• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.45-54
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• 2008

As mobile Web technology becomes more increasingly applicable. the mobile contents market. especially the music downloading for mobile phones, has recorded remarkable growth. In spite of this rapid growth, customers experience high levels of frustration in the process of searching for desired music contents. It affects to a re-purchasing rate of customers and also. music mubile content providers experience a decrease in the benefit. Therefore, in aspects of a customer relationship management (CRM), a new way to increase a benefit by providing a convenient shopping environment to mobile customers is necessary. As an solution for this situation, we propose a new music recommender system to enhance the customers' search efficiency by combining collaborative filtering with mobile web mining and ordinal scale based customer preferences. Some experiments are also performed to verify that our proposed system is more effective than the current recommender systems in the mobile Web.

• Journal of the Korean Society for information Management
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• v.36 no.2
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• pp.223-254
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• 2019

The research on the archiving performing arts has recently been conducted on various aspects in Korea, but there has been no research or attempts to build a digital archive that can systematically identify the information on classical music performances in one place and get the past performance information. In this study, we proposed a participatory archive portal for providing, preserving and servicing information on all classical music performances, and tried to design the functions based on the requirements of the performance archive portal identified in previous research. We identified and proposed functional requirements of the portal, reorganized the characteristics of classical music performance information, and designed metadata elements. Then we presented the design and implementation direction of search and facet navigation, as well as user participation and communication functions. Lastly, we developed a prototype that implemented the requirements of the interface.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.75-87
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• 2009

This paper, which is about the method of creating the audio fingerprint and comparing with the audio data, presents how to distinguish music using the characteristics of audio data. It is a process of applying the Difference of Gaussian (DoG: generally used for recognizing images) to the audio data, and to extract the music that changes radically, and to define the location of fingerprint. This fingerprint is made insensitive to the changes of sound, and is possible to extract the same location of original fingerprint with just a portion of music data. By reducing the data and calculation of fingerprint, this system indicates more efficiency than the pre-system which uses pre-frequency domain. Adopting this, it is possible to indicate the copyrighted music distributed in internet, or meta information of music to users.

• Journal of Gifted/Talented Education
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• v.19 no.3
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• pp.729-758
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• 2009

The domestic Gifted education is evaluated to attain many achievements and to reach stable circle in short term. What about the present situation of artistic talent education which is one of the talent education areas, especially music talent education? The result of domestic Gifted education can be comprehensively understood by actually searching the present situation of diverse Gifted education areas. In this sense, this research aims to search the overall situation of domestic music talent education and to draw the tasks to be improved later mainly on the basis of important matters for efficient operation of music talent education. Thus far, many researches have been made mainly through quantitative statistical data or survey materials in the form of questionnaire. Meanwhile, this research tries to deeply understand the problems that have been superficially managed so far by collecting the voice of diverse practical staffs related to music talent education for comprehensive analysis and investigation. This research is meaningful in that it establishes the direction of more effective music talent education in the future by lessening the gap between policy and reality, intent and result, etc through diverse comprehension of actual situation and position related to music talent education and provides the basic materials based on reality to cultivate teacher and administrator and to develop curriculum.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.884-889
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• 2010

Recently, a music genre classification has been studied. However, experts use different criteria to classify each of these classifications is difficult to derive accurate results. In addition, when the emergence of a new genre of music genre is a newly re-defined. Music as a genre rather than to separate search should be classified as emotional words. In this paper, the feelings of people on the basis of brightness and darkness tries to categorize music. The proposed classification system by applying VCM(Variance Considered Machines) is the contrast of the music. In this paper, we are using three kinds of musical characteristics. Based on surveys made throughout the learning, based on musical attributes(beat, timbre, note) was used to study in the VCM. VCM is classified by the trained compared with the results of the survey were analyzed. Note extraction using the MATLAB, sampled at regular intervals to share music via the FFT frequency analysis by the sector average is defined as representing the element extracted note by quantifying the height of the entire distribution was identified. Cumulative frequency distribution in the entire frequency rage, using the difference in Timbre and were quantified. VCM applied to these three characteristics with the experimental results by comparing the survey results to see the contrast of the music with a probability of 95.4% confirmed that the two separate.

• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.727-732
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• 2007

Most of previous work on indexing and searching time series focused on the similarity matching and retrieval of one-attribute time series. However, multimedia databases such as music, video need to handle the similarity search in multi-attribute time series. The limitation of the current similarity models for multi-attribute sequences is that there is no consideration for attributes' sequences. The multi-attribute sequences are composed of several attributes' sequences. Since the users may want to find the similar patterns considering attributes's sequences, it is more appropriate to consider the similarity between two multi-attribute sequences in the viewpoint of attributes' sequences. In this paper, we propose the similarity search method based on attributes's sequences in multi-attribute time series databases. The proposed method can efficiently reduce the search space and guarantees no false dismissals. In addition, we give preliminary experimental results to show the effectiveness of the proposed method.

• Journal of Advanced Navigation Technology
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• v.25 no.5
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• pp.403-408
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• 2021

Harmony Search(HS) algorithm is an emerging meta-heuristic optimization algorithm, which is inspired by the music improvisation process and has been successfully applied to solve different optimization problems. In order to further improve the performance of HS, this paper proposes a new method which is called Fast Harmony Search(FSH) algorithm. For the purpose, this paper suggest a method to unify two independent improvisation processes by newly defining the boundary value of a object variable using HM. As the result, the process time of the algorithm is shorten and explicit decision of bandwidth is no more needed. Furthermore, exploitative power of random selection is improved. The numerical results reveal that the proposed algorithm can find better solutions and is faster when compared to the conventional HS.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.182-188
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• 2007

모바일 음악 재생 장치의 보급이 활성화 되면서 모바일 환경에서 음악을 즐기고자 하는 욕구가 확대되었다. 모바일 음악 재생 장치의 저장 공간이 확대되어 한번에 많은 곡을 보유하게 되었지만, 실제적으로 많은 곡 중에서 자신이 원하는 곡을 쉽게 찾을 수 있는 방법이 존재하지 않고 있다. 이런 문제들을 해결하기 위해 해당 음악 고유의 Metadata를 활용하여 쉽게 찾고자 하는 경향이 있지만, 현재까지는 단순한 사용자 인터페이스만 제공하고 있다. 각각의 음악은 음악 고유의 Context도 가지게 되며, 사용자의 음악 감상 로그에 의해 생성되는 개인화 Context 및 같은 음악을 즐기는 다른 사용자들에 의해 생성되는 Social Context등으로 하나의 음악과 관련된 Context가 증가되는 추세에 있다. 이와 같이 추가되는 Context들은 음악을 탐색하는데 있어 효과적인 수단이 제공되어야 하지만 모바일 음악 재생장치에 있는 음악 탐색 프로그램은 새롭게 추가되는 Context 에 의한 효과적으로 대응하지 못하고 있다. 이러한 문제점을 해결하기 위해서 모바일 장치에 Embedded Database Engine을 장착하여 동적 트리 생성/탐색을 통한 Context 기반 연관 음악 탐색 방법을 제안하게 되었다. 본 논문에서는 새롭게 고안된 음악 탐색 방법에 대하여 3가지 사항에 대해서 제시하였다. 첫째, 새로운 Context추가에 대한 동적 메뉴 추가 방법을 제시하였다. 둘째, 실제로 새롭게 추가된 사용자 인터페이스에 대해서 알아보았으며, 마지막으로 제시된 방법이 얼마나 효과적인가를 계산하여 일반화 하였다.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.288-294
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• 2013

The diagnosis of motor failures using an on-line method has been the aim of many researchers and studies. Several spectral analysis techniques have been developed and are used to facilitate on-line diagnosis methods in industry. This paper discusses the first application of a motor flux spectral analysis to the identification of broken rotor bar (BRB) faults in induction motors using a multiple signal classification (MUSIC) technique as an on-line diagnosis method. The proposed method measures the leakage flux in the radial direction using a radial flux sensor which is designed as a search coil and is installed between stator slots. The MUSIC technique, which requires fewer number of data samples and has a higher detection accuracy than the traditional fast Fourier transform (FFT) method, then calculates the motor load condition and extracts any abnormal signals related to motor failures in order to identify BRB faults. Experimental results clearly demonstrate that the proposed method is a promising candidate for an on-line diagnosis method to detect motor failures.

• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.314-319
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• 2019

Computing chromagram similarity is indispensable in constructing cover song identification system. This paper proposes a code-based chromagram similarity to reduce the computational and the storage costs for cover song identification. By learning a song-specific codebook, a chromagram sequence is converted into a code sequence, which results in the reduction of the feature storage cost. We build a lookup table over the learned codebooks to compute chromagram similarity efficiently. Experiments on two music datasets were performed to compare the proposed code-based similarity with the conventional one in terms of cover song search accuracy, feature storage, and computational cost.