• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.849-857
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• 2018

In this paper, we propose an automatic composition method using time series embedding of RNN Auto-Encoder. RNN Auto-Encoder can learn existing songs and can compose new songs from the trained RNN decoder. If one song is fully trained in the RNN Auto-Encoder, the song is embedded into the vector values of RNN nodes in the Auto-Encoder. If we train a lot of songs and apply a specific vector to the decoder of Auto-Encoder, then we can obtain a new song that combines the features of trained multiple songs according to the given vector. From extensive experiments we could find that our method worked well and generated various songs by selecting of the composition vectors.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1358-1366
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• 2015

This paper proposes an automatic composition method using the training capability of artificial neural networks and chord progression rules that are widely used by human composers. After training a given song, the new melody is generated by the trained artificial neural networks through applying a different initial melody to the neural networks. The generated melody should be modified to fit the rhythm and chord progression rules for generating natural melody. In order to achieve this object, we devised a post-processing method such as chord candidate generation, chord progression, and melody correction. From some tests we could find that the melody after the post-processing was very improved from the melody generated by artificial neural networks. This enables our composition system to generate a melody which is similar to those generated by human composers.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.449-459
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• 2016

This paper proposes a new method to improve the three problems of existing automatic composition method using artificial neural networks. The first problem is that the existing beat post-processing to fit into music theories could not handle all the cases of occurring. The second one is that the pitch space generated by artificial neural networks is distorted because the rest is trained with the pitch on the same neural network with large values. The last problem is caused by the difference between the initial melody and beats given by user and those generated by an artificial neural network in the process of new composition. In order to treat these problems, we propose an enhanced post-processing of beats, initial melody processing, and adoption of artificial neural network for rest. It was found from experiments that the proposed methods totally resolved the three problems.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.6
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• pp.445-451
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• 2016

This paper introduces a postprocessing method, an iteration method for melody, and an average neural network method for learning a large number of songs in order to improve musically insufficient parts in automatic composition using existing artificial neural network. The melody of songs composed by artificial neural networks is produced according to the melodies of trained songs, so it can not be a specific tonality and it is difficult to have a repetitive composition. In order to solve these problems, we propose a postprocessing method that converts the melody composed by artificial neural networks into a melody having a specific tonality according to music theory and an iteration method for melody by iteratively composing measure divisions of artificial neural networks. In addition, the existing training method of many songs has some disadvantages. To solve this problem, we adopt an average neural network that is made by averaging the weights of artificial neural networks trained each song. From some experiments, it was confirmed that the proposed method solves the existing problems.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.315-320
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• 2014

Composition is a creative activity of a composer in order to express his or her emotion into melody based on their experience. However, it is very hard to implement an automatic composition program whose composition process is the same as the composer. On the basis that the creative activity is possible from the imitation we propose a method to implement an automatic composition system using the learning capability of ANN(Artificial Neural Networks). First, we devise a method to convert a melody into time series that ANN can train and then another method to learn the repeated melody with melody bar for correct training of ANN. After training of the time series to ANN, we feed a new time series into the ANN, then the ANN produces a full new time series which is converted a new melody. But post processing is necessary because the produced melody does not fit to the tempo and harmony of music theory. In this paper, we applied a tempo post processing using tempo post processing program, but the harmony post processing is done by human because it is difficult to implement. We will realize the harmony post processing program as a further work.

• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.113-120
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• 2008

Web Services composition has gained a considerable attention because of the widespread use of the Web Services and SOA. Recently, various researches on automatic Web Services composition are on going to realize more dynamic and intelligent SOA environments. However, there is no complete solution for automatic Web Services composition now and previous researches have several problems. Automatic composition based on syntactic information has low correctness through incorrect semantic linking. Moreover, many researches make an process as the result of composition which is hard for actual execution. In this paper, improved automatic Web Services composition based on Web Services choreography is proposed. In this system, the correctness is improved and the result of composition is more concrete process.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.393-396
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• 2008

웹 서비스는 XML, SOAP, WSDL, UDDI, BPEL 등의 표준을 기본 구조로 하고 있으며 이러한 기술들은 SOA에서 요구되는 이기종 분산 플랫폼 상의 복잡한 애플리케이션 통합 문제를 유연하게 해결할 수 있는 다양한 인터페이스를 제공하고 있다. 본 논문에서는 SOA의 핵심 기술인 반자동 웹 서비스 조합 기법을 구현하기 위해 WS-BPEL 기법과 OWL-S 기법을 융합한 새로운 SemanticBPEL 조합 기법을 제안한다. 이 기법은 실험 분석을 통해 기존의 검색 방법보다 성능이 우수함을 보인다.

• Journal of Digital Contents Society
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• v.18 no.4
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• pp.641-647
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• 2017

In this paper, we propose a method to automatically generate a configured song with melodies composed of front/middle/last parts by using hierarchical artificial neural networks in automatic composition. In the first layer, an artificial neural network is used to learn an existing song or a random melody and outputs a song after performing rhythm post-processing. In the second layer, the melody created by the artificial neural network in the first layer is learned by three artificial neural networks of front/middle/last parts in the second layer in order to make a configured song. In the artificial neural network of the second layer, we applied a method to generate repeatability using measure identity in order to make song with repeatability and after that the song is completed after rhythm, chord, tonality post-processing. It was confirmed from experiments that our proposed method produced configured songs well.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.433-435
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• 2004

소프트웨어 프로덕트 라인은 핵심 소프트웨어 자산의 개발을 위한 도메인 공학과 실제 소프트웨어 부품을 조립하여 구체적인 소프트웨어 시스템을 개발하는 응용 공학을 포함한다. 소프트웨어 프로덕트 라인 구축 시 가장 중요한 점은 특정 도메인에 존재하는 가변성(variability)을 지원할 수 있어야 한다는 것으로, 재사용자의 목적에 따라 효율적으로 소프트웨어를 맞춤 생산할 수 있는 컴포넌트 재구성성(reconfigurability)이 핵심 요소라 할 수 있다. 본 논문에서는 재사용자가 선택한 특성 구성을 바탕으로 계층 구조 조립 자동화를 통해 컴포넌트 코드를 자동 생성하는 도구를 구현하였다. 이를 위하여, 컴포넌트 패밀리의 특성 모델에서 표현되는 차이점에 따라 계층 구조의 각 컴포넌트들이 조립되도록 XSLT 스크립트를 사용하였다. 특성 모델과 XML/XSLT 기술을 이용하여 컴포넌트 코드 생성 시에 재구성성을 지원하고 재사용자의 요구에 맞는 컴포넌트 소스 코드를 자동 생성함으로써 소프트웨어 프로덕트 라인 개발 생산성을 향상시킨다.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04a
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• pp.367-369
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• 2004

근래 정보보안의 필요성이 대두됨에 따라 개인 사용자의 보안 지식이 다방면으로 필요하게 되었다. 특정 그룹에 속한 개인 사용자들의 보안패치나 백신 등에 대한 지식이 비슷한 수준일 수 없으므로 보안패치나 백신 등을 관리해 주는 솔루션이 필요하게 되었다. 이는 통합관제 센터나 흑은 보안패치 자동분배 솔루션를 사용하여 해결할 수 있으나, 시스템 관리자의 지속적인 패치 확인과 업데이트가 필요한 일이다. 시스템 관리자가 벤더를 검색하여 패치를 가져오는 방법은 지극히 주관적이고, 실수로 가져오지 못하거나 혹은 벤더의 업데이트 시간과 맞지 않아 긴급패치를 누락시키는 경우가 종종 발생한다. 또한, 자동분배 솔루션을 사용하는 네트워크의 병합이나 패치분배의 추가에 이렇다 할 대안이 없다. 이 논문에서 제안하는 패치 자동업데이트와 자동구성에 대한 방안은 패치의 누락을 미연에 방지하고 네트워크의 병합 등 패치분배 서버가 늘어나면서 생기는 문제점을 해결해준다.