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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 9,199 Documents
 446   447   448   449   450 
Prospects of using the UFMC technology In 5g / Imt-2020 networks Ahmed Sabri Ghazi Behadili; Emad Jadeen Abdualsada Alshebaney; Aqeel Lateef Khudhair attaby
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 2: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i2.pp855-860

Abstract

The article considers the technology of frequency multiplexing with universal filtering UFMC, planned to be introduced in the fifth generation of mobile communication networks, which allows maximizing the rate of decay of the side lobes of the multifrequency signal spectrum that cause out-of-band emissions. As a method of investigation, a computational experiment was chosen. The parameters of the OFDM and UFMC signals were compared to determine the gain of the UFMC technology in the occupied bandwidth of the signal spectrum, as well as the number of arithmetic operations, required to generate a data symbol compared to the OFDM technology, on the basis of which, conclusions were made about the practical application of UFMC technology in networks mobile communication of the fifth generation. The conducted analysis can help to select the optimal number of sub-channels in groups in order to minimize the amount of computations during the UFMC symbol generation process.
Design of New Transformer Protection Device Based on Wavelet Energy Entropy-Neural Network Theory and FPGA Na Wu; Yinjing Guo; Yongqin Wei; Shuxian Fan; Xuehua Li
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 11: November 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Transformer differential protection may be of malfunction at the emergence of inrush current, and it will affect the normal operation of the transformer. So the paper puts forward a new application of wavelet energy spectrum entropy-neural network theory in transformer microcomputer protection, in which the multi-resolution analysis of wavelet transform and information entropy technology are combined firstly and forms a new conception named wavelet energy spectrum entropy, and it will be put into neural network theory as the feature vector, forms the new algorithm in the end. This method decomposes signal through wavelet transform, and  extracts the high frequency part of energy in each scale of wavelet transform from inrush current signal and the short circuit current signal, and calculates the wavelet energy entropy value, which will be as the input feature vector of modified BP neural network. And this feature vector is used as training characteristic value for training in BP neural network. According to the measured data of the system, it has achieved good effect. At the same time, for the large amount of calculation and the high requirements of signal sampling rate in wavelet energy entropy - neural network algorithm, a new idea which uses the high-speed hardware platform of FPGA to realize the algorithm application is put forward, and it will break the bottleneck of traditional microcomputer protection that the MCU would not give consideration to both the speed and the accuracy of the protection at the same time.  DOI: http://dx.doi.org/10.11591/telkomnika.v11i11.3524
Electroencephalogram (EEG) stress analysis on alpha/beta ratio and theta/beta ratio Tee Yi Wen; Siti Armiza Mohd Aris
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 1: January 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i1.pp175-182

Abstract

This paper presents an analysis of stress feature using the power ratio of frequency bands including Alpha to Beta and Theta to Beta. In this study, electroencephalography (EEG) acquisition tool was utilized to collect brain signals from 40 subjects and objectively reflected stress features induced by virtual reality (VR) technology. The EEG signals were analyzed using Welch’s fast Fourier transform (FFT) to extract power spectral density (PSD) features which represented the power of a signal distributed over a range of frequencies. Slow wave versus fast wave (SW/FW) of EEG has been studied to discriminate stress from resting baseline. The results showed the Alpha/Beta ratio and Theta/Beta ratio are negatively correlated with stress and indicated that the power ratios can discriminate the data characteristics of brainwaves for stress assessment.
Single Image Haze Removal Method for Inland River Zhongyi Hu; Qiu Liu
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 1: January 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Due to environmental pollution, the climate is worsening. The fog days up to 60% of the year in inland certain segments, which it has seriously affected the marine electronic cruise normal operation and navigation safety. According to the inland video image becomes gray and lack of visibility in foggy weather conditions, and in order to remove the haze to get a clear image color and contour, this paper presents a method based on Jones Extension Matrix and the Dark Channel Prior. First, we obtain the light intensity in the atmosphere and the estimated concentration of the haze by using Dark Channel Prior, and via using the Jones Extension Matrix and the parameters of Stokes' Law to eliminate part of the scattered light. At last, we have completed the function of image dehazing by brightness adjustment factor based on N pixels in the field of step brightness and improve the brightness based on Retinex Principle for the recovered image. Experimental results show this algorithm improves scenery visual effect in condition of haze. It is provided a clear video image for the marine electronic cruise in the foggy day. DOI: http://dx.doi.org/10.11591/telkomnika.v11i1.1908
A New Digital Image Hiding Algorithm Based on Wavelet Packet Transform and Singular Value Decomposition Yueli Cui; Shiqing Zhang; Zhigang Chen; Wei Zheng
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 7: July 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i7.pp5408-5413

Abstract

The paper presents a new digital image hiding algorithm based on wavelet packets transform and singular value decomposition. The low-frequency sub-band of wavelet packets transform has strong anti-jamming capacity and the singular value has very strong stability. The presented algorithm implements bit plane decomposition on the secret image and wavelet packet decomposition on the carrier image. Then, it hides the bit planes with important information into the singular value matrix of the low frequency coefficient matrix, and also hides the bit planes with secondary information into the remainder sub-band matrix with higher entropy energy. The hiding location is adaptively determined by the carrier image. The experimental results indicate that, the proposed image hiding algorithm has strong robustness and anti-attack, and it also has good invisibility and big capability.
Moving Vehicle Detection and Tracking Algorithm in Traffic Video Shisong Zhu; Min Gu; Jing Liu
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 6: June 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Aiming at the defects and shortages of traditional moving vehicles detection algorithms, by the analysis and comparison of the existing detection algorithms, we propose an algorithm that combined with frames with symmetric difference and background difference to detect moving vehicle in this paper. First, two different difference images by using frames with symmetric difference and background difference are gained respectively and two binary images can be gained by the appropriate threshold, then the contour of moving vehicles can be extracted by applying OR operation in the two binary images. Finally, the precise moving vehicles will be gained by mathematic morphological methods. In this paper we use Harris operator, Feature Points such as edges and corners are extracted, followed by block-matching to track the Feature Points in successive viedo frames. Many vehicles can be tracked at the same time automatically since  the  information is obtained from video sequences. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2613
Detailed Analysis of Extrinsic Plagiarism Detection System Using Machine Learning Approach (Naive Bayes and SVM) Zakiy Firdaus Alfikri; Ayu Purwarianti
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 11: November 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i11.pp7884-7894

Abstract

In this report we proposed a detailed analysis method of plagiarism detection system using machine learning approach. We used Naive Bayes and Support Vector Machine (SVM) as learning algorithms. Learning features used in the method are words similarity, fingerprints similarity, latent semantic analysis (LSA) similarity, and word pair. The purpose in selecting those features is to retrieve information from the state-of-the-art detailed analysis methods (words similarity, fingerprinting, and LSA) in order to integrate the strength of each method in detecting plagiarism. Several experiments were conducted to test the performance of the proposed method in detecting many cases of plagiarism. The experiments used data test that contains cases of literal plagiarism, partial literal plagiarism, paraphrased plagiarism, plagiarism with changed sentence structure, and translated plagiarism. The data test also contains cases of non-plagiarism of different topics and non-plagiarism of the same topic. The results obtained in experiments using SVM showed an average accuracy of 92.86% (reaching 95.71% without using words similarity feature). While the result obtained using Naive Bayes showed an average accuracy of 54.29% (reaching 84.29% without using the word pair features).
Storage Capacity Configuration to Improve Prediction Accuracy of Photovoltaic Output Jian chun Luo; Qin Chao
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: March 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

The short-term prediction accuracy of Photovoltaic(PV) output may not meet power scheduling requirements, the combined use of photovoltaic generator and energy storage device can improve the prediction accuracy. Storage capacity configuration is an important issue for the economy of PV plant and PV prediction accuracy.In this paper, the distribution character of PV prediction error is analyzed based on the probability density function evolution method. A storage capacity configuration model is built to consider economic prediction accuracy and capacity .A storage device controlling strategy was bulit.Last, a tracking - economic factor is defined which can be used for economic evaluation of the energy storage device. An example is shown that PV prediction error is in normal distribution and the proposed method can improve the prediction accuracy of PV output while increasing the level of economic use of energy storage devices. DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.3838
A comparison on two discordancy tests to detect outlier in von mises (VM) sample Fatin Najihah Badarisam; Adzhar Rambli; Mohammad Illyas Sidik
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp156-163

Abstract

This paper focuses on comparing two discordancy tests between robust and non-robust statistic to detect a single outlier in univariate circular data. So far, to the best author knowledge that there is no literature make a comparison between both tests of RCDu Statistic and ????1 Statistic. The test statistics are based on the circular median and spacing theory. In addition, those statistics can detect multiple and patches outliers. The performance tests of RCDu Statistic and ????1 Statistic are tested in outlier proportion of correct detection, masking and swamping effect. At the beginning stage, we obtained the cut-off points for the RCDu Statistic and ????1 Statistic by applying Monte Carlo simulation studies. Then, generated sample from von Mises (VM) with the combination of sample size and concentration parameter. The estimating process of cut-off points for both statistics is repeated 3000 times at 10%, 5% and 1% upper percentiles. As a result, the RCDu Statistic perform well in detecting a correct single outlier. Moreover, the RCDu Statistic has a lower masking rate compared to ????1 Statistic.  However, the ????1 Statistic is better than RCDu Statistic for swamping effect due to a lower swamping rate. Thus, RCDu Statistic performs better than ????1 Statistic in detecting a single outlier for von Mises (VM) sample. As an illustration, both statistics were applied to the real data set from a conducted experiments series to investigate the northen cricket frogs homing ability.
Improved Fuzzy Evaluation Model Analysis of Nuclear Power Plant Operational Safety Performance Dongxiao Niu; Zongyun Song; Jinpeng Liu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 6: June 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i6.pp4505-4511

Abstract

The evaluation on nuclear power plant operational safety performance had great significance on whether the nuclear power plant operated safely or not. Currently the academic literatures on nuclear power plant operational safety performance are rare. Improved Fuzzy evaluation model which introduce confidence level had been used into the evaluation of nuclear power plant operational safety performance. The article built safety performance indicator system and further established importance level evaluation matrix which showed the indexes relative importance, and established performance evaluation matrix which represented indicators impact on operational effect. From the importance level evaluation matrix the weigh and confidence of indicators can be gained and from the performance evaluation matrix the evaluation matrix can be gained. The preliminary evaluation result and synthetic confidence can be obtained by multiplying evaluation matrix by indicator weigh and confidence, and then the final evaluation result can be achieved. DOI: http://dx.doi.org/10.11591/telkomnika.v12i6.5389

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