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Wavelet based de-noising for on-site partial discharge measurement signal
A. Z. Abdullah;
M. Isa;
S. N. M. Arshad;
M. N. K. H. Rohani;
H. S. A. Halim;
A. N. Nanyan;
H. A. Hamid
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i1.pp259-266
This paper presents, wavelet based de-noising technique for on-site partial discharge (PD) measurement signal. The signal is measured from medium voltage power cable at 11 kV distribution substation. The best mother wavelet, decomposition level and the type of threshold for the de-noising technique are selected based on the signal to noise ratio (SNR) aggregation. The SNR aggregation is determined based on the minimum, maximum, mean and standard deviation parameters. The same standard de-noising procedure is applied for two different PD signals and the selection parameters are done based on the accuracy of de-noising analysis. The analysis is performed in MATLAB software environment and Daubechies 2 (db2) is found as the best mother wavelet at tenth decomposition levels with soft threshold type. This study is specifically performed to develop the de-noising procedure for on-site PD measurement. Overall results indicate that the right selection of the de-noising procedure will help to improve the PD signal detection from on–site measurement.
Hybrid methods of brandt’s generalised likelihood ratio and short-term energy for malay word speech segmentation
Noraini Seman;
Ahmad Firdaus Norazam
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i1.pp283-291
Speech segmentation is an important part for speech recognition, synthesizing and coding. Statistical based approach detects segmentation points via computing spectral distortion of the signal without prior knowledge of the acoustic information proved to be able to give good match, less omission but lot of insertion. In this study the segmentation is done both manually and automatically using Malay words in traditional Malay poetry. This study proposed a hybrid method of Brandt’s generalized likelihood ratio (GLR) and short-term energy algorithm. The Brandt’s algorithm tries to estimate the abrupt change in energy to determine the segmentation points. A total of five Pantun are used in read mode and spoken by one male student in a noise free room. Experiments are conducted to see the the accuracy, insertion, and omission of the segmentation points. Experimental results show on average 80% accuracy with 0.2 second time tolerance for automatic segmentation with the algorithm having no knowledge of the acoustic characteristics.
A modified cascaded h-bridge multilevel inverter based on particle swarm optimisation (PSO) technique
Mohammed Rasheed;
Rosli Omar;
Marizan Sulaiman;
Wahidah Abd Halim
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i1.pp41-51
In this paper, modified multilevel inverter, via addition of an auxiliary bidirectional switch, based on Newton Raphson (NR) and Particle Swarm Optimization (PSO) techniques is presented. The NR and PSO techniques were employed for selective harmonics elimination (SHE) solution in a modified Cascaded H Bridge Multilevel inverter (CHB-MLI). The Selective Harmonic Elimination Pulse-Width Modulation (SHE-PWM) is a powerful technique for harmonic minimization in multilevel inverter. The NR and PSO techniques were used to determine the switching angles by solving the non-linear equations of the output voltage waveform of the modified CHB-MLI in order to control the fundamental component and eliminate some low order harmonics. The proposed NR and PSO techniques are capable to minimize the Total Harmonic Distortion (THD) of the output voltage of the modified inverter within allowable limits. This paper aims to modeling and simulation by MATLAB of the modified topology of the CHB-MLI for a single-phase prototype for 13-levels. The inverter offers less THD and greater efficiency using PSO control algorithm compared with the NR algorithm. The performance of the proposed controllers based on NR and PSO techniques is verified through simulation.
Business intelligence addressing service quality for big data analytics in public sector
Sadesh Manikam;
Shamsul Sahibudin;
Vinothini Kasinathan
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i1.pp491-499
With the inauguration of Big Data Analytics initiative nationally, many nations have participated and paved way for BDA ecosystem. The initiative is a catalyst to further encourage economic growth in Public Sectors. Some of the common key deliverables identified are increasing productivity involving information communications technology, cost savings, shared benefits, and encourage innovation. The objectives can be further elaborated by driving big data analytics demands in various public sectors agency, adopting big data analytics framework supporting the building of big data industry. This has encouraged talents and startup companies inspiring their capabilities by developing various technology platform, collaborate and innovate amongst public and private sectors, and further strengthen data governance by creating policy and procedures. With the establishment of big data analytics framework, performance measurement can be enforced effortlessly using the principles of business intelligence maturity model and the technological stack comes with it. Various data sources can be used to benchmark service quality using advanced analytics and data science techniques.
Modified spiht algorithm for quincunx wavelet image coding
Ismahane Benyahia;
Abdesselam Bassou;
Chems El Houda Allaoui;
Mohammed Beladgham
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i1.pp230-242
In this paper, an image compression method based on the Quincunx algorithm coupled with the modified SPIHT encoder (called SPIHT-Z) is presented. The SPIHT-Z encoder (coupled with quincunx transform) provides better compression results compared with two other algorithms: conventional wavelet and quincunx both coupled with the SPIHT encoder. The obtained results, using the algorithm that applies (Quincunx with SPIHT-Z) are evaluated by image quality evaluation parameters (PSNR, MSSIM, and VIF). The compression results on twenty test images showed that the proposed algorithm achieved better levels of the image evaluation parameters at low bit rates.
Implementation of embedded real-time monitoring temperature and humidity system
Firdaus Hashim;
Roslina Mohamad;
Murizah Kassim;
Saiful Izwan Suliman;
Nuzli Mohamad Anas;
Ahmad Zaki Abu Bakar
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i1.pp184-190
Temperature and humidity are among the parameters that significant to the industrial and agricultural. Traditionally, these elements are monitored inefficiently through wired monitoring system that caused higher implementation and maintenance cost. In addition, the device to detect the temperature such thermometer is not suitable for real-time monitoring since it need a longer response time to measure. With the advent of wireless technology, the temperature and humidity are monitored remotely and effectively. This paper aims to describe the implementation of an embedded real-time temperature and humidity monitoring system, using Arduino for Internet of Things (IoT) application. The system integrates the Arduino node with a dashboard system call Node-FRED, which interfaced to the LoRa radio through the Things Network gateway. This IoT application is deployed on both indoor and outdoor environment, to investigate the relation between the temperature and humidity level in order to manage the environment at more comfort level.
Practical understanding of the operating principle of digital communication systems
Gebrehiwet Gebrekrstos Lema;
Teklehaymanot Baweke Reda;
Dawit Hailu;
Tole Sutikno
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i1.pp299-310
There are many students and researcher who doesn’t really understand the practical operating principle of digital communication system. Hence in this paper, the digital communication system is studied and simulated. In the system kit development text and audio inputs are taken and encrypted with different encryption techniques including additive cipher, multiplicative cipher and affine ciphers. The encrypted data is converted in to an 8-bit binary, channel encoded with distinct channel coding styles like linear block encoder, cyclic encoder and convolutional encoder, line coded and band pass modulated by different digital modulation techniques. Finally, the developed software is tested with equivalent inputs of the current national TV broadcasting and the results found are correct according to the theoretical analysis of the discussion.
Comparison of malware detection techniques using machine learning algorithm
Nur Syuhada Selamat;
Fakariah Hani Mohd Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i1.pp435-440
Currently, the volume of malware grows faster each year and poses a thoughtful global security threat. The number of malware developed increases as computers became interconnected, at an alarming rate in the 1990s. This scenario resulted the increment of malware. It also caused many protections are built to fight the malware. Unfortunately, the current technology is no longer effective to handle more advanced malware. Malware authors have created them to become more difficult to be evaded from anti-virus detection. In the current research, Machine Learning (ML) algorithm techniques became more popular to the researchers to analyze malware detection. In this paper, researchers proposed a defense system which uses three ML algorithm techniques comparison and select them based on the high accuracy malware detection. The result indicates that Decision Tree algorithm is the best detection accuracy compares to others classifier with 99% and 0.021% False Positive Rate (FPR) on a relatively small dataset.
The design of virtual lower limb rehabilitation for post-stroke patients
Lee Wei Jian;
Syadiah Nor Wan Shamsuddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i1.pp544-552
Stroke is one of the leading causes that elicits to disability for adults over a long period. Post-stroke patients often have difficulties with joints and muscles in their legs, which prevents them from moving around. Lower limb rehabilitation helps to regain normal mobility and functionality of patients such as standing, walking and climbing stairs. The implementation of virtual reality in stroke rehabilitation helps to encourage patients on frequent engagement with exercise. This paper briefly presents the ongoing research regarding lower limb rehabilitation systems for post-stroke patient in virtual reality environment to provide an overview of the conceptual design, limitations, and suggestions for future work in this direction.
Evolving spiking neural networks methods for classification problem: a case study in flood events risk assessment
Mohd Hafizul Afifi Abdullah;
Muhaini Othman;
Shahreen Kasim;
Siti Aisyah Mohamed
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i1.pp222-229
Analysing environmental events such as predicting the risk of flood is considered as a challenging task due to the dynamic behaviour of the data. One way to correctly predict the risk of such events is by gathering as much of related historical data and analyse the correlation between the features which contribute to the event occurrences. Inspired by the brain working mechanism, the spiking neural networks have proven the capability of revealing a significant association between different variables spike behaviour during an event. Personalised modelling, on the other hand, allows a personal model to be created for a specific data model and experiment. Therefore, a personalised modelling method incorporating spiking neural network is used to create a personalised model for assessing a real-world flood case study in Kuala Krai, Kelantan based on historical data of 2012-2016 provided by Malaysian Meteorological Department. The result shows that the method produces the highest accuracy among the selected compared algorithms.