Number of Issues

2

Article View

7,165

PDF Download

9,866

View Per Article

255.89

PDF Download Per Article

352.36

Number of Submissions

49

Rejected Submissions

3

Reject Rate

6

Accepted Submissions

26

Acceptance Rate

53

Time to Accept (Days)

168

Number of Indexing Databases

9

Number of Reviewers

46

The Journal of Data Science and Modeling is an open-access, double-blind, peer-reviewed journal published by Allameh Tabataba’i University the leading university in Humanities and Social Sciences in Iran. Data Science and Modeling has been established to provide an intellectual platform for national and international researchers working on issues related to Data Science and Modeling.

To allow for easy and worldwide access to the most updated research findings, the journal is set to be an open-access journal. All submitted papers should report original and unpublished experimental or theoretical research results until they will be reviewed. Papers submitted to the journal should meet those criteria and must not be under consideration for publishing elsewhere. The journal is published in both a print and an online version.

About Journal of Data Science and Modeling:

  • Country of Publication: Iran
  • Publisher: Allameh Tabataba’i University Press
  • Format: Print and Online
  • Start Publishing: 2022
  • Print-ISSN: 2676-5926
  • E-ISSN: 2980-9010
  • Available from: ATU Press, Google Scholar, Magiran, Civilica, ...
  • Impact Factor (ISC): --
  • Frequency: Semiannual
  • Publication Dates: 2022
  • Language: English
  • Scope: Computational Statistics, Statistical modeling,  Data science.
  • Article Processing Charges: No
  • Type of Journal: Academic / Scholarly
  • Open Access: Yes
  • Indexed & Abstracted: Google Scholar, Civilica
  • Policy: Peer Review
  • Initial Review Time: up to ten days
  • Review Time: Three Weeks, approximately
  • Contact E-mail: jcsm@atu.ac.ir
  • Alternate E-mail: askandari@atu.ac.ir
Statistical Computing
Investigating the Effective Factors on Adoption of E-Learning System in Qazvin University of Medical Sciences

Hassan Rashidi; Hamed Heidari; Marzie Movahedin; Maryam Moazami Gudarzi; Mostafa Shakerian

Volume 1, Issue 2 , June 2023, Pages 1-27

https://doi.org/10.22054/jcsm.2019.43349.1017

Abstract
  The purpose of this research is to identify and introduce effective factors in adoption of e-learning based on technology adoption model. Accordingly, by considering the studies conducted in this field, several variables such as computer self-efficacy, content quality, system support, interface design, ...  Read More

Mathematical Computing
Some Theoretical Results on the Tensor Elliptical Distribution

Mohammad Arashi

Volume 1, Issue 2 , June 2023, Pages 29-41

https://doi.org/10.22054/jcsm.2021.47404.1019

Abstract
  The multilinear normal distribution is a widely used tool in the tensor analysis of magnetic resonance imaging (MRI). Diffusion tensor MRI provides a statistical estimate of a symmetric 2nd-order diffusion tensor for each voxel within an imaging volume. In this article, tensor elliptical (TE) distribution ...  Read More

Statistical Computing
Assessment and Modeling of Interval-Valued Variables in Generalized Linear Models

farzad eskandari

Volume 1, Issue 2 , June 2023, Pages 43-70

https://doi.org/10.22054/jcsm.2021.52523.1020

Abstract
  Interval-valued data are observed as ranges instead of single values and contain richer information thansingle-valued data. Meanwhile, interval-valued data are used for interval-valued characteristics. An intervalgeneralized linear model is proposed for the first time in this research. Then a suitable ...  Read More

Estimation for the Reliability Characteristics of a Family of Lifetime Distributions under Progressive Censoring

Alireza Safariyan; Reza Arabi Belaghi

Volume 1, Issue 2 , June 2023, Pages 71-86

https://doi.org/10.22054/jcsm.2021.53672.1021

Abstract
  In this paper, the probability of failure-free operation until time t, along with the probability of stress-strength, based on progressive censoring data is studied in a family of lifetime distributions. Since the number of data in a progressive censoring scheme is usually reduced, so shrinkage methods ...  Read More

Bayesian Network
A Simple Gibbs Sampler for Learning Bayesian Network Structure

Vahid Rezaei Tabar

Volume 1, Issue 2 , June 2023, Pages 87-97

https://doi.org/10.22054/jcsm.2021.55657.1022

Abstract
  The aim of this paper is to learn a Bayesian network structure for discrete variables. For this purpose, we introduce a Gibbs sampler method. Each sample represents a Bayesian network. Thus, in the process of Gibbs sampling, we obtain a set of Bayesian networks. For achieving a single graph that represents ...  Read More

Statistical Simulation
Estimation of Fixed Parameters in Negative Binomial Mixed Model Using Shrinkage Estimators

Zahra Zandi; Hossein Bevrani; Reza Arabi Belaghi

Volume 1, Issue 2 , June 2023, Pages 99-124

https://doi.org/10.22054/jcsm.2021.56488.1023

Abstract
  ‎In this paper‎, ‎we consider the problem of parameter estimation in {color{blue} negative binomial mixed model} when it is suspected that some of the fixed parameters may be restricted to a subspace via linear shrinkage‎, ‎{color{blue} preliminary test}‎, ‎shrinkage {color{blue} ...  Read More

Mathematical Computing
Mathematical Modeling of Behavior of Retrofitted RC Frames

Ali Moafi; Ali Kheyroddin; Hamid Saberi; Vahid Saberi

Volume 1, Issue 2 , June 2023, Pages 125-138

https://doi.org/10.22054/jcsm.2021.59910.1024

Abstract
  Due to several reasons as the low resistance of constructed concrete and also change in codes or application of structures, some concrete frames need to be retrofitted. By adding the steel prop and curb to the reinforced concrete, many parameters are changed such as ductility, resistance, and stiffness. ...  Read More

Mathematical Computing
New ‎Adaptive Monte Carlo Algorithm ‎t‎o Solve ‎Financial‎ Option ‎Pricing Problems‎

Mahboubeh Aalaei

Volume 1, Issue 2 , June 2023, Pages 139-151

https://doi.org/10.22054/jcsm.2021.60573.1025

Abstract
  In this paper, a new adaptive Monte Carlo algorithm is proposed to solve ‎the ‎systems ‎of ‎linear ‎algebraic ‎equations ‎arising ‎from‎ the Black–Scholes model ‎to ‎price‎ European and American options. The proposed algorithm offers several advantages ...  Read More

Routing Optimization in Wireless Sensor Networks to Increase Network Life by Managing Network Energy

bahareh asadi

Volume 1, Issue 2 , June 2023, Pages 153-169

https://doi.org/10.22054/jcsm.2022.64359.1029

Abstract
  One of the important challenges in Wireless Sensor Networks is to proceeds data transmission in a way that tries to increase the life of the network. One of the main issues is the reduction of latency in the node and energy in the sink nodes. Due to the limited energy of the nodes, data transmission ...  Read More

Semiparametric Models in Finite Mixture of Negative Binomial Responses

sima naghizadeh

Volume 1, Issue 2 , June 2023, Pages 171-190

https://doi.org/10.22054/jcsm.2022.66414.1031

Abstract
  Abstract: so many natural phenomena of determining relationship and the effect of input variables on response variable in statistical studies may be different from the suggested model that the researcher selects for his study due to the occupant exists in the structure of data. It may be so influential ...  Read More

Static Sign Language Recognition Using Depth Data Based on Geometric Features

Zahra Aghajani; mostafa karbasi; Bahareh asadi

Volume 1, Issue 2 , June 2023, Pages 191-203

https://doi.org/10.22054/jcsm.2022.63486.1028

Abstract
  Deaf people or people with hearing loss have a major problem in everyday communication. There are many applications available in the market to help blind people to interact with the world. Voice-based email and chatting systems are available to communicate with each other by blinds. This helps to interact ...  Read More

A Bayesian Semiparametric Random Effect Model for Meta-Regression

Ehsan Ormoz

Volume 1, Issue 2 , June 2023, Pages 205-223

https://doi.org/10.22054/jcsm.2022.69925.1032

Abstract
  In this paper, we will introduce a Bayesian semiparametric model concerned with both constant and coefficients. In Meta-Analysis or Meta-Regression, we usually use a parametric family. However, lately the increasing tendency to use Bayesian nonparametric and semiparametric models, entered this area too. ...  Read More

The impact of audit quality on reducing collateral facilities and the role of major shareholders in listed companies of Tehran exchange market

Mahsa Ghajarbeigi; Hamid Reza Vakely fard; Ramzanali Roeayi

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

https://doi.org/10.22054/jcsm.2022.70725.1035

Abstract
  The purpose of this paper was to investigate the impact of audit quality on the reduction of collateral facilities, taking into account the role of major shareholders in companies listed on the Tehran Stock Exchange during the period 2017 to 2022. Considering the research conditions, 179 companies were ...  Read More

A New Approach Based on Business Intelligence and Bayesian Network for Analysis of Corporate Accounting Systems

azar ghyasi; hanieh rashidi

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

https://doi.org/10.22054/jcsm.2022.69949.1033

Abstract
  Due to the inherent complexity and increasing competition, today's business environment requires new approaches in organizing and managing. One of the new approaches is business intelligence, which is the most critical technology to help manage and deliver smart services, especially business reporting. ...  Read More

Machine Learning
INTELLIGENT MODELING OF PERSIAN VERNACULAR ARCHITECTURE BASED ON THE FUZZY DELPHI METHOD (FDM)

Mostafa Azghandi; Mahdi Yaghoobi; Elham Fariborzi

Articles in Press, Accepted Manuscript, Available Online from 03 March 2024

https://doi.org/10.22054/jdsm.2024.78060.1042

Abstract
  By focusing on the fuzzy Delphi technique (FDM), the current research introduces a novel approach to modeling Persian vernacular architecture. Fuzzy Delphi is a more advanced version of the Delphi Method, which utilizes triangulation statistics to determine the distance between the levels of consensus ...  Read More

Statistical Simulation
Automatic evaluation of record linkage methods in the expert system of producing statistical registers: string metric approach

Vadood keramati; Ramin Sadeghian; Maryam Hamedi; Ashkan Shabbak

Articles in Press, Accepted Manuscript, Available Online from 03 June 2024

https://doi.org/10.22054/jdsm.2024.76812.1039

Abstract
  Record linkage is a tool used to gather information and data from different sources. It is used in activities related to government, such as e-government and the production of register-based data. This method compares the strings in the databases and there are different methods for record linkage, such ...  Read More