• Journal of Korean Academy of Nursing
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• v.36 no.2
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• pp.321-329
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• 2006

Purpose: The purpose of this study was to determine the effects of music therpy on anxiety and depression in patients undergoing hemodialysis. Method: The study was designed using a nonequivalent control group pretest-posttest design. The subjects consisted of 36 patients (Experimental group: 18, Control group: 18) who received hemodialysis in three hospitals located in Seoul. The measures were a Music Preference Questionnaire (MPQ), anxiety measurement, and depression measurement. Data was collected from December 26, 2004 to April 2, 2005 through questionnaires. The collected data was analyzed by the SPSS 10.0 program. Result: The first hypothesis that patients undergoing hemodialysis who received music therapy would have less anxiety than patients undergoing hemodialysis who did not receive music therapy was supported(F=8.05, p=.008). The second hypothesis that patient undergoing hemodialysis who received music therapy would have less depression than patients undergoing hemodialysis who did not receive music therapy was supported(F=11.86, p=.002). Conclusion: The results of this study suggest that music therapy may be applied as a method of nursing intervention contributing to the improvement of quality life by reducing their anxiety and depression of patients undergoing hemodialysis.

• Journal of IKEEE
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• v.14 no.4
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• pp.305-311
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• 2010

Most recent web search engines perform effective keyword-based multimedia contents retrieval by investigating keywords associated with multimedia contents on the Web and comparing them with query keywords. On the other hand, most music and compilation albums provide professional artwork as cover art that will be displayed when the music is played. If the cover art is not available, then the music player just displays some dummy or random images, but this has been a source of dissatisfaction. In this paper, in order to automatically create cover art that is matched with music contents, we propose a music album cover art creation scheme based on music contents analysis and result synthesis. We first (i) analyze music contents and their lyrics and extract representative keywords, (ii) expand the keywords using WordNet and generate various queries, (iii) retrieve related images from the Web using those queries, and finally (iv) synthesize them according to the user preference for album cover art. To show the effectiveness of our scheme, we developed a prototype system and reported some results.

• Journal of Music and Human Behavior
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• v.8 no.2
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• pp.47-64
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• 2011

This study was to examine music preferences of school-aged cochlear implant(CI) recipients in comparison with normal hearing(NH) children. Participants were 12 CI recipients and 155 NH children. CI children were recruited from a hospital in Seoul and they had cochlear implants for longer than two years(M = 4.7). NH children were randomly sampled. All participants were asked to respond to a questionnaire and rate their music preferences. The results showed that while 58.33% of CI recipients preferred child voices, 71.61% of NH children preferred adult voices. For preferred frequency range, both of CI and NH groups preferred higher frequency. With regard to preferred musical styles, while CI children gave the highest rating(M = 3.58) to Korean folk songs on the 5-point Likert scale, popular music and TV and soundtrack music were found to be the highest-rated styles(M = 3.83) for NH children. These results indicate that self-rated music preferences of CI recipients may be affected by a musical environment that these children have experienced. The results also implies that the provision of appropriate musical input and experiences would significantly affect future music preferences and appreciation of CI children. Providing useful information about music preferences of CI recipients in comparison with NH children, this study has significant implications for further studies on this population.

• Journal of Music and Human Behavior
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• v.12 no.1
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• pp.23-42
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• 2015

This study investigated the harmonic preference of children and adolescents depending on age and musical training. A total of 684 primary and secondary school students participated in this study. For this study, a four-measure melody was composed and constructed in four levels of harmonic complexity, determined by the rate of nonharmonic notes used and immediacy of harmonic resolution. Participants rated the degree of their perceived complexity and their preferences after listening to each musical stimulus. Ratings from the participants were analyzed in terms of the effect of age and the length of musical training. The results showed that younger students demonstrated little to no change in their preference regardless of the complexity level. Middle and high school students showed significantly decreased preference with increased harmonic complexity. High school students with more musical instrument training perceived changes in harmonic complexity more sensitively and showd higher level of optimal complexity. Younger students was affected by musical training relatively less than older students. This study presents the baseline data to be considered when determining the appropriate level of harmonic complexity for music appreciation of young population.

• The KIPS Transactions:PartB
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• v.17B no.4
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• pp.263-274
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• 2010

To provide context-aware music recommendation service, first of all, we need to catch music mood that a user prefers depending on his situation or context. Among various music characteristics, music mood has a close relation with people‘s emotion. Based on this relationship, some researchers have studied on music mood detection, where they manually select a representative segment of music and classify its mood. Although such approaches show good performance on music mood classification, it's difficult to apply them to new music due to the manual intervention. Moreover, it is more difficult to detect music mood because the mood usually varies with time. To cope with these problems, this paper presents an automatic method to classify the music mood. First, a whole music is segmented into several groups that have similar characteristics by structural information. Then, the mood of each segments is detected, where each individual's preference on mood is modelled by regression based on Thayer's two-dimensional mood model. Experimental results show that the proposed method achieves 80% or higher accuracy.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.14 no.2
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• pp.173-180
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• 2007

Purpose: The present study was done to examine the effect of music therapy on anxiety and pain in patients for whom a ureteral stent was inserted under local anesthesia. Method: The participants in this study were 22 patients who received a ureteral stent at the Day Surgery Center of C University Hospital during the period from May to October in 2006. The patients were divided into a control group (n=11) and an experimental group (n=11). For the experimental group, music was played according to their musical preference using headphones. The music was provided from the point when the patient took the posture for the operation and was covered with a sterilized drape to the point when the cystoscope was removed after finishing the operation. The control group was only provided with ordinary nursing services. Results: The results show that the provision of music therapy to these patients is effective in reducing the patients' salivary cortisol and Vas-anxiety score and stabilizing their systolic blood pressure. Conclusion: We conclude that music therapy can be actively used as a nursing intervention for reducing anxiety in patients who receive operations under local anesthesia.

• Korean Institute of Interior Design Journal
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• v.24 no.4
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• pp.143-151
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• 2015

This study was conducted under the premise that the university library's subject specialization room is in need of major modifications in order to accommodate the needs of various majors. The subject specialization room will be able to support university library users who are inclined to use the general reading room. Therefore, the study presents spatial planning for the average university library's subject specialization room by taking into account student majors. This could be a guideline for the construction and renovation of university libraries in the future. The summary of results for this study and the conclusions are as follows: 1)Natural sciences subject specialization room should be, partially connected with the humanities/social science subject specialization room in order to provide an open-concept reference room. In the shared area connecting the two subject specialization rooms needs to be installed a staff counter and subject specialist librarian service booth for users of both subject specialization rooms. 2)For humanities/social sciences subject specialization room, partially connect with the natural sciences subject specialization room. In the connecting area between the two rooms, plan an open-concept lounge for resting and reading. 3)It is best to plan subject specialization room for art/music/physical education majors separate from the subject specification room of other majors. Structurally separate art/music/physical education major subject specialization rooms from the building or plan a separate room in an art/music/physical education building. Users of art/music/physical education majors showed a high preference for a spatially separated and specialized library structure, which proves that an art/music/physical education library need to be planed based on the specialized library structure found in law school libraries or medical school libraries. Plan the center of the room with open-concept based reading room. Use wall-sides, partitions, or shelves to create reading space separate from the shelving area.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.133-140
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• 2012

In this paper, we propose a music recommendation method considering users' tags by collaborative tagging in a social music site. Since collaborative tagging allows a user to add keywords chosen by himself to web resources, it provides users' preference about the web resources concretely. In particular, emotional tags which represent human's emotion contain users' musical preference more directly than factual tags which represent facts such as musical genre and artists. Therefore, to classify the tags into the emotional tags and the factual tags and to assign weighted values to the emotional tags, a tag ontology called UniTag is developed. After preprocessing the tags, the weighted tags are used to create user profiles, and the music recommendation algorithm is executed based on the profiles. To evaluate the proposed method, a conventional playcount-based recommendation, an unweighted tag-based recommendation, and an weighted tag-based recommendation are executed. Our experimental results show that the weighted tag-based recommendation outperforms other two approaches in terms of precision.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.19-24
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• 2010

The rise of music resources has led to a parallel rise in the need to manage thousands of songs on user devices. So users have a tendency to build playlist for manage songs. However the manual selection of songs for creating playlist is a troublesome work. This paper proposes an auto playlist generation system considering user context of use and preferences. This system has two separated systems; 1) the mood and emotion classification system and 2) the music recommendation system. Firstly, users need to choose just one seed song for reflecting their context of use. Then system recommends candidate song list before the current song ends in order to fill up user playlist. User also can remove unsatisfied songs from the recommended song list to adapt the user preference model on the system for the next song list. The generated playlists show well defined mood and emotion of music and provide songs that the preference of the current user is reflected.

• 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.