• Journal of the Korean Institute of Educational Facilities
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• v.13 no.1
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• pp.17-25
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• 2006

Elementary school classroom designs have been developed toward open education system to provide students diverse and improved educational environments since the early of 1990 in Korea. Unfortunately, the quality of music room has not still shown dramatic improvements due to the lack of the acoustical knowledges of architects. This report aims to investigate typical acoustic quality of previous or current music room of elementary schools and show new acoustic treatment technologies to improve the room acoustic of music room by adapting composite perforated panel system and diffusion technology. The music room at Daihyun Elementary school in Yongin was chosen as a case study of this report. The music room was measured to be analyzed using field measurements and the acoustical specifications of composite perforated panel systems and kinds of diffusors were set. Acoustic measurements were performed after the renovation to show the differences between previous room acoustic and after the acoustic renovations. As the result, the case study has shown that the new composite perforated panel systems and diffusion surfaces lowered reverberation time at proper level along with improving the clarity of music, RASTI, and spatial impressions. Also, acoustic interferences such as comb filtering and flutter echoes have been controlled dramatically by diffusive surfaces. The study shows music rooms in elementary schools, middle and high schools can be improved by adapting composite perforated panel systems and diffusors.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.4
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• pp.337-342
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• 2016

In this paper, we studied a modified linear prediction method to estimate target signal correctly. Linear prediction method estimate direction-of-arrival to linear combination for any antenna element and other antenna elements. Modified linear prediction used optimal weight and posterior probability method. Through simulation, we are comparative analysis about the performance of proposed, bartlett and MUSIC method. From simulation, Bartlett and MUSIC method was estimation 3 targets signal, and proposed method estimated 4 targets. We showed the superior performance of the proposed algorithm relative to the classical method in order to estimate of target signals.

• Journal of The Korean Society of Integrative Medicine
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• v.4 no.3
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• pp.31-37
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• 2016

Purpose : The purpose of this study was to conduct a music listening program and investigate its effects on depression and academic stress. Method : 30 male and female at K university located in Busan Metropolitan City were selected as subject of this study and a half of them was experimental group, other were control group. An academic stress tester formed by modifying and supplementing sentences and vocabularies of the questionnaire developed by Oh, Mi Hyang and Cheon, Seong Mun (1994) to help understanding of students was used with Beck Depression Inventory (BDI) by Beck(1967), both before and after conductance of music listening program. Result : First of all, In the Academic stress was no difference between each group and there was no difference in effect according to the comparison period. Second, Score of depression in Experimental group was decreased after application of music listening program than control group's. Third, Score of depression in Experimental group was lower than control group's, depending on period. Conclusion : Put the results of this research together, music listening program dosen't affect the academic stress. But this program deceased the depression. In further study, it will be required to subdivided for academic stress and depression study from evaluation of the several times and apply a variety of diseases.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.400-404
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• 2015

In this paper, we study for direction of arrival MUSIC spatial spectrum algorithm in order to desired signal estimation in spatial. Proposal MUSIC spatial spectrum algorithm in paper use model error and Bayesian method to estimation on correct target position. Receiver array response vector using adaptive array antenna use Bayesian method, and target position estimate to update weight value with model error method. Target's signal estimation of desired direction of arrival in this paper apply weight value of signal covariance matrix for array response vector after removing incident signal interference and noise, respectively. Though simulation, we analyze to compare proposed method with general method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.691-696
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• 2018

We propose an algorithm to update weight to use the mean square error method and mutual coupling matrix in a coherent channel. The algorithm proposed in this paper estimates the desired signal by using the updated weight. The updated weight is obtained by covariance matrix using mean square error and mutual coupling matrix. The MUSIC algorithm, which is direction of arrival estimation method, is mostly used in the desired signal estimation. The MUSIC algorithm has a good resolution because it uses subspace techniques. The proposed method estimates the desired signal by updating the weights using the mutual coupling matrix and mean square error method. Through simulation, we analyze the performance by comparing the classical MUSIC and the proposed algorithm in a coherent channel. In this case of the coherent channel for estimating at the three targets (-10o, 0o, 10o), the proposed algorithm estimates all the three targets (-10o, 0o, 10o). But the classical MUSIC algorithm estimates only one target (x, x, 10o). The simulation results indicate that the proposed method is superior to the classical MUSIC algorithm for desired signal estimation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.869-876
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• 2021

In the field of music, various AI composition methods using machine learning have recently been attempted. However, most of this research has been centered on Western music, and little research has been done on Korean traditional music. Therefore, in this paper, we will create a data set of Korean traditional music, create a melody using three algorithms based on the data set, and compare the results. Three models were selected based on the similarity between language and music, LSTM, Music Transformer and Self Attention. Using each of the three models, a melody generator was modeled and trained to generate melodies. As a result of user evaluation, the Self Attention method showed higher preference than the other methods. Data set is very important in AI composition. For this, a Korean traditional music data set was created, and AI composition was attempted with various algorithms, and this is expected to be helpful in future research on AI composition for Korean traditional music.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.10
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• pp.3673-3679
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• 2010

This study is prepared to suggest how to develop sight-singing and ear-training program for applied music-major students. Starting from analysing the internal environment and currently existing materials, based on the questions collected for applied music-major students, integrated program for sight-singing and ear-training was considered. The use of the various kinds of classical and popular music literature, the examples of improvisation in rhythm and harmony, based on the music theories, are focal points of this program recommended here with.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.438-449
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• 2015

Recognition systems for scanned or printed music scores that have been implemented on personal computers have received attention from numerous scientists and have achieved significant results over many years. A modern trend with music scores being captured and played directly on mobile devices has become more interesting to researchers. The limitation of resources and the effects of illumination, distortion, and inclination on input images are still challenges to these recognition systems. In this paper, we introduce a novel approach for recognizing music scores captured by mobile cameras. To reduce the complexity, as well as the computational time of the system, we grouped all of the symbols extracted from music scores into ten main classes. We then applied each major class to SVM to classify the musical symbols separately. The experimental results showed that our proposed method could be applied to real time applications and that its performance is competitive with other methods.

• Journal of Information Technology Services
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• v.14 no.4
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• pp.199-220
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• 2015

Recently, many internet users are using mobile music service. In this paper, we aim to examine the effects of system quality factors and relation quality factors on continuance intention in the context of mobile music service. In order to analyze the antecedents of continuance intention, we introduced independent variables such as ease of use, stability, trust, involvement and unity. We also consider customer value and customer satisfaction as mediators. For empirical analysis, we surveyed 240 users of mobile music service. We conduct PLS (Partial Least Square) analysis for SEM (Structural Equation Modeling). As a result, 8 of proposed 12 hypotheses were accepted. Especially, system quality, trust and unity show positive influence on customer satisfaction significantly. Involvement and unity are positively related to customer value. Customer value and customer satisfaction show positive influence on continuance intention significantly. The results of this research can be useful guidelines for mobile music service users and providers.

• Journal of the Korea Computer Graphics Society
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• v.29 no.4
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• pp.1-6
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• 2023

To enhance immersive experiences for metaverse environements, background music is often used. However, the background music is mostly pre-matched and repeated which might occur a distractive experience to users as it does not align well with rapidly changing user-interactive contents. Thus, we implemented a system to provide a more immersive metaverse conversation experience by 1) developing a regression neural network that extracts emotions from an utterance using KEMDy20, the Korean multimodal emotion dataset 2) selecting music corresponding to the extracted emotions from an utterance by the DEAM dataset where music is tagged with arousal-valence levels 3) combining it with a virtual space where users can have a real-time conversation with avatars.