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국내 소셜커머스의 특성이 구매의도에 미치는 영향 - SNS 활용정도의 조절효과를 중심으로
한서형 ( Seohyoung Han ),김용원 ( Yongwon Kim ),이봉규 ( Bong Gyou Lee ) 한국인터넷정보학회 2011 인터넷정보학회논문지 Vol.12 No.6
스마트폰의 활성화로 인해 모바일 혁명이 불고 있다. 모바일 혁명은 SNS 서비스를 단순한 커뮤니케이션 도구에서 소셜커머스의 확산에 매우 중요한 수단으로 만들었다. 하지만 최근 많은 관심을 받고 있는 국내 소셜커머스 시장에서 SNS가 어떠한 역할을 하는지에 관한 연구는 아직까지 미비한 실정이다. 따라서 본 연구의 목적은 국내 소셜커머스의 다양한 특성들이 소셜커머스의 구매의도에 어떠한 영향을 미치며, SNS가 어떠한 효과가 있는지를 알아보는 것이다. 이를 위해 본 연구에서는 국내·외 기존 연구를 바탕으로 소셜커머스 특성을 비용절감, 충동구매, 사회적영향, 의사결정지원, 구전효과 등으로 도출한 후 SNS활용정도와의 상호작용 효과를 검정하였다. 회귀분석결과 모든 소셜커머스 특성은 종속변수에 유의한 것으로 나타났다. 또 SNS 활용정도와의 상호작용 효과 검정 결과 비용절감과 구전효과가 SNS를 많이 활용할수록 소셜커머스 활성화에 유의한 영향을 주는 것으로 나타났다. 결국 본 연구의 의의는 소셜커머스 특성과 SNS와의 관계를 살펴봄으로써 소셜커머스 사업자의 전략 수립을 위한 단초를 제공했다는 데에 있다. Due to the vitalization of the smart phones, mobile revolution has been started. The mobile revolution has elevated SNS service, which was once considered as just one of many communication tools, to the single most important communication method as well as diffusion of social commerce. Yet, there has not been an adequate study of the roles of SNS in the domestic social commerce market, which has gotten a lot of spotlights. Therefore, the purpose of this study is to investigate the influence of various characteristics of social commerce that it has an impact on the purchase intension as well as the moderating effects of SNS. For these purposes, this study has drawn up the characteristics of social commerce in cost cutting, impulse buy, social influence, decision support, word of mouth effect and etc. to prove the interaction effect of SNS. The regression analysis showed that the characteristics of all the social commerce are related to the dependent variable. As a result of drawing up the interaction effect of SNS, it has shown that the cost cutting and word of mouth have significant influence in the social commerce diffusion as the usage of SNS increased. In conclusion, the main implication of this study is to provide the basic grounds for social commerce business strategy as it investigated the characteristics of SNS and its relation.
한서원(Han Seo Won),엄경배(Eum Kyoung Bae),이준환(Lee Joon Whaon) 한국정보처리학회 1999 정보처리학회논문지 Vol.6 No.9
Chromakey method is one of key technologies for realizing virtual studio, and the blue portions of a captured image in virtual studio, are replaced with a computer generated or real image. The replaced image must be changed according to the camera parameter of studio for natural merging with the non-blue portions of a captured image. This paper proposes a novel method to extract camera parameters using the recognition of pentagonal patterns that are painted on a blue screen. We extract corresponding points between a blue screen and a captured image using the projective invariant features of a pentagon. Then, calculate camera parameters using corresponding points by the modification of Tsai's method. Experimental results indicate that the proposed method is more accurate compared to conventional method and can process about twelve frames of video per a second in Pentium-MMX processor with CPU clock of 166MHz.
GPGPU를 활용한 OpenFOAM 기반 해석자 성능 분석
한서음(Seoeum Han),정황희(Hwanghui Jeong),이복직(Bok Jik Lee) 한국전산유체공학회 2021 한국전산유체공학회지 Vol.26 No.2
Two benchmark tests were carried out to analyze the performance of OpenFOAM-based CFD solvers using General-Purpose computing on Graphics Processing Units(GPGPU). In the present study, RapidCFD, which is an implementation of OpenFOAM capable of running most of the functions of OpenFOAM on GPUs, was used to apply GPGPU to OpenFOAM. The numerical simulations of 1) 3D lid-driven cavity incompressible flows and 2) steady flows around a motorbike were conducted on two kinds of CPU, single-GPU, and multi-GPU systems, and the computational times were analyzed. For the test of cavity flows, as the number of cells increased, the performance and the scalability of GPGPU were improved. When the number of cells was 2503, a system with 8-GPUs showed the highest performance with 42 times of speedup over a CPU system. For the test of flows around a motorbike, a system with 8-GPUs showed the highest performance with 20 times of speedup over a CPU system. For both single precision and double precision calculations, the performance improvements using GPGPU were efficient. The results demonstrate that GPGPU would be more efficient than computing on CPUs when computing large-scale flows and practical problems that require massive parallelism.