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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Firas Sabah Al-Turaihi
University of Babylon
Electrical & Electronics Engineering

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Sentiment classification of user's reviews on drugs based on global vectors for word representation and bidirectional long short-term memory recurrent neural network Hadab Khalid Obayed; Firas Sabah Al-Turaihi; Khaldoon H. Alhussayni
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp345-353

Abstract

The process of product development in the health sector, especially pharmaceuticals, goes through a series of precise procedures due to its directrelevance to human life. The opinion of patients or users of a particular drugcan be relied upon in this development process, as the patients convey their experience with the drugs through their opinion. The social media field provides many datasets related to drugs through knowing the user's ratingand opinion on a drug after using it. In this work, a dataset is used that includes the user’s rating and review on the drug, for the purpose of classifying the user’s opinions (reviews) whether they are positive ornegative. The proposed method in this article includes two phases. The first phase is to use the Global vectors for word representation model for converting texts into the vector of embedded words. As for the second stage, the deep neural network (Bidirectional longshort-termmemory) is employedin the classification of reviews. The user's rating is used as a ground truth inevaluating the classification results. The proposed method present sencouraging results, as the classification results are evaluated through threecriteria, namely Precision, Recall and F-score, whose obtained values equal(0.9543, 0.9597and0.9558), respectively. The classification results of theproposed method are compared to a number of classifiers, and it was noticed that the results of the proposed method exceed those of the alternative classifiers.
Reducing waiting and idle time for a group of jobs in the grid computing Mahdi S. Almhanna; Firas Sabah Al-Turaihi; Tariq A. Murshedi
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.4729

Abstract

Johnson's rule is a scheduling method for the sequence of jobs. Its primary goal is to find the perfect sequence of functions to reduce the amount of idle time, and it also reduces the total time required to complete all functions. It is a suitable method for scheduling the purposes of two functions in a specific time-dependent sequence for both functions and where the time factor is the only parameter used in this way. Therefore, it is not suitable for scheduling work for computers network, where there are many factors affecting the completion time such as CPU speed, memory, bandwidth, and size of data. In this research, Johnson's method will adopt by adding many factors that affect the completion time of the work so that it becomes suitable for the site’s job scheduling purposes to reduce the waiting and idle time for a group of jobs.
Co-Authors Hadab Khalid Obayed Khaldoon H. Alhussayni Mahdi S. Almhanna Tariq A. Murshedi