Evolution of a model journal in the era of digital revolution

The scientific journal Integrated Computer-Aided Engineering (ICAE) is approaching its 30th anniversary. For nearly three decades it has been promoting innovative multidisciplinary research with absolute consistency, maintaining the highest standards of quality without compromise. The scientific community has honored ICAE with its trust and with a very high impact factor. I wish to thank the Editor in Chief Professor Hojjat Adeli, for giving me the chance to write and publish this brief analysis. We are grateful for his invaluable contribution. The recent flourishing of the 4th Industrial Revolution (4IR) is calling for interdisciplinary research efforts, aiming in the development of intelligent nonlinear models applied in every real-life domain. ICAE is a leading journal for the dissemination of timely synergistic research efforts in the fields of Engineering and Information-Communication technologies. It opens new frontiers for solving complex problems to meet the needs of our post-modern 21st century societies. A major part of the research papers published in the journal during the past three decades has been related mainly but not limited to a wide spectrum of Artificial Intelligence (AI) algorithms and approaches. In the 4IR era, the technological developments in the field of Intelligent Information Systems are rapid and having a decisive impact on the respective engineering applications. And ICAE has been at the forefront of this developments. The following Fig. ??, shows the frequency distribution of the topics covered by the journal’s publications during the past two years (2018–2019). More specifically, 15 published papers are in the thematic area of Image-Video Processing (IMVP), 12 are related to Machine Learning (ML), 9 to Robotics, and 8 to Optimization (OPT). It is of great importance that the ICAE journal also covers a wide spectrum of topics namely: Big Data, Filtering, Control Systems, Autonomous Vehicles, Cognitive modeling and Bioinformatics. ML publications are related to Classification, Ensembles, Deep – Convolutional and Transfer Learning algorithms with respective applications. On the other hand, OPT papers have employed Meta Heuristic approaches. A comparison of the 2012–2013 article list with 2018–2019 article list shows many additional research