• Journal of the Korea Convergence Society
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• v.11 no.7
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• pp.105-112
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• 2020

This paper presents an investigation into the development of a fabric electronics based smart bag for festival users of the 2029 generation with customizable tech flaps (music media control/ LED animated graphic functions) based on the application of traditional Korean patterns and goblin patterns in an electric circuit. The investigator took into consideration functional and design strategies to enable custom service according to users' tastes and situations. Based on these considerations, a customizable smart bag platform was proposed in a detachable module based on a computer embroidery machine. The study is significant in that it developed a product that is different from the old PCB smart products in hard form and proposed a new business model.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.4
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• pp.183-190
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• 2018

Predicting accurate electricity prices is an important task in the electricity trading market. To address the electricity price forecasting problem, various approaches have been proposed so far and it is known that linear regression-based approaches are the best. However, the use of such linear regression-based methods is limited due to low accuracy and performance. In traditional linear regression methods, it is not practical to find a nonlinear regression model that explains the training data well. If the training data is complex (i.e., small-sized individual data and large-sized features), it is difficult to find the polynomial function with n terms as the model that fits to the training data. On the other hand, as a linear regression model approximating a nonlinear regression model is used, the accuracy of the model drops considerably because it does not accurately reflect the characteristics of the training data. To cope with this problem, we propose a new electricity price forecasting method that divides the entire dataset to multiple split datasets and find the best linear regression models, each of which is the optimal model in each dataset. Meanwhile, to improve the performance of the proposed method, we modify the proposed localized linear regression method in the map and reduce way that is a framework for parallel processing data stored in a Hadoop distributed file system. Our experimental results show that the proposed model outperforms the existing linear regression model. Specifically, the accuracy of the proposed method is improved by 45% and the performance is faster 5 times than the existing linear regression-based model.

• Journal of Digital Convergence
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• v.16 no.6
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• pp.85-93
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• 2018

The Latent Growth Modeling(LGM) is known as the arising analysis method of longitudinal data and it could be classified into unconditional model and conditional model. Unconditional model requires estimated value of intercept and slope to complete a model of fitness. However, the existing LGM is in absence of a structured methodology to estimate slope when longitudinal data is neither simple linear function nor the pre-defined function. This study used Sequential Pattern of Association Rule Mining to calculate slope of unconditional model. The applied dataset is 'the Youth Panel 2001-2006' from Korea Employment Information Service. The proposed methodology was able to identify increasing fitness of the model comparing to the existing simple linear function and visualizing process of slope estimation.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.141-147
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• 2014

Diffusion model is popular research topic in marketing and economy particularly for the areas of model specification and market size forecasting. In particular, Bass model can explain Roger's innovation diffusion and product life cycle through easy mathematical representation and hence the model has been widely used for the explanation of adopting innovative new products and technologies. Nonetheless, there're only a couple of pioneering researches about semiconductor market, using diffusion models. Consequently, we'd utilise NLS approach diffusion model to estimate the market potential of MOSFET, major switching device for power management of system, and explain the process to industry stakeholders and policy makers for delivery of managerial implication with pragmatic purpose.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.361-370
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• 2022

This paper suggested a plan to increase the start-up survival rate by identifying independent variables that significantly affect start-up success through analysis of the founder's internal and external factors. As a result of this study, it was found that internal factors (financial ability, risk sensitivity) and external factors (start-up environment, start-up support policy) had a direct positive (+) effect on start-up success. Meanwhile, self-efficacy for business models partially mediated the relationship between factors(financing ability, risk sensitivity, start-up environment and start-up support policies) and start-up success. Self-efficacy for business models fully mediated the relationship between factors(start-up expertise and challenge spirit) and start-up success. Finally, trust in business models partially mediated the relationship between factors(start-up expertise, risk sensitivity, and start-up support policies) and start-up success. And the trust in business models fully mediated the factors(the spirit of challenge, start-up environment) and start-up success.

• Journal of information and communication convergence engineering
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• v.1 no.3
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• pp.150-156
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• 2003

This paper explored the use of an algorithm for the data mining and method in handling missing data which had generated enhanced association patterns observed using the data illustrated here. The evaluations showed that more association patterns are generated in the second analysis which suggests more meaningful rules than in the first situation. It showed that the model offer more precise and important association rules that is more valuable when applied for business decision making. With the discovery of accurate association rules or business patterns, strategies could be efficiently planned out and implemented to improve marketing schemes. This investigation gives rise to a number of interesting issues that could be explored further like the effect of outliers and missing data for detecting fraud and devious database entries.

• International journal of advanced smart convergence
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• v.7 no.2
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• pp.86-94
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• 2018

This study focuses on presenting the IT program module provided by real - time forecasting and database of the voluntary disclosure quality measure in order to solve the problem of capital cost due to information asymmetry of external investors and corporate executives. This study suggests a model of the algorithm that the quality of real - time voluntary disclosure can be provided to all investors immediately by IT program in order to deliver the meaningful value in the domestic capital market. This is a method of generating and analyzing real-time or non-real-time prediction models by transferring the predicted estimates delivered to the Big Data Log Analysis System through the statistical DB to the statistical forecasting engine.

• Journal of Digital Convergence
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• v.2 no.1
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• pp.57-73
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• 2004

Due to the rapid development of Information Technology and the Internet, e-business has bloomed and prevailed recently. As the result of this phenomenon, enterprises introduce CRM as a new process accessible to customers. The purpose of this study is to examine the factors affecting the performance of CRM based on precedent theoretical studies. So, the empirical test is conducted to various hypotheses related to the research model. 206 questionnaires for this study are collected. The result of how the organizational characteristics influence on the performance of CRM shows that they have a positively significant effect on it in order of expert security, top management's support and customer information-centric culture, and department collaboration. Evaluation and compensation system don't influence on the performance of CRM directly.

• Journal of Industrial Convergence
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• v.1 no.2
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• pp.107-124
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• 2003

With rapid growth and competition of electronic commerce through internet, various buying types and business models are being appeared. In this paper, we studied group buying which is new business model to consumer and factors affecting on trust and participation of group buying. The followings are the regression result of this study. First, familiarity factor, customer service factor, seal of security and product value factor made a significant effect on trust. Second, familiarity factor, perceived reputation factor, customer service factor, seal of security and product value factor made a significant effect on participation of group buying. Third, trust of group buying made a significant effect on participation of group buying. In this study, modeling and empirical test were implemented about structure of trust and participation of group buying. We can know where our group buying strategies should focus and which factor we should improve.

• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.217-228
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• 2019

In the 4th Industrial Revolution, the Internet of Things emerged and various services and convenience improved. As the frequency of use increases, security threats such as leakage of personal information coexist and the importance of security are increasing. In this paper, we analyze the security threats of the Internet of things and propose a model for enhancing security through user authentication using Fast IDentity Online (FIDO). As a result, we propose to implement strong user authentication by introducing second authentication through FIDO.