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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control)
Jesmeen M. Z. H.
Multimedia University
Computer Science & IT Electrical & Electronics Engineering

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A Survey of Machine Learning Techniques for Self-tuning Hadoop Performance Md. Armanur Rahman; J. Hossen; Venkataseshaiah C; CK Ho; Tan Kim Geok; Aziza Sultana; Jesmeen M. Z. H.; Ferdous Hossain
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 3: June 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (475.262 KB) | DOI: 10.11591/ijece.v8i3.pp1854-1862

Abstract

The Apache Hadoop framework is an open source implementation of MapReduce for processing and storing big data. However, to get the best performance from this is a big challenge because of its large number configuration parameters. In this paper, the concept of critical issues of Hadoop system, big data and machine learning have been highlighted and an analysis of some machine learning techniques applied so far, for improving the Hadoop performance is presented. Then, a promising machine learning technique using deep learning algorithm is proposed for Hadoop system performance improvement.
An Efficient Microcontroller Based Sun Tracker Control for Solar Cell Systems E.M.H. Arif; J. Hossen; G. Ramana Murthy; Jesmeen M. Z. H.; J. Emerson Raja
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (25.088 KB) | DOI: 10.11591/ijece.v9i4.pp2743-2750

Abstract

The solar energy is fast becoming a different means of electricity resource. Now in world Fossil fuels are seriously depleting thus the need for another energy source is a necessity. To create effective utilization of its solar, energy efficiency must be maximized. An attainable way to deal with amplifying the power output of sun-powered exhibit is by sun tracking. This paper presents the control system for a solar cell orientation device which follows the sun in real time during daytime.
AUTO-CDD: automatic cleaning dirty data using machine learning techniques Jesmeen M. Z. H.; Abid Hossen; J. Hossen; J. Emerson Raja; Bhuvaneswari Thangavel; S. Sayeed; Tawsif K.
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 4: August 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i4.12780

Abstract

Cleaning the dirty data has become very critical significance for many years, especially in medical sectors. This is the reason behind widening research in this sector. To initiate the research, a comparison between currently used functions of handling missing values and Auto-CDD is presented. The developed system will guarantee to overcome processing unwanted outcomes in data Analytical process; second, it will improve overall data processing. Our motivation is to create an intelligent tool that will automatically predict the missing data. Starting with feature selection using Random Forest Gini Index values. Then by using three Machine Learning Paradigm trained model was developed and evaluated by two datasets from UCI (i.e. Diabetics and Student Performance). Evaluated outcomes of accuracy proved Random Forest Classifier and Logistic Regression gives constant accuracy at around 90%. Finally, it concludes that this process will help to get clean data for further analytical process.
Co-Authors Abid Hossen Aziza Sultana Bhuvaneswari Thangavel CK Ho E.M.H. Arif Ferdous Hossain G. Ramana Murthy J. Emerson Raja J. Hossen Md. Armanur Rahman S. Sayeed Tan Kim Geok Tawsif K. Venkataseshaiah C