• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.587-590
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• 2014

Spread of smart devices increases, the App Store market is formed so huge, even at this point, every day the scale is increasing now. As a result, for the benefit of companies and private individuals, malicious apps that threaten the security of smart devices, have appeared occasionally in the App Store. Security of the terminal, has issued various solutions through research at many universities and companies, and country. However, solutions for research and policy approaches that are blocking the procedure to register the application malicious app, so that it is not registered in the App Store, Only company that operates the app store is doing it. And the reference is also insufficient, various problems have occurred. In this study, after analyzing the problem of the security policy of the current App Store, presenting the breaking point.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.25-38
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• 2019

This study is to develop a diagnostic model for the effective introduction of smart factories in the manufacturing industry, to diagnose SMEs that have difficulties in building their own smart factory compared to large enterprise, to identify the current level and to present directions for implementation. IT, AT, and OT experts diagnosed 18 SMEs using the "Smart Factory Capacity Diagnosis Tool" developed for smart factory level assessment of companies. They analyzed the results and assessed the level by smart factory diagnosis categories. Companies' smart factory diagnostic mean score is 322 out of 1000 points, between 1 level (check) and 2 level (monitoring). According to diagnosis category, Factory Field Basic, R&D, Production/Logistics/Quality Control, Supply Chain Management and Reference Information Standardization are high but Strategy, Facility Automation, Equipment Control, Data/Information System and Effect Analysis are low. There was little difference in smart factory level depending on whether IT system was built or not. Also, Companies with large sales amount were not necessarily advantageous to smart factories. This study will help SMEs who are interested in smart factory. In order to build smart factory, it is necessary to analyze the market trends, SW/ICT and establish a smart factory strategy suitable for the company considering the characteristics of industry and business environment.

• Journal of Arbitration Studies
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• v.28 no.4
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• pp.89-110
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• 2018

The purposes of this study are as follows: First, this study reviews the Online Dispute Resolution (ODR) regulations of the EU to resolve disputes which can arise in international e-commerce in the future. Second, this study tries to seek out alternative solutions to dispute resolutions based on these regulations. Third, this study increases the efficiency of the transactions by proposing effective and satisfactory dispute resolution methods for international e-commerce. First, this study reviews the concept of cross-border e-commerce, generally explores ODR, and creates comparisons with Alternative Dispute Resolution (ADR). Subsequently, this study looks into domestic ODR system and analyzes the regulations of EU ODR. This study suggests the implications of the European ODR regulations in the conclusion. The EU ODR platform is considered greatly significant in that it has increased the possibility of settlements in small disputes by enhancing consumers' accessibility to ADR procedures. Therefore, this thesis proposes a method for Korean companies to resolve disputes that may arise in e-commerce with EU by using the ODR platform. As a result, it is expected to increase the competitiveness of Korean companies in the EU market. Both legislative trends related to the ODR of the EU and establishment of the EU ODR platform have significant implications for Korean businesses in Europe. This study is expected to be useful for our businesses in the EU in reviewing the applicability of the EU ODR regulations and the dispute settlement procedures through the EU ODR platform. In addition, this study is expected to prove useful in relation to consumer protection by enhancing consumers' accessibility to dispute settlement institutions in domestic electronic commerce.

• Fashion & Textile Research Journal
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• v.21 no.5
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• pp.574-585
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• 2019

The acceleration of digital transformation (DX) has resulted in SNS influencer marketing trends becoming the mainstream of the new market. SNS influencers act as early adopters in the process of new products being accepted. Chinese consumers are most affected by Hallyu, which increases interest in K-beauty products. This study analyzes how K-beauty SNS influencers are related to Chinese consumers. A survey was conducted among Chinese millennial consumers after watching videos provided by K-beauty SNS influencer; subsequently, 456 responses were used for data analysis. As a result, the analysis based on the Elaboration Likelihood Model (ELM) distinguishes the central route and the peripheral route in the process of Chinese consumers accepting new SNS products. The study findings suggested that information quality, credibility, accuracy, and usefulness had significant effects on acceptance intention for new products among central route factors, and similarity, trustworthiness, pleasure, expertise, and attractiveness also had significant effects on the acceptance intention of new product among peripheral route factors. It was found that variables of the central route, rather than those of peripheral route, had stronger effects on the acceptance intention for new products. Consequently, the central route of K-beauty SNS influencer is more important to Chinese consumers' acceptance of new products. It is expected that this study will offer beauty influencer marketing-based cosmetics brands efficient consumer management suggestions.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.3
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• pp.123-128
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• 2019

This paper proposes the stock price prediction based on the artificial intelligence, where the model with recurrent convolution neural network (RCNN) layers is adopted. In the motivation of this prediction, long short-term memory model (LSTM)-based neural network can make the output of the time series prediction. On the other hand, the convolution neural network provides the data filtering, averaging, and augmentation. By combining the advantages mentioned above, the proposed technique predicts the estimated stock price of next day. In addition, in order to emphasize the recent time series, a custom weighted loss function is adopted. Moreover, stock data related to the stock price index are adopted to consider the market trends. In the experiments, the proposed stock price prediction reduces the test error by 3.19%, which is over other techniques by about 19%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.435-440
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• 2020

The application of the unmanned vehicles in various fields has been attracting attention, and the development of a service utilizing unmanned vehicles has been proceeding. As the service market using the unmanned vehicles rapidly increases, the demand for the development of software for performing the mission with unmanned vehicles is increasing. In particular, as the demand for unmanned vehicle utilization services for public missions such as fire detection, mail delivery, and facility management increases, the importance of developing mission software for unmanned vehicle is increasing. To develop common mission software, architecture design should be made so that unmanned vehicle service provider can easily develop software using reusable libraries or functions through analysis commonly required by various public institutions. In this paper, we discuss the research trends of mission software for public mission unmanned vehicles. In addition, the architecture design of developing formal mission software is proposed. Finally, we propose a data transfer architecture between mission software and data platform.

• Korea Real Estate Review
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• v.27 no.3
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• pp.41-50
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• 2017

Previous studies, especially that by Lee (2014), showed how time series volatility models can be applied to the house price series. As the regional housing market trends, however, have shown significant differences of late, analysis with national data may have limited practical implications. This study applied volatility models in analyzing and forecasting regional house prices. The estimation of the AR(1)-ARCH(1), AR(1)-GARCH(1,1), and AR(1)-EGARCH(1,1,1) models confirmed the ARCH and/or GARCH effects in the regional house price series. The RMSEs of out-of-sample forecasts were then compared to identify the best-fitting model for each region. The monthly rates of house price changes in the second half of 2017 were then presented as an example of how the results of this study can be applied in practice.

• The Southeast Asian review
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• v.20 no.2
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• pp.135-178
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• 2010

This study is to seek alternatives for regional governance related to transnational labor migration issues in Southeast Asia. This study examined the present situation and trends of labor migration in the region, reviewed involved transnational issues, and identified the current issues of governance to seek alternatives for regional governance. The increase in cross-border labor migration is no doubt a sign of growth and dynamism of the region and greater integration of their economies. But it also poses complex policy and management issues as well as transnational issues over such as unequal economic profits, illegal migration, human rights, and social security issues. In this reality, regional governance is a very important theme and the efforts to manage their migration inherently involve fundamental conflict and tension between related countries and regions. However, politics and governance of transnational migrant workers in Southeast Asia are still pursued at the national level. To resolve these issues, it is urgently required to secure not only collaboration between the parties concerned but also governance at the regional level. Findings of this study are: First, although labor migration has been a relatively long-time transnational issue, the history of addressing the issue at the regional governance is very short and still inceptive. Second, given its size, labor migration in Southeast Asia requires effective regional governance but no breakthrough was possible due to the conflict of interests between origin and destination countries and the conflict of logic between the labor market and the state. Third, the issue of labor migration is an important element for the formation of economic and socio-cultural communities the ASEAN countries have pursued. Fourth, it is urgently needed to seek alternatives for good and effective regional governance as a key to resolving these issues over migrant workers in Southeast Asia.

• The Southeast Asian review
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• v.23 no.3
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• pp.1-48
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• 2013

Taking the cases of Korean garment factories in Binh Duong area, this study aims to explain the phases and causes of the wildcat strikes that have rapidly expanded recently in Vietnam. For the purpose, this study raises several questions as follows. Why the strikes sometimes increase and decrease other times? Why the factory workers prefer a wildcat strike even though it is politically risky, unproductive, and complicated? By the same token, why the foreign management cannot or will not preemptively preclude the wildcat strikes that are usually predictable and the workers are mostly able to accomplish their demands? While answering these questions, this study explores the economic, political, and socio-cultural conditions of the wildcat strikes respectively. Based on the fieldwork in around 30 Korean owned garment factories and the interview with around 100 Vietnamese factory workers in Binh Duong, this study confirms several findings on the phases and causes of the strikes in the area in specific and in Vietnam in general. First, the annual trends of the wildcat strikes reflect the macroeconomic conditions in which the consumer prices and the labor market in Vietnamese economy and business conditions in the world economy are pivotal. Second, however, the influence of macroeconomic conditions on both the management and the workers in the garment factories are differential, depending on the financial situations of the multinational corporations and the workers' capability of reproducing their household economies. Thirdly, the possibility of the wildcat strike in each factory is relatively independent on the financial conditions of a factory and rather associated with the stable political structure and active political processes within the factory that enable the management and the workers to efficiently communicate each other. Lastly, the necessity of establishing political stability in a factory arises from the distinctive social and cultural characteristics of the multinational corporation in which foreign managers and native workers inevitably live in separate and different socio-cultural worlds.

• Smart Media Journal
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• v.10 no.1
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• pp.116-123
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• 2021

Due to the rapid growth of the online fashion market and the resulting expansion of online choices, there is a problem that the seller cannot directly respond to a large number of consumers individually, although consumers are increasingly demanding for more personalized recommendation services. Images are being tagged as a way to meet consumer's personalization needs, but when people tagging, tagging is very subjective for each person, and artificial intelligence tagging has very limited words and does not meet the needs of users. To solve this problem, we designed an algorithm that recognizes the shape, attribute, and emotional information of the product included in the image with AI, and codes this information to represent all the information that the image has with a combination of codes. Through this algorithm, it became possible by acquiring a variety of information possessed by the image in real time, such as the sensibility of the fashion image and the TPO information expressed by the fashion image, which was not possible until now. Based on this information, it is possible to go beyond the stage of analyzing the tastes of consumers and make hyper-personalized clothing recommendations that combine the tastes of consumers with information about trends and TPOs.