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허성진,김지용,Hur, S.J.,Kim, J.Y. 한국전자통신연구원 2021 전자통신동향분석 Vol.36 No.2
In this paper, we discussed the necessity and importance of introducing feature stores to establish a collaborative environment between data engineering work and data science work. We examined the technology trends of feature stores by analyzing the status of some major feature stores. Moreover, by introducing a feature store, we can reduce the cost of performing artificial intelligence (AI) projects and improve the performance and reliability of AI models and the convenience of model operation. The future task is to establish technical requirements for establishing a collaborative environment between data engineering work and data science work and develop a solution for providing a collaborative environment based on this.
최종선(C.S Choi),전태원(T.W Chun),김지용(S.Y Kim),김흥근(H.K Kim) 전력전자학회 2008 전력전자학술대회 논문집 Vol.- No.-
An inverter with large capacity has been demanded at a factory automation and diffusion of the energy saving work. As the capacity of inverter is larger, the stary inductance has much influence on both the di/dt of IGBT current, and voltage stress across IGBT. Also, the life of the snubber capacitor may be shortened due to overheating of the snubber capacitor. In this paper, a planar busbar which consists of two layers is applied to N700-series inverter in order to minimize stray inductance. The voltage stress across IGBT is changed by both the DC busbar structure and the capacity of snubber capacitor.
김창수,박춘서,이태휘,김지용,C.S. Kim,C.S. Park,T.W. Lee,J.Y. Kim 한국전자통신연구원 2023 전자통신동향분석 Vol.38 No.6
Recently, artificial intelligence has been in the spotlight across various fields. Artificial intelligence uses massive amounts of data to train machine learning models and performs various tasks using the trained models. For model training, large, high-quality data sets are essential, and database systems have provided such data. Driven by advances in artificial intelligence, attempts are being made to improve various components of database systems using artificial intelligence. Replacing traditional complex algorithm-based database components with their artificial-intelligence-based counterparts can lead to substantial savings of resources and computation time, thereby improving the system performance and efficiency. We analyze trends in the application of artificial intelligence to database systems.