Web-Platform for Cloud Computing in Neuro-Physiological Research Based on Eye-Tracking Data

The purpose of the work is to develop the architecture and web version of the software complex based on the proposed new concept of cloud computing organization, which allows to expand the diagnostic capabilities of the tools of model-oriented information technology for assessing the neurophysiological state of a person using methods of nonlinear dynamic identification of the oculomotor system based on eye tracking data. The concept of cloud computing is proposed, which is based on the combination of PaaS and SaaS services as part of the developed software complex, due to which the cross-platform nature of cloud computing is ensured, the productivity and efficiency of scientific research increases. The developed architecture allows you to easily expand the functionality of the software complex and adapt it to different application conditions. The key feature of the complex is its undemanding hardware on the client side thanks to the use of cloud computing and its modular structure, which allows for easy scaling of the complex, as well as the isolation of the script code execution process in the cloud computing environment to increase the level of security when interpreting the script code on the server . Compared to other similar services, the complex has several advantages: it provides effective work in research and educational applications, supports Python and JavaScript programming languages, and also allows the use of software-implemented identification methods through specially developed GUI interfaces. In addition, the complex offers social opportunities and a high level of abstraction, which allows to optimize the research process.

Authors

Publication Details

Journal
Mathematical and computer modelling Series Technical sciences
Published
2024-09-30
DOI
https://doi.org/10.32626/2308-5916.2024-25.46-62
Primary Topic
Cognitive Computing and Networks
Type
article
Field-Weighted Citation Impact
0.00
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article

Web-Platform for Cloud Computing in Neuro-Physiological Research Based on Eye-Tracking Data

Vitaliy Pavlenko, Andrii S. Ilutsa, Vadym I. Gidulian
Mathematical and computer modelling Series Technical sciences
Cognitive Computing and Networks
article

Web-Platform for Cloud Computing in Neuro-Physiological Research Based on Eye-Tracking Data

Vitaliy Pavlenko, Andrii S. Ilutsa, Vadym I. Gidulian
article en

Abstract

The purpose of the work is to develop the architecture and web version of the software complex based on the proposed new concept of cloud computing organization, which allows to expand the diagnostic capabilities of the tools of model-oriented information technology for assessing the neurophysiological state of a person using methods of nonlinear dynamic identification of the oculomotor system based on eye tracking data. The concept of cloud computing is proposed, which is based on the combination of PaaS and SaaS services as part of the developed software complex, due to which the cross-platform nature of cloud computing is ensured, the productivity and efficiency of scientific research increases. The developed architecture allows you to easily expand the functionality of the software complex and adapt it to different application conditions. The key feature of the complex is its undemanding hardware on the client side thanks to the use of cloud computing and its modular structure, which allows for easy scaling of the complex, as well as the isolation of the script code execution process in the cloud computing environment to increase the level of security when interpreting the script code on the server . Compared to other similar services, the complex has several advantages: it provides effective work in research and educational applications, supports Python and JavaScript programming languages, and also allows the use of software-implemented identification methods through specially developed GUI interfaces. In addition, the complex offers social opportunities and a high level of abstraction, which allows to optimize the research process.

Mathematical and computer modelling Series Technical sciencesVol. 25
Openalex Percentile: Top 83%
Cognitive Computing and Networks
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