• 한국자기공명학회논문지
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• 제24권1호
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• pp.23-29
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• 2020

Mozart's music has been suggested to affect spatio-temporal reasoning of listeners, which has been called "Mozart effect". However, the effects of Mazart's music on human metabolism have not been known. We dissected Mozart's music into its compositional elements and studied their effects on metabolism of experimental animals. Mozart music significantly reduced cortisol level induced by stress. NMR metabolomic study revealed different urine metabolic profile according to the listening to Mozart's music. In addition, each element of music exhibited different metabolic profile. Functional MRI study also showed enhanced brain activity upon listening to Mozart's music. Taken together, Mozart's music seems to be related with brain activity, stress hormone and whole body metabolism.

• 한국항행학회논문지
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• 제17권4호
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• pp.386-395
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• 2013

본 논문에서는 AOA (Angle of Arrival)기반의 재머위치 결정기법에 사용되는 DOA 추정 알고리즘을 대상으로 Root-MUSIC으로 1차 DOA 추정을 수행한 후 MUSIC을 이용한 2차 DOA 추정을 수행하는 성능 개선 알고리즘을 제시하였다. 또한 제안한 알고리즘을 검증하기 위해 소프트웨어 기반의 시뮬레이션 플랫폼을 구성하여 오차환경에 따른 DOA 추정 성능 분석을 수행하고, 본 논문에서 제시한 DOA 추정 알고리즘의 DOA 추정 정확도 및 분해능의 개선 정도를 분석하였다.

• International Journal of Computer Science & Network Security
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• 제21권12호
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• pp.300-308
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• 2021

The processes of informatization of the modern educational space are inextricably linked with the active introduction of innovative information technologies, which diversify the forms of education and upbringing. The use of these technologies in education due to their specific properties significantly enhances the clarity of learning, emotional impact on students, helps to deepen interdisciplinary links, intensifies students' work, and improves the organization of educational activities. Innovative information technologies offer new opportunities for the use of text, audio, graphic, and video information in lessons, enriching the methodological possibilities of the lesson. Today, the use of these technologies is becoming an integral part of the study of any subject. Using multimedia presentations, publications, and websites created by students in the learning process, they can develop learning skills. According to researchers, there are many multimedia programs for working with a computer in a music lesson, namely: a music player, a program for singing karaoke, a music constructor, music encyclopedias, and training programs. The introduction of innovative information technologies in the system of music education allows expanding learning opportunities.

• 대한인간공학회지
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• 제32권5호
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• pp.421-427
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• 2013

Objective: This paper is to analyze the impact of musical training to the fast ${\alpha}$ wave activation of the EEG. Background: EEG is neurological research method that can observe the brain function in real time. EEG can be used to determine the nervousness and relaxedness of a person who receives stimuli in a structured environment. Therefore, it is possible to interpret the functional state of human brain by the analysis of EEG. Method: The brain activities of two groups of university students in the point of RFA(Relative Fast Alpha) caused by different music are analyzed in this paper. One is the group of music majors and the other is the group of non-majors. Results: Music major and non-major groups show meaningful differences in RFA during exposed to classic and metal music. Conclusion: Learning experience on music affects RFA increment of music majors. Application: The result of this study will be used as basic data to evaluate the learning effects of students who want to study music.

• Journal of Web Engineering
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• 제20권8호
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• pp.2335-2360
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• 2021

A folksonomy is a classification system in which volunteers collaboratively create and manage tags to annotate and categorize content. The folksonomy has several problems in retrieving music using tags, including problems related to synonyms, different tagging levels, and neologisms. To solve the problem posed by synonyms, we introduced a mood vector with 12 possible moods, each represented by a numeric value, as an internal tag. This allows moods in music pieces and mood tags to be represented internally by numeric values, which can be used to retrieve music pieces. To determine the mood vector of a music piece, 12 regressors predicting the possibility of each mood based on acoustic features were built using Support Vector Regression. To map a tag to its mood vector, the relationship between moods in a piece of music and mood tags was investigated based on tagging data retrieved from Last.fm, a website that allows users to search for and stream music. To evaluate retrieval performance, music pieces on Last.fm annotated with at least one mood tag were used as a test set. When calculating precision and recall, music pieces annotated with synonyms of a given query tag were treated as relevant. These experiments on a real-world data set illustrate the utility of the internal tagging of music. Our approach offers a practical solution to the problem caused by synonyms.

• 한국멀티미디어학회논문지
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• 제19권5호
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• pp.826-836
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• 2016

Mastering a musical instrument for an unskilled beginning learner is not an easy task. It requires playing every note correctly and maintaining the tempo accurately. Any music comes in two forms, a music score and it rendition into an audio music. The proposed method of assisting beginning music players in both aspects employs two popular pattern recognition methods for audio-visual analysis; they are support vector machine (SVM) for music score recognition and hidden Markov model (HMM) for audio music performance tracking. With proper synchronization of the two results, the proposed music learning assistant system can give useful feedback to self-training beginners.

• Journal of Information Processing Systems
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• 제14권1호
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• pp.32-55
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• 2018

The digitization of music has seen a considerable increase in audience size from a few localized listeners to a wider range of global listeners. At the same time, the digitization brings the challenge of smoothly retrieving music from large databases. To deal with this challenge, many systems which support the smooth retrieval of musical data have been developed. At the computational level, a query music piece is compared with the rest of the music pieces in the database. These systems, music information retrieval (MIR systems), work for various applications such as general music retrieval, plagiarism detection, music recommendation, and musicology. This paper mainly addresses two parts of the MIR research area. First, it presents a general overview of MIR, which will examine the history of MIR, the functionality of MIR, application areas of MIR, and the components of MIR. Second, we will investigate music similarity measurement methods, where we provide a comparative analysis of state of the art methods. The scope of this paper focuses on comparative analysis of the accuracy and efficiency of a few key MIR systems. These analyses help in understanding the current and future challenges associated with the field of MIR systems and music similarity measures.

• International Journal of Contents
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• 제10권4호
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• pp.63-68
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• 2014

In this paper, we propose a smart system that can optically recognize a music score within a document and can play the music after recognition. Many historic handwritten documents have now been digitalized. Converting images of a music score within documents into digital files is particularly difficult and requires considerable resources because a music score consists of a 2D structure with both staff lines and symbols. The proposed system takes an input image using a mobile device equipped with a camera module, and the image is optimized via preprocessing. Binarization, music sheet correction, staff line recognition, vertical line detection, note recognition, and symbol recognition processing are then applied, and a music file is generated in an XML format. The Music XML file is recorded as digital information, and based on that file, we can modify the result, logically correct errors, and finally generate a MIDI file. Our system reduces misrecognition, and a wider range of music score can be recognized because we have implemented distortion correction and vertical line detection. We show that the proposed method is practical, and that is has potential for wide application through an experiment with a variety of music scores.

• 디지털융복합연구
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• 제15권7호
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• pp.343-350
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• 2017

점자악보는 시각장애인들이 음악을 배우고 즐길 수 있게 하는 필수적인 교육적 자료이다. 현재 우리나라에서는 전자점자악보의 제작은 국립장애인도서관에서 신청제작 할 수 있으며 점자악보제작 및 교육에 특성화 된 시각장애인음악 재활센터에서 가장 많이 제작되고 있다. 그러나 대부분의 전국의 지역별 점자도서관은 점자악보의 분류조차 되어 있지 않고 소장하는 점자악보의 수도 다른 점자도서에 비해 비중이 낮다. 본 연구는 국립장애인도서관의 점자악보 제작과 그 현황을 파악하여 점자악보의 제작의 정확성과 시각장애인들이 점자악보를 사용함에 있어 효율성이 있는지를 알아보고자 한다. 그리고 각 지역별 점자도서관의 점자도서의 수와 그 안에서의 점자악보의 비중을 알아보고 전자점자악보의 필요성과 DB구축의 필요성을 제안하고자 한다. 시각장애인들의 음악교육 및 예술활동을 위한 전자점자악보의 활성화와 체계화를 통해 우리나라의 시각장애인들이 장애인 당사자주의를 바탕으로 더 좋은 문화적, 예술적 환경을 조성하는데 일익을 담당하고자 한다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2007년도 춘계종합학술대회
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• pp.258-261
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• 2007

본 논문에서는 신경회로망 알고리즘 중 하나인 Backpropagation Network을 이용한 악보인식 기법과 그에 필요한 악보 이미지에 대한 전처리 기법을 제안한다. 전처리과정으로 이진화, 기울기 보정, 오선제거 등의 과정을 수행하여 인식에 필요한 음악 기호와 음표를 분리한다. 분리된 음악 기호와 음표들은 Backpropagation 알고리즘을 사용하여 구성된 음표 인식 신경망과 비음표 인식 신경망을 통해 각각 음표와 비음표 인식과정을 거친다. 다양한 복잡도를 가진 악보를 대상으로 한 실험 및 분석 결과를 통해 제안한 악보 인식 기법의 정확도를 기술하였다.