Deep learning‐driven distributed communication systems for cluster online educational platform considering human–computer interaction

Author(s):  
Jinrong Zhou
Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2972
Author(s):  
Qinghua Gao ◽  
Shuo Jiang ◽  
Peter B. Shull

Hand gesture classification and finger angle estimation are both critical for intuitive human–computer interaction. However, most approaches study them in isolation. We thus propose a dual-output deep learning model to enable simultaneous hand gesture classification and finger angle estimation. Data augmentation and deep learning were used to detect spatial-temporal features via a wristband with ten modified barometric sensors. Ten subjects performed experimental testing by flexing/extending each finger at the metacarpophalangeal joint while the proposed model was used to classify each hand gesture and estimate continuous finger angles simultaneously. A data glove was worn to record ground-truth finger angles. Overall hand gesture classification accuracy was 97.5% and finger angle estimation R 2 was 0.922, both of which were significantly higher than shallow existing learning approaches used in isolation. The proposed method could be used in applications related to the human–computer interaction and in control environments with both discrete and continuous variables.


Author(s):  
Kijpokin Kasemsap

This article explains the overview of Human-Computer Interaction (HCI); cognitive models, socio-organizational issues, and stakeholder requirements; HCI and hand gesture recognition; and the multifaceted applications of HCI. HCI is a sociotechnological discipline whose goal is to bring the power of computers and communication systems to people in ways and forms that are both accessible and useful in the effective manner. HCI plays an important role in identifying the environmental and social issues which can affect the use of systems, and providing techniques to ensure the design of the system will be usable, effective, and safe. HCI draws on computer science, computer and communications engineering, graphic design, management, psychology, and sociology as it tries to make computer and communications systems ever more usable in executing tasks. HCI is an important consideration for any business that uses computers in their everyday operation.


Author(s):  
Kijpokin Kasemsap

This chapter explains the overview of human-computer interaction (HCI); cognitive models, socio-organizational issues, and stakeholder requirements; HCI and hand gesture recognition; and the multifaceted applications of HCI. HCI is a sociotechnological discipline whose goal is to bring the power of computers and communication systems to people in ways and forms that are both accessible and useful in the effective manner. HCI plays an important role in identifying the environmental and social issues that can affect the use of systems, and provide techniques to ensure the design of the system will be usable, effective, and safe. HCI draws on computer science, computer and communications engineering, graphic design, management, psychology, and sociology as it tries to make computer and communications systems ever more usable in executing tasks. HCI is an important consideration for any business that uses computers in their everyday operation.


Author(s):  
Inguna Skadiņa ◽  
Didzis Goško

Human-computer interaction, especially in form of dialogue systems and chatbots, has become extremely popular during the last decade. The dominant approach in the recent development of practical virtual assistants is the application of deep learning techniques. However, in case of less resourced language (or domain), the application of deep learning could be very complicated due to the lack of necessary training data. In this paper, we discuss possibility to apply hybrid approach to dialogue modelling by combining data-driven approach with the knowledge-based approach. Our hypothesis is that by combining different agents (general domain chatbot, frequently asked questions module and goal oriented virtual assistant) into single virtual assistant we can facilitate adequacy and fluency of the conversation. We investigate suitability of different widely used techniques in less resourced settings. We demonstrate feasibility of our approach for morphologically rich less resourced language Latvian through initial virtual assistant prototype for the student service of the University of Latvia.


interactions ◽  
2021 ◽  
Vol 28 (1) ◽  
pp. 78-82
Author(s):  
Huy Viet Le ◽  
Sven Mayer ◽  
Niels Henze

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