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권영수 한국전자통신연구원 2018 전자통신동향분석 Vol.33 No.5
The Von Neumann based architecture of the modern computer has dominated the computing industry for the past 50 years, sparking the digital revolution and propelling us into today’s information age. Recent research focus and market trends have shown significant effort toward the advancement and application of artificial intelligence technologies. Although artificial intelligence has been studied for decades since the Turing machine was first introduced, the field has recently emerged into the spotlight thanks to remarkable milestones such as AlexNet-CNN and Alpha-Go, whose neural-network based deep learning methods have achieved a ground-breaking performance superior to existing recognition, classification, and decision algorithms. Unprecedented results in a wide variety of applications (drones, autonomous driving, robots, stock markets, computer vision, voice, and so on) have signaled the beginning of a golden age for artificial intelligence after 40 years of relative dormancy. Algorithmic research continues to progress at a breath-taking pace as evidenced by the rate of new neural networks being announced. However, traditional Von Neumann based architectures have proven to be inadequate in terms of computation power, and inherently inefficient in their processing of vastly parallel computations, which is a characteristic of deep neural networks. Consequently, global conglomerates such as Intel, Huawei, and Google, as well as large domestic corporations and fabless companies are developing dedicated semiconductor chips customized for artificial intelligence computations. The AI Processor Research Laboratory at ETRI is focusing on the research and development of super low-power AI processor chips. In this article, we present the current trends in computation platform, parallel processing, AI processor, and super-threaded AI processor research being conducted at ETRI.
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권영수,전세근,설정욱,김임규,Kwon, Young Soo,Jeon, Se Kun,Seol, Jeong Wook,Kim, Im Gyu 강원대학교 산림과학연구소 2012 Journal of forest and environmental science Vol.28 No.4
This study was conducted from April 2012 to June 2012 to analyze breeding status of Black woodpeckers (Dryocopus martius) in the Gayasan National Park. Nest height, tree diameter which a nest built and altitude at the nest site of Black woodpeckers were 17.4 m, 63.8 cm and 587 m, respectively. A pair of Black woodpeckers completed a clutch in 4 eggs on 7 May and 3 of eggs hatched on 24 May 2012. Both female and male incubated eggs and never left eggs without one of parents. A male more contributed to build a nest than a female. Incubation duration was higher in a male than in a female. Nestlings made a begging call in a nest during the growing period. Begging frequency of nestlings increased from 11 days up to 20 days after hatching. After then, nestlings reduced begging and fledged a nest 24 days after hatching. This study provided information of breeding ecology to protect and manage population of Black woodpeckers which are endangered species in South Korea.
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