• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.469-474
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• 2020

This study explains the characteristics of micro-insurance based on the theoretical model of health insurance, such as the low demand of low-income people and the lower demand of higher risk aversion. In particular, these characteristics contradict the existing insurance theory which states that the lower the income, the higher the risk aversion, and the higher the demand for insurance. This study postulates a two-period model focusing on health insurance, contrary to a one-period model assumed in existing studies. As a result, first, we show that the decrease in income leads to a decrease in the preventive effort for illness. Second, we offer a model for micro-insurance in which the individual chooses a partial insurance under an actuarially fair insurance premium, while full insurance is optimal in existing studies. Third, we also show that the insurance demand decreases when the outlook for the future improves. Fourth, we finally show that the lack of trust and default risk of the insurer decrease the insurance demand as risk aversion increases.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6959-6968
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• 2015

This study aims to update the supply-demand model of wood products(FOSMO-2013) and to forecast mid and long run supply and demand for each products. The subjects of the study include sawnwood, plywood, particle board, fiberboard(MDF), and pulp. The updated partial equilibrium model is composed of supply function, import demand function, demand function, price relation function. The long run outlooks of world prices of wood and wood products are imported from the results of Buongiorno(2012). This study also adopt Buongiorno's scenarios, which includes three scenarios of IPCC(A1B, A2, B2) and the other one with assumption of increasing fuelwood consumption of A1B scenario. The result says that the domestic productions of wood products are expecting to decrease while the imports of them increase even there are some differences among the products as well as scenarios.

• Journal of Digital Contents Society
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• v.11 no.4
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• pp.529-536
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• 2010

Currently many people are awfully concerned about smart device in domestic and foreign mobile market. The need of smart device has been rapidly increased. Unlike a feature phone smart devices provide us with an intuitive interface which is easy to control. They are enable to smoothly interact between user and device. Though higher market outlook, there is a lack of empirical research on user interface in touch screen based on smart device. In this paper, we propose the touch interface conceptual model concentrating on user based on the result of previous research. Materials of this research are three kinds of smart devices which are currently released. Through expert's depth interview and observation of user, user's cognitive actions in smart device are defined. Since the method of the touch interface which is suitable for the action has been derived, we have proposed the conceptual model of user's cognitive action. This research imply to offer the excellent design guideline in order to implement touch interface to optimize user experience in touch screen based on smart device to release in the future.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.2
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• pp.79-83
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• 2018

According to the Korea Robotics Industry Association, the number of robots companies, sales and production are steadily increasing until 2016, and the global robot market outlook is expected to continue to increase until 2025. We need to develop more attention to robots that can make life easier for us and can replace human tasks that we cannot do. It is predicted that robots will be more developed in the future with the above statistics, and future robots will be more activated by robots that can depend on each other, fix each other, and adapt to the changing environment without humans. Therefore, the shape of the robots in the future will be developed as a group robot(swarmbot) that cooperate with each other while the robot works. These robots have been studied for a longtime, but there are only two community robots that are applied in real life, only two of which are jailbreaking robots made in KAIST and KIVA robots made in Amazon company. In the future, as these robots develop more and more, and environment where robots can live without human intervention is created, so that a plurality of robots can collaborate and do individual work.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4625-4647
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• 2020

The Generative Adversarial Networks, as one of the most creative deep learning models in recent years, has achieved great success in computer vision and natural language processing. It uses the game theory to generate the best sample in generator and discriminator. Recently, many deep learning models have been applied to the security field. Along with the idea of "generative" and "adversarial", researchers are trying to apply Generative Adversarial Networks to the security field. This paper presents the development of Generative Adversarial Networks. We review traditional generation models and typical Generative Adversarial Networks models, analyze the application of their models in natural language processing and computer vision. To emphasize that Generative Adversarial Networks models are feasible to be used in security, we separately review the contributions that their defenses in information security, cyber security and artificial intelligence security. Finally, drawing on the reviewed literature, we provide a broader outlook of this research direction.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.71-71
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• 2020

최근 기후변화의 영향으로 극심한 가뭄과 홍수가 발생하고 기온 또한 꾸준히 상승하고 있으며, 이러한 변화에 대응하기 위해 전 세계에서 이산화탄소를 줄이고 국제 에너지 시장을 재구성하려는 시도가 꾸준히 이루어지고 있다. World Energy Outlook(2012)에 따르면 특히 에너지 시장에서 개발도상국의 수력분야 개발투자가 2035년까지 15,490억 달러에 이를 것으로 전망됨에 따라 국내에서 해외 수력발전사업에 적극적으로 나서고 있다. 그러나 국내와는 달리 댐 건설의 사전조사에 필요한 자료가 없거나 구축하는데 문제가 있어 손쉽게 구할 수 있는 자료로 사전에 수력발전 댐 적지를 조사할 수 있는 기술의 개발이 필요하다. 따라서 본 연구에서는 수력발전용 댐 위치 결정을 위한 예비 적지 분석 알고리즘을 개발하고, 분석 알고리즘에 위성영상자료인 30m 해상도의 ASTGTM(ASTER Global Digital Elevation Model)와 500m 해상도의 MCD12Q1(MODIS/Terra Aqua Land Cover) 토지피복자료를 사용하고자 한다. 예비 적지 분석 알고리즘은 DEM의 전처리, 하천망생성, 유역분할과 지형정보를 고려한 자동적지탐색과 댐 건설시 수몰면적에 따른 보상면적 산정 알고리즘을 포함하고 있으며 Python기반의 오픈소스 GIS로 구현되었다. 적지산정은 DEM으로부터 낙차, 도달시간, 내용적곡선과 같은 지형정보와 토지피복도를 통한 보상면적을 기반으로 순위를 매겨 사용자에게 최적의 위치들을 표출한다. 본 연구의 결과는 향후 해외 수력 댐 적지 예비분석 및 해외 수력산업 진출을 지원할 수 있을 것으로 기대된다.

• Journal of the Semiconductor & Display Technology
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• v.23 no.2
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• pp.12-18
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• 2024

A Electrostatic chuck is a device that fixes the substrate, using the force between charges applied between two parallel plates to attract substrates such as wafers or OLED panels. Unlike mechanical suction methods, which rely on physical fixation, this method utilizes the force of electrostatics for fixation, making it important to verify the adhesion force. As the size of the substrate increases, deformations due to gravity or chucking force also increase, and the adhesion force decreases rapidly as the distance between the chuck and the substrate increases. The outlook for displays is shifting from small to large OLEDs, necessitating consideration of substrate deformations. In this paper, to confirm the deformation of the substrate through various patterns, a simplified 2D model using Ansys' electromagnetic field analysis program, Maxwell, and the static structural analysis program, Mechanical, was utilized to observe changes in adhesion force according to the variation in the air gap between the substrate and the chuck. Additionally, the chucking force was analyzed for the size of the substrate, and the deformation of the substrate was confirmed when gravity and chucking force act simultaneously.

• Journal of Distribution Science
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• v.15 no.6
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• pp.77-96
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• 2017

Purpose - This study aims to develop correspondence strategies to the environment change in domestic retail store types. Recently, new types of retails have emerged in retail industries. Therefore, trade area platform has developed focusing on the speed of data, no longer trade area from district border. Besides, 'trade area smart' brings about change in retail types with the development of giga internet. Thus, context shopping is changing the way of consumers' purchase pattern through data capture, technology capability, and algorithm development. For these reasons, the sales estimation model has been shown to be flawed using the notion of former scale and time, and it is necessary to construct a new model. Research design, data, and methodology - This study focuses on measuring retail change in large multi-shopping mall for the outlook for retail industry and competition for trade area with the theoretical background understanding of retail store types and overall domestic retail conditions. The competition among retail store types are strong, whereas the borders among them are fading. There is a greater need to analyze on a new model because sales expectation can be hard to get with business area competition. For comprehensive research, therefore, the research method based on the statistical analysis was excluded, and field survey and literature investigation method were used to identify problems and propose an alternative. In research material, research fidelity has improved with complementing research data related with retail specialists' as well as department stores. Results - This study analyzed trade area survival and its pattern through sales estimation and empirical studies on trade areas. The sales estimation, based on Huff model system, counts the number of households shopping absorption expectation from trade areas. Based on the results, this paper estimated sales scale, and then deducted modified probability model. Conclusions - In times of retail store chain destruction and off-line store reorganization, modified Huff model has problems in estimating sales. Transformation probability model, supplemented by the existing problems, was analyzed to be more effective in competitiveness business condition. This study offers a viable alternative to figure out related trade areas' sale estimation by reconstructing new-modified probability model. As a result, the future task is to enlarge the borders from IT infrastructure with data and evidence based business into DT infrastructure.

• Korean Journal of Agricultural Science
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• v.44 no.4
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• pp.613-619
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• 2017

In Korea, the government introduced the $6^{th}$ industrialization policy for the agricultural sector in 2013, to increase farmers' incomes and the value-added of agricultural products. Although some research has been done on the $6^{th}$ industrialization of agriculture, the relationship between the level of consumers' awareness and the $6^{th}$ industrialization of agriculture has not yet been discussed. The purpose of this paper is to analyze the effect of consumers' awareness levels on the development of the $6^{th}$ industrialization of agriculture. The results of a survey and seemingly unrelated bivariate probit model present the following findings: an increased consumers' awareness of the $6^{th}$ industrialization of agriculture positively affects the agricultural sector. More particularly, it was found that consumers who agree that the $6^{th}$ industrialization increases farmers' income and creates value-added agricultural products will also have an optimistic prospect for a successful $6^{th}$ industrialization. In addition, consumers who like to experience agro-tourism type activities give higher scores to the infrastructure level of the $6^{th}$ industrialization. Consumers who think that production section should take lead the $6^{th}$ industrialization of the agricultural sector will also have an optimistic prospect for a successful $6^{th}$ industrialization. However, consumers who think that farmers or farmers' organizations, should take lead the $6^{th}$ industrialization have a more pessimistic prospect for a successful $6^{th}$ industrialization. Consumers who got information on the $6^{th}$ industrialization from the internet think that the infrastructure of the $6^{th}$ industrialization is not good enough.