This work intends to classify and integrate music genres and emotions to improve the quality of music education. This work proposes a web image education resource retrieval method based on semantic network and interactive image filtering for a music education environment. It makes a judgment on these music source data and then uses these extracted feature sequences as the emotions expressed in the model of the combination of Long Short-Term Memory (LSTM) and Attention Mechanism (AM), thus judging the emotion category of music. The emotion recognition accuracy has increased after improving LSTM-AM into the BiGR-AM model. The greater the difference between emotion genres is, the easier it is to analyze the feature sequence containing emotion features, and the higher the recognition accuracy is. The classification accuracy of the excited, relieved, relaxed, and sad emotions can reach 76.5%, 71.3%, 80.8%, and 73.4%, respectively. The proposed interactive filtering method based on a Convolutional Recurrent Neural Network can effectively classify and integrate music resources to improve the quality of music education.

Fatigue is a common physiological phenomenon observed in athletes.The mechanisms of fatigue in sports have been described through various theories, such as energy exhaustion theory, protective inhibition theory, blockage theory, internal environment stability disorder theory, and free radical theory (Pengyi & Changlin, 2016). According to the Pavlov school, exercise conducts nerve impulses to the cerebral cortex, which leads to long-term excitation and increased energy consumption.Additionally, the body inhibits the cerebral cortex for self-protection, which leads to exercise-induced fatigue (Shuxun et al., 2001). The application of external intervention is conducive to fatigue recovery, though exercise-induced fatigue can restore normal physical functions after a period of rest and adjustment (Rong et al., 2010).Heart rate (HR) variability reflects the variation in the heartbeat cycle and can be used to analyze the successive heart cycle time

Purpose: The present study attempted to explore the effects of different tempos of piano music on heart rate and autonomous nervous system during the recovery period after high-intensity exercise. In addition, the study analyzed the influence of different tempos on the recovery period of athletes to devise methods for accelerating fatigue recovery through piano music.Method: A total of 57 college students majoring in physical education were selected as experimental subjects and were divided into three groups, namely Lento group (n = 20), Moderato group (n = 20), and Allegretto group (n = 20; only 17 students completed the experiment). Results: Under the same high-intensity exercise regimen, the three groups did not differ significantly in the body composition, high-intensity exercise ability, and time-domain variation indices, namely heart rate (HR), Heart rate variability index parameters(P > .05). The time-domain variation analysis in the recovery period revealed significant differences in HR frequency domain indices among the groups exposed to different rhythms (P < .05).Conclusion: Moderate-tempo piano music was the most effective in facilitating HR and autonomic nervous system recovery during the recovery period.

At present, the academic education of Chinese students is basically public education, but the quality training is mainly handed over to the market for training. Therefore, China’s online education and training institutions have gradually developed under this demand. With the improvement of people’s living standards, families have higher and higher requirements for children’s education, expecting that children can be well improved in physical, mental and psychological aspects, and hoping that they will have their own advantages in the future competition. Therefore, this paper studies the influence of parents’ perception on the brand recognition of online education and training. Through the analysis of dance online training institutions, the research shows that among the three categories, teachers’ Graduation schools account for the highest proportion, with an average proportion of 47.07%, followed by teachers’ grade certificates, with a proportion of 32.29%, and teachers’ competition scores of 25.57%. Therefore, in the process of operation, online dance training institutions should meet the needs of parents to understand the professional level of teachers. Improve the service system of training institutions, improve the parent brand recognition and the number of customers of training institutions, further improve online education and training institutions, and provide them with improvement suggestions and measures for reference.