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International Journal of System Assurance Engineering and Management - Call for Papers: Special Issue on 'Leveraging Computational Paradigms for System Performance'

Introduction

In today’s Industry 5.0 era of uncertainty and disruption, automation integration in the business models have gained importance. Computational Intelligence has evolved focusing on new technologies and novice computational methods. It’s has leveraged digital transformation in a reliable and sustainable ecosystem. The new automation techniques are useful in solving the complex real-life problems using probabilistic decisions, design, applications using biologically and linguistically motivated computational paradigms. The approaches of computational intelligence, viz. fuzzy logic, neural networks, probabilistic methods, Artificial Intelligence and Machine learning have its function in all domains of engineering and management.

This special issue focuses on new development and advances in computational intelligence and its application in multi-disciplinary research. It not only links the new paradigms originating from computational intelligence but also fills the gap between production and scalability. When comes to services, it improves the decision-making capability and enhances the system performance. Mathematical modelling, reliability and testing with new AI and ML techniques help taking informed strategic decisions.

The Journal invites research scholars, academicians, scientists and industrialists worldwide to submit original unpublished manuscripts that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following topics of interest include, but are not limited to:

  • Software Quality
  • Software Reliability & Testing
  • Software Reliability Engineering
  • Total Quality Management
  • System and Network Security
  • Reliability Maintenance & Models
  • Multi Criteria Decision Making
  • Artificial Intelligence and Machine Learning
  • Computation through Neural Networks
  • Bigdata Analytics
  • Blockchain
  • Internet of things
  • Interdisciplinary Research
  • Data and Intelligent System Modelling
  • System Performance through Computation
  • Vulnerability Modelling and Patching
  • Application in Business & Engineering
  • Inventory/ Material Management
  • Nature Inspired Optimization Algorithms
  • Marketing of Social Innovations
  • Flexibility/Agility in Technology & Management
  • Sustainable Operation/ Logistics
  • Sustainable Supply Chain


Important Date: Submission deadline is 30 June 2024

Manuscript Submission Information

Please follow the instructions of the journal while preparing your manuscript. A guide for authors can be found at: https://www.springer.com/journal/13198/submission-guidelines (this opens in a new tab)

Please submit your manuscript through the Journal’s homepage at https://www.springer.com/journal/13198 (this opens in a new tab)

This special issue will comprise, in addition to fresh submissions, some selected papers from the 3rd International Conference on Recent Trends in Engineering, Technology and Business Management (ICRTETBM 2024), to be held on February 21-23, 2024 at Amity University, Noida, India.

Decision on paper – the review process will start a soon as the author uploads the paper and the decision on the paper will be informed to the authors as soon as the reviews are complete.

To ensure a paper is considered for the Special Issue, reply “yes” when asked during submission whether it is intended for a special issue and select “SI on Leveraging Computational Paradigms for System Performance” from the drop-down menu.

For questions, please contact:

Guest Editors

Dr. Vivek Kumar, AIBS, Amity University, Noida, India
email: vivekrajput.du.aor@gmail.com (this opens in a new tab)

Prof. Suraj Rane, Goa College of Engineering, Ponda, Goa, India 
email: ssr@gec.ac.in (this opens in a new tab)

Prof. Syed Mohd Rizwan, National University of Science and Technology, Sultanate of Oman
email: syedrizwan@nu.edu.om (this opens in a new tab)

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