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About the Journal

Topics of Interest
The field of computing and engineering is witnessing rapid transformation, with emerging technologies and complex challenges that demand fresh perspectives and scholarly exchange. Revolutionary Advances in Computing and Electronics: An International Journal provides a platform for publishing original, peer-reviewed research that addresses both foundational and cutting-edge developments in subject engineering, specialised areas such as AI, cybersecurity,  embedded systems, IoT, electronics design, robotics, quantum, communication networks, antenna 6G, sustainable engineering, and interdisciplinary applications. The journal promotes innovative algorithm design, system architecture, and real-world engineering solutions.

Open Access Journal
Revolutionary Advances in Computing and Electronics: An International Journal is a free, open-access journal committed to the global exchange of scientific knowledge. We believe that removing access and publication barriers helps accelerate the impact of research. All articles are available without subscription, and authors are not required to pay any publication or processing fees. Each submission undergoes rigorous single-blind peer review to ensure academic integrity and quality.

Current Issue

Volume 2 Issue 2 (2026)
					View Volume 2 Issue 2 (2026)
Published: 21-07-2026

Research Articles

  • Intelligent Software Fault Prediction Using Machine Learning and Neural Network Techniques

    Pooja Singh, Saoud Sarwar, Kaveri Umesh Kadam
    1-16
    DOI: https://doi.org/10.65890/race.v2i2.173
  • AI-Based Document Analysis and Question Answering System

    Radhika Sharma, Devraj Gautam
    17-32
    DOI: https://doi.org/10.65890/race.v2i2.192
  • Deep Research Agent: An AI-Powered System for Automated Research Paper Analysis and Citation-Based Answer Generation

    Mukul Negi, Rajdeep Ramola, Vipul Bijalwan, Gopal Datt, Aakanksha Pundir
    33-39
    DOI: https://doi.org/10.65890/race.v2i2.204

Review Articles

  • A Study on Adopting Machine Learning to Develop Predictive Models for Diabetes

    Nafees Akhter Farooqui, Saquib Ali, Raza Abbas Haidri, Mazhar Khaliq
    40-55
    DOI: https://doi.org/10.65890/race.v2i2.195
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