• Journal of Korea Water Resources Association
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• v.47 no.2
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• pp.145-159
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• 2014

This study is to evaluate the future climate change impact on turbidity water and eutrophication for Chungju Lake by using CE-QUAL-W2 reservoir water quality model coupled with SWAT watershed model. The SWAT was calibrated and validated using 11 years (2000~2010) daily streamflow data at three locations and monthly stream water quality data at two locations. The CE-QUAL-W2 was calibrated and validated for 2 years (2008 and 2010) water temperature, suspended solid, total nitrogen, total phosphorus, and Chl-a. For the future assessment, the SWAT results were used as boundary conditions for CE-QUAL-W2 model run. To evaluate the future water quality variation in reservoir, the climate data predicted by MM5 RCM(Regional Climate Model) of Special Report on Emissions Scenarios (SRES) A1B for three periods (2013~2040, 2041~2070 and 2071~2100) were downscaled by Artificial Neural Networks method to consider Typhoon effect. The RCM temperature and precipitation outputs and historical records were used to generate pollutants loading from the watershed. By the future temperature increase, the lake water temperature showed $0.5^{\circ}C$ increase in shallow depth while $-0.9^{\circ}C$ in deep depth. The future annual maximum sediment concentration into the lake from the watershed showed 17% increase in wet years. The future lake residence time above 10 mg/L suspended solids (SS) showed increases of 6 and 17 days in wet and dry years respectively comparing with normal year. The SS occupying rate of the lake also showed increases of 24% and 26% in both wet and dry year respectively. In summary, the future lake turbidity showed longer lasting with high concentration comparing with present behavior. Under the future lake environment by the watershed and within lake, the future maximum Chl-a concentration showed increases of 19 % in wet year and 3% in dry year respectively.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.181-199
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• 2010

As rapid progress of population aging and strong interest in health, the demand for new healthcare service is increasing. Until now healthcare service has provided post treatment by face-to-face manner. But according to related researches, proactive treatment is resulted to be more effective for preventing diseases. Particularly, the existing healthcare services have limitations in preventing and managing metabolic syndrome such a lifestyle disease, because the cause of metabolic syndrome is related to life habit. As the advent of ubiquitous technology, patients with the metabolic syndrome can improve life habit such as poor eating habits and physical inactivity without the constraints of time and space through u-healthcare service. Therefore, lots of researches for u-healthcare service focus on providing the personalized healthcare service for preventing and managing metabolic syndrome. For example, Kim et al.(2010) have proposed a healthcare model for providing the customized calories and rates of nutrition factors by analyzing the user's preference in foods. Lee et al.(2010) have suggested the customized diet recommendation service considering the basic information, vital signs, family history of diseases and food preferences to prevent and manage coronary heart disease. And, Kim and Han(2004) have demonstrated that the web-based nutrition counseling has effects on food intake and lipids of patients with hyperlipidemia. However, the existing researches for u-healthcare service focus on providing the predefined one-way u-healthcare service. Thus, users have a tendency to easily lose interest in improving life habit. To solve such a problem of u-healthcare service, this research suggests a u-healthcare recommender system which is based on collaborative filtering principle and social network. This research follows the principle of collaborative filtering, but preserves local networks (consisting of small group of similar neighbors) for target users to recommend context aware healthcare services. Our research is consisted of the following five steps. In the first step, user profile is created using the usage history data for improvement in life habit. And then, a set of users known as neighbors is formed by the degree of similarity between the users, which is calculated by Pearson correlation coefficient. In the second step, the target user obtains service information from his/her neighbors. In the third step, recommendation list of top-N service is generated for the target user. Making the list, we use the multi-filtering based on user's psychological context information and body mass index (BMI) information for the detailed recommendation. In the fourth step, the personal information, which is the history of the usage service, is updated when the target user uses the recommended service. In the final step, a social network is reformed to continually provide qualified recommendation. For example, the neighbors may be excluded from the social network if the target user doesn't like the recommendation list received from them. That is, this step updates each user's neighbors locally, so maintains the updated local neighbors always to give context aware recommendation in real time. The characteristics of our research as follows. First, we develop the u-healthcare recommender system for improving life habit such as poor eating habits and physical inactivity. Second, the proposed recommender system uses autonomous collaboration, which enables users to prevent dropping and not to lose user's interest in improving life habit. Third, the reformation of the social network is automated to maintain the quality of recommendation. Finally, this research has implemented a mobile prototype system using JAVA and Microsoft Access2007 to recommend the prescribed foods and exercises for chronic disease prevention, which are provided by A university medical center. This research intends to prevent diseases such as chronic illnesses and to improve user's lifestyle through providing context aware and personalized food and exercise services with the help of similar users'experience and knowledge. We expect that the user of this system can improve their life habit with the help of handheld mobile smart phone, because it uses autonomous collaboration to arouse interest in healthcare.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.4
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• pp.1-12
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• 2014

It is essential factor for business operation to raise funds effectively. However, in Korea, many start-ups and small businesses have difficulties in fund-raising. In recent years, crowdfunding, a new method for funding a project of individuals or organizations by raising monetary contributions from a large number of people, has been growing up simultaneously with diffusion of social media. Crowdfunding is on early stage in Korea, and the majority of projects are focused on cultural or art categories. There is high proportion of projects that have social value in start-up sector. Crowdfunding in Korea has great potential because success rate of it is much higher than its of advanced countries, although market size is much smaller than them. The purpose of this paper is to propose success strategies of crowdfunding for start-up through case study. 5 crowdfunding platforms of Korea and Kickstarter, the platform of United States were investigated. Then we checked the figures related to the operation of the whole Korean projects on start-up. Finally, we made comparison between the cases of success and failure by analyzing 8 project characteristics. The study shows that it were the differences in trustworthiness and activeness of project creator, value of reward and efforts for interactivity that have great effects on success of the project. Whereas there was no significant influence of societal contribution and sponsor engagement. The thesis provides success strategies of crowdfunding for start-up as follows. Firstly, creator of the project should make support base by enthusiastic activites before launching funding project. Secondly, there should be contents that can easily show the process of business development in the project information. Thirdly, there must be appropriate design of rewards for each amounts of support money. Finally, efforts for interactivity, such as frequent updates, response for comments and SNS posting, should be followed after the launch of the project.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.187-201
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• 2011

KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.8
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• pp.52-59
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• 2007

In this paper, we analyzed and measured implant isolation characteristics for a 1.25 Gbps monolithic integrated hi-directional (M-BiDi) optoelectronic system-on-a-chip, which is a key component to constitute gigabit passive optical networks (PONs) for a fiber-to-the-home (FTTH). Also, we derived an equivalent circuit of the implant structure under various DC bias conditions. The 1.25 Gbps M-BiDi transmit-receive SoC consists of a laser diode with a monitor photodiode as a transmitter and a digital photodiode as a digital data receiver on the same InP wafer According to IEEE 802.3ah and ITU-T G.983.3 standards, a receiver sensitivity of the digital receiver has to satisfy under -24 dBm @ BER=10-12. Therefore, the electrical crosstalk levels have to maintain less than -86 dB from DC to 3 GHz. From analysed and measured results of the implant structure, the M-BiDi SoC with the implant area of 20 mm width and more than 200 mm distance between the laser diode and monitor photodiode, and between the monitor photodiode and digital photodiode, satisfies the electrical crosstalk level. These implant characteristics can be used for the design and fabrication of an optoelectronic SoC design, and expended to a mixed-mode SoC field.

• Journal of Korean Home Economics Education Association
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• v.28 no.1
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• pp.19-39
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• 2016

The purpose of this study was to develop the safety theme-based integrated teaching learning process plans for the middle school Home Economics(HE) Instruction and ultimately to contribute for the middle school students to live their safe lives. To achieve the goals of this study, HE curriculum documents from the 1st to the 2015 revision were analyzed and a survey was conducted to identify the middle school students' current status of safety accidents and needs on the HE safety education. The respondents of the survey were the 512 students of one ${\bigcirc}{\bigcirc}$ Girls' Middle School in Busan. And then, the seven integrated themes were selected, each seven integrated theme-networks were formed, and safety theme-based Home Economics curriculum and learning materials were developed. The results of this study were as the follows. The safety education content has continually been included from the first HE curriculum of 1954 to the 2015 revised HE curriculum. The middle school student respondents highly needed the content of 'the methods to deal with sexual violence and prostitution prevention', 'suicide prevention', and 'bullying net' for the HE safety education. All the 42 items were needed for the HE safety education by the respondents. The safety theme-based HE teaching learning process plans developed finally included the seven integrated themes, which were (1) dietary life safety, (2) adolescents' sex and safety, (3) adolescents' relationships with friends and safety, (4) family life and safety, (5) dwelling life and safety, (6) adolescents' egos and safety, and (7) social environment and safety. Each integrated theme consisted of three to six small themes, which amounted to total 28(for 35 lessons). Each small theme was presented with learning objectives and particular goals. The total 157 learning materials including the Home Economics curriculum were developed, which offered learning objectives and content for each safety theme, total 28 teaching and learning plans(for 35 lessons) were developed, which offered specific instructions for the easy implementation of the curriculum in the classroom, 28 PPTs, 25 film materials, four reading materials, 61 workbooks, 14 activity sheets, 16 evaluation sheets, 3 test sheets, 2 reference materials, and 4 learning material models(the refrigerator model, traffic lights for discussions, food tray model and stickers, and food mileage card). In this study, the safety education themes of 'clothing life and safety', 'conflict and safety', 'professional life and safety', and 'consumer and safety' were not addressed because these theme were not needed highly by the respondents. Therefore, for the further development of the teaching learning process plans for the HE safety education, it is necessary to develop and evaluate the teaching learning process plans to address the themes of 'clothing life and safety', 'conflict and safety', 'professional life and safety', and 'consumer and safety'.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.2
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• pp.60-74
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• 2017

To facilitate prevention of highly pathogenic avian influenza (HPAI), a GIS is widely used for monitoring, investigating epidemics, managing HPAI-infected farms, and eradicating the disease. After the outbreak of foot-and-mouth disease in 2010 and 2011, the government of the Republic of Korea (ROK) established the GIS-based Korean Animal Health Integrated System (KAHIS) to avert livestock epidemics, including HPAI. However, the KAHIS is not sufficient for controlling HPAI outbreaks due to lack of responsibility in fieldwork, such as sterilization of HPAI-infected poultry farms and regions, control of infected animal movement, and implementation of an eradication strategy. An outbreak prediction model to support efficient HPAI control in the ROK is proposed here, constructed via analysis of HPAI outbreak patterns in the ROK. The results show that 82% of HPAI outbreaks occurred in Jeolla and Chungcheong Provinces. The density of poultry farms in these regions were $2.2{\pm}1.1/km^2$ and $4.2{\pm}5.6/km^2$, respectively. In addition, reared animal numbers ranged between 6,537 and 24,250 individuals in poultry farms located in HPAI outbreak regions. Following identification of poultry farms in HPAI outbreak regions, an HPAI outbreak prediction model was designed using factors such as the habitat range for migratory birds(HMB), freshwater system characteristics, and local road networks. Using these factors, poultry farms which reared 6,500-25,000 individuals were filtered and compared with number of farms actually affected by HPAI outbreaks in the ROK. The HPAI prediction model shows that 90.0% of the number of poultry farms and 54.8% of the locations of poultry farms overlapped between an actual HPAI outbreak poultry farms reported in 2014 and poultry farms estimated by HPAI outbreak prediction model in the present study. These results clearly show that the HPAI outbreak prediction model is applicable for estimating HPAI outbreak regions in ROK.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.6
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• pp.98-109
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• 2011

Habitat restoration initiative is an important factor for the on-site preservation of butterflies. A new habitat necessitates the investigation of the ecology of the butterfly, the landscape of the habitat, the work process, and a cost analysis. In this study, these factors were analyzed through1) re-consideration of the secured results from three years of field work, and 2) a habitat area estimation conducted according to the presence or absence of larvae and adults via a Parnassius bremeri Bremer survey. The investigation of the natural habitat, done for both larvae and adult butterflies found in South Korea, suggested that multiple patches with a minimum size exceeding $300m^2$ and with an average size of about $1,600m^2$were required for survival of this butterfly. Therefore, more than five patches should be considered for butterfly habitat and patches should have similarity to the present habitat environment with transplantation plans for diet plants and honeydew plants. In addition, to activate the migration of the butterfly, cutting down trees that are obstacles to migration, minimizing the distance between patches and the addition of a stepping patch are also required. A patch connectivity analysis showed that patches should be located within 300m of neighboring patches, as the migration of the butterfly will fail if it is more than 600m. Additionally, more than $10,000m^2$ for a single patch or a patch network composed more than five patches over $1,600m^2$ in size were recommended, with a total patch size of $8,000m^2$. Additionally, neighboring multiple patch networks are more desirable than a single habitat in the event a cyclic habitat pattern arises. In this study, we suggest a habitat restoration and optimal prerequisites for a butterfly habitat. It is expected that this research will lead to the creation of a good model for the restoration of butterfly species.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.47-65
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• 2020

With the era of the Fourth Industrial Revolution in sight, innovative business models utilizing new technologies are emerging, and startups are enjoying an abundance of opportunities based on the agility to respond to disruptive innovations and the opening to new technologies. However, what is most important in creating a sustainable start-up ecosystem is not the start-up itself, but the process of research-start-investment-investment-the leap to listing and big business-in order to build a virtuous circle of startups that leads to re-investment. To this end, the environment created in the hub area where start-ups were conducted is important, and these material and non-material environmental factors are described as being inclusive by the word "entrepreneurial ecosystem." This study aims to provide implications for Korea's entrepreneurial ecosystem through the study of the interaction of the elements that make up the start-up ecosystem and the relationship of ecosystem participants in Singapore. Singapore has been consistently mentioned as the top two Asian countries in assessing the start-up environment and business environment. In this process, six elements of the entrepreneurial ecosystem presented by Isenberg(2010)-policies, finance, culture, support, human resources, and market-are the best frameworks for analyzing entrepreneurial ecosystems in terms of well encompassing prior studies related to entrepreneurial ecosystem elements, and a model of regional transformation is formed focusing on some elements to suit Singapore, the target area of study. By considering that Singapore's political nature would inevitably have a huge impact on finance, Smart Nation policy was having an impact on university education related to entrepreneurship, and that the entrepreneurial networks and global connectivity formed within Singapore's start-up infrastructure had a significant impact on Singapore's start-up's performance, researches needed to look more at the factors of policy, culture and market. In addition, qualitative research of participants in the entrepreneurial ecosystem was essential to understand the internal interaction of the elements of the start-up ecosystem, so the semi-structured survey was conducted by visiting the site. As such, this study examined the status of the local entrepreneurial ecosystem based on qualitative research focused on policies, culture and market elements of Singapore's start-up ecosystem, and intended to provide implications for regulations related to start-ups, the role of universities and start-up infrastructure through comparison with Korea. This could contribute not only to the future research of the start-up ecosystem, but also to the creation of a start-up infrastructure, boosting the start-up ecosystem, and the establishment of the orientation of the start-up education in universities.