Original/Review Paper
1. Classification of sEMG Signals for Diagnosis of Unilateral Posterior Crossbite in Primary Dentition using Fast Fourier Transform and Logistic Regression

H. Kalani; E. Abbasi

Articles in Press, Accepted Manuscript, Available Online from 19 February 2022

http://dx.doi.org/10.22044/jadm.2022.10908.2234

Abstract
  Posterior crossbite is a common malocclusion disorder in the primary dentition that strongly affects masticatory function. To the best of the author’s knowledge, for the first time, this article presents a reasonable and computationally efficient diagnostic system for detecting characteristics ...  Read More

Original/Review Paper
2. A Novel Classification and Diagnosis of Multiple Sclerosis Method using Artificial Neural Networks and Improved Multi-Level Adaptive Conditional Random Fields

Seyedeh R. Mahmudi Nezhad Dezfouli; Y. Kyani; Seyed A. Mahmoudinejad Dezfouli

Articles in Press, Accepted Manuscript, Available Online from 27 February 2022

http://dx.doi.org/10.22044/jadm.2021.10647.2201

Abstract
  Due to the small size, low contrast, variable position, shape, and texture of multiple sclerosis lesions, one of the challenges of medical image processing is the automatic diagnosis and segmentation of multiple sclerosis lesions in Magnetic resonance images. Early diagnosis of these lesions in the first ...  Read More

Original/Review Paper
3. Clustering Methods to Analyze Social Media Posts during Coronavirus Pandemic in Iran

F. Amiri; S. Abbasi; M. Babaie mohamadeh

Articles in Press, Accepted Manuscript, Available Online from 11 April 2022

http://dx.doi.org/10.22044/jadm.2022.11270.2285

Abstract
  During the COVID-19 crisis, we face a wide range of thoughts, feelings, and behaviors on social media that play a significant role in spreading information regarding COVID-19. Trustful information, together with hopeful messages, could be used to control people's emotions and reactions during pandemics. ...  Read More

Technical Paper
4. Abnormal Behavior Detection over Normal Data and Abnormal-augmented Data in Crowded Scenes

V. Fazel Asl; B. Karasfi; B. Masoumi

Articles in Press, Accepted Manuscript, Available Online from 12 April 2022

http://dx.doi.org/10.22044/jadm.2022.11061.2253

Abstract
  In this article, we consider the problems of abnormal behavior detection in a high-crowded environment. One of the main issues in abnormal behavior detection is the complexity of the structure patterns between the frames. In this paper, social force and optical flow patterns are used to prepare the system ...  Read More

Original/Review Paper
5. Increasing Performance of Recommender Systems by Combining Deep Learning and Extreme Learning Machine

Z. Nazari; H.R. Koohi; J. Mousavi

Articles in Press, Accepted Manuscript, Available Online from 13 April 2022

http://dx.doi.org/10.22044/jadm.2022.11248.2279

Abstract
  Nowadays, with the expansion of the internet and its associated technologies, recommender systems have become increasingly common. In this work, the main purpose is to apply new deep learning-based clustering methods to overcome the data sparsity problem and increment the efficiency of recommender systems ...  Read More

Applied Article
6. Distributed Online Pre-Processing Framework for Big Data Sentiment Analytics

M. Molaei; D. Mohamadpur

Articles in Press, Accepted Manuscript, Available Online from 17 April 2022

http://dx.doi.org/10.22044/jadm.2022.11330.2293

Abstract
  Performing sentiment analysis on social networks big data can be helpful for various research and business projects to take useful insights from text-oriented content. In this paper, we propose a general pre-processing framework for sentiment analysis, which is devoted to adopting FastText with Recurrent ...  Read More

Original/Review Paper
7. A hybridization method of prototype generation and prototype selection for K-NN rule based on GSA

M. Rezaei; H. Nezamabadi-pour

Articles in Press, Accepted Manuscript, Available Online from 26 April 2022

http://dx.doi.org/10.22044/jadm.2021.10159.2154

Abstract
  The present study aims to overcome some defects of the K-nearest neighbor (K-NN) rule. Two important data preprocessing methods to elevate the K-NN rule are prototype selection (PS) and prototype generation (PG) techniques. Often the advantage of these techniques is investigated separately. In this paper, ...  Read More

Original/Review Paper
8. Detecting Group Review Spammers in Social Media

Zeinab Teimoori; Mostafa Salehi; Vahid Ranjbar; Saeedreza Shehnepoor; Shaghayegh Najari

Articles in Press, Accepted Manuscript, Available Online from 26 April 2022

http://dx.doi.org/10.22044/jadm.2022.10981.2245

Abstract
  Nowadays, some e-advice websites and social media like e-commerce businesses, provide not only their goods but a new way that their customers can give their opinions about products. Meanwhile, there are some review spammers who try to promote or demote some specific products by writing fraud reviews. ...  Read More

Other
9. Automatic Detection of Lung Nodules on Computer Tomography Scans with a Deep Direct Regression Method

Kh. Aghajani

Articles in Press, Accepted Manuscript, Available Online from 26 April 2022

http://dx.doi.org/10.22044/jadm.2022.11431.2303

Abstract
  Deep-learning-based approaches have been extensively used in detecting pulmonary nodules from computer Tomography (CT) scans. In this study, an automated end-to-end framework with a convolution network (Conv-net) has been proposed to detect lung nodules from CT images. Here, boundary regression has been ...  Read More

Original/Review Paper F.2. Numerical Analysis
10. Upgrading the Human Development Index (HDI) to control pandemic mortality rates: A data mining approach to COVID-19

Saba Sareminia

Articles in Press, Accepted Manuscript, Available Online from 04 May 2022

http://dx.doi.org/10.22044/jadm.2022.11503.2307

Abstract
  In recent years, the occurrence of various pandemics (COVID-19, SARS, etc.) and their widespread impact on human life have led researchers to focus on their pathology and epidemiology components. One of the most significant inconveniences of these epidemics is the human mortality rate, which has highly ...  Read More

Original/Review Paper
11. Automatic Visual Inspection System based on Image Processing and Neural Network for Quality Control of Sandwich Panel

V. Torkzadeh; S. Toosizadeh

Articles in Press, Accepted Manuscript, Available Online from 06 May 2022

http://dx.doi.org/10.22044/jadm.2022.11002.2247

Abstract
  In this study, an automatic system based on image processing methods using features based on convolutional neural networks is proposed to detect the degree of possible dipping and buckling on the sandwich panel surface by a colour camera. The proposed method, by receiving an image of the sandwich panel, ...  Read More

Original/Review Paper
12. A Hybrid Deep Network Representation Model for Detecting Researchers’ Communities

A. Torkaman; K. Badie; A. Salajegheh; M. H. Bokaei; Seyed F. Fatemi

Articles in Press, Accepted Manuscript, Available Online from 06 May 2022

http://dx.doi.org/10.22044/jadm.2022.11243.2277

Abstract
  Recently, network representation has attracted many research works mostly concentrating on representing of nodes in a dense low-dimensional vector. There exist some network embedding methods focusing only on the node structure and some others considering the content information within the nodes. In this ...  Read More

Original/Review Paper
13. Voice Activity Detection using Clustering-based Method in Spectro-Temporal Features Space

N. Esfandian; F. Jahani bahnamiri; S. Mavaddati

Articles in Press, Accepted Manuscript, Available Online from 14 May 2022

http://dx.doi.org/10.22044/jadm.2022.11439.2304

Abstract
  This paper proposes a novel method for voice activity detection based on clustering in spectro-temporal domain. In the proposed algorithms, auditory model is used to extract the spectro-temporal features. Gaussian Mixture Model and WK-means clustering methods are used to decrease dimensions of the spectro-temporal ...  Read More

Original/Review Paper
14. A New Approach to Estimate Motion and Structure of a Moving Rigid Object in a 3D Space with a Single Hand-held Camera

R. Serajeh; A. Mousavinia; F. Safaei

Articles in Press, Accepted Manuscript, Available Online from 14 May 2022

http://dx.doi.org/10.22044/jadm.2022.11167.2267

Abstract
  Classical SFM (Structure From Motion) algorithms are widely used to estimate the three-dimensional structure of a stationary scene with a moving camera. However, when there are moving objects in the scene, if the equation of the moving object is unknown, the approach fails. This paper first demonstrates ...  Read More

Original/Review Paper
15. AgriNet: a new classifying convolutional neural network for detecting agricultural products’ diseases

F. Salimian Najafabadi; M. T. Sadeghi

Articles in Press, Accepted Manuscript, Available Online from 21 May 2022

http://dx.doi.org/10.22044/jadm.2022.11360.2295

Abstract
  An important sector that has a significant impact on the economies of countries is the agricultural sector. Researchers are trying to improve this sector by using the latest technologies. One of the problems facing farmers in the agricultural activities is plant diseases. If a plant problem is diagnosed ...  Read More

Viewpoint/Perspective/Opinion
16. Q-LVS: A Q-learning-based algorithm for video streaming in peer-to-peer networks considering a token-based incentive mechanism

Z. Imanimehr

Articles in Press, Accepted Manuscript, Available Online from 21 May 2022

http://dx.doi.org/10.22044/jadm.2022.11293.2287

Abstract
  Peer-to-peer video streaming has reached great attention during recent years. Video streaming in peer-to-peer networks is a good way to stream video on the Internet due to the high scalability, high video quality, and low bandwidth requirements. In this paper the issue of live video streaming in peer-to-peer ...  Read More