The opera performance market is maturing, and at the same time, new opera performance and marketing methods are being introduced on a regular basis to meet the growing spiritual needs of the audience. It is the foundation for opera to achieve its business goals by going to the market and completing commodity exchange. The success of opera performances on the market has a direct impact on whether they can achieve market success and achieve the ultimate goal of maximizing profits. An in-depth analysis and discussion of industrial data mining technology in the positioning and market selection of opera performance art is presented in this paper, and it is of great theoretical and practical importance for improving the positioning and market selection of opera performance art and promoting the development of the opera performance industry. The application of artistic orientation and market selection in industrial data mining will be developed, which will aid in the systematic development of artistic orientation and market selection in opera performance of industrial data mining systems, improve industrial data mining efficiency, and promote the application of artistic orientation and market selection in opera performance of industrial data mining systems.
Development of various media in contemporary society has increased the demand for interactive media and video that uses projection mapping in broadcast, concert, theatre, musicals and so on rather than merely selecting video clips to play, and computer technology development has introduced interactive functions that simultaneously process the audience reaction. While selecting video clips require large OB vans and equipment of broadcasting equipment switcher, smaller size of DJing and VJing and various types of sensor allowed simultaneous screen and sound from audience motion or performance motion, and based on this, we created DJing and VJing using simultaneous interactive elements. 1322Haehyun Jung et al.
Patients with weak or no symptoms accelerate the spread of COVID-19 through various mutations and require more aggressive and active means of validating the COVID-19 infection. More than 30% of patients are reported as asymptomatic infection after the delta mutation spread in Korea. It means that there is a need for a means to more actively and accurately validate the infection of the epidemic via pre-symptomatic detection, besides confirming the infection via the symptoms. Mishara et al.[1] reported that physiological data collected from smartwatches could be an indicator to suspect COVID-19 infection. It shows that it is possible to identify an abnormal state suspected of COVID-19 by applying an anomaly detection method for the smartwatch’s physiological data and identifying the subject’s abnormal state to be observed. This paper proposes to apply the One Class-Support Vector Machine (OC-SVM) for pre-symptomatic COVID-19 detection. We show that OC-SVM can provide better performance than the Mahalanobis distance-based method used by Mishara et al.[1] in three aspects: earlier (23.5%-40% earlier) and more detection (13.2%-19.1% relative better) and fewer false positives. As a result, we could conclude that OC-SVM using RHR (Resting Heart Rate) with 350 and 300 moving average size is the most recommended technique for COVID-19 pre-symptomatic detection based on physiological data from the smartwatch.
Abstract. By exploring a relationship between creativity and character and examining Creativity-Character Elements, this study intends to provide foundational materials for practical Creativity-Character Education in educational fields. As the result of investigating Creativity-Character Elements, there were 12 elements required in social relations and 24 elements required for individuals. In this research, the total of 36 creativity-character elements was identified.
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