Volume 8 (2020)
Volume 7 (2019)
Volume 6 (2018)
Volume 5 (2017)
Volume 4 (2016)
Volume 3 (2015)
Volume 2 (2014)
Volume 1 (2013)

Facts & Figures

(Up to Date)

Number of Volumes

9

Number of Issues

22

Article View

358,449

PDF Download

382,833

View Per Article

1280.18

PDF Download Per Article

1367.26

Reject Rate %

61

Acceptance Rate %

24

Number of Reviewers

3170

First Decision

(Approximately)

48(Days)

 

The Journal of Artificial Intelligence & Data Mining (JAIDM) is an international scientific journal that aims to develop the international exchange of scientific and technical information in all areas of Artificial Intelligence and Data Mining.

 All manuscripts with significant research results in the scope of the journal are welcome if they are not published or not being considered for publication elsewhere.

Journal of Artificial Intelligence & Data Mining appears quarterly considering the increasing importance of rapid, effective, international communication. JAIDM offers:

  • Publication within a short period after acceptance
  • On-line publication in advance of the printed journal
  • One journal copy  will be sent to the corresponding author
  • Printing, Processing and Delivery without any charges

Topics of interest include, but are not limited to, the following:

  • Artificial Intelligence Algorithms, Tools & Applications
  • Data Mining and Machine Learning Tools
  • Semantic Web Techniques and Technologies
  • Soft computing theory and applications
  • Web Intelligence Applications & Search
  • Bioinformatics
  • Natural Language Processing
  • Computer Vision and Image Processing
  • Speech Understanding
  • Fuzzy Logic
  • Information Retrieval
  • Intelligent System Architectures
  • Knowledge-based/ Expert Systems
  • Automatic Control
  • Neural Networks
  • Parallel Processing
  • Pattern Recognition
  •  Software & Hardware Architectures
   

All accepted papers will be checked by iThenticate against plagiarism. 


All type papers published by JAIDM are made freely and permanently accessible online immediately upon publication. JAIDM is an "Open access" publishing allows an immediate, world-wide, barrier-free, open access to the full text of research papers, which is in the best interests of the scientific community.

High visibility for maximum global exposure with open access publishing model rigorous peer review (blind peer-review) of research papers prompt faster publication.

JAIDM has no publication charges and no submission fees.

All corresponding authors of each manuscript should be download "COPYRIGHT RELEASE FORM" from above this page then complete and sign this form by all authors and submit this form with all mandatory files which mentioned in bellow. By signing this form, copyright transfer to JAIDM.

Submission of a manuscript implies that:

1) The work described has not been published before (except in the form of an abstract or as part of a published lecture, review, or thesis).

2) It is not under consideration for publication elsewhere.

3) Its publication has been approved by all coauthors, if any, as well as by the responsible authorities at the institute where the work has been carried out.

4) Authors agree to automatic transfer of the copyright to the publisher, if and when their manuscript is accepted for publication.

5) The manuscript will not be published elsewhere.

 

JAIDM respect all aspects of publication ethics of the Committee on Publication Ethics (COPE). COPE is a forum for editors and publishers of peer reviewed journals to discuss all aspects of publication ethics. COPE provides advice to editors and publishers on all aspects of publication ethics and, in particular, how to handle cases of research and publication misconduct. COPE does not investigate individual cases but encourages editors to ensure that cases are investigated by the appropriate authorities (usually a research institution or employer).

 

Original/Review Paper
1. 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 , Spring 2021, Pages 141-151

http://dx.doi.org/10.22044/jadm.2021.9618.2100

Abstract
  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
2. Automatic Facial Expression Recognition Method Using Deep Convolutional Neural Network

Seyedeh H. Erfani

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

http://dx.doi.org/10.22044/jadm.2020.8801.2018

Abstract
  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
3. 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 , Spring 2021, Pages 161-168

http://dx.doi.org/10.22044/jadm.2021.9783.2109

Abstract
  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
4. Automatic Persian Text Emotion Detection using Cognitive Linguistic and Deep Learning

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

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

http://dx.doi.org/10.22044/jadm.2020.9992.2136

Abstract
  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
5. 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 , Spring 2021, Pages 181-192

http://dx.doi.org/10.22044/jadm.2020.9949.2143

Abstract
  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
6. 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 , Spring 2021, Pages 193-202

http://dx.doi.org/10.22044/jadm.2021.10433.2179

Abstract
  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
7. Online Recommender System Considering Changes in User's Preference

J. Hamidzadeh; M. Moradi

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

http://dx.doi.org/10.22044/jadm.2020.9518.2085

Abstract
  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
8. An Energy-aware Real-time Task Scheduling Approach in a Cloud Computing Environment

H. Momeni; N. Mabhoot

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

http://dx.doi.org/10.22044/jadm.2021.10344.2171

Abstract
  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
9. A Novel Approach to Communicate with Video Game Character using Cascade Classifiers

M. Mohammadzadeh; H. Khosravi

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

http://dx.doi.org/10.22044/jadm.2020.9788.2110

Abstract
  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
10. 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 , Spring 2021, Pages 235-244

http://dx.doi.org/10.22044/jadm.2021.9583.2090

Abstract
  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
11. Relevance Feedback-based Image Retrieval using Particle Swarm Optimization

F. Jafarinejad; R. Farzbood

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

http://dx.doi.org/10.22044/jadm.2020.9014.2037

Abstract
  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
12. 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 , Spring 2021, Pages 259-268

http://dx.doi.org/10.22044/jadm.2021.9898.2121

Abstract
  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

1. Credit scoring in banks and financial institutions via data mining techniques: A literature review

Seyed Mahdi sadatrasoul; Mohammadreza gholamian; Mohammad Siami; Zeynab Hajimohammadi

Volume 1, Issue 2 , Summer 2013, , Pages 119-129

http://dx.doi.org/10.22044/jadm.2013.124

Abstract
  This paper presents a comprehensive review of the works done, during the 2000–2012, in the application of data mining techniques in Credit scoring. Yet there isn’t any literature in the field of data mining applications in credit scoring. Using a novel research approach, this paper investigates ...  Read More

H.5. Image Processing and Computer Vision
2. Multi-Focus Image Fusion in DCT Domain using Variance and Energy of Laplacian and Correlation Coefficient for Visual Sensor Networks

M. Amin-Naji; A. Aghagolzadeh

Volume 6, Issue 2 , Summer 2018, , Pages 233-250

http://dx.doi.org/10.22044/jadm.2017.5169.1624

Abstract
  The purpose of multi-focus image fusion is gathering the essential information and the focused parts from the input multi-focus images into a single image. These multi-focus images are captured with different depths of focus of cameras. A lot of multi-focus image fusion techniques have been introduced ...  Read More

3. Outlier Detection in Wireless Sensor Networks Using Distributed Principal Component Analysis

Mohammad Ahmadi Livani; mahdi Abadi; Meysam Alikhany; Meisam Yadollahzadeh Tabari

Volume 1, Issue 1 , Winter 2013, , Pages 1-11

http://dx.doi.org/10.22044/jadm.2013.98

Abstract
  Detecting anomalies is an important challenge for intrusion detection and fault diagnosis in wireless sensor networks (WSNs). To address the problem of outlier detection in wireless sensor networks, in this paper we present a PCA-based centralized approach and a DPCA-based distributed energy-efficient ...  Read More

4. On improving APIT algorithm for better localization in WSN

Seyed M. Hosseinirad; M. Niazi; J Pourdeilami; S. K. Basu; A. A. Pouyan

Volume 2, Issue 2 , Summer 2014, , Pages 97-104

http://dx.doi.org/10.22044/jadm.2014.148

Abstract
  In Wireless Sensor Networks (WSNs), localization algorithms could be range-based or range-free. The Approximate Point in Triangle (APIT) is a range-free approach. We propose modification of the APIT algorithm and refer as modified-APIT. We select suitable triangles with appropriate distance between anchors ...  Read More

5. QoS-Based web service composition based on genetic algorithm

Mohammad AllamehAmiri; Vali Derhami; Mohammad Ghasemzadeh

Volume 1, Issue 2 , Summer 2013, , Pages 63-73

http://dx.doi.org/10.22044/jadm.2013.97

Abstract
  Quality of service (QoS) is an important issue in the design and management of web service composition. QoS in web services consists of various non-functional factors, such as execution cost, execution time, availability, successful execution rate, and security. In recent years, the number of available ...  Read More

Original/Review Paper
1. Multi-Task Feature Selection for Speech Emotion Recognition: Common Speaker-Independent Features Among Emotions

E. Kalhor; B. Bakhtiari

Articles in Press, Accepted Manuscript, Available Online from 15 May 2021

http://dx.doi.org/10.22044/jadm.2021.9800.2118

Abstract
  Feature selection is the one of the most important steps in designing speech emotion recognition systems. Because there is uncertainty as to which speech feature is related to which emotion, many features must be taken into account and, for this purpose, identifying the most discriminative features is ...  Read More

Original/Review Paper
2. A Heuristic Algorithm for Multi-layer Network Optimization in Cloud Computing

A. Hadian; M. Bagherian; B. Fathi Vajargah

Articles in Press, Accepted Manuscript, Available Online from 15 May 2021

http://dx.doi.org/10.22044/jadm.2021.9955.2133

Abstract
  Background: One of the most important concepts in cloud computing is modeling the problem as a multi-layer optimization problem which leads to cost savings in designing and operating the networks. Previous researchers have modeled the two-layer network operating problem as an Integer Linear Programming ...  Read More

Original/Review Paper
3. A Hybrid Framework for Personality Prediction based on Fuzzy Neural Networks and Deep Neural Networks

N. Taghvaei; B. Masoumi; M. R. Keyvanpour

Articles in Press, Accepted Manuscript, Available Online from 23 May 2021

http://dx.doi.org/10.22044/jadm.2021.10583.2197

Abstract
  In general, humans are very complex organisms, and therefore, research into their various dimensions and aspects, including personality, has become an attractive subject of research. With the advent of technology, the emergence of a new kind of communication in the context of social networks has also ...  Read More

Original/Review Paper
4. Sequential Multi-objective Genetic Algorithm

L. Falahiazar; V. Seydi; M. Mirzarezaee

Articles in Press, Accepted Manuscript, Available Online from 25 May 2021

http://dx.doi.org/10.22044/jadm.2021.9598.2092

Abstract
  Many of the real-world issues have multiple conflicting objectives that the optimization between contradictory objectives is very difficult. In recent years, the Multi-objective Evolutionary Algorithms (MOEAs) have shown great performance to optimize such problems. So, the development of MOEAs will always ...  Read More

Original/Review Paper
5. Camera Arrangement using Geometric Optimization to Minimize Localization Error in Stereo-vision Systems

H. Kamali Ardakani; Seyed A. Mousavinia; F. Safaei

Articles in Press, Accepted Manuscript, Available Online from 25 May 2021

http://dx.doi.org/10.22044/jadm.2021.9855.2117

Abstract
  Stereo machine vision can be used as a Space Sampling technique and the cameras parameters and configuration can effectively change the number of Samples in each Volume of space called Space Sampling Density (SSD). Using the concept of Voxels, this paper presents a method to optimize the geometric configuration ...  Read More

Original/Review Paper
6. An Efficient Approach to Solve Software-defined Networks based Virtual Machines Placement Problem using Moth-Flame Optimization in the Cloud Computing Environment

A. H Safari-Bavil; S. Jabbehdari; M. Ghobaei-Arani

Articles in Press, Accepted Manuscript, Available Online from 29 May 2021

http://dx.doi.org/10.22044/jadm.2021.9737.2106

Abstract
  Generally, the issue of quality assurance is a specific assurance in computer networks. The conventional computer networks with hierarchical structures that are used in organizations are formed using some nodes of Ethernet switches within a tree structure. Open Flow is one of the main fundamental protocols ...  Read More

Review Article
7. A Mobile Charger based on Wireless Power Transfer Technologies: A Survey of Concepts, Techniques, Challenges, and Applications on Rechargeable Wireless Sensor Networks

N. Nowrozian; F. Tashtarian

Articles in Press, Accepted Manuscript, Available Online from 15 June 2021

http://dx.doi.org/10.22044/jadm.2021.9936.2127

Abstract
  Battery power limitation of sensor nodes (SNs) is a major challenge for wireless sensor networks (WSNs) which affects network survival. Thus, optimizing the energy consumption of the SNs as well as increasing the lifetime of the SNs and thus, extending the lifetime of WSNs are of crucial importance in ...  Read More

Original/Review Paper
8. Automatic Grayscale Image Colorization using a Deep Hybrid Model

K. Kiani; R. Hematpour; R. Rastgoo

Articles in Press, Accepted Manuscript, Available Online from 01 April 2021

http://dx.doi.org/10.22044/jadm.2021.9957.2131

Abstract
  Image colorization is an interesting yet challenging task due to the descriptive nature of getting a natural-looking color image from any grayscale image. To tackle this challenge and also have a fully automatic procedure, we propose a Convolutional Neural Network (CNN)-based model to benefit from the ...  Read More

Special Issue IJE

IJE Special Issue on Cyber Security and AI

Keywords Cloud