• Title/Summary/Keyword: Music Selection

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Implementation of Lighting Technique and Music Therapy for Improving Degree of Students Concentration During Lectures

  • Han, ChangPyoung;Hong, YouSik
    • International Journal of Internet, Broadcasting and Communication
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    • v.12 no.3
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    • pp.116-124
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    • 2020
  • The advantage of the distance learning universities based on the 4th Industrial Revolution is that anyone can conveniently take lectures anytime, anywhere on the web. In addition, research has been actively conducted on the effect of light color and temperature control upon student performance during online classes. However, research on how the conditions of subjects, lighting colors, and music selection improve the degree of a student's concentration during online lectures has not been completed. To solve these problems in this paper, we have developed automatic analysis system SW for the weak subjects of learners by applying intelligent analysis algorithm, have proposed and simulated music therapy and art therapy. Moreover, It proposed in this paper an algorithm for an automatic analysis system, which shows the weak subjects of learners by adopting intelligence analysis algorithms. We also have presented and simulated a music therapy and art therapy algorithms, based on the blended learning, in order to increase students concentration during lecture.

Noise Source Localization by Applying MUSIC with Wavelet Transformation (웨이블렛 변환과 MUSIC 기법을 이용한 소음원 추적)

  • Cho, Tae-Hwan;Ko, Byeong-Sik;Lim, Jong-Myung
    • Transactions of the Korean Society of Automotive Engineers
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    • v.16 no.2
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    • pp.18-28
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    • 2008
  • In inverse acoustic problem with nearfield sources, it is important to separate multiple acoustic sources and to measure the position of each target. This paper proposes a new algorithm by applying MUSIC(Multiple Signal Classification) to the outputs of discrete wavelet transformation with sub-band selection based on the entropy threshold, Some numerical experiments show that the proposed method can estimate the more precise positions than a conventional MUSIC algorithm under moderately correlated signal and relatively low signal-to-noise ratio case.

Study on Background Music of Distributors (유통점의 배경음악에 관한 연구)

  • LEE, Joon-Pyo;HWANG, Hee-Joong
    • Journal of Distribution Science
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    • v.17 no.9
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    • pp.127-131
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    • 2019
  • Purpose - This study focuses on clues that can clearly amplify the effects of background music. Review which store environments have a direct and positive impact on consumer responses, such as purchases. Research design, data, and methodology - This study focuses on clues that can clearly amplify the effects of background music. The purpose of this study is to examine what kind of store environment, combined with background music, has a direct and positive effect on consumer reactions such as purchase, and suggest future research directions. Results - The manager decides to use background music in the store because it is relatively inexpensive and easy to identify the emotional response of the consumer. In addition, appropriate background music lowers the psychological purchasing barriers of consumers. Previous studies have often not conducted a basic review of whether consumers perceive background music when it is used in retail stores. For example, it is necessary to make sure that the volume of the background music is loud enough and that the noise is properly excluded despite the congestion of the store so that the pure influence of the background music on the consumer can be measured. A way for store managers to clarify and differentiate their identity is to create a unique and satisfying store atmosphere for their customers. In order to help customers focus on their purchases, store managers must use marketing elements to integrate the five senses. And they should plan background music aiming at synergy effect of these five senses. In other words, in order to make the store atmosphere positive, it is not enough to have a suitable visual design interior or background music in the store, and consumers should have the opportunity to smell, taste and touch it directly. Conclusions - In conclusion, we hope that the following issues will be studied by several scholars in the future. It should be clarified that the impact of background music on customers varies depending on the customer's movement in the store, the selection of the background music genre order, and the timing (interval) of background music exposure to the customer.

Music Recommendation Technique Using Metadata (메타데이터를 이용한 음악 추천 기법)

  • Lee, Hye-in;Youn, Sung-dae
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.75-78
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    • 2018
  • Recently, the amount of music that can be heard is increasing exponentially due to the growth of the digital music market. Because of this, online music service users have had difficulty choosing their favorite music and have wasted a lot of time. In this paper, we propose a recommendation technique to minimize the difficulty of selection and to reduce wasted time. The proposed technique uses an item - based collaborative filtering algorithm that can recommend items without using personal information. For more accurate recommendation, the user's preference is predicted by using the metadata of the music source and the top-N music with high preference is finally recommended. Experimental results show that the proposed method improves the performance of the proposed method better than it does when the metadata is not used.

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An Investigation on Solution of Insecurity Sense Using a Music Performing Magnetic Resonance Imaging: Case report (자기공명영상 검사 시 음악을 이용하여 환자의 불안감 해소에 관한 고찰: 사례 보고)

  • Goo, Eun-Hoe;Kang, Soo-Cheol
    • Korean Journal of Digital Imaging in Medicine
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    • v.11 no.2
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    • pp.59-62
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    • 2009
  • The purpose of this study is to know about solution of insecurity sense for solving the tediousness and inducing comfortableness in long time MRI examination. Studies were examined with total of 117 patients that the intention expression of self is possible for a month without dividing man and woman in november 2006. Examination methods were filled in questionnaire after testing using Siemens Impact 1.0T. The musical art were selected through intranet search and record sale inquiry using CD player and speaker. That kind of a music were selected with Korean classical music's 10 chapter, pop song 10's chapter, classic's 10 chapter and Korean popular song's 10 chapter. With analytical method, patients of under 40 year-old, or older and patients using ear-pad and head-phone were classified into groups. As analysis result with question item of questionnaire, most of the patients were showed a favor(36.72%) in playing a music, specially, examination of about 15.38% which uses the headphone prefer a music as older generation of over 40 year-old. In conclusion, with installing of the professional musical program in MRI test rooms, if listening to the music with selection by oneself before testing by season, age, time through development of appropriate musical program will be able to expect the more effect.

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Comparison of EEG Feature Vector for Emotion Classification according to Music Listening (음악에 따른 감정분류을 위한 EEG특징벡터 비교)

  • Lee, So-Min;Byun, Sung-Woo;Lee, Seok-Pil
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.63 no.5
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    • pp.696-702
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    • 2014
  • Recently, researches on analyzing relationship between the state of emotion and musical stimuli using EEG are increasing. A selection of feature vectors is very important for the performance of EEG pattern classifiers. This paper proposes a comparison of EEG feature vectors for emotion classification according to music listening. For this, we extract some feature vectors like DAMV, IAV, LPC, LPCC from EEG signals in each class related to music listening and compare a separability of the extracted feature vectors using Bhattacharyya distance. So more effective feature vectors are recommended for emotion classification according to music listening.

Speech/Music Discrimination Using Multi-dimensional MMCD (다차원 MMCD를 이용한 음성/음악 판별)

  • Choi, Mu-Yeol;Song, Hwa-Jeon;Park, Seul-Han;Kim, Hyung-Soon
    • MALSORI
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    • no.60
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    • pp.191-201
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    • 2006
  • Discrimination between speech and music is important in many multimedia applications. Previously we proposed a new parameter for speech/music discrimination, the mean of minimum cepstral distances (MMCD), and it outperformed the conventional parameters. One weakness of MMCD is that its performance depends on range of candidate frames to compute the minimum cepstral distance, which requires the optimal selection of the range experimentally. In this paper, to alleviate the problem, we propose a multi-dimensional MMCD parameter which consists of multiple MMCDS with combination of different candidate frame ranges. Experimental results show that the multi-dimensional MMCD parameter yields an error rate reduction of 22.5% compared with the optimally chosen one-dimensional MMCD parameter.

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The Effects of Music Interventions on High-risk Neonates in NICUs: Systematic Review and Meta-analysis (신생아집중치료실 고위험 신생아 대상 음악중재연구에 대한 체계적 문헌고찰 및 메타분석)

  • Kim, Hye Rang;Park, Hye Young
    • Journal of Music and Human Behavior
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    • v.20 no.2
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    • pp.115-142
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    • 2023
  • The purpose of this study was to analyze and evaluate music intervention research conducted with high-risk neonates in NICUs in both domestic and international settings. Seventeen music intervention studies were identified, and their characteristics, including type of music, music provider, and treatment frequency, and outcomes (i.e., neonatal vital signs) were reviewed and analyzed along with meta-analysis. For music interventions targeting high-risk neonates in NICUs, the effect sizes of the neonates' vital signs were classified as either medium or large. In addition, larger effect sizes were associated with a combination of live and recorded music, nonmusical therapists as the music providers, and treatment frequency of one to five sessions per week. These research findings verify the clinical value of music for high-risk neonates and provide insights into the selection of music elements, music delivery methods, and music providers in NICU music interventions.

Case Study on Career Decision Process of Music Therapy Graduate Students without Music Training (비음악 전공자들의 음악치료 진로선택과정에 대한 연구)

  • Park, Hye Young
    • Journal of Music and Human Behavior
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    • v.10 no.1
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    • pp.25-45
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    • 2013
  • The purpose of this study is to explain experiences of non-music majors to changing their majors into music therapy and to provide the preliminary study for deriving a grounded theory. For that, in-depth interviews were performed targeting 5 students who did not major in music in their undergraduate courses selected from the graduate students who are majoring in music therapy at the colleges located in Seoul. Data was analyzed for the study by applying the modified grounded theory. The result of study showed that they selected the course of music therapy career as they were motivated by the realistic demand for future employment, career potentials and other realistic causes. These factors caused them to study the surrounding situations and conduct the detailed research on the possibility of music therapy. These factors were also dependent on the individual characteristics, external elements and music background. These experiences were connected to the self-integration and pursuit of growth by newly setting their relation to the 'Music Child'. In addition, the demand of being the meaningful existence in relationship also affected them to more specify their aspirations in the progress of career selection on a continual basis. This study is meaningful as it provides the actual information on them.

Bayesian network based Music Recommendation System considering Multi-Criteria Decision Making (다기준 의사결정 방법을 고려한 베이지안 네트워크 기반 음악 추천 시스템)

  • Kim, Nam-Kuk;Lee, Sang-Yong
    • Journal of Digital Convergence
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    • v.11 no.3
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    • pp.345-352
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    • 2013
  • The demand and production for mobile music increases as the number of smart phone users increase. Thus, the standard of selection of a user's preferred music has gotten more diverse and complicated as the range of popular music has gotten wider. Research to find intelligent techniques to ingeniously recommend music on user preferences under mobile environment is actively being conducted. However, existing music recommendation systems do not consider and reflect users' preferences due to recommendations simply employing users' listening log. This paper suggests a personalized music-recommending system that well reflects users' preferences. Using AHP, it is possible to identify the musical preferences of every user. The user feedback based on the Bayesian network was applied to reflect continuous user's preference. The experiment was carried out among 12 participants (four groups with three persons for each group), resulting in a 87.5% satisfaction level.