WITHDRAWN: Modeling analysis of the coping effect of dance piano accompaniment music on interpersonal pressure at work

Abstract

Piano accompaniment is necessary for the creation and performance in music atmosphere and exhibits dance motion, passionate appeal, or qualities of the style. These are stated positively, and work rates were poor with no music, while removing the music is considered the longest in limited research to find the differences with reports that could derive from methodological problems. Performing a complete evaluation of music affects hormones, autonomous behavior, and human stress response with health deficiencies. Therefore, music classification analysis using the machine learning (MCA-ML) technique has been introduced to predict this qualitative method to explore dance, music as a rehabilitation process described in a stressful life event by persons involved and affected. A convolution neural network (CNN) approach is frequently employed to analyze various coping effects of different music pattern-based classification issues to attain high advantages. A musical perception approach based on cloud computing is introduced to efficiently allocate resources to analyze the music with cognitive systems efficiently. Empirical analysis revealed that the proposed architecture permits real-time access to the data and successfully supports several parallel applications with 97.81%performance.