• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.11
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• pp.1598-1603
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• 2013

Recently, researches on analyzing relationship between the state of emotion and musical stimuli are increasing. In many previous works, data sets from all extracted channels are used for pattern classification. But these methods have problems in computational complexity and inaccuracy. This paper proposes a selection of optimal EEG channel to reflect the state of emotion efficiently according to music listening by analyzing stochastic feature vectors. This makes EEG pattern classification relatively simple by reducing the number of dataset to process.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.2
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• pp.124-128
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• 2011

Music emotion recognition is currently one of the most attractive research areas in music information retrieval. In order to use emotion as clues when searching for a particular music, several music based emotion recognizing systems are fundamentally utilized. In order to maximize user satisfaction, the recognition accuracy is very important. In this paper, we develop a new music emotion recognition system, which employs a multilabel feature selector and multilabel classifier. The performance of the proposed system is demonstrated using novel musical emotion data.

• 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.

• 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.

• 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.

• Journal of Naturopathy
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• v.12 no.2
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• pp.77-84
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• 2023

Background: Examining the fidelity of intervention using music for pain alleviation is crucial in developing effective music intervention for pain management. Purposes: This study aims to examine the fidelity of music intervention studies purported to alleviate post-surgery pain. Methods: Thirteen studies from 2000 to 2023 were searched and reviewed for their intervention providers, music protocol, session management, duration, music selection, and implementation rationale. Results: Four studies (30.77%) provided interventions based on therapeutic principles for music on pain management; reporting 4 intervention components out of 7. Intervention design and evidence varied, indicating low fidelity. Conclusion: Enhancing fidelity in music interventions for post-joint replacement pain alleviation is vital for further use of music for pain management. Researchers should develop systematic interventions based therapeutic mechanism of music.

• 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.

• 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.

• 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.

• 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.