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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 96 Documents
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Search results for , issue "Vol 11, No 3: June 2021" : 96 Documents clear
Counteraction to information influence in social networking services by means of fuzzy logic system Kateryna Molodetska; Vladyslav Solonnikov; Oleksandr Voitko; Ihor Humeniuk; Oleksandr Matsko; Oleksii Samchyshyn
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2490-2499

Abstract

The article describes a decision support system based on fuzzy inference aimed to automate the procedure of choosing a model of formalizing the interaction between actors in virtual communities of social networking services and synergistic management of such processes. The developed system aims to increase the effectiveness of counteracting threats to information security of the state in social networking services. The mathematical apparatus of the fuzzy set theory and the Mamdani algorithm are the basis for the functioning of the decision support system. The usage of the developed fuzzy inference system will remove the ambiguity of information security expertise in the course of choosing approaches to formalization and the model of synergistic management of actors’ interaction in the conditions of incomplete information and ambiguous assessment of the state information security threat in social networking services.
Web document classification using topic modeling based document ranking Youngseok Lee; Jungwon Cho
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2386-2392

Abstract

In this paper, we propose a web document ranking method using topic modeling for effective information collection and classification. The proposed method is applied to the document ranking technique to avoid duplicated crawling when crawling at high speed. Through the proposed document ranking technique, it is feasible to remove redundant documents, classify the documents efficiently, and confirm that the crawler service is running. The proposed method enables rapid collection of many web documents; the user can search the web pages with constant data update efficiently. In addition, the efficiency of data retrieval can be improved because new information can be automatically classified and transmitted. By expanding the scope of the method to big data based web pages and improving it for application to various websites, it is expected that more effective information retrieval will be possible.
Pine wilt disease spreading prevention system using semantic segmentation Chulhyun Hwang; Jaean Jeong; Hoekyung Jung
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2666-2673

Abstract

Pine wilt disease is a disease that affects ecosystems by rapidly killing trees in a short period of time due to the close interaction between three factors such as trees, mediates, and pathogens. There is no 100% mortality infectious forest pests. According to the Korea Forest Service survey, as of April 2019, the damage of pine re-nematode disease was about 490,000 dead trees in 117 cities, counties and wards across the country. It's a fatal condition. In order to prevent this problem, this paper proposes a system that detects dead trees, early infection trees, and the like, using deep learning-based semantic segmentation. In addition, drones were used to photograph the area of the forest, and a separate pixel segmentation label could be used to identify three levels of transmission information: Suspicion, attention, and confirmation. This allows the user to grasp information such as area, location, and alarm to prevent the spread of re-nematode disease.
Substrate treatment for the increment of electric power potential from plants microbial fuel cells Melisa Acosta-Coll; Adalberto Ospino-Castro; Stalin Carbonell-Navarro; Jaider Escobar-Duque; Rafael Peña-Gallardo; Ronald Zamora-Musa
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp1933-1941

Abstract

Plants microbial fuel cells (PMFC) is novel sytem that generates renewable, clean, and sustainable electricity with minimal environmental impact. However, PMFC has limitations in power generation and current density, since its production values is lower than other renewable technologies. Different studies show that the highest limitation for energy generation through MFC is the high resistivity of the cathode, and the solution is to replace the metallic electrodes with non-metallic materials to obtain a better performance, however, the application of these materials requires complex interdisciplinary work. This study conducted three experimental tests using metallic electrodes for the extraction of electrons and combined a black earth substrate with different natural materials, types of plants, and water to determine their influence in the increment of the electric power output.
Model reduction of unstable systems based on balanced truncation algorithm Ngoc Kien Vu; Hong Quang Nguyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2045-2053

Abstract

Model reduction of a system is an approximation of a higher-order system to a lower-order system while the dynamic behavior of the system is almost unchanged. In this paper, we will discuss model order reduction (MOR) strategies for unstable systems, in which the method based on the balanced truncation algorithm will be focused on. Since each MOR algorithm has its strengths and weakness, practical applications should be suitable for each specific requirement. Simulation results will demonstrate the correctness of the algorithms.
Expert cancer model using supervised algorithms with a LASSO selection approach Pronab Ghosh; Asif Karim; Syeda Tanjila Atik; Saima Afrin; Mohd. Saifuzzaman
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2631-2639

Abstract

One of the most critical issues of the mortality rate in the medical field in current times is breast cancer. Nowadays, a large number of men and women is facing cancer-related deaths due to the lack of early diagnosis systems and proper treatment per year. To tackle the issue, various data mining approaches have been analyzed to build an effective model that helps to identify the different stages of deadly cancers. The study successfully proposes an early cancer disease model based on five different supervised algorithms such as logistic regression (henceforth LR), decision tree (henceforth DT), random forest (henceforth RF), Support vector machine (henceforth SVM), and K-nearest neighbor (henceforth KNN). After an appropriate preprocessing of the dataset, least absolute shrinkage and selection operator (LASSO) was used for feature selection (FS) using a 10-fold cross-validation (CV) approach. Employing LASSO with 10-fold cross-validation has been a novel steps introduced in this research. Afterwards, different performance evaluation metrics were measured to show accurate predictions based on the proposed algorithms. The result indicated top accuracy was received from RF classifier, approximately 99.41% with the integration of LASSO. Finally, a comprehensive comparison was carried out on Wisconsin breast cancer (diagnostic) dataset (WBCD) together with some current works containing all features.
The quality of service of the deployed LTE technology by mobile network operators in Abuja-Nigeria Anabi Hilary Kelechi; Uyi Aiyudubie Samson; Matthew Simeon; Okoyeigbo Obinna; Aligbe Alex; Atayero Aaron Aderemi
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2191-2202

Abstract

In this study, the real-world performance analysis of four Nigerian mobile network operators (MNOs), namely MTN, GLO, Airtel, and 9Mobile long-term evolution (LTE) cellular network, were analyzed and compared. The Nigerian MNOs utilize 5 MHz, 10 MH, and 20 MHz channel bandwidths based on third-generation partnership project’s (3 GPPs) recommendation. The presented analysis shows the uplink (UL), and downlink (DL) throughputs gaps in mobility condition as well as other LTE’s system quality of service (QoS) key performance indicators (KPI’s) of: Connection drop rate, connection failure rate, peak physical downlink throughput, minimum radio link control (RLC) downlink throughput threshold and latency are not strictly followed. The reason may be due to a lack of regulatory oversight enforcement. The comparative studies showed that MTN provides the best QoS. The introduction of novel LTE QoS metrics herein referred to as national independent wireless broadband quality reporting (NIWBQR) is the significant contribution of this study. The goal of this study is to show the quality of the network as it affects the user's experience. Important observation showed that all the MNOs are not adhering to the 3 GPPs specified user plane latency of 30 ms and control plane latency of 100 ms, respectively, which makes video streaming and low latency communication a near-impossible task.
Atar: Attention-based LSTM for Arabizi transliteration Bashar Talafha; Analle Abuammar; Mahmoud Al-Ayyoub
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2327-2334

Abstract

A non-standard romanization of Arabic script, known as Arbizi, is widely used in Arabic online and SMS/chat communities. However, since state-of-the-art tools and applications for Arabic NLP expects Arabic to be written in Arabic script, handling contents written in Arabizi requires a special attention either by building customized tools or by transliterating them into Arabic script. The latter approach is the more common one and this work presents two significant contributions in this direction. The first one is to collect and publicly release the first large-scale “Arabizi to Arabic script” parallel corpus focusing on the Jordanian dialect and consisting of more than 25 k pairs carefully created and inspected by native speakers to ensure highest quality. Second, we present Atar, an attention-based encoder-decoder model for Arabizi transliteration. Training and testing this model on our dataset yields impressive accuracy (79%) and BLEU score (88.49).
An internet of things based smart waste system Ali M. Jasim; H. H. Qasim; Ethar Habeeb Jasem; Raed Hasan Saihood
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2577-2585

Abstract

The importance of preserving the environment from waste and its pollution lies in many matters such as preserving people health, enhancing the aesthetic character of cites, attracting tourists, and protecting society from environmental disasters. The environmental wastes are the main dilemmas in our daily life and in the world at large. With the existence of modern technology, development and the field of the internet, many solutions have been undertaken to get rid these dilemmas. In this paper, a smart waste system based on internet of things (IoT) technique has been proposed using ESP-32 Wi-Fi microcontroller. This system can be adopted to avoid the accumulation of waste in the streets that distort the face of civilization, also to reduce the burden of workers and limit the workforce. The system is based on a multiple sensors in the garbage baskets, as they measure the waste level by using ultrasonic sensor, the moisture percent and temperature degree using DHT-22 sensor. The sensors data are processed by ESP32 microcontroller and displayed to both LCD screen using I2C protocol and mobile application using IoT cloud. System baskets automatically open their covers when the person approaches with a distance less or equal to 30 cm to throw garbage. Any approval waste basket is automatically discharged through an underground dump system using conveyor belt if the basket is full by 80% garbage and/or the basket moisture reaches to 40%.
Novel hybrid framework for image compression for supportive hardware design of boosting compression Premachand D. R.; U. Eranna
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp1985-1993

Abstract

Performing the image compression over the resource constrained hardware is quite a challenging task. Although, there has been various approaches being carried out towards image compression considering the hardware aspect of it, but still there are problems associated with the memory acceleration associated with the entire operation that downgrade the performance of the hardware device. Therefore, the proposed approach presents a cost effective image compression mechanism which offers lossless compression using a unique combination of the non-linear filtering, segmentation, contour detection, followed by the optimization. The compression mechanism adapts analytical approach for significant image compression. The execution of the compression mechanism yields faster response time, reduced mean square error, improved signal quality and significant compression ratio performance.

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