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Internet of Things (IoT) in Smart Systems and Applications
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General Information
ISSN:
1798-2340 (Online)
Frequency:
Monthly
DOI:
10.12720/jait
Indexing:
ESCI (Web of Science)
,
Scopus
,
CNKI
,
etc
.
Acceptance Rate:
12%
APC:
1000 USD
Average Days to Accept:
87 days
Journal Metrics:
Impact Factor 2023: 0.9
4.2
2023
CiteScore
57th percentile
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Editor-in-Chief
Prof. Kin C. Yow
University of Regina, Saskatchewan, Canada
I'm delighted to serve as the Editor-in-Chief of
Journal of Advances in Information Technology
.
JAIT
is intended to reflect new directions of research and report latest advances in information technology. I will do my best to increase the prestige of the journal.
What's New
2025-01-10
All 12 papers published in JAIT Vol. 15, No. 10 have been indexed by Scopus.
2024-12-23
JAIT Vol. 15, No. 12 has been published online!
2024-06-07
JAIT received the CiteScore 2023 with 4.2, ranked #169/394 in Category Computer Science: Information Systems, #174/395 in Category Computer Science: Computer Networks and Communications, #226/350 in Category Computer Science: Computer Science Applications
Home
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Published Issues
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2025
>
Volume 16, No. 1, 2025
>
Volume 16, No. 1, 2025
Article#
Article Title & Authors (Volume 16, No. 1, 2025)
Page
1
Deep Neural Networks for Skin Cancer Classification: Analysis of Melanoma Cancer Data
Stephen Afrifa*, Vijayakumar Varadarajan*, Peter Appiahene, Tao Zhang, Daniel Gyamfi, and Rose-Mary Owusuaa Mensah Gyening
1
2
Initial Coin Offerings Success Prediction Using Social Media and Large Language Models
Khouloud Safi Eljil*, Essia Hamouda, and Farid Nait-Abdesselam
12
3
Enhanced Negation Detection in Arabic Reviews Using Supervised Classification Approach
Ahmed S. Abuhammad* and Mahmoud A. Ahmed
21
4
An Improved Pix2pix Generative Adversarial Network Model to Enhance Thyroid Nodule Segmentation
Huda F. AL-Shahad, Razali Yaakob*, Nurfadhlina Mohd Sharef, Hazlina Hamdan, and Hasyma Abu Hassan
37
5
An Efficacious Detecting Tomato Leaf Disease Using RCOA-Based RNN Method
T. George Princess* and E. Poovammal
49
6
A Novel Deep Learning Model for Flood Detection from Synthetic Aperture Radar Images
Thanh-Nghi Doan* and Duc-Ngoc Le-Thi
57