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      • KCI등재

        Effects of the Attributes of Mobile Shopping Apps on Purchase Intention of Fashion Products

        Sangwoon BYUN,Moon-Soo KYUNG 한국유통과학회 2020 The Journal of Industrial Distribution & Business( Vol.11 No.1

        Purpose : The purpose of this study is to examine the effect of the attributes of mobile shopping apps on the purchase intention of fashion products in the steadily growing mobile commerce market and analyze the mediation effect of shopping flow. Research design, data and methodology : In this study, a survey was conducted on users in their 20s to 50s who had experience of fashion products via mobile shopping apps. The questionnaire was analyzed on the final 507. The research issues were verified using Frequency analysis, Exploratory factor analysis, Reliability analysis, Confirmatory factor analysis, and Structural equation model. Results : Among the attributes of mobile shopping apps, reliability, enjoyment and ease of use were found to have a significant impact on shopping flow and fashion product purchase intention, while shopping flow had a significant impact on fashion product purchase intention. Product diversity and usefulness of shopping apps didn’t show a significant effect. After examining the mediation effect, reliability, enjoyment, and ease of use were shown to have indirect effects by showing partial mediation effects. Conclusions : Studies show that consumers are not putting much emphasis on how diverse a product line is available and how useful a mobile shopping app is when they shop for fashion products on mobile devices. Factors that affect consumers’ purchase intention are reliability, enjoyment and ease of use of shopping apps. These results shows that it is important to provide reliable information about fashion products, provide reliability to customers by setting up means for safe transactions, and provide a wider variety of services and information to make using the mobile shopping app enjoyable. In addition, there is a need to make it easy to find a fashion product that consumers like and make it easy to purchase when consumers find out fashion products that they like, and to configure how to use the app easily. Consequently, consumers become immersed in shopping which is also able to improve consumers’ purchase intention on fashion products when a reliable, enjoyable and easy to use mobile shopping app is provided.

      • KCI등재

        A memory efficient incremental gradient method for regularized minimization

        Sangwoon Yun 대한수학회 2016 대한수학회보 Vol.53 No.2

        In this paper, we propose a new incremental gradient method for solving a regularized minimization problem whose objective is the sum of $m$ smooth functions and a (possibly nonsmooth) convex function. This method uses an adaptive stepsize. Recently proposed incremental gradient methods for a regularized minimization problem need $O(mn)$ storage, where $n$ is the number of variables. This is the drawback of them. But, the proposed new incremental gradient method requires only $O(n)$ storage.

      • SCOPUSKCI등재
      • KCI등재

        Metal-free Synthesis of β-Nitrostyrenes via DDQ-Catalyzed Nitration

        Sangwoon Park,Seungri Yoon,Sun-Joon Min 대한화학회 2021 Bulletin of the Korean Chemical Society Vol.42 No.3

        In this study, we have developed a facile synthesis of (E)-?-nitrostyrenes by using tert-butyl nitrite as a source of nitro group and DDQ as a key oxidant under aerobic condition. This process highlighted that a wide range of ?-nitrostyrenes could be synthesized under mild metal-free reaction conditions at room temperature starting from readily available styrenes.

      • A New Multiplicative Denoising Variational Model Based on <tex> $m$</tex>th Root Transformation

        Sangwoon Yun,Hyenkyun Woo IEEE 2012 IEEE TRANSACTIONS ON IMAGE PROCESSING - Vol.21 No.5

        <P>In coherent imaging systems, such as the synthetic aperture radar (SAR), the observed images are contaminated by multiplicative noise. Due to the edge-preserving feature of the total variation (TV), variational models with TV regularization have attracted much interest in removing multiplicative noise. However, the fidelity term of the variational model, based on maximum a posteriori estimation, is not convex, and so, it is usually difficult to find a global solution. Hence, the logarithmic function is used to transform the nonconvex variational model to the convex one. In this paper, instead of using the log, we exploit the th root function to relax the nonconvexity of the variational model. An algorithm based on the augmented Lagrangian function, which has been applied to solve the log transformed convex variational model, can be applied to solve our proposed model. However, this algorithm requires solving a subproblem, which does not have a closed-form solution, at each iteration. Hence, we propose to adapt the linearized proximal alternating minimization algorithm, which does not require inner iterations for solving the subproblems. In addition, the proposed method is very simple and highly parallelizable; thus, it is efficient to remove multiplicative noise in huge SAR images. The proposed model for multiplicative noise removal shows overall better performance than the convex model based on the log transformation.</P>

      • KCI등재

        청원경찰 채용 개선방안

        Sangwoon Kim,Jaehun Shin 한국재난정보학회 2016 한국재난정보학회 논문집 Vol.12 No.3

        이 연구는 청원경찰의 채용을 개선하기 위한 목적을 가진 연구로서, 청원경찰 채용의 공정 성을 확보하여 우수한 청원경찰을 선발하기 위한 목적을 가지고 있다. 청원경찰은 청원주의 요청에 의하여 해당지역 내에서 경찰활동을 하는 것으로서 민간경비 와 달리 국가주요시설에서 경찰의 업무를 수행하기 때문에 특수한 성격을 가지고 있어 채용 이 중요한 역할을 한다. 그러나, 현재 청원경찰의 채용은 비공개채용, 면접위주의 채용, 면접위원의 구성문제 등으 로 채용상의 문제가 지속적으로 발생하고 있다. 따라서 이 연구에서는 문제의 해결방안으로 청원경찰 공개채용 의무규정 마련, 경비시설의 특성을 고려한 체력검정 또는 필기시험 등 도입, 면접위원 구성 시 외부위원 위촉 의무화를 해결방안으로 제시하였다. This study has to improve the recruitment of Private Police Guards. Secure fairness on recruitment of Private Police Guards has secure excellent Private Police Guards. Under the request of requesting entity, private police guards perform police tasks at the relevant area. Recruitment takes a pivotal role because they take unusual characteristics as they perform police duties at key national institutions, unlike private security. However, problems have continuously arouse due to issues like closed recruitment, interview-based recruitment, and composition of interviewers. Accordingly, this research suggested arranging mandatory regulation to recruit publically, adaptation of physical or written exams in view of characteristics of guarding facilities, and obligating external members when consisting interviewers as solutions.

      • KCI등재
      • KCI등재

        함수 요약을 이용한 모듈단위 포인터분석

        박상운(Sangwoon Park),강현구(Hyun-Goo Kang),한태숙(Taisook Han) 한국정보과학회 2008 정보과학회논문지 : 소프트웨어 및 응용 Vol.35 No.10

        본 논문에서는 업데이트 기록에 기반한 모듈단위 포인터 분석 알고리즘을 제안한다. 여기서 모듈이란 상호 재귀적인 함수들의 집합을 의미하며, 모듈단위 분석이란 한 모듈을 분석 시에 다른 모듈의 소스코드가 필요하지 않는 분석을 의미한다. 일반적으로 이러한 형태의 분석은 분석 대상 모듈의 호출 문맥을 알 수 없는 상태에서 분석을 수행하여야 하기 때문에, 프로그램의 흐름 또는 호출 문맥에 관련하여 분석의 정확도를 잃을 수 있다. 본 논문에서는 업데이트 기록이라 이름 지어진 모듈단위 분석 공간을 고안하여, 프로그램 문맥과 흐름에 민감한 정확도를 가지는 모듈단위 포인터 분석 방법을 제안한다. 업데이트 기록은 함수의 호출 문맥에 독립적으로 메모리 상태를 요약할 수 있을 뿐만 아니라, 메모리 반응이 일어난 순서에 관한 정보를 유지할 수 있다. 업데이트 기록의 이러한 특성은 모듈단위 분석을 정형화 하는 데 효과적으로 사용되었을 뿐만 아니라, 분석의 정확도를 높이기 위해 죽은 메모리 반응 또는 관련된 별칭 문맥을 구분하는 데에도 효과적으로 사용될 수 있었다. In this paper, we present a modular pointer analysis algorithm based on the update history. We use the term ‘module’ to mean a set of mutually recursive procedures and the term ‘modular analysis’ to mean a program analysis that does not need the source codes of the other modules to analyze a module. Since a modular pointer analysis does not utilize any information on the callers, it is difficult to design a precise analysis that does not lose the information related to the program flow or the calling context. In this paper, we propose a modular and flow- and contextsensitive pointer analysis algorithm based on the update history that can abstract memory states of a procedure independently of the information on the calling context and keep the information on the order of side effects performed. Such a memory representation not only enables the analysis to be formalized as a modular analysis, but also helps the analysis to effectively identify killed side effects and relevant alias contexts.

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