• International Journal of Internet, Broadcasting and Communication
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• 제8권1호
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• pp.83-90
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• 2016

The emergence of cloud has been able to provide a variety of IT service to the user. As organizations and companies are increased that provide these cloud service, many problems arises on integration. However, with the advent of latest technologies such as big data, document-oriented database, and MapReduce, this problem can be easily solved. This paper is intended to design the Cloud Aggregator to provide them as a service to collect information of the cloud system providing each service. To do this, we use the DBaaS(DataBase as a Service) and MapReduce techniques. This makes it possible to maintain the functionality of existing system and correct the problem that may occur depending on the combination.

• Asian review of World Histories
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• 제4권1호
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• pp.83-123
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• 2016

We describe a vision of historical analysis at the world scale, through the digital assembly of historical sources into a cloud-based database, where machine-learning techniques can be used to summarize the database into a time-integrated actor-to-actor complex network. Using this time-integrated network as a template, we then apply the method of automatic narratives to discover key actors ('who'), key events ('what'), key periods ('when'), key locations ('where'), key motives ('why'), and key actions ('how') that can be presented as hypotheses to world historians. We show two test cases on how this method works. To accelerate the pace of knowledge discovery and verification, we describe how historians would interact with these automatic narratives through an online, map-based knowledge aggregator that learns how scholars filter information, and eventually takes over this function to free historians from the more important tasks of verification, and stitching together coherent storylines. Ultimately, multiple coherent storylines that are not necessary compatible with each other can be discovered through human-computer interactions by the map-based knowledge aggregator.

• 한국전자통신학회논문지
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• 제17권2호
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• pp.299-308
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• 2022

최근 에너지전환정책은 소규모 태양광발전기 수량을 증가시키고 있다. 계통운영자는 이러한 소규모 태양광 발전량을 정확하게 예측하기가 어렵고 급전계획을 방해할 수도 있으며, 결과적으로 비용상승이 초래될 것이다. 이러한 문제를 해결하는 방법으로 소규모 태양광발전소에서 생산되는 발전량, 전압제어에 대하여 불확실성을 줄이고 예비전력을 공급하는 소규모 태양광발전소의 집합체로서 가상발전소가 떠오르고 있다. 본 연구에서는 가상발전소 클라우드 요금산정을 위하여 순현재가치법과 수익성지수법을 사용하며, 두 종류의 비용평가법 계산결과가 상세하게 설명된다. 계산결과로부터 수익성지수가 1.22로 산정되어 수익성을 확보한 것으로 나타났으며, 순현재가치가 수익성을 충분히 만족시키기 때문에 중개사업자 관점에서 매력적이다.