• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.8
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• pp.750-757
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• 2016

The effect of new building on the HF direction finding(DF) is analyzed. Commercially available software is used to get array manifold of the HF DF system. The terrain, building and the array antenna system are modelled. New building near the antenna system is also modelled to see whether it actually has an effect on the performance of the DF system. MUSIC and interferometer DF algorithms have been employed.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.137-138
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• 1998

The purpose of this study is to evaluate the HRV(Heart Rate Variability) to visual and auditory stimulation. We analysed psychological effect and HRV of music, light, and music with light. The results show that HRV pattern is significantly related to the psychological effect, and HRV spectrum is useful to extract more information when various stimulation are presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.417-420
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• 2005

This report shows the new music player's system which could separate music's tempo by analysis Peak level frequency by time from some percussion instruments. After this process, the new music player could classify some fast or slow genre's musics without a user's order, then we should listen to a fast or slow genre's music by a button.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.1195-1198
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• 2014

이 논문은 실시간으로 취득되는 뇌파를 기반으로 자동으로 음악을 추천하는 음악추천 기능의 시스템인 MyMusicShuffler 를 소개한다. 이 시스템은 뇌파 분석을 통한 사용자의 감성을 자동으로 분류하는 방식으로 멀티태스킹 환경에 익숙한 사용자들의 음악 청취를 위한 소모적인 상호작용을 없애는 새로운 방식의 인터페이스 환경을 실험하였다. 뇌파의 분석을 통하여 실시간으로 사용자의 감성 관련 반응을 반영하여 음악을 선택하여 제공하는 시스템이다. 이 논문은 개인의 감성적 반응에 의하여 상호작용하는 음악 추천 서비스인 MyMusicShuffler 시스템의 구현 내용을 설명할 것이다.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.687-692
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• 2023

This research began with the intention to create music using the superposition characteristics of quantum computers. Existing music has characteristics that are limited to those composed by composers. However, music using the overlap of quantum computers has musical characteristics that change when executed within a limited range. Using this, you will be able to create music that changes based on specific chords at run time. In this paper, quantum computers and existing computers are connected to generate sound, And it focuses on creating changing sounds by applying the nature of superposition.

• The Journal of Korea Robotics Society
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• v.8 no.3
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• pp.217-227
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• 2013

We introduce a learning system for the sight reading of simple drum sequences. Sight reading is a cognitive-motor skill that requires reading of music symbols and actions of multiple limbs for playing the music. The system provides knowledge of results (KR) pertaining to the learner's performance by color-coding music symbols, and guides the learner by indicating the corresponding action for a given music symbol using additional auditory or vibrotactile cues. To evaluate the effects of KR and guidance cues, three learning methods were experimentally compared: KR only, KR with auditory cues, and KR with vibrotactile cues. The task was to play a random 16-note-long drum sequence displayed on a screen. Thirty university students learned the task using one of the learning methods in a between-subjects design. The experimental results did not show statistically significant differences between the methods in terms of task accuracy and completion time.

• Journal of IKEEE
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• v.24 no.1
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• pp.254-259
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• 2020

This paper is the implementation of the conversion system from image to music based on intentional synesthesia. The input image based on color, texture, and shape was converted into melodies, harmonies and rhythms of music, respectively. Depending on the histogram of colors, the melody can be selected and obtained probabilistically to form the melody. The texture in the image expressed harmony and minor key with 7 characteristics of GLCM, a statistical texture feature extraction method. Finally, the shape of the image was extracted from the edge image, and using Hough Transform, a frequency component analysis, the line components were detected to produce music by selecting the rhythm according to the distribution of angles.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.8
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• pp.1370-1376
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• 2008

Recently years There are numerous music contents on the internet and it can easily be used without any authority. because of this, casualties of music contents has been increased and music market has collapsed. Therefore Record Copyright Association protection law has revised and using music contents are being managed by copyright holders group from this year. It is one of ways to protect their contents copyright. So on this paper Internet Radio solution is provided to solve the problem between copyright holders and someone wants to use their contents and to make a part of new market on the music contents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.807-824
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• 2016

In this paper, a method of mood classification based on user brainwaves is proposed for real-time application in commercial services. Unlike conventional mood analyzing systems, the proposed method focuses on classifying real-time user moods by analyzing the user's brainwaves. Applying brainwave-related research in commercial services requires two elements - robust performance and comfortable fit of. This paper proposes a filter based on Regularized Common Spatial Patterns (RCSP) and presents its use in the implementation of mood classification for a music service via a wireless consumer electroencephalography (EEG) device that has only 14 pins. Despite the use of fewer pins, the proposed system demonstrates approximately 10% point higher accuracy in mood classification, using the same dataset, compared to one of the best EEG-based mood-classification systems using a skullcap with 32 pins (EU FP7 PetaMedia project). This paper confirms the commercial viability of brainwave-based mood-classification technology. To analyze the improvements of the system, the changes of feature variations after applying RCSP filters and performance variations between users are also investigated. Furthermore, as a prototype service, this paper introduces a mood-based music list management system called MyMusicShuffler based on the proposed mood-classification method.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.8
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• pp.1129-1135
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• 2012

To employ NMF to transcribe music by extracting feature matrix and weight matrix at the same time, it is necessary to know in advance the dimension of the feature matrix, and to determine the pitch of each extracted feature vector. Another drawback of this approach is that it becomes more difficult to accurately extract the feature matrix as the number of pitches included in the target music increases. In this study, we prepare a feature matrix database, and apply the matrix to transcribe real music. Transcription experiments are conducted by applying the feature matrix to the music played on the same piano on which the feature matrix is extracted, as well as on the music played on another piano. These results are also compared to those of another experiment where the feature matrix and weight matrix are extracted simultaneously, without making use of the database. We could observe that the proposed method outperform the method in which the two matrices are extracted at the same time.