Seifedine Kadry
Beirut Arab University

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Journal : Bulletin of Electrical Engineering and Informatics

Selection of optimal hyper-parameter values of support vector machine for sentiment analysis tasks using nature-inspired optimization methods Lakshmana Kumar Ramasamy; Seifedine Kadry; Sangsoon Lim
Bulletin of Electrical Engineering and Informatics Vol 10, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i1.2098

Abstract

Sentiment analysis and classification task is used in recommender systems to analyze movie reviews, tweets, Facebook posts, online product reviews, blogs, discussion forums, and online comments in social networks. Usually, the classification is performed using supervised machine learning methods such as support vector machine (SVM) classifier, which have many distinct parameters. The selection of the values for these parameters can greatly influence the classification accuracy and can be addressed as an optimization problem. Here we analyze the use of three heuristics, nature-inspired optimization techniques, cuckoo search optimization (CSO), ant lion optimizer (ALO), and polar bear optimization (PBO), for parameter tuning of SVM models using various kernel functions. We validate our approach for the sentiment classification task of Twitter dataset. The results are compared using classification accuracy metric and the Nemenyi test.
An efficient apriori algorithm for frequent pattern mining using mapreduce in healthcare data M. Sornalakshmi; S. Balamurali; M. Venkatesulu; M. Navaneetha Krishnan; Lakshmana Kumar Ramasamy; Seifedine Kadry; Sangsoon Lim
Bulletin of Electrical Engineering and Informatics Vol 10, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i1.2096

Abstract

The development for data mining technology in healthcare is growing today as knowledge and data mining are a must for the medical sector. Healthcare organizations generate and gather large quantities of daily information. Use of IT allows for the automation of data mining and information that help to provide some interesting patterns which remove manual tasks and simple data extraction from electronic records, a process of electronic data transfer which secures medical records, saves lives and cuts the cost of medical care and enables early detection of infectious diseases. In this research paper an improved Apriori algorithm names enhanced parallel and distributed apriori (EPDA) is presented for the health care industry, based on the scalable environment known as Hadoop MapReduce. The main aim of the work proposed is to reduce the huge demands for resources and to reduce overhead communication when frequent data are extracted, through split-frequent data generated locally and the early removal of unusual data. The paper shows test results, whereby the EPDA performs in terms of the time and number of rules generated with a database of healthcare and different minimum support values.
Image processing based eye detection methods a theoretical review B. Vijayalaxmi; Chavali Anuradha; Kaushik Sekaran; Maytham N. Meqdad; Seifedine Kadry
Bulletin of Electrical Engineering and Informatics Vol 9, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (458.912 KB) | DOI: 10.11591/eei.v9i3.1783

Abstract

Lately, many of the road accidents have been attributed to the driver stupor. Statistics revealed that about 32% of the drivers who met with such accidents demonstrated the symptoms of tiredness before the mishap though at varying levels. The purpose of this research paper is to revisit the various interventions that have been devised to provide for assistance to the vehicle users to avert unwarranted contingencies on the roads. The paper tries to make a sincere attempt to encapsulate the body of work that has been initiated so far in this direction. As is evident, there are numerous ways in which one can identify the fatigue of the driver, namely biotic or physiological gauges, vehicle type and more importantly the analysis of the face in terms of its alignment and other attributes.