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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 : -
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Articles 50 Documents
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Search results for , issue "Vol 12, No 11: November 2014" : 50 Documents clear
Design and Analysis of Parallel MapReduce based KNN-join Algorithm for Big Data Classification Xuesong Yan
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.pp7927-7934

Abstract

In data mining applications, multi-label classification is highly required in many modern applications. Meanwhile, a useful data mining approach is the k-nearest neighbour join, which has high accuracy but time-consuming process. With recent explosion of big data, conventional serial KNN join based multi-label classification algorithm needs to spend a lot of time to handle high volumn of data.  To address this problem, we first design a parallel MapReduce based KNN join algorithm for big data classification. We further implement the algorithm using Hadoop in a cluster with 9 vitual machines. Experiment results show that our MapReduce based KNN join exhibits much higher performance than the serial one. Several interesting phenomenon are observed from the experiment results.
Effects of the Presence of Distributed Generation on Protection and Operation of Smart Grid Implemented in Iran; Challenges and Solutions Hossein Shahinzadeh
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.pp7595-7602

Abstract

Installation of distributed generation (DG) in distribution networks, in addition to the benefits, will also cause drawback and disadvantages which can bring difficulties for grid operator. Thus, prior to installation of DGs, it is essential to have deeply studied about their installation in the network and it is needed to make some changes in traditional network. Implementation of smart grids is one of the main requirements for the proper and efficient operation of DGs. In Iran, Smart grid is also being implemented, but with the development of DGs, electricity distribution companies face new problems related to DGs every day. One of the most important problems is about effects of the DGs on proper operation of protective equipment which is mainly due to radial distribution network. That is because in Iran, despite the implementation of smart grids, distribution networks are designed and implemented radially and airlines with isolated neutral point is usually used in the distribution network. So, in this article, the impacts of distributed generation resources on distribution networks in Iran and Protection and operational problems which may cause in this area are studied and solutions to these problems are provided.
Review of the Urban Traffic Modeling Zhu Song; Zhiguang Qin
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

Abstract

Nowadays, the urban traffic modeling, which is helpful in planning and controlling the traffic system, has becoming a research hotspot of traffic engineering.  After decades of research and development, there now exists hundreds of models choosing different modeling methods to simulate the traffic flow. It is important for us to understand these models by classifying them and analyzing their features. The features of traffic models, including the scalability, accuracy and computability, are becoming important indicators to measure their performance. In this paper, we introduce and compare some grounded models. In particular, we analyze the advantages and disadvantages of existing models, and classify them into three categories according their granularity: macroscopic, mesoscopic and microscopic models. http://dx.doi.org/10.11591/telkomnika.v12i11.6128 
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).
Perspective and Challenge of Tidal Power in Bangladesh Md. Alamgir Hossain; Md. Zakir Hossain; Md. Mijanur Rahman; Md. Atiqur Rahman
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.pp7558-7563

Abstract

Tidal power can play a vital role in integrating as new source of renewable energy to the off-grid power connection in isolated areas, namely Sandwip, in Bangladesh. It can reduce the present energy crisis and improve the social, environmental and economical perspective of Bangladesh. Tidal energy is becoming popular around the world due to its own facilities. The development of any country largely depends on energy sector improvement. Lack of energy sector is because hampering of progress of any country development and energy sector will be stable by only depend on sustainable energy sources. Renewable energy is the only sustainable solution of secure energy which is environmental friendly. Bangladesh has a huge potential of tidal power at different locations but effective measure on this issue have not been considered sincerely. This paper summarizes the current energy scenario and Bangladesh can produce power approximately 53.19MW across the country to reduce the growing energy demand utilizing tidal energy as well as it is shown that Sandwip has high potential of producing tidal power which is approximately 16.49MW by investing only US $10.37 millions. Besides this, cost management for tidal power plant also has been discussed.
Robustness Estimation of Wireless MEMS Vibration Test under Harsh Environment Changjian Deng
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.pp7697-7704

Abstract

Robustness estimation is important issue to ensure stability, reliability, and precision of Wireless MEMS vibration test under harsh environment stressing. Although the robustness of vibration test is limited mainly by the embedded electronics and sensors, how to obtain precise and robust data by using energy effective and resources constrained wireless sensor nodes is still a problem. Paper uses the multivariate uncertainty statistics method to estimate robustness of online test data under harsh environment, and uses Fisher information distance to estimate transmitting robustness in its complication communication process. Experiments and simulation are designed to analyze the robustness and precise of wireless MEMS nodes in numerical value, results show estimation methods and model are effective.
PTS Method with Combined Partitioning Schemes for Improved PAPR Reduction in OFDM System Zeyid T. Ibraheem; Md. Mijanur Rahman; S. N. Yaakob; Mohammad Shahrazel Razalli; F Salman; Kawakib K. Ahmed
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.pp7845-7853

Abstract

Although orthogonal frequency division multiplexing (OFDM) is an efficient wireless transmission system, it suffers from a crucial drawback namely high peak-to-average power ratio (PAPR) that limits transmitter power efficiency. Thus, different PAPR reduction algorithms have been introduced. Partial transmit sequence (PTS) is the most attractive solution which can provide good PAPR reduction performance without distortion. In any PTS system, partitioning of the OFDM frame into disjoint sub-blocks is a significant step. Out of the existing partitioning techniques, adjacent partitioning (AP) is a fairly simple partitioning scheme achieving efficient PAPR reduction performance. This paper presents an enhanced PTS approach that combines two PTS partitioning schemes, adjacent and interleaved partitioning, in order to effectively reduce the PAPR of OFDM systems. With an aim of determining the effects of length variability of adjacent partitions, we performed an investigation into the performances of a variable length adjacent partitioning (VL-AP) and fixed length adjacent partitioning in comparison with the enhanced PTS scheme.
Hysteresis Current Control with Input Filter Design for High Frequency Series Resonant Full Bridge Inverter Debabrata Roy; Pradip Kumar Sadhu; Nitai Pal
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.pp7650-7658

Abstract

This paper talks about the analysis of a high frequency series resonant inverter for using domestic and industrial induction heating purpose. It is a technique i.e. used for heat conductive materials hard and soft metals.  Series Resonant inverters which operate at high frequency preferable for induction heating which normally works in 5-55KHz. High frequency series resonant inverters which is made up of Insulated Gate Bipolar Transistor (IGBT). Power control is obtained by Hysteresis Current Control and filter design is incorporated in the input power supply. Soft switching techniques is performed which minimizes switching losses and proper filter design minimizes harmonic injection in the power supply.
Mosquito Tracking by Image Segmentation of Optical Flow Field Jahangir Alam S.M.; Hu Guoqing
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.pp7798-7807

Abstract

High speedy Mosquito tracking and a time efficient technique have been presented by considering on image segmentation of the optical flow which has been computed by image successive frames to track the Mosquito of a specific region of interest (SROI) on the region of field (ROF) with segmented flow regions. The optical flow has been established by the successive two frames to consider acquiring the image for computing. A fuzzy antagonism index has been indicated as the degree of the consistency of flying Mosquito. The image frames are used to segment the optical flow field. The images have been segmented in flow field with in the different consistency of region of interest (ROI). The specific region of interest (SROI) can be detected in the different ROI spaces. Therefore, the Mosquito can be tracked from two subsequent images. However, the detected specific region of interest (SROI) is a sub-region of ROI. The SROI is smaller in the image frames which can reduce the time to compute the SROI. It is the facilitating real-time process of Mosquito. In the proposed technique, it has been demonstrated image sequences of moving or flying Mosquito for detection and position tacking.
Winner-Takes-All based Multi-Strategy Learning for Information Extraction Dwi Hendratmo Widyantoro; Kurnia Muludi; Kuspriyanto Kuspriyanto
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.pp7935-7945

Abstract

This paper proposes a winner-takes-all based multi-strategy learning for information extraction. Unlike the majority of multi-strategy approaches that commonly combine the prediction of all base learnings involved, our approach takes a different strategy by employing only the best, single predictor for a specific information task. The best predictor (among other predictors) is identified during training phase using k-fold cross validation, which is then retrained on the full training set. Empirical evaluation on two benchmarks data sets demonstrates the effectiveness of our strategy. Out of 26 information extraction cases, our strategy outperforms other information extraction algorithms and strategies in 16 cases. The winner-takes-all strategy in general eliminates the difficult situation in multi-strategy learning when the majority of base learners cannot make correct prediction, resulting in incorrect prediction on its output. In such a case, the best predictor with correct prediction  in our strategy will take over for the overal prediction.

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