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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 64 Documents
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Search results for , issue "Vol 27, No 3: September 2022" : 64 Documents clear
TiO2 nanoparticles impacts over color deviation in white light-emitting diodes Thanh Binh Ly; Nguyen Doan Quoc Anh; Phan Xuan Le
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1304-1310

Abstract

The effects of injecting TiO2nanoparticles with phosphorus silicone packing on white color light-emitting diodes (WLEDs) are examined. In WLED packages, the proposed approach may increase luminance emission by 2.7%, while the coordinated color temperature will increase by 39%. At the same time, the required phosphorus quantity will be lowered by 5% along with the joint temperature of 6.5°C. The modifications, which boost illuminating performance and also reduce temperature aggregation, are because of the packing material's increased illuminating dispersion efficiency or even refracting indices, along with lower illuminating reduction, for which colour fusing inside the parcels is responsible. Consequently, the results suggest improved-WLED lighting system performance makes the products more appropriate in solid-state lighting.
Ca9La(PO4)7:Eu2+,Mn2+: a radiation-adjustable phosphor usable for high-perfomance white light-emitting diodes Phuc Dang Huu; Phung Ton That; Phan Xuan Le; Nguyen Le Thai
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1290-1296

Abstract

We used solid-condition processes to make a sequence of radiation-adjustable phosphors Eu2+/Mn2+ co-doped Ca9La(PO4)7 (shortened as CaLa:EM), which show a consistently variable hue from green to yellow and red via an efficient resonance-form energy transition as well as the strength of green and red radiations may be controllable through altering the Mn2+concentration. We examined the transition of energy (Eu2+®Mn2+) for CaLa:EM. It is proved to be a resonant kind using a dipole-quadrupole process, having power shift critical range calculated to be 11.36 Å by using the spectral overlap techniques. Mixing a 365 nm UV-InGaN chip as well as one phosphor combination containing (Ca0.98Eu0.005Mn0.015)9La(PO4)7 in yellow with BaMgAl10O17:Eu2+in blue produced a warming WLED having CIE color coordinates measured at (0.35, 0.31), better CRI value (Ra)measured at 91.5 along with smaller CCT value of 4,496 K.
Document classification using term frequency-inverse document frequency and K-means clustering Wasseem N. Ibrahem Al-Obaydy; Hala A. Hashim; Yassen AbdelKhaleq Najm; Ahmed Adeeb Jalal
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1517-1524

Abstract

Increased advancement in a variety of study subjects and information technologies, has increased the number of published research articles. However, researchers are facing difficulties and devote a significant time amount in locating scientific research publications relevant to their domain of expertise. In this article, an approach of document classification is presented to cluster the text documents of research articles into expressive groups that encompass a similar scientific field. The main focus and scopes of target groups were adopted in designing the proposed method, each group include several topics. The word tokens were separately extracted from topics related to a single group. The repeated appearance of word tokens in a document has an impact on the document's weight, which is computed using the term frequency-inverse document frequency (TF-IDF) numerical statistic. To perform the categorization process, the proposed approach employs the paper's title, abstract, and keywords, as well as the categories' topics. We exploited the K-means clustering algorithm for classifying and clustering the documents into primary categories. The K-means algorithm uses category weights to initialize the cluster centers (or centroids). Experimental results have shown that the suggested technique outperforms the k-nearest neighbors algorithm in terms of accuracy in retrieving information.
Evolution of automated learning techniques for combating COVID-19: an analysis Azheen Ghafour Mohammed; Eman Shekhan Hamsheen
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1635-1641

Abstract

It is now more than two years that the world is battling the tiny invisible virus, COVID-19. Since its appearance, it showered humankind with shock, fear, and death. In small words, this pandemic has paused human life in all its aspects and beauties. Governments, health industry researchers and laboratories have put all their efforts to achieve a universal goal that is, overcoming the crisis and putting an end to the pandemic. However, this goal was never achievable without the smart use of automated learning, artificial intelligence, machine learning and deep learning algorithms. This review paper presents a collection of the experimental research articles tackled using real-time official datasets from hospitals and governments. These datasets are processed using automated learning (AL) algorithms in order to find suitable solutions to most of the COVID-19 related problems. This paper presents the AL applications in a story telling manner, starting from the first phases of COVID-19, when doctors had no experience dealing with the disease and had difficulty in diagnosing it, then moving to the other phases like suggesting a medicine, drug repurposing, facial mask detection, fake news detection, vaccine development, pandemic management, post vaccine statistics and lastly post COVID-19 analysis.
Developing mobile game application for introduction to financial accounting Mohamed Imran Mohamed Ariff; Fuad Mohd Khalil; Rahayu Abdul Rahman; Suraya Masrom; Noreen Izza Arshad
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1721-1728

Abstract

The financial accounting subject is one of the core subjects that is essential for any accounting student. However, this subject is perceived as boring and difficult to comprehend particularly for students who lack in the accounting knowledge. The aim of this research paper is to present the adoption of the gamification learning concept in designing and developing a mobile game application to cultivate better understanding in the financial accounting subject. This mobile application was developed for Android operating system and was designed using the modified game methodology. Further, this mobile application was subjected to several testing phases using numerous participants. The results indicate the adoption of gamification has aided the students in understanding the financial accounting subject. Furthermore, the participants also indicated that learning using gamification has encouraged them to think critically which then allowed them to better comprehend the financial accounting subject. The development of this mobile game application also contributes to the gamification literature which is vastly used in learning, and it advantages in improving the understanding of how games can be adopted to foster better understanding in the financial accounting subject.
Improved security and stability of grid connected the wind energy conversion system by unified power flow controller I Made Wartana; Ni Putu Agustini; Sasidharan Sreedharan
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1151-1161

Abstract

The stability and security improvements of the grid-connected to the wind energy conversion system (WECS) can be made by optimizing the placement of a flexible alternating current transmission system (FACTS). This study discusses the optimal placement of one type of WECS, namely the doubly-fed induction generator (DFIG) with a series and a shunt-FACTS control device called unified power flow controller (UPFC). The DFIG and UPFC connected grid dynamic perfor mance improvement with a maximum load bus system scenario. The optimal placement of DFIG and UPFC on the grid is formulated as a multi - objective problem, namely maximizing load bus system (Max. LBS) while minimizing active power loss (Min. P loss ) by pleasi ng numerous security and stability constraints. The non-dominated sorting genetic algorithm II (NSGA-II) have been utilized to settle this opposed bi-objective enhancement problem. The validity of the suggested method was examined on a modified IEEE 14-bus and a utilitarian examine system connected to DFIG with UPFC in power system analysis toolbox ( PSAT ) software. The optimal placement of DFIG and UPFC on the grid has increased the system's dynamic performance, with all the specified particular constraints being encountered.
A  creation in abstract 3D art inspired from Pavo muticus imperator Jirawat Sookkaew; Nakarin Chaikaew; Donticha Chiewsuwan; Somchai Seviset
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1419-1427

Abstract

Creation of art as abstract art by choosing athree-dimensional (3D)art formto be used for creativity, has brought the characteristics of the peacock inspired by its forms, color characteristics, including its habitats to be usedas a mixture and elements in creating this art. Therefore, when combined with the key elements of a 3D object with depth dimension of the object in the Z axis, adopting the colors of the space and the atmosphere of thepeacock's habitat to the surface of the 3D pieces, which provide creative approaches and techniques that enable abstract 3D art to be realized by the shapes and formed by perspectives as a whole. Z-axis can create directions to display hundreds of perspectives. In addition, the colors that have beenused to blend in with the 3D objects create beauty inspired by the colors that can be found in nature. The peacock's art has been passed through with the distinctive features of 3D objects, resulting in creating such abstract 3D artpieces.
Prediction of patient survival from heart failure using a cox-based model Tsehay Admassu Assegie; Thulasi Karpagam; Sathya Subramanian; Senthil Murugan Janakiraman; Jayanthi Arumugam; Dawed Omer Ahmed
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1550-1556

Abstract

The existing heart failure risk prediction models are developed based on machine learning predictors. The objective of this study is to identify the key risk factors that affect the survival time of heart patients and to develop a heart failure survival prediction model using the identified risk factors. A cox proportional hazard regression method is applied to generate the proposed heart failure survival model. We used the dataset from the University of California Irvine (UCI) clinical heart failure data repository. To develop the model we have used multiple risk factors such as age, anemia, creatinine phosphokinase, diabetes history, ejection fraction, presence of high blood pressure, platelet count, serum creatinine, sex, and smoking history. Among the risk factors, high blood pressure is identified as one of the novel risk factors for heart failure. We have validated the performance of the model via statistical and empirical validation. The experimental result shows that the proposed model achieved good discrimination and calibration ability with a C-index (receiver operating characteristic (ROC) of being 0.74 and a log-likelihood ratio of 81.95 using 11 degrees of freedom on the validation dataset.
Performance evaluation of chi-square and relief-F feature selection for facial expression recognition Mayyadah Ramiz Mahmood; Maiwan Bahjat Abdulrazzaq
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1470-1478

Abstract

Pattern recognition is a crucial part of machine learning that has recently piqued scientists' interest. The feature selection method utilized has an impact on the dataset's correctness and learning and training duration. Learning speed, comprehension and execution ease, and properly chosen features influence all high-quality outcomes. The two feature selection methods, relief-F and chi-square, are compared in this research. Each technique assesses and ranks attributes based on distinct criteria. Six of the most important features with the highest ranking have been chosen. The six features are utilized to compare the performance accuracy ratios of the four classifiers: k-nearest neighbor (KNN), naive Bayes (NB), multilayer perceptron (MLP), and random forests (RF) in terms of expression recognition. The final goal of the proposed strategy is to employ the least number of features from both feature selection methods to distinguish the four classifiers' accuracy performance. The proposed approach was trained and tested using the CK+ facial expression recognition dataset. According to the findings of the experiment, RF is the best accurate classifier on chi-square feature selection, with an accuracy of 94.23 %. According to a dataset utilized in this study, the relief-F feature selection approach had the best classifier, KNN, with an accuracy of 94.93 %
Quantification of retinal artery-vein ratio for vascular disease diagnosis using spatial U-Net Lakshmi Kala Pampana; Manjula Sri Rayudu
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1404-1411

Abstract

The retinal vascular morphological caliber changes reveal the signs of systemic health disorder and life threat diseases such as cardio and cerebral diseases. The quantitative vascular parameters like narrowed arteries, widened venules, reduced artery-vein ratio (AVR) have been associated with aforesaid disorders and diseases. Hence the quantitative biomarker AVR is important parameter in diagnosing variety of diseases. The accurate quantification of AVR be possible if and only if accurate classification of arteries and vein is done. In this paper, we proposed a deep learning based robust vessel segmentation and classification algorithm based on spatial U-Net and the accuracy of the algorithm is 97.8%. In the quantification process, this algorithm is applied on region of interest (RoI) of a fundus image and measured the AVR values using central retinal artery equivalent (CRAE) and central retinal vein equivalent (CRVE). The experimentation is carried on the digital retinal images for vessel extraction (DRIVE) dataset. The outcome of this work is the AVR observed to be >0.4 in normal retinal case and AVR value <0.4 for unhealthy case.

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