The Role of Music in Multicultural Education:A Tool for Promoting Cultural Understanding and Inclusion

In this essay,it will be examined how music can be a powerful tool in multicultural education in promoting humanity and cultural sensitivity.As classroom diversity increases,the challenge lies with educators to ensure that an equal and appropriate learning environment for all students with cultural sensitivity is maintained.To address this problem,therefore,the study explores how music may be effectively incorporated into intercultural education approaches.This paper has evidence that music is a language that has transcended cultures and promotes tolerance,appreciation,and acceptance of diversity through a synthesis of literature and examples.Several implications posit that music can make people feel they belong,enhance the relations of people from diverse cultures,and provide a practical way of learning about other cultures.The potential of music as a tool to engage social justice issues and liberate oppressed groups is also discussed in this research.It exists,but with caution to cultural appropriation and stereotyping of students,thus requiring educators to be sensitive and socially-apperceived on the best practice ways on how to integrate music into classrooms.The end explains how music helps in nurturing a generation of embracing the world,more sensitive and more inclined to the happenings in society to create a society that will be more sensitive and tolerant with the growing society which is diversifying.Therefore,the current article recommends further exploration and development of music-facilitated/inclined pedagogy of ME in hopefully enhancing cultural consciousness/sensitivity and fostering more social integration.

The Impact of Music Education on Children’s Cognitive Development:From Traditional Classrooms to Modern Digital Platforms

Music education has long been debated for its influence on children’s cognitive development,particularly regarding their thinking methods and adaptability.This article synthesizes research data to examine the cognitive benefits of music instruction,including increased IQ,language proficiency,memory,and attention.Traditional face-to-face training,while personalized and socially interactive,faces limitations such as budget constraints and accessibility.Modern digital platforms offer individualized learning paths with AI-driven feedback but may lack necessary interpersonal interaction.This paper proposes a hybrid approach to music education,integrating traditional and digital methods to maximize cognitive gains.Further research is recommended to explore the implementation of these integrated learning strategies in varied educational settings.

Analysis of the Role of Problem-Based Independent Learning Model in Teaching Cerebral Ischemic Stroke First Aid in Emergency Medicine

Objective:To analyze the effect of using a problem-based(PBL)independent learning model in teaching cerebral ischemic stroke(CIS)first aid in emergency medicine.Methods:90 interns in the emergency department of our hospital from May 2022 to May 2023 were selected for the study.They were divided into Group A(45,conventional teaching method)and Group B(45 cases,PBL independent learning model)by randomized numerical table method to compare the effects of the two groups.Results:The teaching effect indicators and student satisfaction scores in Group B were higher than those in Group A(P<0.05).Conclusion:The use of the PBL independent learning model in the teaching of CIS first aid can significantly improve the teaching effect and student satisfaction.

Research into the Application of Cooperative Learning to English Reading Teaching of Art Majors in Independent Colleges

This paper first stated some related theories of cooperative learning and English reading teaching.And then an applicationof cooperative learning in English reading teaching of art majors in independent college is implemented based on these literature re-views.The aim of the experiment is to explore the impact of the application of cooperative learning strategies.It mainly discussedthe following questions:(1)Can the group cooperative learning improve students'reading achievement?(2)What factors contributeto the success/failure of cooperative learning?(3)What are the favorite cooperative learning models in reading classes?The experi-ment proved that cooperative learning does not truly improve art students’reading achievement in independent college,but it real-ly has a positive role in promoting the students'learning interest,motivation and emotional attitude.The experiment also indicatesthat cooperative learning is still a valuable teaching strategy for applying,and GI,LT,TGT and other cooperative learning modelare welcomed by classmates.

Reflections on English Listening Autonomous Learning in the Independent College

The self-access learning center emphasizes the principle and significance of student-centeredness rather than teacher-centeredness,which is the focus of the reform of college English in the independent college.To implement belief training program and assist students to grow into proper autonomous learners is the suggestion given when students lack beliefs and motivations.

Music Emotion Recognition Based on Feature Fusion Broad Learning Method

With the rapid development in the field of artificial intelligence and natural language processing(NLP),research on music retrieval has gained importance.Music messages express emotional signals.The emotional classification of music can help in conveniently organizing and retrieving music.It is also the premise of using music for psychological intervention and physiological adjustment.A new chord-to-vector method was proposed,which converted the chord information of music into a chord vector of music and combined the weight of the Mel-frequency cepstral coefficient(MFCC) and residual phase(RP) with the feature fusion of a cochleogram.The music emotion recognition and classification training was carried out using the fusion of a convolution neural network and bidirectional long short-term memory(BiLSTM).In addition,based on the self-collected dataset,a comparison of the proposed model with other model structures was performed.The results show that the proposed method achieved a higher recognition accuracy compared with other models.

Online Batch Process Monitoring Based on Just-in-Time Learning and Independent Component Analysis

A new method was developed for batch process monitoring in this paper. In the devdopad method, just-in-time learning （ JITL ） and independent component analysis （ICA） were integrated to build JITL-ICA monitoring scheme. JITL was employed to tackle with the characteristics of batch process such as inherent time- varying dynamics, multiple operating phases, and especially the case of uneven length stage. According to new coming test data, the most correlated segmentation was obtained from batch-wise unfolded training data by JITL. Then, ICA served as the principal components extraction approach. Therefore, the non.Gaussian distributed data can also be addressed under this modeling framework. The effectiveness and superiority of JITL-ICA based monitoring method was demonstrated by fed-batch penicillin fermentation.

A Constrained Local Neighborhood Approach for Efficient Markov Blanket Discovery in Undirected Independent Graphs

When learning the structure of a Bayesian network,the search space expands significantly as the network size and the number of nodes increase,leading to a noticeable decrease in algorithm efficiency.Traditional constraint-based methods typically rely on the results of conditional independence tests.However,excessive reliance on these test results can lead to a series of problems,including increased computational complexity and inaccurate results,especially when dealing with large-scale networks where performance bottlenecks are particularly evident.To overcome these challenges,we propose a Markov blanket discovery algorithm based on constrained local neighborhoods for constructing undirected independence graphs.This method uses the Markov blanket discovery algorithm to refine the constraints in the initial search space,sets an appropriate constraint radius,thereby reducing the initial computational cost of the algorithm and effectively narrowing the initial solution range.Specifically,the method first determines the local neighborhood space to limit the search range,thereby reducing the number of possible graph structures that need to be considered.This process not only improves the accuracy of the search space constraints but also significantly reduces the number of conditional independence tests.By performing conditional independence tests within the local neighborhood of each node,the method avoids comprehensive tests across the entire network,greatly reducing computational complexity.At the same time,the setting of the constraint radius further improves computational efficiency while ensuring accuracy.Compared to other algorithms,this method can quickly and efficiently construct undirected independence graphs while maintaining high accuracy.Experimental simulation results show that,this method has significant advantages in obtaining the structure of undirected independence graphs,not only maintaining an accuracy of over 96%but also reducing the number of conditional independence tests by at least 50%.This significant performance improvement is due to the effective constraint on the search space and the fine control of computational costs.

Efficient Selection of Linearly Independent Atomic Features for Accurate Machine Learning Potentials

Machine learning potentials are promising in atomistic simulations due to their comparable accuracy to first-principles theory but much lower computational cost.However,the reliability,speed,and transferability of atomistic machine learning potentials depend strongly on the way atomic configurations are represented.A wise choice of descriptors used as input for the machine learning program is the key for a successful machine learning representation.Here we develop a simple and efficient strategy to automatically select an optimal set of linearly-independent atomic features out of a large pool of candidates,based on the correlations that are intrinsic to the training data.Through applications to the construction of embedded atom neural network potentials for several benchmark molecules with less redundant linearly-independent embedded density descriptors,we demonstrate the efficiency and accuracy of this new strategy.The proposed algorithm can greatly simplify the initial selection of atomic features and vastly improve the performance of the atomistic machine learning potentials.

Emotionally Resonant Branding: The Role of AI in Synthesising Dynamic Brand Images for Artists in the Music Industry

Artificial Intelligence (AI) expands its recognition rapidly through the past few years in the context of generating content dynamically, remarkably challenging the human creativity. This study aims to evaluate the efficacy of AI in enhancing personal branding for musicians, particularly in crafting brand images based on emotions received from the artist’s music will improve the audience perceptions regarding the artist’s brand. Study used a quantitative approach for the research, gathering primary data from the survey of 191 people—music lovers, musicians and music producers. The survey focuses on preferences, perceptions, and behaviours related to music consumption and artist branding. The study results demonstrate the awareness and understanding of AI’s role in personal branding within the music industry. Also, results indicate that such an adaptive approach enhances audience perceptions of the artist and strengthens emotional connections. Furthermore, over 50% of the participants indicated a desire to attend live events where an artist’s brand image adapts dynamically to their emotions. The study focuses on novel approaches in personal branding based on the interaction of AI-driven emotional data. In contrast to traditional branding concepts, this study indicates that AI can suggest dynamic and emotionally resonant brand identities for artists. The real time audience response gives proper guidance for the decision-making. This study enriches the knowledge of AI’s applicability to branding processes in the context of the music industry and opens the possibilities for additional advancements in building emotionally appealing brand identities.

Enhancing Music Learning With Digital Tools： A Case Study of a Student Using iSCORE

iSCORE is a digital tool, available without charge, which was designed for students who take lessons from independent music teachers. One of the challenges of this learning format is that students must develop strategies to practice on their own between lessons, iSCORE can help meet that challenge by supporting students as they develop strategies for self-regulation to enhance their goal-setting, practice strategies, and abilities to reflect and critique their progress. This paper describes a case study of a 15-year-old pianist who learned to play a difficult piece of repertoire by using iSCORE to archive and compare performances, develop strategies, and reflect on his learning.

A Study on the Effect of Creative Chinese Characters Learning on the Ability to Learn Chinese Old Sayings and Idioms Using K-Pop Music Video

Music is an extraordinary bridge between people all over the world so much as to be called a universal language. Idols and B-boys stages are fun, touching, and fantastic. Today, South Korean students are excited and enthusiastic about their colorful dance moves. The study is about creative educational methods that use K-pop music videos to learn the proverbs and old words that our ancestors learned to keep in mind and teach. K-pop lyrics are a rich reflection of the experiences of life and the world in which people are living today. Accordingly, this study can present new teaching and learning method examples that are used in class related to the old language associated with K-pop lyrics and can also introduce interesting class materials.

Autonomy and Foreign Language Learning

Independent language learning is one aspect of what the research literature calls learner autonomy, in other words, the ability and willingness of learners to study foreign languages on their own. This article illustrates the strategies I used to design, carry out and sustain my independent language learning project.

How to Use Skype in Autonomy Language Learning

In recent years,web-based language learning becomes a positive force both in education and in society as well as an essential facet of the teaching-learning process.The application of skype offers learners a opportunity to communicate with native spearkers who are geographically unaccessable during their independent learning.The main aim of this essay is trying to explain the langauge learning- friendly features of Skype and how to applicate them into aqusition of English in chinese setting.

Research on the Training Mode of “the Combination of College Students’ Extracurricular English Autonomous Learning and Chinese Culture” Based on WeChat Platform

In today’s college English extracurricular learning,college students often neglect the combination of English language learning and the input of Chinese traditional cultural knowledge,paying too much attention to Western culture learning,ignoring their traditional culture and lead to be speechless when encountering cultural exchange activities.The author believes that college students should pay attention to the input of Chinese traditional cultural content in the process of independent English learning outside the classroom.The creative team of college students led by the author through the WeChat platform,in Xinjiang Agricultural University,conducted a combination of Chinese culture input and English autonomous learning,aiming at strengthening the effectiveness of English learning,improving the self-learning ability and intercultural communication skills.

Educational Practices in the Model of Music Learning Theory of E. Edwin Gordon： An Observational Research

This paper analyzes the supervision activity, to which educators and teachers enrolled with AIGAM （Gordon Italian Association for the Musical Learning） are subject to every year and intends to verify the application of those principles expressed in the learning model of the MLT （Music Learning Theory） developed by educational psychologist E. Edwin Gordon （1989, 1999, 2000, 2001, 2007） and promoted internationally by various institutions and organizations specifically accredited. It describes the influence of the videotaped supervision on the process, functions of monitoring, and evaluation of educational practices, starting with an empirical model that has guided the interventions in a study of supervision on training aimed at consolidating and developing professional skills in music education in early childhood. This paper sought to understand： the kind of practices, interactions, communications developing during an educational actions, the existence of a consistent relationship between the principles expressed in the MLT and their application, the type and benefits of supervision performed by of video recording on stakeholders in terms of change in professional behavior, and finally whether the active supervision could be comparable with other kinds of approaches.

The Use of Music for Learning Languages

Throughout time,healers,philosophers,scientists,and teachers have recognized the place of music for therapeutic and developmental functions(Bancroft,1985:3-7).Researchers over the last twenty years have made astounding advances in the the ory of language acquisition.Many find the pedagogical conjoining of language and music compelling.The first part of this review focuses on the historical and developmental proofs of music' s relationship with language learning.In part two,neurological the ory on music and the mind are covered.Part three summarizes scholarly inquiry on the use of music for learning languages,espe cially those studies that could prove most instructive both for language teachers and for music therapists in the development of curricula.

Effective Paths of Junior Middle School English Autonomous Learning Under the Background of “Internet+”

Under the background of“Internet+”learning method,junior high school English independent learning is individualized,autonomous,and interactive.“Internet+”learning can not only improve students’learning efficiency and learning quality,but also promote their comprehensive development.Therefore,in this paper,we analyzed the significance of developing junior high school English autonomous learning under the background of“Internet+,”explained the theoretical basis of autonomous learning,and how the concept of“Internet+”can be integrated into English teaching.

Anomaly Detection of UAV State Data Based on Single-Class Triangular Global Alignment Kernel Extreme Learning Machine

Unmanned Aerial Vehicles(UAVs)are widely used and meet many demands in military and civilian fields.With the continuous enrichment and extensive expansion of application scenarios,the safety of UAVs is constantly being challenged.To address this challenge,we propose algorithms to detect anomalous data collected from drones to improve drone safety.We deployed a one-class kernel extreme learning machine(OCKELM)to detect anomalies in drone data.By default,OCKELM uses the radial basis(RBF)kernel function as the kernel function of themodel.To improve the performance ofOCKELM,we choose a TriangularGlobalAlignmentKernel(TGAK)instead of anRBF Kernel and introduce the Fast Independent Component Analysis(FastICA)algorithm to reconstruct UAV data.Based on the above improvements,we create a novel anomaly detection strategy FastICA-TGAK-OCELM.The method is finally validated on the UCI dataset and detected on the Aeronautical Laboratory Failures and Anomalies(ALFA)dataset.The experimental results show that compared with other methods,the accuracy of this method is improved by more than 30%,and point anomalies are effectively detected.