• Journal of Korea Multimedia Society
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• v.17 no.11
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• pp.1296-1306
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• 2014

Recently there are many attempts that IT convergence has been studied together with very different sector like art and music. If it is possible to make a formal model with combination of engineering with strong creative sector like music, there will be some advantages to analyze its contents easily. In this study, the model has been provided to utilize music analysis and compose algorithm through the formal model research of Sonata. To this end, this study has been provided a formal model of Sonata with the Petri net model being widely used and verify the effectiveness of the proposed model on the case of Piano Sonata K. 332.

• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.97-106
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• 2017

The purpose of this convergence study was to identify the effects of favorite music therapy on anxiety, fatigue, and vital signs of patients undergoing prostatectomy with spinal anesthesia. This study used a nonequivalent control group design. A sample of 45 patients was included. The experimental group was given music therapy during operation. The data were collected using a structured questionnaire and monitoring at 30 min before operation, at 20 min and 40min undergoing operation, and at arrival recovery room after operation. Data were analyzed using descriptive statistics, ${\chi}^2-test$, Fisher's exact test, t-test, repeated measures ANOVA. The experimental group reported significantly lower anxiety and lower fatigue than the control group(p=.001; p=.020). However there were no significant differences in the systolic blood pressure, diastolic blood pressure and pulse rate between groups(p=.821; p=.473; p=.782). This findings indicate that the tailored favorite music therapy can be an effective nursing intervention for patient undergoing prostatectomy with spinal anesthesia to reduce anxiety and fatigue related to operation.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.214-220
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• 2021

With the rapid spread of smartphones, it has become common to listen to music everywhere, just like background music in life, so it is necessary to create a music database that can make recommendations according to individual circumstances and conditions. This paper proposes a music recommendation model through social media. Since emotions, situations, time of day, weather, etc. are included in hashtags, it is possible to build a social media-based database that reflects the opinions of various people with collective intelligence. We use web crawling to collect and categorize different hashtags from posts with music title hashtags to use real listeners' opinions about music in a database. Data from social media is used to create a music database, and music is classified in a different way from collaborative filtering, which is mainly used by existing music platforms.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.175-182
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• 2020

In this study, we introduced the technique of matching classical music using deep learning to design soundscape that can help the viewer appreciate painting and proposed an evaluation index to evaluate how well matching painting and music. The evaluation index was conducted with suitability evaluation through the Likeard 5-point scale and evaluation in a multimodal aspect. The suitability evaluation score of the 13 test participants for the deep learning based best match between painting and music was 3.74/5.0 and band the average cosine similarity of the multimodal evaluation of 13 participants was 0.79. We expect multimodal evaluation to be an evaluation index that can measure a new user experience. In addition, this study aims to improve the experience of multisensory artworks by proposing the interaction between visual and auditory. The proposed matching of painting and music method can be used in multisensory artwork exhibition and furthermore it will increase the accessibility of visually impaired people to appreciate artworks.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.41-46
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• 2010

In this paper, the DoA(Direction of Arrival) estimator using unitary MUSIC algorithm is studied. The complex-valued correlation matrix of MUSIC algorithm is transformed to the real-valued one using unitary transform for easy implementation. The eigenvalue and eigenvector are obtained by the combined Jacobi-CORDIC algorithm. CORDIC algorithm can be implemented by only ADD and SHIFT operations and MUSIC spectrum computed by 256 point DFT algorithm. Results of unitary MUSIC algorithm designed by System Generator for FPGA implementation is entirely consistent with Matlab results. Its performance is evaluated through hardware co-simulation and resource estimation.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1502-1508
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• 2017

A musical key is a fundamental concept in Western music theory. It is a collective characterization of pitches and chords that together create a musical perception of the entire piece. It is based on a group of pitches in a scale with which a music is constructed. Each key specifies the set of seven primary chromatic notes that are used out of the twelve possible notes. This paper presents a method that identifies the key of a song using Hidden Markov Models given a sequence of chroma features. Given an input song, a sequence of chroma features are computed. It is then classified into one of the 24 keys using a discrete Hidden Markov Models. The proposed method can help musicians and disc-jockeys in mixing a segment of tracks to create a medley. When tested on 120 songs, the success rate of the music key identification reached around 87.5%.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.74-85
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• 2020

In this study, we investigated the necessity and limitations of music composition required in TV documentary by conducting in-depth interviews with 20 music directors currently working at Korean Broadcasting System (KBS). Our research has shown that composition of music is necessary. However, in reality, it is difficult to use the composed music due to problems such as time and cost of composing and trust in the music composer; so music libraries, film music, or other music are used instead of the composed music in many situations. However, at the time when companies like its rival Netflix are aware of the importance of sound, the impact of Netflix could lead to a decline in the quality of terrestrial TV, which could lead to a weakening of competitiveness. Recently, in the case of sound programs, the sales of secondary works are active due to "internet uploading using YouTube" or "exporting programs", but the sales have been hindered by restrictions on the use of copyrighted works. The music source of library is said to be the one whose copyright problem has been resolved. In this study, we show that the composed music is an ultimate alternative to TV documentaries, since the library music is sometimes suspended due to the situations of management companies.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.88-100
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• 2020

This is an exploratory study based on the literature reviews which examined the possibilities and necessities of multimodal writing curriculum for liberal education. The purpose of this study is to analyze the existing research results which utilized the teaching methods associating music and writing, and to find the educational implications, and finally in terms of writing education, to suggest the possibilities of writing classes' convergent forms with music extracted from the results of the existing studies. Those studies were categorized to four patterns: WAC, effects of therapy, materials for writing, and new literacy. Based on Meyrowitz's perspective, firstly music can be utilized as a circumstance, which means a teacher can indirectly take the emotional, reminding, and healing effects of background musics. Secondly, music can play an important role of materials in thinking and writing, which is the most generally utilized pattern today. The effects are found in all of affective, cognitive, and strategic domains by utilizing music as a sort of reading materials. Thirdly, the convergent writing of music and narrative is suggested. Music is an independent language that can interact with narrative and construct text meanings in this kind of writing classes. These three dimensions of convergence have different perspectives, but sometimes occur at a same time or as a connected pattern. This study proposes that writing teachers need to improve their competence in music as well and to have professional concerns and efforts to develop their convergent writing teaching skills with music for these classes. Finally, this study stresses that team teaching can be an alternative for them.

• Design Convergence Study
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• v.14 no.4
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• pp.277-292
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• 2015

Recently, as TV home shopping has entered into the stage of stability, competition between the same lines of business has become more intense. Thus, this research goals have been determined in order to analyze the purchase intent of customers related with the genre and tempo of background music of TV home shopping by different types of products. In order to achieve the research goals, thorough research on related literatures have been conducted and found out about the background music. Furthermore, the characteristics of background music of actual TV home shopping broadcasting have been analyzed, focusing on the genre and tempo of the music. In addition, a survey has been conducted in order to verify what kind of music genre and tempo of the background music has an influence on the highest purchase intent of the chosen three products(sportswear, household appliances, fresh and processed foods). This study investigated the influence of background music of TV home shopping in relation to the purchase intent of customers. Also, this study has significance in the sense that it analyzed the causal relationship between the background music of home shopping and reactions of customers by categorizing products in details and using the music genre and tempo as the independent variables that affect the purchase intent of customers.

• ETRI Journal
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• v.43 no.6
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• pp.1081-1092
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• 2021

Electroencephalography (EEG) recordings taken during the perception of music tempo contain information that estimates the tempo of a music piece. If information about this tempo stimulus in EEG recordings can be extracted and classified, it can be effectively used to construct a music-based brain-computer interface. This study proposes a novel convolutional recurrent attention model (CRAM) to extract and classify features corresponding to tempo stimuli from EEG recordings of listeners who listened with concentration to the tempo of musics. The proposed CRAM is composed of six modules, namely, network inputs, two-dimensional convolutional bidirectional gated recurrent unit-based sample encoder, sample-level intuitive attention, segment encoder, segment-level intuitive attention, and softmax layer, to effectively model spatiotemporal features and improve the classification accuracy of tempo stimuli. To evaluate the proposed method's performance, we conducted experiments on two benchmark datasets. The proposed method achieves promising results, outperforming recent methods.