Special Issue on Human–Computer Interactions 2.0-Reference-Cited by-同舟云学术

Special Issue on Human–Computer Interactions 2.0

Published:2023-03-27 Issue:7 Volume:13 Page:4260
ISSN:2076-3417
Container-title:Applied Sciences
language:en
Short-container-title:Applied Sciences

Author:

Meen Teen-Hang¹^ORCID,Tijus Charles²^ORCID,Chang Chun-Yen³^ORCID

Affiliation:

1. Department of Electronic Engineering, National Formosa University, Yunlin 632, Taiwan

2. Cognitions Humaine et Artificielle Laboratory, University Paris 8, 93526 Saint-Denis, France

3. Graduate Institute of Science Education and Department of Earth Sciences, National Taiwan Normal University, Taipei City 106, Taiwan

Abstract

Human–computer interaction (HCI) research involves the design and use of computer technology, focusing in particular on the interfaces between people (users) and computers. HCI researchers observe the ways in which humans interact with computers and design technologies that allow them to interact in novel ways. As HCI evolves into HCI 2.0, user experiences and feedback become ever more relevant. This Special Issue, “Human Computer Interactions 2.0”, presents 11 excellent papers about topics related to human–computer interactions. It aims to provide a broad international forum for world researchers, engineers and professionals in human–computer interaction research for the discussion and exchange of various scientific, technical and management discoveries across the world.

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Link

https://www.mdpi.com/2076-3417/13/7/4260/pdf

Reference11 articles.

1. Cerqueira, T., Ribeiro, F.M., Pinto, V.H., Lima, J., and Gonçalves, G. (2022). Glove Prototype for Feature Extraction Applied to Learning by Demonstration Purposes. Appl. Sci., 12.

2. Wu, M.-H., Lai, Y.J., Hwang, Y.L., Chang, T.-C., and Hsu, F.H. (2022). MinerGuard: A Solution to Detect Browser-Based Cryptocurrency Mining through Machine Learning. Appl. Sci., 12.

3. Wang, C.P., Tsai, C.H., and Lee, Y.L. (2022). Requesting Help Module Interface Design on Key Partial Video with Action and Augmented Reality for Children with Autism Spectrum Disorder. Appl. Sci., 12.

4. Hsu, F.H., Wu, M.H., Hwang, Y.L., Lee, C.H., Wang, C.S., and Chang, T.C. (2022). WPFD: Active User-Side Detection of Evil Twins. Appl. Sci., 12.

5. Tsai, Y.L., Chang, H.C., Lin, S.N., Chiou, A.H., and Lee, T.L. (2022). Using Convolutional Neural Networks in the Development of a Water Pipe Leakage and Location Identification System. Appl. Sci., 12.

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