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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 9,226 Documents
 449   450   451   452   453 
Review on secured data capabilities of cryptography, steganography, and watermarking domain Farah Qasim Ahmed Al-Yousuf; Roshidi Din
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 2: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i2.pp1053-1058

Abstract

Due to the increment of using Internet to transfer the critical and secret data, many studies interested in secured data and investigated many ways to secure the transferred information. This paper presents a review study on the field that used in a secured data domain. The main objective of this study is explore the capabilities of secured data that used widely by researchers. Furthermore, the benefits and the drawbacks for each of secured data domain are also studied. This paper concludes that cryptography techniques could be utilized with steganography and watermarking in secured data domain to enhance the security mechanisms.
Research on the AVC Testing Platform for the Regional Grid based on Real-Time Digital Simulator (RTDS) Lin Xu; Yang Han
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 1: January 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

The automatic voltage control (AVC) relay provides real-time automatic control for the on-load transformer tap changer (OLTC), which is widely used for power system voltage monitoring and control purposes throughout the world. However, there are no uniform testing standards for the AVC system, and the lack of on-site inspection means has stimulated the introduction of the real-time digital simulator (RTDS)-based testing platform. This paper introduces the testing platform of the AVC controller based on the RTDS. The circuit model of the regional power grid is established, and the OLTC and the reactive power compensation devices are also incorporated. The intermediate data conversion device is utilized for bi-directional data exchange of the remote meter and control signals between the RTDS and the AVC system. The principle of the AVC voltage regulation and the RTDS-based AVC testing platform are introduced, followed by the data flow of the OLTC and capacitor/inductor banks, which formulates the foundation for closed-loop testing of the AVC control system for the electric power system. DOI: http://dx.doi.org/10.11591/telkomnika.v11i1.1677
Performance Analysis of Pathfinding Algorithms Based On Map Distribution Yan Li; Zhenhua Zhou; Wenju Zhao
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.pp5537-5545

Abstract

The distribution information of game maps is highly relevant to the execution efficiency of path searching and the degree of game difficulty. This paper analyzes the relationship between the pathfinding performance and the obstacles distribution in maps from two aspects, pathfinding algorithm design and game’s map design respectively. A hierarchical pathfinding algorithm called CDHPA* is proposed by incorporating the obstacle distribution in traditional HPA* algorithm.  It is used to hierarchical path search in those maps where the obstacles are densely distributed. On the other hand, a map complexity metric is defined based on the accumulation of xor calculations of given maps. This measure describes the complexity of a map and hence could reflect the performance of pathfinding algorithms, which could provide references for game maps design. The experimental results have validated the proposed analysis.
Diagnosis of Hepatocellular Carcinoma Spectroscopy Based on the Feature Selection Approach of the Genetic Algorithm Shao-qing Wang; Qiang Liu; Dong-yue Yu; Guang-ju Liang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 6: June 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

This paper aims to study the application of medical imaging technology with artificial intelligence technology on how to improve the diagnostic accuracy rate for hepatocellular carcinoma. The   recognition method based on genetic algorithm (GA) and Neural Network are presented. GA was used to select 20 optimal features from the 401 initial features. BP (Back-propagation Neural Network, BP) and PNN (Probabilistic Neural Network, PNN) were used to classify tested samples based on these optimized features, and make comparison between results based on 20 optimal features and the all 401 features. The results of the experiment show that the method can improve the recognition rate. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2663
Modelling and Simulation of Tidal Current Turbine with Permanent Magnet Synchronous Generator Marwa Elzalabani; Faten H.Fahmy; Abd El-Shafy A. Nafeh; Gaber Allam
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 1: January 2015
Publisher : Institute of Advanced Engineering and Science

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Abstract

This paper explain the creation of a Matlab-Simulink model for a tidal current turbine system through the modeling of the source, the rotor, drive train and the generator. The aim of the simulation model is to illustrate how the tidal current energy system works and how to make use of it in power generation. Harnessing tidal currents power done through various types of water current turbines. Owing to its advantages in producing power from tidal currents, OpenHydro tidal current turbine will be used in this work. With its Permanent magnet synchronous generator (PMSG) that is suitable for low tidal current speeds and no need for gearbox. The rotational motion of the turbine rotor is transferred to the electrical generator by means of a mechanical transmission system called drive train. MATLAB/SIMULINK interface has been examined and the maximum electrical power extraction within the allowable range of tidal currents can be achieved if the controller can properly follow the optimum curve with any water current speed change. DOI: http://dx.doi.org/10.11591/telkomnika.v13i1.7017
Equipment Fault Prognosis Based on Temporal Association Rules Chao GAN; Yuan LU; Ying HU; Jia GU; Xin QIU
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

Equipment fault prognosis is important for reliability, operational safety, and efficient performance of equipment. Temporal fault data model is built according to the principles of the Apriori traditional association rules algorithm based on the characteristics of fault data. An Improved Apriori algorithm and frequent temporal association rules algorithm are proposed in this study by converting fault data to temporal item sets matrix. Equipment fault trends are predicted by mining the frequent temporal association rules of fault data based on the algorithm, which provides good support for equipment maintenance and management. At last an example is given to prove the feasibility and practical application of proposed algorithms DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.4563
Detecting abnormal movement of driver's head based on spatial-temporal features of video using deep neural network DNN Noor D. Al-Shakarchy; Israa Hadi Ali
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.pp344-352

Abstract

The development of tracking and surveillance devices makes extracting useful information efficiently. Head tracking is an efficient method to obtain then analyze trajectory data and make a decision based on the spatiotemporal information of videos. Many applications are based on head tracking such as diseases some diagnosis,  the gestures languages, and drowsiness detection and so on. Abnormal head movement detection can be achieved using spatial information based on a single image (one frame) at a time without considering the temporal information over time. In this paper, a new method based on multi-images is proposed to track head in order to detect abnormal head movement depending on spatiotemporal Feature using Deep Neural Network DNN that employed the 3-Dimensional Convolution Neural Networks 3D CNN. The proposed method extracts the spatial information as well as the temporal information available in a video then analysis this information to make the decision based on time series (sequences of frames); these time series provides the tracking to the head overtime to make the decision. The new dataset created and gathered to implement with the proposed system and called Normal Abnormal Head Movement Dataset (NAHM) video dataset. The new dataset provides different subjects with different conditions that give more efficiency in the implementation of the proposed system. The accuracy of the training set that achieves by the proposed system reach to 88% and of validation set reaches to 86%. The values of loss function reach to 0.3 for the training set and 0.4 for the validation set.
Forecast Model of Water Quantity Based on Back Propagation Artificial Neural Network Shihua Li
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 6: June 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

Back Propagation (BP) neural network, Widely adopted and utilized in automatic control, image recognition, hydrological forecasting and water quality evaluation, etc., as one of the Artificial Neural Networks, has stronger function and property of mapping, classification, functional fitting. This article takes the water flow of Lanzhou section of Yellow river in China as an example by the way of BP model to predict the water quantity. It is well proved that BP network model can reach the purposes of early warning and forecasting. DOI : http://dx.doi.org/10.11591/telkomnika.v12i6.5444
Petri Net-based Analysis of the Safety Communication Protocol Liu Hongjie; Chen Lijie; Ning Bin
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 10: October 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

There is a few research in area of safety-critical system, therefore the study of performance analyzing method of the protocol has important practical significance for transportation engineering. This paper first briefly introduces the execution procedure of safety communication protocol, then explores the application of Petri net to establish the model of the protocol, including the process of state transition and corresponding timer which record the time, then obtains related performance data such as maintainability and failure probability, which users usually pay most attention to, with different probability of time delay and no fault in channel by simulation. Finally this paper finds that how the probability of time delay and no fault in channel could influent the maintainability and failure probability through data process with theory of probability and mathematical statistic, this could provide a certain reference for development of safety communication protocol. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3462 
An automatic lexicon generation for indonesian news sentiment analysis: a case on governor elections in Indonesia Media A Ayu; Sony Surya Wijaya; Teddy Mantoro
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1555-1561

Abstract

Sentiment analysis has been popularly used in analyzing data from the internet.  One of the techniques used is lexicon based sentiment analysis.  Generating lexicon is not an easy process, and lexicon in Bahasa Indonesia is rarely available.  This paper proposes an automatic lexicon generation in Bahasa Indonesia for sentiment analysis purpose.  Experiments were performed using the generated lexicon for doing sentiment analysis on Indonesian political news about the 2018 governor election in three provinces in Indonesia. The conducted experiments show promising results where it can predict the candidate’s rank, the election winner, and the percentage of votes for each candidate with better accuracy than the previous work which used manually generated lexicon.

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