Original/Review Paper
Convolutional Neural Network Equipped with Attention Mechanism and Transfer Learning for Enhancing Performance of Sentiment Analysis

H. Sadr; Mir M. Pedram; M. Teshnehlab

Volume 9, Issue 2 , April 2021, Pages 141-151


  With the rapid development of textual information on the web, sentiment analysis is changing to an essential analytic tool rather than an academic endeavor and numerous studies have been carried out in recent years to address this issue. By the emergence of deep learning, deep neural networks have attracted ...  Read More

Original/Review Paper
Automatic Facial Expression Recognition Method Using Deep Convolutional Neural Network

Seyedeh H. Erfani

Volume 9, Issue 2 , April 2021, Pages 153-159


  Facial expressions are part of human language and are often used to convey emotions. Since humans are very different in their emotional representation through various media, the recognition of facial expression becomes a challenging problem in machine learning methods. Emotion and sentiment analysis ...  Read More

Original/Review Paper
Diagnosis of Multiple Sclerosis Disease in Brain MRI Images using Convolutional Neural Networks based on Wavelet Pooling

A. Alijamaat; A. Reza NikravanShalmani; P. Bayat

Volume 9, Issue 2 , April 2021, Pages 161-168


  Multiple Sclerosis (MS) is a disease that destructs the central nervous system cell protection, destroys sheaths of immune cells, and causes lesions. Examination and diagnosis of lesions by specialists is usually done manually on Magnetic Resonance Imaging (MRI) images of the brain. Factors such as small ...  Read More

Original/Review Paper
Automatic Persian Text Emotion Detection using Cognitive Linguistic and Deep Learning

Seyedeh S. Sadeghi; H. Khotanlou; M. Rasekh Mahand

Volume 9, Issue 2 , April 2021, Pages 169-179


  In the modern age, written sources are rapidly increasing. A growing number of these data are related to the texts containing the feelings and opinions of the users. Thus, reviewing and analyzing of emotional texts have received a particular attention in recent years. A System which is based on combination ...  Read More

Original/Review Paper
ParsNER-Social: A Corpus for Named Entity Recognition in Persian Social Media Texts

M. Asgari-Bidhendi; B. Janfada; O. R. Roshani Talab; B. Minaei-Bidgoli

Volume 9, Issue 2 , April 2021, Pages 181-192


  Named Entity Recognition (NER) is one of the essential prerequisites for many natural language processing tasks. All public corpora for Persian named entity recognition, such as ParsNERCorp and ArmanPersoNERCorpus, are based on the Bijankhan corpus, which is originated from the Hamshahri newspaper in ...  Read More

Original/Review Paper
Developing a Novel Continuous Metabolic Syndrome Score: A Data Mining Based Model

M. Saffarian; V. Babaiyan; K. Namakin; F. Taheri; T. Kazemi

Volume 9, Issue 2 , April 2021, Pages 193-202


  Today, Metabolic Syndrome in the age group of children and adolescents has become a global concern. In this paper, a data mining model is used to determine a continuous Metabolic Syndrome (cMetS) score using Linear Discriminate Analysis (cMetS-LDA). The decision tree model is used to specify the calculated ...  Read More

Original/Review Paper
Online Recommender System Considering Changes in User's Preference

J. Hamidzadeh; M. Moradi

Volume 9, Issue 2 , April 2021, Pages 203-212


  Recommender systems extract unseen information for predicting the next preferences. Most of these systems use additional information such as demographic data and previous users' ratings to predict users' preferences but rarely have used sequential information. In streaming recommender systems, the emergence ...  Read More

Original/Review Paper
An Energy-aware Real-time Task Scheduling Approach in a Cloud Computing Environment

H. Momeni; N. Mabhoot

Volume 9, Issue 2 , April 2021, Pages 213-226


  Interest in cloud computing has grown considerably over recent years, primarily due to scalable virtualized resources. So, cloud computing has contributed to the advancement of real-time applications such as signal processing, environment surveillance and weather forecast where time and energy considerations ...  Read More

Original/Review Paper
A Novel Approach to Communicate with Video Game Character using Cascade Classifiers

M. Mohammadzadeh; H. Khosravi

Volume 9, Issue 2 , April 2021, Pages 227-234


  Today, video games have a special place among entertainment. In this article, we have developed an interactive video game for mobile devices. In this game, the user can control the game’s character by his face and hand gestures. Cascading classifiers along with Haar-like features and local binary ...  Read More

Original/Review Paper
Rice Classification with Fractal-based Features based on Sparse Structured Principal Component Analysis and Gaussian Mixture Model

S. Mavaddati; S. Mavaddati

Volume 9, Issue 2 , April 2021, Pages 235-244


  Development of an automatic system to classify the type of rice grains is an interesting research area in the scientific fields associated with modern agriculture. In recent years, different techniques are employed to identify the types of various agricultural products. Also, different color-based and ...  Read More

Original/Review Paper
Relevance Feedback-based Image Retrieval using Particle Swarm Optimization

F. Jafarinejad; R. Farzbood

Volume 9, Issue 2 , April 2021, Pages 245-257


  Image retrieval is a basic task in many content-based image systems. Achieving high precision, while maintaining computation time is very important in relevance feedback-based image retrieval systems. This paper establishes an analogy between this and the task of image classification. Therefore, in the ...  Read More

Original/Review Paper
Facial Expression Recognition based on Image Gradient and Deep Convolutional Neural Network

M. R. Fallahzadeh; F. Farokhi; A. Harimi; R. Sabbaghi-Nadooshan

Volume 9, Issue 2 , April 2021, Pages 259-268


  Facial Expression Recognition (FER) is one of the basic ways of interacting with machines and has been getting more attention in recent years. In this paper, a novel FER system based on a deep convolutional neural network (DCNN) is presented. Motivated by the powerful ability of DCNN to learn features ...  Read More