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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 9,174 Documents
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Moodle platform and Zoom videoconference: learning skills in the virtual modality Laberiano Andrade-Arenas; William Wilfredo Reyes Perez; Cesar Augusto Yactayo Arias
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp337-349

Abstract

In Peruvian Universities, most of the Moodle platforms and the Zoom videoconference were used in virtual teaching-learning. The teachers and students of the University of Sciences and Humanities, which is the object of study, used these tools in the class session. Moodle and Zoom complement each other for virtual classes during the pandemic time. The objective of the research is the influence of Zoom and Moodle on learning skills. The methodological design of the research has correlational scope, quantitative, non-experimental approach of cross-section. A survey was conducted of 95 students from the first cycles of the university. The instrument was validated by expert judgments with 86.3% approval. In addition, reliability was performed with Cronbach's Alpha, obtaining the value of 0.875. A p-value of 0000 was obtained as a result and the degree of correlation between Moodle and learning skills was 0.438** and Zoom with learning skills was 0.519**; determining in this way that there is a moderate positive significant correlation. It is concluded that the development of learning skills that correspond to digital skills, the communicative and cognitive part is due to the use of the Moodle platform and the Zoom videoconference in the learning sessions.
Development of renewable energy system for low power underwater devices Sahana Salagare; Pattipati Naga Sudha; Karthik Palani
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp68-76

Abstract

Underwater sensor networks (UWSNs) are an emerging field in the research area as they have potential applications starting from pollution monitoring to defense and ocean exploration. Ocean monitoring is of great importance in marine scientific research. However, battery-operated devices utilized in such systems have limited power and maintenance is difficult. So, devices used underwater suffer from many research challenges and energy issues. Apart from all the problems, harvesting energy underwater is the main limiting factor. Nonrenewable energies come from sources that may not be replenished in our lifetime. Hence, it is very much essential to use renewable energy sources. Ocean has an unlimited amount of energy like wind energy, solar power, and tidal energy. Obtaining sufficient energy is sort of difficult since devices are underwater. Researchers are continuously working on it. Water energy is quite environmentally friendly, and it is a sustainable solution for a secure energy system. This paper implements a renewable energy system using piezoelectric (PZT) sensor, which generates sufficient power for lowpower underwater devices by employing two stage amplifier circuits. Experimental outcome shows the proposed energy harvesting system can generate a maximum voltage of 10.6 V and current of 10.1 mA which is sufficient to run low power underwater device.
Proposed enhanced link failure rerouting mechanism for software-defined exchange point Abdijalil Abdullahi; Selvakumar Manickam; Shankar Karuppayah; Mahmood A. Al-Shareeda
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp259-270

Abstract

Internet eXchange point (IXP) is a way to optimize network bandwidth. It enables a platform in the different providers like internet service providers (ISPs) and content delivery providers (CDNs) to share their traffic through a common point. A software defined exchange point (SDX) is an IXP comprising of a programmable deployed software defined network (SDN) switching fabric to enhance the management of their services, but they met the performance issues. The previous studies proposed various mechanisms and frameworks that tackled with these issues, but they don’t overcome overall challenges like link failure recovery for multi-hop-based SDX particularly packet processing delay and switch memory overhead. To cope with these issues, this paper proposed an enhanced link failure rerouting (ELFR) mechanism for multi-hop-based SDX. The objective of the proposed ELFR mechanism is to reduce the delay of packet processing to recover the link failure quickly and improve the path computation while ensuring the switch storage overhead. The present paper is an effort to retrospect and analyze the critical review of existing work for SDX. Furthermore, this paper provides a background of SDX, its components and its applications. Finally, this paper presents and compares the expected results of ELFR mechanism and related work.
Skin disease detection employing transfer learning approacha fine-tune visual geometry group-19 Md. Al Habib Islam; Sarkar Mohammad Shahriyar; Mohammad Jahangir Alam; Mushfiqur Rahman; Md Rahmatul Kabir Rasel Sarker
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp321-328

Abstract

Your skin may become damaged by skin diseases and conditions. These illnesses can cause skin changes such as rashes, inflammation, itching, and other skin changes. While some skin conditions may run in families, others may result from a person’s way of life. Skin conditions may be treated with pills, creams, ointments, changes in diet, and lifestyle modifications. Deep learning algorithms for computer vision applications have advanced quickly thanks to a significant amount of data for training the model and advancements in evaluation of proposed that can provide stronger simplifications. Undesired skin disease regions are eliminated, quality is raised, and the disease is tinted by discarding artifacts, decrease noise, and improving the image. Three augmentation techniques have raised the quantity of skin disease images. The five transfer learning models and various convolutional neural network (CNN) architectures analyzed the augmentation dataset. Visual geometry group-19 (VGG-19) offers the highest level of accuracy. Following the segmentation of the dermoscopic images, the affected skin cells' features are extracted using a feature extraction technique. The retrieved features are stratified using a CNN classifier, that is focused in deep learning. The best outcomes were obtained using the hyper-tuned VGG-19, which had test and validation accuracy of 99.21% and 99.25%, including both.
Five-level cascaded H-bridge inverter for renewable energy applications Md. Hazrat Ali; Emtiaz Ahmed Mainul; Tawfikur Rahman; Md. Shabuj Hossen; Md. Kamrul Alam Khan; Mohammad Obaidur Rahmann
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp44-53

Abstract

This paper presents a five-level inverter based on the phase-disposition pulse width modulation (PD-PWM) technique for renewable energy applications. The conventional cascaded H-bridge (CHB) five-level inverter structure is reproduced, and an LC filter is designed to get optimum results from the inverter output. Two batteries are used as renewable energy sources to investigate the performance of the designed inverter. The system can provide 220 volts and 50 Hz AC supply with a 6.9 kW power supply to the load/grid. The designed output is compared with filter and without filter circuit. It provides sinusoidal voltage and current output with a very low total harmonic distortion (THD) of 2.75% which is compliant with IEEE 519 standards. MATLAB/Simulink software tool is used for the entire design. The inverter’s output is graphically represented, and discussed various parameters like switching frequency, THD, modulation index, and rated voltage.
A community scale hybrid renewable energy system for sustainable power supply during load shedding Muhammad Paend Bakht; Mohd Norzali Haji Mohd; Shahrin Md. Ayob; Nuzhat Khan; Abba Lawan Bukar
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp33-43

Abstract

Load shedding is an operating condition in which the electrical grid is temporarily disconnected from the load. The objective is to minimize the gap between available generation capacity and load demand while maintaining an equitable supply for all consumers. Load shedding is a prominent problem for many developing countries. To address this issue, this paper explores the potential of a hybrid energy system (HES) to provide uninterrupted power supply at the distribution feeder despite load shedding from electrical grid. The proposed HES in this work combines photovoltaic (PV) array, battery storage system (BSS) and diesel generator (DG). The HES is equipped with energy management scheme (EMS) that ensures continuous power supply, improves energy efficiency, and minimizes the electricity cost. To accomplish these tasks, the EMS operates the system in one of three modes: grid mode, renewable energy source mode and the diesel generator mode. Besides, the proposed methodology allows injecting surplus PV energy into the grid, thus maximizing PV utilization and improving power system’s reliability. The results of this study will assist policymakers to determine the prospect of renewable based hybrid system to supply sustainable power and eliminate the energy problems in the power deficit countries.
Classifying toxicity in the Arabic Moroccan dialect on Instagram: a machine and deep learning approach Rabia Rachidi; Mohamed Amine Ouassil; Mouaad Errami; Bouchaib Cherradi; Soufiane Hamida; Hassan Silkan
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp588-598

Abstract

People crave interaction and connection with other people. Therefore, social media became the center of society’s life. Among the brightest social media platforms nowadays with a massive number of daily users there is Instagram, which is due to its distinctive features. The excessive revealing of personal life has put users in the spots of getting bullied and harassed and getting toxic revues from other users. Numerous studies have targeted social media to fight its harmful side effects. Nevertheless, most of the datasets that were already available were in English, the Arabic Moroccan dialect ones were not. In this work, the Arabic Moroccan dialect dataset has been extracted from the Instagram platform. Furthermore, feature extraction techniques have been applied to the collected dataset to increase classification accuracy. Afterward, we developed models using machine learning and deep learning algorithms to detect and classify toxicity. For the models’ evaluation, we have used the most used metrics: accuracy, precision, F1-score, and recall. The experimental results gave modest scores of around 70% to 83%. These results imply that the models need improvement due to the lack of available datasets and the preprocessing libraries to handle the Moroccan dialect of Arabic.
Genetic algorithm with immigration strategy to solve the fixed charge transportation problem Ahmed Lahjouji El Idrissi; Chakir Tajani
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp313-320

Abstract

This paper is about improving the performance of genetic algorithm (GA) to solve the fixed-charge transportation problem (FCTP). Several approaches have been developed, based on adaptation and improvement of genetic operators. We propose a new genetic algorithm adopting an immigration strategy to maintain the diversity in the population and then overcome the stagnation of the values of the objective function. Thereby, we applied two types of immigration, random immigration and memory-based immigration. The numerical results obtained with several standard instances of the FCTP problem demonstrate the effectiveness of these strategies in improving the performance of the GA. Especilly, for the second strategy.
Corona destroyer based ultra violet sanitizing robot Kadry Ali Ezzat; Lamia Nabil Omran; Ahmed Adel Ismail; Ahmed Ibrahim Bahgat El Seddawy
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp108-114

Abstract

Every country in the globe has been profoundly affected by the coronavirus epidemic, and these countries are struggling with how to clean the affected areas quickly and effectively. This project aims to contribute to the fight against the spread of the coronavirus by quickly, safely, and effectively cleaning medical clinics. Regular cleaning and disinfection might reassure people and increase their confidence in the lessened risk of the spread of communicable diseases. Robots that use ultraviolet C (UVC) sanitizers can quickly and effectively clean the clinic rooms. In addition to cleaning patient seating areas, clinical equipment, restrooms, and above controls. The use of UVC technology effectively eliminates airborne germs in medical clinics. The results of UVC disinfection performance indicated a 92% reduction in the total bacterial count (TBC) at 0.5 metres from the robot after 8 minutes of UVC irradiation.
An innovative smart glass for blind people using artificial intelligence Shantappa G. Gollagi; Kalyan D. Bamane; Dipali Manish Patil; Sanjay B. Ankali; Bahubali M. Akiwate
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp433-439

Abstract

The "Smart Glasses" are made to make it easier for blind persons to read and decipher written English-language content. A blind people find it exceedingly challenging to travel alone, and they run the danger of getting lost and regular sticks won't allow the person to go around independently in public without things growing worse. The objective of our work is to help blind people communicate more easily by developing a smart assistive glasses using artificial intelligence. The function of the glasses is to read out any text picture as audio text, which can then be heard through a headset attached to the spectacles. OpenCV, optical character recognition and efficient and accurate scene text (EAST) detector were used to identify the text in the image; ultrasonic sensor in the glasses is used to calculate the distance to snap a clear picture. The motion sensor directs the blind to the lecture halls, classrooms, and laboratory locations using an radio frequency identification reader. The results shows that combination of optical character recognizer and EAST detector produced a fairly accurate result, demonstrating the potential of the glasses to recognize the text. Currently, the language supported by the glasses is English, and the distance covered is 40 to 150 cm.

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