AUTHOR=Liu Mingxing 

TITLE=An EEG Neurofeedback Interactive Model for Emotional Classification of Electronic Music Compositions Considering Multi-Brain Synergistic Brain-Computer Interfaces

JOURNAL=Frontiers in Psychology

VOLUME=Volume 12 - 2021

YEAR=2022

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2021.799132

DOI=10.3389/fpsyg.2021.799132

ISSN=1664-1078

ABSTRACT=As an important communication medium, the Internet brings the freedom and convenience of publishing, transmitting and acquiring information, while the problems caused by various kinds of information that endanger social stability and involve the vital interests of the country are also increasingly emerging. The traditional network supervision method can no longer adapt to the continuous development of content security needs. Internet regulators in the analysis of network data, the retrieval process mostly focuses only on structured text data. However, the vast majority of data on the Internet is unstructured data, thus causing the ability to regulate such data is greatly limited, especially in the detection and tracking of increasingly serious network hackers of various types of attacks, the lack of a comprehensive system for the analysis and processing of network data. In order to solve the shortage of keyword setting and database indexing in unstructured text data analysis, this paper focuses on the above-mentioned data analysis techniques for web content security. Based on the in-depth study of the technologies related to web data security analysis, an improved KMP algorithm is proposed for the keyword matching problem of unstructured data. Through theoretical analysis and testing of the algorithm, the number of comparisons of the improved algorithm is about 60% of that of the KMP algorithm. According to the characteristics of unstructured text data, an unstructured text data analysis and retrieval system is designed. The system uses distributed technology, which is a distributed unstructured text data security analysis system with feedback and fault tolerance mechanism on Windows platform with task distribution server as the center and computing terminals as task processing units. The detailed design of each functional component of the designed system in the paper is given, the system implementation is completed, and the overall functionality, computing speed, and failure of each module of the system are tested. The tests show that the system is able to detect suspicious data normally after setting effective pattern string rules, and achieves the expected design goal.