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Bulletin of Electrical Engineering and Informatics
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Bulletin of Electrical Engineering and Informatics ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication, computer engineering, computer science, information technology and informatics from the global world. The journal publishes original papers in the field of electrical (power), electronics, instrumentation & control, telecommunication and computer engineering; computer science; information technology and informatics. Authors must strictly follow the guide for authors. Please read these instructions carefully and follow them strictly. In this way you will help ensure that the review and publication of your paper is as efficient and quick as possible. The editors reserve the right to reject manuscripts that are not in accordance with these instructions.
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Articles 539 Documents
Local Entropy and Standard Deviation for Facial Expressions Recognition in Thermal Imaging Yomna M. Elbarawy; Rania S. El-Sayed; Neveen I. Ghali
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (468.654 KB) | DOI: 10.11591/eei.v7i4.1230

Abstract

Emotional reactions are the best way to express human attitude and thermal imaging mainly used to utilize detection of temperature variations as in detecting spatial and temporal variation in the water status of grapevine. By merging the two facts this paper presents the Discrete Cosine Transform (DCT) with Local Entropy (LE) and Local Standard Deviation (LSD) features as an efficient filters for investigating human emotional state in thermal images. Two well known classifiers, K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) were combined with the earlier features and applied over a database with variant illumination, as well as occlusion by glasses and poses to generate a recognition model of facial expressions in thermal images. KNN based on DCT and LE gives the best accuracy compared with other classifier and features results.
Improving Classification Accuracy Using Clustering Technique Norsyela Muhammad Noor Mathivanan; Nor Azura Md.Ghani; Roziah Mohd Janor
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (335.471 KB) | DOI: 10.11591/eei.v7i3.1272

Abstract

Product classification is the key issue in e-commerce domains. Many products are released to the market rapidly and to select the correct category in taxonomy for each product has become a challenging task. The application of classification model is useful to precisely classify the products. The study proposed a method to apply clustering prior to classification. This study has used a large-scale real-world data set to identify the efficiency of clustering technique to improve the classification model. The conventional text classification procedures are used in the study such as preprocessing, feature extraction and feature selection before applying the clustering technique. Results show that clustering technique improves the accuracy of the classification model. The best classification model for all three approaches which are classification model only, classification with hierarchical clustering and classification with K-means clustering is K-Nearest Neighbor (KNN) model. Even though the accuracy of the KNN models are the same across different approaches but the KNN model with K-means clustering had the shortest time of execution. Hence, applying K-means clustering prior to KNN model helps in reducing the computation time.
Sabah Traditional Chinese Medicine Database Aslina Baharum; Neoh Yee Jin; Shaliza Hayati A. Wahab; Mohd Helmy Abd Wahab; Radzi Ambar; Nurul Hidayah Mat Zain
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (466.489 KB) | DOI: 10.11591/eei.v7i3.1273

Abstract

As technology grows, people tend to use or apply anything digitalized instead of printed, especially for references. This is because the printed form references are not easy to find. Even if the references are found successfully, it has already cost a lot of time, money, energy, etc. At the same time, people also put more emphasize on health issues. They are beginning to be more alert in fields that they have ignored before, such as traditional medicine and Chinese medicine. Based on these two points, it can be said that the effort of transforming Traditional Chinese Medicine (TCM) from printed based reference into online reference as a database is a public beneficial effort. There are a lot of online TCM database outside of Malaysia, especially from the People’s Republic of China, Hong Kong, and Taiwan. Those herbal remedies from overseas are somewhat different from the herbal remedies in Malaysia due to the habits and occurrences of the herbs. Through this project, it is hoped that this database will help the local people to discover and identify the herbs that they could find in the surrounding area. The objectives of this project are to identify the validity of the information of the Sabah TCM using mixed method, to develop the Sabah TCM database, and finally to evaluate the usability of the database designed using meCUE. The methodology used was 4D Appreciative Inquiry Model, which included discovery, dream, design, and destiny phases. The advantage of this model was to take a positive core to make any changes instead of finding the weaknesses of the project. Hopefully through the developed database, local Sabahan can take the advantage in identifying the proper usage of existing herbs in their surroundings.
Estimation of Photovoltaic Module Parameters based on Total Error Minimization of I-V Characteristic M. N. Abdullah; M. Z. Hussin; S. A. Jumaat; N. H. Radzi; Lilik J. Awalin
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (597.456 KB) | DOI: 10.11591/eei.v7i3.1274

Abstract

Mathematical Modelling of photovoltaic (PV) modules is important for simulation and performance analysis of PV system. Therefore, an accurate parameters estimation is necessary. Single-diode and two-diode model are widely used to model the PV system. However, it required to determine several parameters such as series and shunt resistances that not provided in datasheet.  The main goal of PV modelling technique is to obtain the accurate parameters to ensure the I-V characteristic is closed to the manufacturer datasheet. Previously, the maximum power error of calculated and datasheet value are considered as objective to be minimized for both models. This paper proposes the PV parameter estimation model based minimizing the total error of open circuit voltage (VOC), short circuit current (ISC) and maximum power (PMAX) where all these parameters are provided by the manufacturer. The performance of single-diode and two-diode models are tested on different type of PV modules using MATLAB. It found that the two-diode model obtained accurate parameters with smaller error compared to single-diode model. However, the simulation time is slightly higher than single-diode model due extra calculation required.
GA-based Optimisation of a LiDAR Feedback Autonomous Mobile Robot Navigation System Siti Nurhafizah Anual; Mohd Faisal Ibrahim; Nurhana Ibrahim; Aini Hussain; Mohd Marzuki Mustafa; Aqilah Baseri Huddin; Fazida Hanim Hashim
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (385.649 KB) | DOI: 10.11591/eei.v7i3.1275

Abstract

Autonomous mobile robots require an efficient navigation system in order to navigate from one location to another location fast and safe without hitting static or dynamic obstacles. A light-detection-and-ranging (LiDAR) based autonomous robot navigation is a multi-component navigation system consists of various parameters to be configured. With such structure and sometimes involving conflicting parameters, the process of determining the best configuration for the system is a non-trivial task. This work presents an optimisation method using Genetic algorithm (GA) to configure such navigation system with tuned parameters automatically. The proposed method can optimise parameters of a few components in a navigation system concurrently. The representation of chromosome and fitness function of GA for this specific robotic problem are discussed. The experimental results from simulation and real hardware show that the optimised navigation system outperforms a manually-tuned navigation system of an indoor mobile robot in terms of navigation time.
Whale Optimization Algorithm Based Technique for Distributed Generation Installation in Distribution System Mohd Nurulhady Morshidi; Ismail Musirin; Siti Rafidah Abdul Rahim; Mohd Rafi Adzman; Mohamad Hatta Hussain
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (856.127 KB) | DOI: 10.11591/eei.v7i3.1276

Abstract

This paper presents Whale Optimization Algorithm (WOA) Based Technique for Distributed Generation Installation in Transmission System. In this study, WOA optimization engine is developed for the installation of Distributed Generation (DG). Prior to the optimization process, a pre-developed voltage stability index termed Fast Voltage Stability Index (FVSI) was used as an indicator to identify the location for the DG to be installed in the system. Meanwhile, for sizing the DG WOA is employed to identify the optimal sizing. By installing DG in the transmission system, voltage stability and voltage profile can be improved, while power losses can be minimized. The proposed algorithm was tested on 30-bus radial distribution network. Results obtained from the EP were compared with firefly algorithm (FA); indicating better results. This highlights the strength of WOA over FA in terms of minimizing total losses.
A Comparative Study for Different Sizing of Solar PV System under Net Energy Metering Scheme at University Buildings T. M. N. T. Mansur; N. H. Baharudin; R. Ali
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (441.678 KB) | DOI: 10.11591/eei.v7i3.1277

Abstract

Malaysia has moved forward by promoting the use of renewable energy such as solar PV to the public to reduce dependency on fossil fuel-based energy resources. Due to the concern on high electricity bill, Universiti Malaysia Perlis (UniMAP) is keen to install solar PV system as an initiative for energy saving program to its buildings. The objective of this paper is to technically and economically evaluate the different sizing of solar PV system for university buildings under the Net Energy Metering (NEM) scheme. The study involves gathering of solar energy resource information, daily load profile of the buildings, sizing PV array together with grid-connected inverters and the simulation of the designed system using PVsyst software. Based on the results obtained, the amount of solar energy generated and used by the load per year is between 5.10% and 20.20% from the total annual load demand. Almost all solar energy generated from the system will be self-consumed by the loads. In terms of profit gained, the university could reduce its electricity bill approximately between a quarter to one million ringgit per annum depending on the sizing capacity. Beneficially, the university could contribute to the environmental conservation by avoiding up to 2,000 tons of CO2 emission per year.
Dynamic Economic Dispatch Assessment Using Particle Swarm Optimization Technique Muhammad Murtadha Othman; Mohd Affendi Ismail Salim; Ismail Musirin; Nur Ashida Salim; Mohammad Lutfi Othman
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (478.557 KB) | DOI: 10.11591/eei.v7i3.1278

Abstract

This paper presents the application of particle swarm optimization (PSO) technique for solving the dynamic economic dispatch (DED) problem. The DED is one of the main functions in power system planning in order to obtain optimum power system operation and control. It determines the optimal operation of generating units at every predicted load demands over a certain period of time. The optimum operation of generating units is obtained by referring to the minimum total generation cost while the system is operating within its limits. The DED based PSO technique is tested on a 9-bus system containing of three generator bus, six load bus and twelve transmission lines.
Evaluation of Support Vector Machine and Decision Tree for Emotion Recognition of Malay Folklores Mastura Md Saad; Nursuriati Jamil; Raseeda Hamzah
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (599.337 KB) | DOI: 10.11591/eei.v7i3.1279

Abstract

In this paper, the performance of Support Vector Machine (SVM) and Decision Tree (DT) in classifying emotions from Malay folklores is presented. This work is the continuation of our storytelling speech synthesis work to add emotions for a more natural storytelling. A total of 100 documents from children short stories are collected and used as the datasets of the text-based emotion recognition experiment. Term Frequency-Inverse Document Frequency (TF-IDF) is extracted from the text documents and classified using SVM and DT. Four types of common emotions, which are happy, angry, fearful and sad are classified using the two classifiers. Results showed that DT outperformed SVM by more than 22.2% accuracy rate. However, the overall emotion recognition is only at moderate rate suggesting an improvement is needed in future work. The accuracy of the emotion recognition should be improved in future studies by using semantic feature extractors or by incorporating deep learning for classification.
Design and implementation of microstrip rotman lens for ISM band applications Mohammed K. Al-Obaidi; Ezri Mohd; Noorsaliza Abdullah; Samsul Haimi Dahlan; Jawad Ali
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1208.481 KB) | DOI: 10.11591/eei.v8i1.1392

Abstract

This work presents the design and implementation of Rotman lens as a beam steering device for Industrial, Scientific, and Medical (ISM) applications. 2.45 GHz is considered as a center frequency design with (2-6) GHz frequency bandwidth. The beam steering is examined to cover ±21o scan angle with maximum main lobe magnitude 10.1 dBi, rectangular patch antennas are used as radiation elements to beam the output far field. The work is extended to compare between the tapered line which is used for matching between 50-Ω ports and lens cavity. CST microwave simulation studio results show that the rectangular taper line can yield 2 dB return loss less than linear taper line with a little bit shifting in responses for same input and load impedance.