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International Research journal of Management Science and Technology (IRJMST)

Publisher :

IRJMST

Scopus Profile
Peer reviewed only
Scopus Profile
Open Access
  • Management
e-ISSN :

2250-1959

Issue Frequency :

3-issues-year

Impact Factor :

8.1026

p-ISSN :

2348-9367

Est. Year :

2009

Mobile :

9582846611

DOI :

YES

Country :

Afghanistan

Language :

English

APC :

YES

Email :

Research@isarasolutions.com

Journal Descriptions

International Research journal of Management Science and Technology was started in June 2010. The prime aim of this Research Journal is to share and link the Science , Technology , Management students and faculties, their views all over the world. IRJMST is a "peer-review" and "refereed" and "widely accepted" International journal. It is the committee through which experts in the field of study assess the quality of articles/journals that are submitted to it for publication. It is an open access journal that publishes high-quality research articles, all areas of Management Science and technology. The Journal welcomes the submission of manuscripts that meet the criteria of significance, academic excellence and great ideologies. Papers will be published approximately one week after acceptance.


International Research journal of Management Science and Technology (IRJMST) is :

International, Peer-Reviewed, Open Access, Refereed, Management , Online or Print, 3-issues-year Journal

UGC Approved, ISSN Approved: P-ISSN - 2348-9367, E-ISSN - 2250-1959, Established in - 2009, Impact Factor - 8.1026

Provide Crossref DOI

Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE

Publications of IRJMST

Research Article
  • dott image March, 2019

ON A RECURRENT FINSLER SPACE

The present paper is in two sections, the first section deals with special projective recurrent tensor fields while the second section deals with special recurrent Normal projective curvatur...

Research Article
  • dott image May, 2023

USER EXPERIENCE OF FEMININE PRODUCTS USAGE

Feminine products empower women but remain among the most challenging development issues today. Not only do deep-rooted taboos, myths, and misinformation create the illusion that feminine pr...

Active Learning for Semi-Supervised Clustering Framework for High Dimensional Data

In certain clustering tasks it is possible to obtain limited supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clusters. The...

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