• Korea Trade Review
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• v.45 no.1
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• pp.279-300
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• 2020

The cosmetic medical information mobile platform is evolving into a new channel for searching and obtaining relevant information before using cosmetic medical service. In addition, the medical institutions can facilitate the medical contracts, and take advantage of systemic customer management through the cosmetic medical information mobile platform. Therefore, the paradigm of the cosmetic medical mobile service industry is facing a flow of change through the use diffusion of cosmetic medical information mobile platform. In this study, in order to explore the factors affecting the use diffusion of the cosmetic medical information mobile platform, this study used the research model of the influence of the characteristics of the cosmetic medical information mobile platform on perceived convenience and usefulness, and use diffusion by applying TAM(Technology Acceptance Model). As a result, immediateness, interactivity, and customization in the characteristics of cosmetic medical information mobile platform had positive effects on the perceived convenience. Also, interactivity, customization, and economics had positive impacts on perceived usefulness. In addition, perceived convenience and usefulness had positive effects on the use diffusion. Through this study, the factors influencing the use diffusion of cosmetic medical information mobile platform were actually explored, and the service value of the cosmetic medical information mobile platform were categorized. Future research is expected to contribute to the continuous improvement of quality and expansion of the cosmetic medical service market based on various research.

• Journal of Information Technology Applications and Management
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• v.17 no.2
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• pp.187-205
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• 2010

This study takes a holistic approach to understand the diffusion of IPTV services by combining the adoption-diffusion model and the use-diffusion model of innovation. IPTV service, a leading digital converged application coupling media content with telecommunications, has been recently launched commercially in Korea. We created a structural model of adoption-diffusion, using the perceived easeof-use and usefulness of TAM(Technology Acceptance Model) as mediating variables, and a structural model of use-diffusion, with the rate of use and the variety of use as mediating variables. To empirically analyze these models, non-users of IPTV were surveyed using the adoption-diffusion model to identify factors influencing their intention to subscribe to the service. Meanwhile, users of IPTV were surveyed using the use-diffusion model to determine the factors that influence their satisfaction with the service and their intention to re-use it. Under the adoption-diffusion model, we found that trialability, household innovativeness and perceived risk were the determinants of user satisfaction with IPTV, and perceived ease-of-use, the mediating factors. Under the use-diffusion model, complementarity and communication were shown to be the determinants of users' satisfaction with IPTV, and variety of use, the mediating factor. We also found that consumers' intention to re-use IPTV was strongly influenced by its relative advantage and perceived risk.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.2-4
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• 2023

Sequence data plays an important role in the field of intelligence, especially for industrial control, traffic control and other aspects. Finding abnormal parts in sequence data has long been an application field of AI technology. In this paper, we propose an anomaly detection method for sequence data using a diffusion model. The diffusion model has two major advantages: interpretability derived from rigorous mathematical derivation and unrestricted selection of backbone models. This method uses the diffusion model to predict and reconstruct the sequence data, and then detects the abnormal part by comparing with the real data. This paper successfully verifies the feasibility of the diffusion model in the field of anomaly detection. We use the combination of MLP and diffusion model to generate data and compare the generated data with real data to detect anomalous points.

• 한국컴퓨터산업교육학회:학술대회논문집
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• 2003.11a
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• pp.87-94
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• 2003

Anisotropic diffusion is a selective smoothing technique that promotes smoothing within a region instead of smoothing across boundaries. In anisotropic diffusion, the rate of smoothing is controlled by the local value of the diffusion coefficient chosen to be a function of the local image gradient magnitude. El-Fallah and Gary E. Ford represented the image as a surface and proved that setting the inhomogeneous diffusion coefficient equal to the inverse of the magnitude of the surface normal results in surface evolving speed that is proportional to the mean curvature of the image surface. This model has the advantage of having the mean curvature diffusion (MCD) render invariant magnitude, thereby preserving structure and locality. In this paper, the proposed MCD model efficiently reduces diffusion coefficient at the thin edges using the smoothness of the surface.

• Journal of Distribution Research
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• v.15 no.4
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• pp.61-85
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• 2010

Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center. $$\array{{S_{i,t}=(p_i+q_i{\frac{Y_{i,t-1}}{m_i}})(m_i-Y_{i,t-1})\;i{\in}\{1,{\cdots},I\}\;(1a)}\\{S_{j,t}=(p_j+q_j{\frac{Y_{j,t-1}}{m_i}}+{\sum\limits_{i=1}^I}{\gamma}_{ij}{\frac{Y_{i,t-1}}{m_i}})(m_j-Y_{j,t-1})\;i{\in}\{1,{\cdots},I\},\;j{\in}\{I+1,{\cdots},I+J\}\;(1b)}}$$ We rise two research questions. (1) The proposed spatial diffusion model is more effective than the Bass model to describe the diffusion of discount stores. (2) The more similar retail environment of diffusing center with that of the vicinity of the contiguous market is, the larger spatial effect of diffusing center on diffusion of the vicinity of the contiguous market is. To examine above two questions, we adopt the Bass model to estimate diffusion of discount store first. Next spatial diffusion model where spatial factor is added to the Bass model is used to estimate it. Finally by comparing Bass model with spatial diffusion model, we try to find out which model describes diffusion of discount store better. In addition, we investigate the relationship between similarity of retail environment(conceptual distance) and spatial factor impact with correlation analysis. Result and Implication: We suggest spatial diffusion model to describe diffusion of discount stores. To examine the proposed spatial diffusion model, 347 domestic discount stores are used and we divide nation into 5 districts, Seoul-Gyeongin(SG), Busan-Gyeongnam(BG), Daegu-Gyeongbuk(DG), Gwan- gju-Jeonla(GJ), Daejeon-Chungcheong(DC), and the result is shown