Computer Assisted Methods in Engineering and Science (CAMES) is a referred international journal, published quarterly, indexed by Scopus and EBSCO, providing a scientific exchange forum and an authoritative source of information in the field of computational sciences and related areas of applied engineering. The objective of the journal is to support researchers and practitioners by offering them the means facilitating access to the newest research results reported by leading experts in the field, publication of own contributions, and dissemination of information relevant to the scope of the journal.

Papers published in the journal will fall largely into three main categories:

  • Contributions presenting new research methods of mathematical modeling and computer simulations in engineering and applied sciences, including traditional areas such as solid and structural mechanics, material science, fluid dynamics, acoustics and electromagnetics but going beyond them to account for application relevant issues in physics, chemistry, biology and mathematics, scientific computing, large scale optimization, intelligent systems as well as in multi-scale and multi-physics problems.
  • Articles describing novel applications of computational techniques supporting engineering practice and education in areas like mechanical, aerospace, civil, naval, software, chemical and architectural engineering, materials science as well as demonstrations of their practical use in solving real life problems.
  • State-of-the-art tutorials, providing the readership with a guidance on important research directions as observed in the current world literature on computer assisted methods in engineering and sciences.

The journal will also publish book reviews and information on activities of the European Community on Computational Methods in Applied Sciences (ECCOMAS).

Print ISSN: 2299-3649

Journal Metrics

MNiSW (2021): 70   |   CiteScore 2020: 0.5   |   SJR 2020: 0.126   |   SNIP 2020: 0.111


Call for Papers on Digital Twin Empowered Internet of Intelligent Things for Engineering Cyber-Physical Human Systems


Future engineering systems will rely heavily on Cyber-Physical Human Systems (CPHSs) to design and build new capabilities that exceed today's levels of autonomy, flexibility, affordability, durability, and cyber security. A digital twin is a digitized representation of a physical object or action connected to the Internet of Things (IoT) in real-time. It can be used for multiple things such as monitoring, diagnosing, optimizing, and controlling asset performance and utilization. Recent breakthroughs in healthcare are increasingly reliant on medical devices and systems networked via the Internet of Intelligent Things (IoIT ) and must address the needs of patients in unusual circumstances.
As a result, dynamically reconfigured intelligent patient interaction complex IoIT will be required. There are numerous challenges in cyber-physical human systems when integrated with IoT. Appropriate digital twin configuration through advanced multi-sensors can be used to overcome the limitations in the CPHSs. Similarly, the design and management of smart renewable energy systems and power distribution using smart grids can be optimized using IoIT.   To produce high-performance, dependable, and low-cost CPHSs that serve humanity, several key problems must be answered.

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