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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 9,174 Documents
 490   491   492   493   494 
Design of ECC Controller and its Validation Based on FPGA Cao Yan; Du Lixia; Wang Zhengyu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 10: October 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i10.pp7253-7261

Abstract

ECC is an advanced technology for memory error detection and correction, which is used to support high reliability of computers. It is widely used in sever memory while it can detect 2-bit error and correct 1-bit error. This paper introduces the ECC algorithm, then discusses the more general correction coding mathematics, realizing it by programming with VHDL. After finishing these parts, a debug experiment is executed on the Altera Stratix IV family FPGA. Finally, the paper analyzes the simulation results and gives some suggestions for improving the performance of ECC controllers.
Comparing the linear and logarithm normalized extreme learning machine in flow curve modeling of magnetorheological fluid Irfan Bahiuddin; Abdul Y Abd Fatah; Saiful A Mazlan; Mohd I Shapiai; Fitrian Imaduddin; Ubaidillah Ubaidillah; Dewi Utami; Mohd N Muhtazaruddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 3: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i3.pp1065-1072

Abstract

The extreme learning machine (ELM) plays an important role to predict magnetorheological (MR) fluid behavior and to reduce the computational fluid dynamics (CFD) calculation cost while simulating the MR fluid flow of an MR actuator. This paper presents a logarithm normalized method to enhance the prediction of ELM of the flow curve representing the MR fluid rheological properties. MRC C1L was used to test the performance of the proposed method, and different activation functions of ELMs were chosen to be the neural networks setting. The Normalized Root Mean Square Error (NRMSE) was selected as the indicator of the ELM prediction accuracy. NRMSE of the proposed method is found to improve the model accuracy up to 77.10 % for the prediction or testing case while comparing with the linear normalized ELM
High-Order Sliding Mode Control of Greenhouse Temperature H. Oubehar; A. Ed-Dahhak; A. Selmani; M. Outanoute; A. Lachhab; M. Guerbaoui; M.H. Archidi; B. Bouchikhi
Indonesian Journal of Electrical Engineering and Computer Science Vol 4, No 3: December 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v4.i3.pp548-554

Abstract

This paper deals with the design and implementation of the high order sliding mode controller to control temperature greenhouse. The control objective aims to ensure a favorable microclimate for the culture development and to minimize the production cost. We propose performing regulation for the greenhouse internal temperature based on the second order sliding mode technique known as Super Twisting Algorithm (STA). This technique is able to ensure robustness with respect to bounded external disturbances. A successful feasibility study of the proposed controller is applied to maintien a desired temperature level under an experimental greenhouse. The obtained results show promising performances despite changes of the external meteorological conditions.
Video application to accommodate students’ learning style for moral education in teacher education institutes Mohd Razimi Bin Husin; Hishamuddin Bin Ahmad; Mahizer Bin Hamzah
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i1.pp349-354

Abstract

The purpose of this study is to explore the favored video applications in video use, compatible techniques and technology to accommodate the learning styles of moral education students in Teacher Education Institutes. This study is also to explore the contents of lesson suit to technology preferred by students in learning Moral Education. This is a case study in where data were collected through interviews. Six semester four students were chosen through purposive sampling from two Teacher Education Institutes in Malaysia. The constructs and internal validity were verified by experts while the external validity was verified through support from existing studies and theories. Data of the study were analyzed by using the Nvivo software to identify the features of favored video, compatible techniques and contents of lesson suit to technology that enhance the quality of teaching and learning of Moral Education to students. The Physiological Stimulus of Dunn and Dunn Learning Styles Model was used as guidance in the interviews because this model was the most suitable to be applied to students with Physiological Stimulus. The results of the analysis showed that short videos with suitable musics and short duration are the favored video for moral education students in teacher education institutes that enabled students to memorize the content knowledge. This research could be the learning guidelines on the use of videos and consequences activities of the shown videos that accommodate the learning styles of moral education students in Teacher Education Institutes which could be used by instructors in their professional practice in the lecture room.
The Agricultural Irrigation District Information System based on Multi-Agent Tinghong Zhao; Zibin Man; Huimin Hou
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 5: May 2014
Publisher : Institute of Advanced Engineering and Science

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

Abstract

Irrigation district informative construction is an effective way to improve the management and to rational allocate and effectively utility irrigation water resources. This paper is directed against the characteristics such as large-scale monitoring data amount, complex data types, high real-time requirement, strong spatial correlation, etc. combine Multi-Agent theory with irrigation district information system together, and use GSM communication network as the communication network of system, established an agricultural irrigation district information system based on Multi-Agent and GSM, which can full utility intelligent of Agent and the good communication coordination of Multi-Agent system, so to provide comprehensive technical support for irrigation management and decision making. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.3583
Wireless Environment Aware Adaptive Scheduling Technique For Cellular Networks Anand Reddy; Jitendranath Mungara
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 1: July 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i1.pp318-332

Abstract

It is now well known that employing channel knowledge based on signaling techniques in wireless mobile ad-hoc networks (MANET) system can yield large improvements in almost all performance metric. Here we proposed the adaptive scheduling, in which the work done is based upon the bandwidth information of channel to provide better quality of service (‘QoS’) to the cell-edge mobile stations. Channel information is critical based on which scheduling is carried out. The bandwidth channel information contains estimation delay, the pilot channel noise and pilot contamination. Afterwards, Zero Forcing precoding methodology has applied for removing the interference at user nodes, destination nodes and gateway side. By extending the characteristics of ZF, the modified Zero Forcing (MZF) has proposed to achieve higher throughput rate and higher spectrum efficiency. The achievable-rates of the ZF and MZF has derived under the comprehensive model of imperfect bandwidth information.
Modelling foreign exchange rates: a comparison between markov-switching and markov-switching GARCH Mohd Azizi Amin Nunian; Siti Meriam Zahari; S.Sarifah Radiah Shariff
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 2: November 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i2.pp917-923

Abstract

Foreign exchange rate is important as it determines a country's economic condition. It is used to carry out transfers of purchasing power between two or more countries. Volatility in exchange rates may result in difficulty in decision making especially, in financial sectors as high volatility could increase the risk in exchange rates. Thus, Markov switching model is employed in this study as it is believed to be efficient in handling not only volatilility but also nonlinearity characteristics in exchange rates. The aims of this study are to model the foreign exchange rates using two models; markov switching (M-S) models and markov switching generalized autoregressive conditional heteroscedasticity (M-S GARCH) and to compare these two models based on log-likelihood, AIC and BIC criteria. This study used the quarterly data of foreign exchange rates for singapore dollar (SGD), korean won (KRW), China yuan renminbi (CNY), Japanese yen (JPY) and the US dollar (USD) against Malaysia ringgit (MYR) which were collected from Quarter 4, 2006 to Quarter 1, 2018. The findings indicate that Markov Switching is the best model since it has the highest log-likelihood value, and the lowest AIC and BIC values. The results show that JPY and SGD have highly persistent trends on regime 1 with probability values 0.96 and 0.84, respectively as compared to CNY, KRW and USD, while the latter have high persistent trends on regime 2 with probability values, 0.99, 0.95, 0.82, respectively.
Conceptual Search Based on Semantic Relatedness Abdoulahi Boubacar; Zhendong Niu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 8: August 2014
Publisher : Institute of Advanced Engineering and Science

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

Abstract

Traditional search engines based on syntactic search are unable to solve key issues like synonymy and polysemy. Solving these issues leads to the invention of the semantic web. The semantic search engines indeed overcome these issues. Nowadays the most important part of the data remains unstructured documents. It is consequently very time consuming to annotate such big data. Concept based retrieval systems intend to manage directly unstructured documents. Semantic relationships are their main feature to extend syntactic search. In most of the methods implemented so far, concepts are used for both indexing and searching. Words remain the smallest unit to process semantic relatedness. The differences persist in the way that concepts are represented, mapped to each other, and managed for the sake of indexing and/or searching. Our approach is based on Wikipedia concepts. Concepts are represented as an undirected graph. Their semantic relatedness are computed with a distance derived from a semantic similarity measure. The same distance is used to calculate both semantic relatedness and query matching. DOI:  http://dx.doi.org/10.11591/telkomnika.v12i8.5143 
A noble approach to develop dynamically scalable namenode in hadoop distributed file system using secondary storage Tumpa Rani Shaha; Md. Nasim Akhtar; Fatema Tuj Johora; Md. Zakir Hossain; Mostafijur Rahman; R. B. Ahmad
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp729-736

Abstract

For scalable data storage, Hadoop is widely used nowadays. It provides a distributed file system that stores data on the compute nodes. Basically, it represents a master/slave architecture that consists of a NameNode and copious Data Nodes. Data Nodes contain application data and metadata of application data resides in the Main Memory of NameNode. In cached approach, they fragment the metadata depending on the last access time and move the least frequently used data to secondary memory. If the requested data is not found in main memory then the secondary data will be loaded again on the RAM. So when the secondary data reloads to the primary memory then the NameNode main memory limitation arises again. The focus of this research is to reduce the namespace problem of main memory and to make the system dynamically scalable. A new Metadata Fragmentation Algorithm is proposed that separates the metadata list of NameNode dynamically. The NameNode creates Secondary Memory File in perspective of the threshold value and allocates secondary memory location based on the requirement. According to the proposed algorithm the maximum third, out of fourth of main memory is used at the secondary file caching time. The free space aids in faster operation by Dynamically Scalable NameNode approach. This proposed algorithm shows that the space utilization is increased to 17% and time utilization is increased to 0.0005% with the comparison of the existing fragmentation algorithm.
A Strategy Research on MPPT Technique in Photovoltaic Power Generation System Fu Qiang; Tong Nan
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 12: December 2013
Publisher : Institute of Advanced Engineering and Science

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

Abstract

Output mode of photovoltaic cell is a complex transcendental equation, which is rather difficult to figure out by the numerical method. Traditional MPPT requests highly of initial value with low accuracy. In this thesis, simulation model of photovoltaic cell is built to simulate environmental situations under different lights and temperatures, taking advantage of particle swarm and ant colony intelligent algorithm to track the maximum power point of photovoltaic cell. Furthermore, a kind of intelligent perturbative tracking method is put forward combined with traditional perturbative tracking and intelligent tracking. The simulation result showing that intelligent perturbative tracking strategy has superior accuracy and adaptability than traditional MPPT method. DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.3685

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