The Journal of Soft Computing and Computer Applications (JSCCA) is a biannual, open-access scientific journal that undergoes peer review. It is dedicated to advancing the field of artificial intelligence and computer applications. The journal is established by the Department of Computer Science at the University of Technology-Iraq (UOT) in Baghdad. JSCCA is a recently established online journal, with its inception date recorded as August 2023. JSCCA has chosen to utilize the Digital Common's platform for its publication.
The journal's website serves as the primary source for accessing most of its articles. As a comprehensive platform, JSCCA offers a diverse papers on various subjects related to artificial intelligence and computer applications. While not limited to these areas, the journal serves as a valuable reference source, fostering the exchange of ideas and encouraging collaboration among researchers, academics, and practitioners in different fields. Some of the areas covered include Data Mining and Big Data, Database Systems, Data Science, Robotics, Cognitive Neuroscience, Image Processing, Computer Networks, Software Engineering, Information Security, IoT & Mobile Computing, Parallel & Distributed Systems, Human-Computer Interaction, Pattern Recognition, and Cloud Computing.
JSCCA journal adheres to a rigorous peer-review process that guarantees the high quality of its published articles. This journal operates a single-blind review process (the names and information of the reviewers are hidden from the author). Every submitted paper undergoes a comprehensive evaluation by field experts before acceptance for publication. To be eligible for publication, papers must satisfy the originality criteria, where all papers must present original work and should not be concurrently submitted to other journals or conferences. All papers must be written in United States English. The manuscript similarity index must be less than 20%.
The JSCCA is dedicated to upholding high standards for its publications, and authors are expected to comply with these guidelines when submitting their work. Authors of peer-reviewed articles should consider account the following considerations:
- Clearly articulate the significance of their work within the broader field of study, providing context and demonstrating their contribution.
- Explain the motivation behind their research, emphasizing the reasons and objectives that drive their work.
The Journal JSCCA welcomes submissions of various article types, including:
- Original research articles: These papers present original findings and contribute new knowledge to the field. They typically include a clear research question, methodology, results, and discussion of the findings.
- Comprehensive review articles: These articles offer a thorough and critical analysis of existing literature on a specific topic. Comprehensive review articles synthesize and evaluate previous research, identify gaps in knowledge, and provide insights for future studies.
The average time for submission to the first decision is 6 weeks and the final decision is 12 weeks.
See the Aims and Scope for a complete coverage of the journal.
Current Issue: Volume 1, Issue 1 (2024)
Surveying Machine Learning in Cyberattack Datasets: A Comprehensive Analysis
Azhar F. Al-zubidi, Alaa Kadhim Farhan, and El-Sayed M. El-Kenawy
FOXANN: A Method for Boosting Neural Network Performance
Mahmood A. Jumaah, Yossra H. Ali, Tarik A. Rashid, and S. Vimal
The Robust Digital Video Watermarking Methods: A Comparative Study
Ebtehal Talib, Abeer Salim Jamil, Nidaa Flaih Hassan, and Muhammad Ehsan Rana
A Novel Approach to Generate Dynamic S-Box for Lightweight Cryptography Based on the 3D Hindmarsh Rose Model
Ala'a Talib Khudhair, Abeer Tariq Maolood, and Ekhlas Khalaf Gbashi
A Comprehensive Analysis of Deep Learning and Swarm Intelligence Techniques to Enhance Vehicular Ad-hoc NETwork Performance
Hussein K. Abdul Atheem, Israa T. Ali, and Faiz A. Al Alawy
Strangeness Detection from Crowded Video Scenes by Hand-Crafted and Deep Learning Features
Ali A. Hussan, Shaimaa H. Shaker, and Akbas Ezaldeen Ali
Face Mask Detection Based on Deep Learning: A Review
Shahad Fadhil Abbas, Shaimaa Hameed Shaker, and Firas. A. Abdullatif
Optimization of Resources Allocation using Evolutionary Deep Learning
Sanaa Ali Jabber, Soukaena H. Hashem, and Shatha H. Jafer
Unraveling the Versatility and Impact of Multi-Objective Optimization: Algorithms, Applications, and Trends for Solving Complex Real-World Problems
Noor A. Rashed, Yossra H. Ali, Tarik A. Rashid, and A. Salih