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Electrical & Electronics Engineering

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Articles 25 Documents

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Search results for , issue "Vol 7, No 3: September 2018" : 25 Documents clear

Assessing Information System Integration Using Combination of the Readiness and Success Models A'ang Subiyakto
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Information system integration (ISI) is one of the development concerns for organizations to enhance business competitiveness. However, the implementations still present its failures. Despite the ISI may successful technically; but it still seems to be unsuccessful because of the human and management issues. The issues may relate to the readiness constructs of ISI. This study was aimed to know the status of the readiness and success of ISI and to assess the influential factors of the integration in the sampled institution. About 160 samples were purposely involved by considering their key informant characteristics. The data were analyzed using the partial least squares-structural equation modeling (PLS-SEM) method. The findings revealed only the user satisfaction variable that mediated the positive effects of the readiness variables towards variable of the system integration success. Besides, the findings may practically helpful for stakeholders in the sampled institution, but it may also theoretically useful for researchers in regard to the readiness and success issues of ISI.

A Finite State Machine Fall Detection Using Quadrilateral Shape Features Mohd Fadzil Abu Hassan; Mohamad Hanif Md Saad; Mohd Faisal Ibrahim; Aini Hussain
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

A video-based fall detection system was presented; which consists of data acquisition, image processing, feature extraction, feature selection, classification and finite state machine. A two-dimensional human posture image was represented by 12 features extracted from the generalisation of a silhouette shape to a quadrilateral. The corresponding feature vectors for three groups of human pose were statistically analysed by using a non-parametric Kruskal Wallis test to assess the different significance level between them. From the statistical test, non-significant features were discarded. Four selected kernel-based Support Vector Machine: linear, quadratics, cubic and Radial Basis Function classifiers were trained to classify three human posture groups. Among four classifiers, the last one performed the best in terms of performance matric on testing set. The classifier outperformed others with high achievement ofaverage sensitivity, precision and F-score of 99.19%, 99.25% and 99.22%, respectively. Such pose classification model output was further used in a simple finite state machine to trigger the falling event alarms. The fall detection system was tested on different fall video sets and able to detect the presence offalling events in a frame sequence of videos with accuracy of 97.32% and low computional time.

Signal-to-Noise Ratio Study on Pipelined Fast Fourier Transform Processor Hassan, L. M.; S. Shariffudin, S.; N. T. Yaakub, T.; L. M. Hassan, S.
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 | DOI: 10.11591/eei.v7i3.1271

Fast Fourier transform (FFT) processor is a prevailing tool in converting signal in time domain to frequency domain. Â This paper provides signal-to-noise ratio (SNR) study on 16-point pipelined FFT processor implemented on field-programable gate array (FPGA). This processor can be used in vast digital signal applications such as wireless sensor network, digital video broadcasting and many more. These applications require accuracy in their data communication part, that is why SNR is an important analysis. SNR is a measure of signal strength relative to noise. The measurement is usually in decibles (dB). Previously, SNR studies have been carried out in software simulation, for example in Matlab. However, in this paper, pipelined FFT and SNR modules are developed in hardware form. SNR module is designed in Modelsim using Verilog code before implemented on FPGA board. The SNR module is connected directly to the output of the pipelined FFT module. Three different pipelined FFT with different architectures were studied. The result shows that SNR for radix-8 and R4SDC FFT architecture design are above 40dB, which represent a very excellent signal. SNR module on the FPGA and the SNR results of different pipelined FFT architecture can be consider as the novelty of this paper.

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

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

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

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

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

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

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

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.

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