swarm optimization (PSO) and Taguchi algorithm-based power system stabilizer (PSS) is presented in this paper. It incorporates a novel concept in which Taguchi and PSO techniques are integrated for stabilization of single machine infinite bus (SMIB). The system tolerates uncertainty and imprecision to a maximum extent. The proposed controller's effectiveness is proved through experiments covering light load condition using MATLAB/Simulink platform. The performance of the system is compared without PSS and with a conventional PSS. The settling time of the optimal PSS is decreased by more than 75% to conventional PSS. The study reveals that the proposed hybrid controller offers enhanced performance with respect to settling time as well as peak overshoot of the system.
On the applicability of some existing tropospheric scintillation prediction models for Ikeja and Abuja, Nigeria Zachaeus Kayode Adeyemo; Ridwan Olalekan Yusuf; Hammed Oyebamiji Lasisi; Samson Iyanda Ojo; Rebecca Olufunmilayoa Omowaiye; Adebukola Ayoade Adedeji
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5084-5092

Abstract

Tropospheric scintillation which causes rapid fluctuation of signal due to the turbulence in the atmosphere is of significance in satellite link budget design. Existing models that predict the intensity of scintillation such as Karasawa, International Telecommunication Union Radiocommunication (ITU-R) Sector, Otung, Van de Kamp and Ortgies are not appropriate for predicting scintillation intensity (SI) in Nigeria due to localization of the models to particular regions. The monthly average air temperature and relative humidity for Ikeja and Abuja, Nigeria, retrieved from the Nigerian Meteorological Centre data bank were used for the investigation. An elevation angle of 5° was used as look angle, antenna diameter of 0.3 m, 40 GHz and 45 GHz frequencies were considered in this study. The existing scintillation model values were then compared with the measured values for the two locations to determine the best performance model. The SI results at 40 GHz and 45 GHz were obtained for each of the existing models. It could be deduced from the results obtained that orgies model values were the most closet to the measured values. Therefore, Orgies-N model was the most appropriate for SI prediction in Ikeja and Abuja.

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