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Bulletin of Electrical Engineering and Informatics
Published by Universitas Ahmad Dahlan
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 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. The journal publishes original papers in the field of electrical, computer and informatics engineering.
Arjuna Subject : -
Articles 2,901 Documents
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Power quality disturbances classification using complex wavelet phasor space reconstruction and fully connected feed forward neural network R. Likhitha; A. Manjunatha
Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i6.3207

Abstract

Power quality disturbances (PQD) degrades the quality of power. Detection of these PQDs in real time using smart systems connected to the power grid is a challenge due to the integration of energy generation units and electronic devices. Deep learning methods have shown advantages for PQD classification accurately. PQD events are non-stationary and occur at discrete events. Pre-processing of power signal using dual tree complex wavelet transform in localizing the disturbances according to time-frequency-phase information improves classification accuracy.Phase space reconstruction of complex wavelet sub bands to 2D data and use of fully connected feed forward neural network improves classification accuracy. In this work, a combination of DTCWT-PSR and FC-FFNN is used to classify different complex PSDs accurately.The proposed algorithm is evaluated for its performance considering different network configurations and the most optimum structure is developed. The classification accuracy is demonstrated to be 99.71% for complex PQDs and is suitable for real time activity with reduced complexity.
An approach of re-organizing input dataset to enhance the quality of emotion recognition using the bio-signals dataset of MIT Van-Dung Pham; Thanh-Long Cung
Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i6.3248

Abstract

The purpose of this paper is to propose an approach of re-organizing input data to recognize emotion based on short signal segments and increase the quality of emotional recognition using physiological signals. MIT's long physiological signal set was divided into two new datasets, with shorter and overlapped segments. Three different classification methods (support vector machine, random forest, and multilayer perceptron) were implemented to identify eight emotional states based on statistical features of each segment in these two datasets. By re-organizing the input dataset, the quality of recognition results was enhanced. The random forest shows the best classification result among three implemented classification methods, with an accuracy of 97.72% for eight emotional states, on the overlapped dataset. This approach shows that, by re-organizing the input dataset, the high accuracy of recognition results can be achieved without the use of EEG and ECG signals.
Development of 3D convolutional neural network to recognize human activities using moderate computation machine Malik A. Alsaedi; Abdulrahman Saeed Mohialdeen; Baraa Munqith Albaker
Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i6.2802

Abstract

Human activity recognition (HAR) is recently used in numerous applications including smart homes to monitor human behavior, automate homes according to human activities, entertainment, falling detection, violence detection, and people care. Vision-based recognition is the most powerful method widely used in HAR systems implementation due to its characteristics in recognizing complex human activities. This paper addresses the design of a 3D convolutional neural network (3D-CNN) model that can be used in smart homes to identify several numbers of activities. The model is trained using KTH dataset that contains activities like (walking, running, jogging, handwaving handclapping, boxing). Despite the challenges of this method due to the effectiveness of the lamination, background variation, and human body variety, the proposed model reached an accuracy of 93.33%. The model was implemented, trained and tested using moderate computation machine and the results show that the proposal was successfully capable to recognize human activities with reasonable computations.
Frequency based edge-texture feature using Otsu’s based enhanced local ternary pattern technique for digital image splicing detection Vikas Srivastava; Sanjay Kumar Yadav
Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i6.3188

Abstract

Sharing information through images is a trend nowadays. Advancements in the technology and user-friendly image editing tool make easy to edit the image and spread fake news through different social networking platforms. Forged image has been generated through an advanced image editing tool, so it is very challenging for image forensics to detect the micro discrepancy which distorted the micro pattern. This paper proposes an image forensic detection technique, which implies multi-level discrete wavelet transform to implement digital image filtering. Canny edge detection technique is implemented to detect the edge of the image to implement Otsu’s based enhanced local ternary pattern (OELTP), which can detect forgery-related artifact. DWT is implemented over Cb and Cr components of the image and using edge texture to improve the Otsu global threshold, which is used to extract features using ELTP technique. Support vector machine (SVM) is used for classification to find the image is forged or not. The performance of the work evaluated on three different open available data sets CASIA v1, CASIA v2, and Columbia. Our proposed work gives better results with some of the previous states of the work in terms of detection accuracy.
Customized moodle-based learning management system for socially disadvantaged schools Ika Qutsiati Utami; Muhammad Noor Fakhruzzaman; Indah Fahmiyah; Annaura Nabilla Masduki; Ilham Ahmad Kamil
Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i6.3202

Abstract

This study aims to develop Moodle-based LMS with customized learning content and modified user interface to facilitate pedagogical processes during covid-19 pandemic and investigate how teachers of socially disadvantaged schools perceived usability and technology acceptance. Co-design process was conducted with two activities: 1) need assessment phase using an online survey and interview session with the teachers and 2) the development phase of the LMS. The system was evaluated by 30 teachers from socially disadvantaged schools for relevance to their distance learning activities. We employed computer software usability questionnaire (CSUQ) to measure perceived usability and the technology acceptance model (TAM) with insertion of 3 original variables (i.e., perceived usefulness, perceived ease of use, and intention to use) and 5 external variables (i.e., attitude toward the system, perceived interaction, self-efficacy, user interface design, and course design). The average CSUQ rating exceeded 5.0 of 7 point-scale, indicated that teachers agreed that the information quality, interaction quality, and user interface quality were clear and easy to understand. TAM results concluded that the LMS design was judged to be usable, interactive, and well-developed. Teachers reported an effective user interface that allows effective teaching operations and lead to the system adoption in immediate time.
Noise resistance territorial intensity-based optical flow using inverse confidential technique on bilateral function Darun Kesrarat; Vorapoj Patanavijit
Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i6.3243

Abstract

This paper presents the use of the inverse confidential technique on bilateral function with the territorial intensity-based optical flow to prove the effectiveness in noise resistance environment. In general, the image’s motion vector is coded by the technique called optical flow where the sequences of the image are used to determine the motion vector. But, the accuracy rate of the motion vector is reduced when the source of image sequences is interfered by noises. This work proved that the inverse confidential technique on bilateral function can increase the percentage of accuracy in the motion vector determination by the territorial intensity-based optical flow under the noisy environment. We performed the testing with several kinds of non-Gaussian noises at several patterns of standard image sequences by analyzing the result of the motion vector in a form of the error vector magnitude (EVM) and compared it with several noise resistance techniques in territorial intensity-based optical flow method.
Fabrication and characterization of printed zinc batteries M. A. Nazri; Anis Nurashikin Nordin; L. M. Lim; M. Y. Tura Ali; I. Mansor; Muhammad Irsyad Suhaimi; R. Othman; S. R. Meskon; Z. Samsudin
Bulletin of Electrical Engineering and Informatics Vol 10, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i3.2858

Abstract

Zinc batteries are a more sustainable alternative to lithium-ion batteries due to its components being highly recyclable. With the improvements in the screen printing technology, high quality devices can be printed with at high throughput and precision at a lower cost compared to those manufactured using lithographic techniques. In this paper we describe the fabrication and characterization of printed zinc batteries. Different binder materials such as polyvinyl pyrrolidone (PVP) and polyvinyl butyral (PVB), were used to fabricate the electrodes. The electrodes were first evaluated using three-electrode cyclic voltammetry, x-ray diffraction (XRD), and scanning electron microscopy before being fully assembled and tested using charge-discharge test and two-electrode cyclic voltammetry. The results show that the printed ZnO electrode with PVB as binder performed better than PVP-based ZnO. The XRD data prove that the electro-active materials were successfully transferred to the sample. However, based on the evaluation, the results show that the cathode electrode was dominated by the silver instead of Ni(OH)2, which leads the sample to behave like a silver-zinc battery instead of a nickel-zinc battery. Nevertheless, the printed zinc battery electrodes were successfully evaluated, and more current collector materials for cathode should be explored for printed nickel-zinc batteries.
Personal air-conditioning system using evapolar as heat waste management Nor Azazi Ngatiman; Abdul Qaiyum Mohd Shariff; Tole Sutikno; Suparje Wardiyono; Mustafa Manap; Mohd Hatta Jopri
Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i6.3283

Abstract

Air-conditioning system that uses compressor-based initiate more energy and affects bill rate. As a result, an application of the Peltier impact module, a portable air-conditioning system is introduced to compensate user convenience by lowering sensible and latent heat inside the office area. Thermoelectric Peltier module is a thermoelectric semiconductor that offers cooling and hot plate once the plate is supplied by electric. The result reduces the cost, power consumption, and give thermal comfort in a dedicated space. The advantage of the study is the ability to cost deduction due to low power consumption and green technology devices factor because without refrigerant that harms the environment. Redesign the product with Evapolar as heat waste management affect the performance and need to be validated. The development stage of this product is better compared to a previous product which offers small scale, light, and portable. This product focuses on the office room, which gives a good feeling to users. This product uses air to remove the heat waste and the result indicates Evapolar is fit enough in dissipating heat. Finally, the performance of this system developed demonstrated that it can attain thermal comfort level.
E-commerce online review for detecting influencing factors users perception Irvan Krisna Arsad; Djoko Budiyanto Setyohadi; Paulus Mudjihartono
Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i6.3182

Abstract

To date, online shopping using e-commerce services becomes a trend. The emergence of e-commerce truly helps people to shop more effectively and efficiently. However, there are still some problems encountered in e-commerce, especially from the user perspective. This research aims to explore user review data, particularly on factors that influence user perception of e-commerce applications, classify, and identify potential solutions to finding problems in e-commerce applications. Data is grabbed using web scraping techniques and classified using proper machine learning, i.e., support vector machine (SVM). Text associations and fishbone analysis are performed based on the classified user review data. The results of this study show that the user satisfaction problem can be captured. Furthermore, various services that should be provided as a potential solution to experienced customers' problems or application users' perception problems can be generated. A detailed discussion of these findings is available in this article.
A cascaded converter using hybrid cells and H-bridge structure Satya Subrahmanya Ajay Dangeti; Chaitanya Kishore Patnaik Sekharamantry; Venkata Kowshik Bayanti; B. A. Raju Ch; KVS Ramachandra Murthy; Abhilash Tirupathi
Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i6.2783

Abstract

This paper introduces a cascaded converter structure using hybrid two-level cells to form a single-phase seven-level inverter. Compared to various conventional and existing multilevel (MLI) topologies, this topology requires a lower number of devices. It uses several DC sources integrated in two-stage cells to provide the required voltage. In this topology, the DC-link condensers are not necessary. The modes of operation and modulation of the structure proposed are described in depth. Finally, in the MATLAB/Simulink platform the new topology is evaluated and the results reported. 

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