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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Subhi R. M. Zeebaree
Duhok Polytechnic University

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Classification techniques’ performance evaluation for facial expression recognition Mayyadah R. Mahmood; Maiwan B. Abdulrazaq; Subhi R. M. Zeebaree; Abbas Kh. Ibrahim; Rizgar Ramadhan Zebari; Hivi Ismat Dino
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp1176-1184

Abstract

Facial exprestion recognition as a recently developed method in computer vision is founded upon the idea of analazing the facial changes in which are witnessed due to emotional impacts on an individual. This paper provides a performance evaluation of a set of supervised classifiers used for facial expression recognition based on minimum features selected by chi-square. These features are the most iconic and influential ones that have tangible value for result dermination. The highest ranked six features are applied on six classifiers including multi-layer preceptron, support vector machine, decision tree, random forest, radial baised function, and k-nearest neioughbor to figure out the most accurate one when the minum number of features are utilized. This is done via analyzing and appraising the classifiers’ performance. CK+ is used as the research’s dataset. Random forest with the total accuracy ratio of 94.23 % is illustrated as the most accurate classifier amongst the rest. 
A state-of-the-art survey on semantic similarity for document clustering using GloVe and density-based algorithms Shapol M. Mohammed; Karwan Jacksi; Subhi R. M. Zeebaree
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp552-562

Abstract

Semantic similarity is the process of identifying relevant data semantically. The traditional way of identifying document similarity is by using synonymous keywords and syntactician. In comparison, semantic similarity is to find similar data using meaning of words and semantics. Clustering is a concept of grouping objects that have the same features and properties as a cluster and separate from those objects that have different features and properties. In semantic document clustering, documents are clustered using semantic similarity techniques with similarity measurements. One of the common techniques to cluster documents is the density-based clustering algorithms using the density of data points as a main strategic to measure the similarity between them. In this paper, a state-of-the-art survey is presented to analyze the density-based algorithms for clustering documents. Furthermore, the similarity and evaluation measures are investigated with the selected algorithms to grasp the common ones. The delivered review revealed that the most used density-based algorithms in document clustering are DBSCAN and DPC. The most effective similarity measurement has been used with density-based algorithms, specifically DBSCAN and DPC, is Cosine similarity with F-measure for performance and accuracy evaluation.
DES encryption and decryption algorithm implementation based on FPGA Subhi R. M. Zeebaree
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 2: May 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i2.pp774-781

Abstract

Nowadays there is a lot of importance given to data security on the internet. The DES is one of the most preferred block cipher encryption/decryption procedures used at present. This paper presents a high throughput reconfigurable hardware implementation of DES Encryption algorithm. This achieved by using a new proposed implementation of the DES algorithm using pipelined concept.  The implementation of the proposed design is presented by using Spartan-3E (XC3S500E) family FPGAs and is one of the fastest hardware implementations with much greater security. At a clock frequency of 167.448MHz for encryption and 167.870MHz for decryption, it can encrypt or decrypt data blocks at a rate of 10688Mbps.
Co-Authors Abbas Kh. Ibrahim Hivi Ismat Dino Karwan Jacksi Maiwan B. Abdulrazaq Mayyadah R. Mahmood Rizgar Ramadhan Zebari Shapol M. Mohammed