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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 28, No 1: October 2022" : 64 Documents clear
How to determinate water quality using an artificial intelligent model based on grey clustering? Alexi Delgado; Carlos López; Noe Jacinto; Mario Chungas; Laberiano Andrade-Arenas
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp450-459

Abstract

Water quality is an important topic for countries like Peru, where the mining sector is one of the main economic activities, so the study of its impact on water quality is also necessary to have a regular control of benefits and dangers. In this way, to achieve this objective, the chosen methodology was grey clustering, which is based on artificial intelligent theory. Specifically, the central point triangular whitening weight function better known as CTWF, which is an approach from grey clustering, was used. The case study was focused on the Mashcon and Chonta rivers, located in the province of Cajamarca, Peru, these rivers are directly affected by an open pit mine. The study was carried out taking into account thirteen monitoring points taken by National Water Authority (ANA). The results showed that all the points considered were classified as not contaminated, A1 category, this using the parameters of the Peruvian government. With these results, the mining company was able to demonstrate that they are taking the water quality into account and that they are making an effort to keep these rivers as healthy as possible.
Text mining and sentiment analysis of teacher performance satisfaction in the virtual learning environment Omar Chamorro-Atalaya; Dora Arce-Santillan; José Antonio Arévalo-Tuesta; Lilia Rodas-Camacho; Genaro Sandoval-Nizama; Rosa Valle-Chavez; Yadit Rocca-Carvajal
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp525-534

Abstract

Although it is true that artificial intelligence and data science have become key tools that contribute to the improvement of many processes, identifying patterns and contributing to decision making, however, there are environments in which they are not yet being using it relevantly and effectively. The objective of this study is to identify the relevant factors, based on the opinions expressed by the students through the social network Twitter regarding the perception of satisfaction with the teaching performance during the virtual learning environment. For which sentiment analysis and text mining are used under the Python programming language environment, through JupyterLab. As results, it was determined that a predominance of 57.27% of positive polarity, identifying that the relevant factors of student satisfaction with teaching performance, are related to the development of the teacher in the class sessions that contributes to the learning of the process control subject through the use of simulation tools such as simulink and tools linked to proportional integral derivative (PID) controllers; on the other hand, there is a percentage of negative polarity of 15.45% that belongs to the factors linked to the laboratory sessions in which graphic representation and block diagrams were used to explain the class session.
Implementation of a sensor node for monitoring and classification of physiological signals in an edge computing system Ricardo Yauri; Antero Castro; Rafael Espino; Segundo Gamarra
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp98-105

Abstract

We describe the design and development of sensor nodes, based on Edge computing technologies, for the processing and classification of events detected in physiological signals such as the electrocardiographic signal (ECG is the electrical signal of the heart), temperature, heart rate, and human movement. The edge device uses a 32-bit Tensilica microcontroller-based module with the ability to transmit data wirelessly using Wi-Fi. In addition, algorithms for classification and detection of movement patterns were implemented to be implemented in devices with limited resources and not only in high-performance computers. The Internet of Things and its application in smart environments can help non-intrusive monitoring of daily activities by implementing support vector machine (SVM is a machine learning algorithm) for implementation in embedded systems with low hardware resources. This paper shows experimental results obtained during the acquisition, transmission, and processing of physiological signals in a edge computing system and their visualization in a web application.
Predicting the value of sperm analysis using an electronic nose Raden Aa Koesoema Wijaya; Ahmad Kusumaatmaja; Dicky Moch Rizal
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp174-182

Abstract

Total motile sperm count and DNA fragmentation Index are two parameters in sperm analysis that have recently been used to determine the outcome of the management of cases of male infertility. Total Motile Sperm Count is one of the values considered better than the 2010 World Health Organization standard sperm analysis in terms of predictive value for the success of the spontaneous ongoing pregnancy rate. High DNA Fragmentation Index values were associated with lower pregnancy success and an increased risk of low fertilization rate or total fertilization failure. In this study, we developed a method to classify sperm analysis based on total motility sperm count and DNA Fragmentation Index values by using an electronic nose. In the total motility sperm count (TMSC) study, we use four algorithms with the result of accuracy values 95% and in the DNA fragmentation Index study, we get a fairly good accuracy value for two algorithms with the accuracy values 70%.
Advanced control with extended Kalman filter and disturbance observer Tidjani Naoual; Ounnas Djamel; Guessoum Abderrezak; Ramdani Messaoud
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp124-136

Abstract

This paper describes a novel fuzzy tracking control for permanent magnet synchronous motors (PMSM) using an extended Kalman filter (EKF) and disturbance observer (DO). The goal is to create a robust controller able to drive the system’s states to track a virtual reference model and provide a low disturbance effect on the synchronous machine. First, the PMSM is represented using a fuzzy model Takagi-Sugeno (T-S) attended by the load torque variation. Next, To simplify the construction of a virtual reference model and nonlinear tracking control, a fuzzy tracking control based on virtual desired variables (VDVs) is proposed. Using this concept, a two-stage design procedure is developed: i) determine the VDVs using the desired output and the load torque, which can be estimated using DO and EKF and ii) calculate the fuzzy controller gains by solving linear matrix inequalities (LMIs). The efficiency of the suggested strategy is eventually shown through simulation results
Analytic survey on the challenges of Moroccan students in higher education institutions face to distance learning Kaouni Mouna; Lakrami Fatima; Labouidya Ouidad
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp284-296

Abstract

This research presents an investigation of the problems faced by Moroccan higher education students after the face-to-face learning was reinstated following the COVID-19 pandemic crisis. The proposed methodology is based on an exploratory descriptive analysis through a survey that involved students from different higher education institutions and residing in various regions of Morocco. The collected results revealed that students face pedagogical, technical and organizational constraints that prevent them from making a successful transition to distance learning, even if only partially. Indeed, many students are not motivated by the use of information and communication technology (ICT). The study finally provides recommendations for understanding and overcoming these problems.
Key-cipher policy attribute-based encryption mechanism for access control of multimedia data in cloud storages Kavyasri Madakaripura Nagaraju; Ramesh Boraiah
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp545-550

Abstract

Cloud technology is advancing at a rapid pace. Many applications and multimedia data are hosted in the cloud, Security, confidentiality, and efficiency are the key drawbacks of cloud computing. There are a variety of access control systems on the market to secure the data and applications on the cloud. But key generation time is a major flaw both in multi-authority and single authority systems. Cipher policy attribute-based encryption (CPABE) is one of many cryptographic algorithms available for ensuring user confidentiality which provides fine-grained access control. It also addreses a number of issues related attribute revocation, key generation time, and issues in handling a large number of attributes. We present a mechanism called key-cipher-policy-based ABE (KCP) in this article, which is a hybrid approach and combines CP-ABE and KP ABE approaches which result in handling a wide range of attributes, an efficient key generation process, and addresses challenges in attribute revocation.
Single board re-spin for testing bridge transducer products Frances D. de la Rama; Marwin L. Tocama; Glenn N. Ortiz; Mark Joseph B. Enojas
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp88-97

Abstract

Integrated circuit (IC) testing involves equipment and product interface board setup. Complex interfaces and obsolete components are some of the factors affecting the board functionality which results in manufacturing downtime. The legacy boards must be simplified so that it needs advanced tools for the lay-out and designing of test boards. This study proposes a solution for board functionality issues by re-spinning the legacy two-board interface into a single board interface. It converts the standard use of boards and standard contacting to single board interface (SBI) and plunge-to-board (PTB) contacting. As a result, the setup time is improved, minimizing board and system repair due to mismatch and contact issues. The board endorsement for contact issues were trimmed from 82 to 46 counts. Other board related issues are decreased by 60% based on the analysis of the correlation in the processes. Additionally, mismatches, which are system issues, are lessened which promotes fixtures maintainability.
A new design of a printed reconfigurable coplanar multiband antenna Fatima Ouberri; Abdelali Tajmouati; Jamal Zbitou; Mohamed Latrach
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp234-240

Abstract

The demand for multi-functional components has increased enormously in recent years. Advances in integrated technology have enabled researchers to adapt diverse applications operating at different frequencies in a single wireless device. A compact broadband coplanar waveguide (CPW)-fed square aperture monopole antenna with inverted-L grounded strips is first described. The proposed antenna has a small size of 60×60×0.74 mm3 and has excellent performances which include a good input impedance matching with a much wider operating bandwidth, an excitation of the circular polarization at 2.45 GHz, and a stable omnidirectional radiation pattern. Then, a multiband reconfigurable antenna design is developed from this structure. The frequency reconfigurable approach is obtained using a varactor diode. In this work, it is observed that frequency diversity can be obtained by varying the value of the capacity by leaving the dimensions antenna unchanged. The results are given using CST microwave studio and show good performances in terms of return loss, bandwidth, gain and radiation pattern and demonstrate that the proposed antenna offers a reconfigurable solution for multi-standard wireless communication applications.
Deep learning application for real-time prediction of COVID-19 outbreak with susceptible-infected-recovered-deceased model Hoang-Sy Nguyen; Thu Ngan Phan Thi; Cong-Danh Huynh
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp567-576

Abstract

Due to the complex nature of a pandemic such as COVID-19, forecasting how it would behave is difficult, but it is indeed of utmost necessity. Furthermore, adapting predictive models to different data sets obtained from different countries and areas is necessary, as it can provide a wider view of the global pandemic situation and more information on how models can be improved. Therefore, we combine here the long-short-term memory (LSTM) model and the traditional susceptible-infected-recovered-deceased (SIRD) model for the COVID-19 prediction task in Ho Chi Minh City, Vietnam. In particular, LSTM shows its strength in processing and making accurate numerical predictions on a large set of historical input. Following the SIRD model, the whole population is divided into 4 states (S), (I), (R), and (D), and the changes from one state to another are governed by a parameter set. By assessing the numerical output and the corresponding parameter set, we could reveal more insights about the root causes of the changes. The predictive model updates every 10 days to produce an output that is closest to reality. In general, such a combination delivers transparent, accurate, and up-to-date predictions for human experts, which is important for research on COVID-19.

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