Preface to Special Issue on Digital Twin Empowered Internet of Intelligent Things for Engineering Cyber-Physical Human Systems

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Authors

  • C. Venkatesan Department of Electronics and Communication Engineering, HKBK College of Engineering, Bengaluru, Karnataka, India
  • Yu-Dong Zhang Knowledge Discovery and Machine Learning and Department of Informatics, University of Leicester, Leicester, United Kingdom
  • Qin Xin Faculty of Science and Technology, University of the Faroe Islands, Tórshavn, Faroe Islands

Abstract

This special issue entitled Digital Twin Empowered Internet of Intelligent Things for Engineering Cyber-Physical Human Systems contains a collection of selected papers all discussing the state-of-the-art cyber-physical human systems, artificial intelligence techniques, biomedical engineering and optimization algorithms. All the articles published in this special issue were accepted for publication after a careful peer-review process to fulfill the standard quality requirements and fall within the journal’s scope.

Keywords:

Internet of Things, Intenrent of Intelligent Things for Engineering, Cyber-Physical Human Systems

References

1. B. Ramalingam, G. Angappan, A deep hybrid model for human-computer interaction using dynamic hand gesture recognition, Computer Assisted Methods in Engineering and Science, 30(3): 263–276, 2023, https://doi.org/10.24423/cames.559

2. D. Verma, S. Agrawal, A novel framework for fetal nuchal translucency abnormality detection using hybrid maxpool matrix histogram analysis, Computer Assisted Methods in Engineering and Science, 30(3): 277–290, 2023, https://doi.org/10.24423/cames.631

3. B. Mohan Rao, A. Kumar, Congestive heart failure detection based on electrocardiomatrix method with ECG signal, Computer Assisted Methods in Engineering and Science, 30(3): 291–304, 2023, https://doi.org/10.24423/cames.644

4. T. Balamurugan, E. Gnanamanoharan, Brain tumor classification in MRI images using genetic algorithm appended CNN, Computer Assisted Methods in Engineering and Science, 30(3): 305–321, 2023, https://doi.org/10.24423/cames.649

5. W. Pakhira, R. Kumar, F.C. Panwala, K.M. Ibrahimi, Microfluidic design for continuous separation of blood particles and plasma using dielectrophoretic force principle, Computer Assisted Methods in Engineering and Science, 30(3): 323–345, 2023, https://doi.org/10.24423/cames.653

6. K.M. Ibrahimi, R. Kumar, W. Pakhira, F.C. Panwala, Enhanced design and analysis of microcantilever-based bio-sensor to detect carcinoembryonic antigen tumor biomarkers, Computer Assisted Methods in Engineering and Science, 30(3): 347–367, 2023, https://doi.org/10.24423/cames.654

7. S.R. Karanam, Y. Srinivas, S. Chakravarty, A supervised approach to musculoskeletal imaging fracture detection and classification using deep learning algorithms, Computer Assisted Methods in Engineering and Science, 30(3): 369–385, 2023, https://doi.org/10.24423/cames.682