Quantitative cost comparison of on-premise and cloud infrastructure based EEG data processing

Focusing on virtual reality (VR) and film cutting, this study compared and evaluated the effect of visual mode (2D, VR) and cutting rate (fast, medium, slow) on a load, to make an attempt for VR research to enter the cognitive field. This study uses a 2 × 3 experimental research design. Forty participants were divided into one of two groups randomly and watched films with three cutting rates. The subjective and objective data were collected during the experiment. The objective results confirm that VR films bring more powerful alpha, beta, theta wave activities, and bring a greater load. The subjective results confirm that the fast cutting rate brings a greater load. These results provide a theoretical support for further exploring the evaluation methods and standards of VR films and improving the viewing experience in the future.

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Using Fictive Powers as Event Markers in EEG Data Processing

The Neurobiology of Computation ◽

10.1007/978-1-4615-2235-5_53 ◽

1995 ◽

pp. 323-328

Author(s):

Richard X. Tang ◽

Kouichi Sugita ◽

Walter J. Freeman ◽

Sven Jakubith

Keyword(s):

Data Processing ◽

Eeg Data

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The development of models of an analytical data processing system for monitoring information security of an informatization object using cloud infrastructure

Российский технологический журнал ◽

10.32362/2500-316x-2021-9-6-16-25 ◽

2021 ◽

Vol 9 (6) ◽

pp. 16-25

Author(s):

V. A. Sizov ◽

A. D. Kirov

Keyword(s):

Information Security ◽

Data Processing ◽

Information Technologies ◽

Analytical Data ◽

Processing System ◽

Skill Level ◽

Information Support ◽

Cloud Infrastructure ◽

Data Processing System ◽

Monitoring Information

The article is devoted to the problem of developing an analytical data processing system for monitoring information security within the information security management system of modern companies conducting their main activities in cyberspace and using cloud infrastructure. Based on the analysis of modern information technologies related to ensuring information security of cloud infrastructure and the most popular products for ensuring information security of cloud infrastructures, as well as existing scientific approaches, a formalized approach to the synthesis of an analytical data processing system for monitoring the information security of an informatization object using cloud infrastructure is proposed. This approach takes into account the usefulness of the used information technologies from the viewpoint of information security. A general model of the structure of information support of an analytical data processing system for monitoring information security, as well as a model of the dependence of the usefulness of information technology on time and the ratio of the skill level of an information security specialist and an attacker are presented. The quality of the information security monitoring system is used as a criterion in the first optimization model. The following limitations are suggested: limitation on the time of making a decision on an incident; limitation on the degree of quality of analysis of information security events by the analytical data processing system and limitation on the compatibility of data analysis functions with data types about information security events. The cited results of the study of the second model show a logically consistent dependence of the usefulness of information technology on time and the ratio of the skill level of an information security specialist to the skill level of an attacker. The particular models of the structure of the information support of ASOD are presented. They make it possible to determine the rational structure information support of ASOD according to particular criteria. The following particular criteria are used: the maximin criterion of the usefulness of the information support of ASOD for monitoring the information security of an informatization object in the cloud infrastructure; the criterion for the maximum relevance of information support distributed over the nodes of the cloud infrastructure for systems with a low degree of centralization of management.

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EEG data processing in ADHD diagnosis and neurofeedback

Engineering review ◽

10.30765/er.40.3.12 ◽

2020 ◽

Vol 40 (3) ◽

pp. 116-123

Author(s):

Zoran Šverko ◽

Ivan Markovinović ◽

Miroslav Vrankić ◽

Saša Vlahinić

Keyword(s):

Data Processing ◽

Mean Value ◽

Adhd Group ◽

Eeg Signal ◽

Statistical Features ◽

Eeg Signals ◽

New Approach ◽

Mean Values ◽

Adhd Diagnosis ◽

Eeg Data

In this paper, EEG data processing was conducted in order to define the parameters for neurofeedback. A new survey was conducted based on a brief review of previous research. Two groups of participants were chosen: ADHD (3) and nonADHD (14). The main part of this study includes EEG signal data pre-processing and processing. We have outlined statistical features of observed EEG signals such as mean value, grand-mean value and their ratios. It can be concluded that an increase in grand-mean values of power theta-low beta ratio on Cz electrode gives confirmation of previous research. The value of alpha-delta power ratio higher than 1 on C3, Cz, P3, Pz, P4 in ADHD group is proposed as a new approach to classification. Based on these conclusions we will design a neurofeedback protocol as a continuation of this work.

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JupyTEP IDE as an Online Tool for Earth Observation Data Processing

Remote Sensing ◽

10.3390/rs11171973 ◽

2019 ◽

Vol 11 (17) ◽

pp. 1973 ◽

Cited By ~ 5

Author(s):

Rapiński ◽

Bednarczyk ◽

Zinkiewicz

Keyword(s):

User Interface ◽

Data Processing ◽

European Space Agency ◽

Earth Observation ◽

Observation Data ◽

Cloud Infrastructure ◽

Integrated Development Environment ◽

Development Environment ◽

Integrated Development ◽

Earth Observation Data

The paper describes a new tool called JupyTEP integrated development environment (IDE), which is an online integrated development environment for earth observation data processing available in the cloud. This work is a result of the project entitled “JupyTEP IDE—Jupyter-based IDE as an interactive and collaborative environment for the development of notebook style EO algorithms on network of exploitation platforms infrastructure” carried out in cooperation with European Space Agency. The main goal of this project was to provide a universal earth observation data processing tool to the community. JupyTEP IDE is an extension of Jupyter software ecosystem with customization of existing components for the needs of earth observation scientists and other professional and non-professional users. The approach is based on configuration, customization, adaptation, and extension of Jupyter, Jupyter Hub, and Docker components on earth observation data cloud infrastructure in the most flexible way; integration with accessible libraries and earth observation data tools (sentinel application platform (SNAP), geospatial data abstraction library (GDAL), etc.); adaptation of existing web processing service (WPS)-oriented earth observation services. The user-oriented product is based on a web-related user interface in the form of extended and modified Jupyter user interface (frontend) with customized layout, earth observation data processing extension, and a set of predefined notebooks, widgets, and tools. The final IDE is addressed to the remote sensing experts and other users who intend to develop Jupyter notebooks with the reuse of embedded tools, common WPS interfaces, and existing notebooks. The paper describes the background of the system, its architecture, and possible use cases.

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