• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.151-176
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• 2021

As the information technology industry develops, various kinds of data are being created, and it is now essential to process them and use them in the industry. Analyzing and utilizing various digital data collected online and offline is a necessary process to provide an appropriate experience for customers in the industry. In order to create new businesses, products, and services, it is essential to use customer data collected in various ways to deeply understand potential customers' needs and analyze behavior patterns to capture hidden signals of desire. However, it is true that research using data analysis and UX methodology, which should be conducted in parallel for effective service development, is being conducted separately and that there is a lack of examples of use in the industry. In thiswork, we construct a single process by applying data analysis methods and UX methodologies. This study is important in that it is highly likely to be used because it applies methodologies that are actively used in practice. We conducted a survey on the topic to identify and cluster the associations between factors to establish customer classification and target customers. The research methods are as follows. First, we first conduct a factor, regression analysis to determine the association between factors in the happiness data survey. Groups are grouped according to the survey results and identify the relationship between 34 questions of psychological stability, family life, relational satisfaction, health, economic satisfaction, work satisfaction, daily life satisfaction, and residential environment satisfaction. Second, we classify clusters based on factors affecting happiness and extract the optimal number of clusters. Based on the results, we cross-analyzed the characteristics of each cluster. Third, forservice definition, analysis was conducted by correlating with keywords related to happiness. We leverage keyword analysis of the thumb trend to derive ideas based on the interest and associations of the keyword. We also collected approximately 11,000 news articles based on the top three keywords that are highly related to happiness, then derived issues between keywords through text mining analysis in SAS, and utilized them in defining services after ideas were conceived. Fourth, based on the characteristics identified through data analysis, we selected segmentation and targetingappropriate for service discovery. To this end, the characteristics of the factors were grouped and selected into four groups, and the profile was drawn up and the main target customers were selected. Fifth, based on the characteristics of the main target customers, interviewers were selected and the In-depthinterviews were conducted to discover the causes of happiness, causes of unhappiness, and needs for services. Sixth, we derive customer behavior patterns based on segment results and detailed interviews, and specify the objectives associated with the characteristics. Seventh, a typical persona using qualitative surveys and a persona using data were produced to analyze each characteristic and pros and cons by comparing the two personas. Existing market segmentation classifies customers based on purchasing factors, and UX methodology measures users' behavior variables to establish criteria and redefine users' classification. Utilizing these segment classification methods, applying the process of producinguser classification and persona in UX methodology will be able to utilize them as more accurate customer classification schemes. The significance of this study is summarized in two ways: First, the idea of using data to create a variety of services was linked to the UX methodology used to plan IT services by applying it in the hot topic era. Second, we further enhance user classification by applying segment analysis methods that are not currently used well in UX methodologies. To provide a consistent experience in creating a single service, from large to small, it is necessary to define customers with common goals. To this end, it is necessary to derive persona and persuade various stakeholders. Under these circumstances, designing a consistent experience from beginning to end, through fast and concrete user descriptions, would be a very effective way to produce a successful service.

• Journal of the Korea Organic Resources Recycling Association
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• v.29 no.1
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• pp.19-27
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• 2021

Hydroponic farming is a method to grow a plant without soil. Plants can be grown on water or hydroponic growing media, and they are fed with mineral nutrient solutions, which are fertilizers dissolved into water. Hydroponic farming has the advantage of increasing plant productivity over conventional greenhouse farming. Previous studies of hydroponic nutrient wastewater from acyclic hydroponic farms pointed out that hydroponic nutrient wastewater contained residual nutrients, and they were drained to a nearby river bank which causes several environmental issues. Also, previous studies suggest that excessive use of the nutrient solution and disposal of used hydroponic growing media and crop wastes in hydroponic farms are major problems to hydroponic farming. This study was conducted to determine the impact of hydroponic nutrient wastewater, used hydroponic growing media, and crop wastes from acyclic hydroponic farms on the surrounding environment by analyzing water quality and soil analysis of the above three factors. Three soil cultivation farms and several hydroponic farms in the Gangwon C region were selected for this study. Samples of water and soils were collected from both inside and outside of each farm. Also, a sample of soil and leachate from crop waste piles stacked near the farm was collected for analysis. Hydroponic nutrient wastewater from acyclic hydroponic farm contained an average of 402 mg/L of total nitrogen (TN) concentration, and 77.4 mg/L of total phosphate (TP) concentration. The result of TP in hydroponic nutrient wastewater exceeds the living environmental standard of the river in enforcement decree of the framework act on environmental policy by 993.7 times. Also, it exceeds the standard of industrial wastewater discharge standards under the water environment conservation act by 6~19 times in TN, and 2~27 times in TP. Leachate from crop waste piles contained 11,828 times higher COD and 395~2662 times higher TP than the standard set by the living environmental standard of the river in enforcement decree of the framework act on environmental policy and exceeds 778 times higher TN and 5 times higher TP than the standard of industrial wastewater discharge standards under the water environment conservation act. For more precise studies of the impact of hydroponic nutrient wastewater, used hydroponic growing media, and crop wastes from acyclic hydroponic farms on the surrounding environment, additional information regarding a number of hydroponic farms, arable area(ha), hydroponic farming area, seasonal, weather, climate factor around the river, and the property of the area and farm is needed. Analysis of these factors and additional water and soil samples are needed for future studies.

• Journal of Environmental Impact Assessment
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• v.30 no.2
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• pp.105-116
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• 2021

In the city of high population density crowded with buildings, Urban Heat Island (UHI) is intensified, and the city is vulnerable to thermal comfort. The maintenance of vacant land in downtown is treated as a factor that undermines the residential environment, spoils the urban landscape, and decreases the economic vitality of the whole region. Therefore, this study compared the effects on microclimate in the surrounding area according to the development scenarios targeting the vacant land in Songhyeon-dong, Jongno-gu, Seoul. The status quo, green oriented, building oriented and green-building mediation scenarios were established and ENVI-met was used to compare and analyze the impact of changes in wind speed, air temperature and mean radiant temperature (MRT) within 1 km of the target and the target site. The result of inside and 1 km radius the targeted area showed that the seasonal average temperature decreased and the wind speed increased when the green oriented scenario was compared with the current state one. It was expected that the temperature lowered to -0.73 ℃ or increased to 1.5 ℃ in summer, and the wind speed was affected up to 210 meters depending on the scenario. And it was revealed that green area inside the site generally affects inside area, but the layout and size of the buildings affect either internal and external area. This study is expected to help as a decision-making support tool for developing Songhyeon-dong area and to be used to reflect the part related to microclimate on the future environmental effects evaluation system.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.265-282
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• 2022

Sea surface temperature (SST) is a factor that greatly influences ocean circulation and ecosystems in the Earth system. As global warming causes changes in the SST near the Korean Peninsula, abnormal water temperature phenomena (high water temperature, low water temperature) occurs, causing continuous damage to the marine ecosystem and the fishery industry. Therefore, this study proposes a methodology to predict the SST near the Korean Peninsula and prevent damage by predicting abnormal water temperature phenomena. The study area was set near the Korean Peninsula, and ERA5 data from the European Center for Medium-Range Weather Forecasts (ECMWF) was used to utilize SST data at the same time period. As a research method, Long Short-Term Memory (LSTM) algorithm specialized for time series data prediction among deep learning models was used in consideration of the time series characteristics of SST data. The prediction model predicts the SST near the Korean Peninsula after 1- to 7-days and predicts the high water temperature or low water temperature phenomenon. To evaluate the accuracy of SST prediction, Coefficient of determination (R²), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) indicators were used. The summer (JAS) 1-day prediction result of the prediction model, R²=0.996, RMSE=0.119℃, MAPE=0.352% and the winter (JFM) 1-day prediction result is R²=0.999, RMSE=0.063℃, MAPE=0.646%. Using the predicted SST, the accuracy of abnormal sea surface temperature prediction was evaluated with an F1 Score (F1 Score=0.98 for high water temperature prediction in summer (2021/08/05), F1 Score=1.0 for low water temperature prediction in winter (2021/02/19)). As the prediction period increased, the prediction model showed a tendency to underestimate the SST, which also reduced the accuracy of the abnormal water temperature prediction. Therefore, it is judged that it is necessary to analyze the cause of underestimation of the predictive model in the future and study to improve the prediction accuracy.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• Korean Journal of Culture and Social Issue
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• v.26 no.1
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• pp.25-45
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• 2020

Intentionality judgement in criminal cases is a core area of fact finding that is root of guilty and sentencing judgment on the defendant. However, the third party is not sure the intentionality because it reflects subjective aspect of agent. Thus, mechanism behind intentionality judgment is an important factor to be properly understood by the academia and the criminal justice system. However, previous studies regarding intentionality judgment models have shown inconsistent results. Mental-state models proposed foreseeability(belief) and desire of agent at the time of the offence as key factors in intentionality judgment. These factors consistent with central things on intentionality judgment in criminal law. However, key factors in moral-evaluation models are blameworthiness of agent and badness of outcome reflected on the consequent aspect of act. Recently, deep-self concordance model emerged suggesting important factors on intentionality judgment are not mental states and moral evaluations but individual's deep-self. However, these models are limited in that they do not consider the important features of criminal cases, that the consequence of the case is inevitably negative, and therefore the actor who is a party to legal punishment rarely expresses his or her mental state at the time of the act. Therefore, this study suggests that, based on the existing intentionality judgment studies and the characteristics of the criminal case, the inference about who the agent was originally will play a key role in judging the intentionality in the criminal case. This is the moral-character model. Futhermore, In this regard, this study discussed what the media and criminal justice institutions should keep in mind and the directions for future research.

• Journal of Bio-Environment Control
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• v.31 no.1
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• pp.14-21
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• 2022

Uniform scions and rootstocks should be produced to ensure grafting success. Light quality is an important environmental factor that regulates seedling growth. The effects of warm- and cool-white light emitting diode (LED) ratios on seedling growth were investigated. Scions and rootstocks of cucumber, tomato, and watermelon were grown in a closed transplant production system using LED as the sole lighting source. The LED treatments were W1C0 (only warm-white), W1C1 (warm-white: cool-white = 1:1), W3C1 (warm-white: cool-white = 3:1), and W5C2 (warm-white: cool-white = 5:2). The seedlings grown in W1C1 had the shortest hypocotyls, and the seedlings grown in W1C0 had the longest hypocotyls among the three tested vegetables. The hypocotyls of watermelon scions, watermelon rootstocks, and tomato rootstocks were shortest in W1C1, followed by those in W3C1, W5C2, and W1C0, but there was no significant difference between W3C1 and W5C2, which remained the same as the ratio of cool-white LEDs increased. In addition, tomato scions had the first and second longest hypocotyls in W1C0 and W3C1, respectively, and the shortest hypocotyls in W5C2 and W1C1, along with W5C2 and W1C1, although the difference was not significant. The stem diameter was highest in W1C0 except for tomato seedlings and rootstocks of watermelon. The shoot fresh weight of scions and rootstocks of cucumber and watermelon and the root fresh weight of cucumber scions were lowest in W1C1. These results indicated that different ratios of LED lighting sources had a strong effect on the hypocotyl elongation of seedlings.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.105-117
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• 2022

This study analyzes the effects between stock returns and interest rate spread, difference between long-term and short-term interest rate through the polynomial linear regression analysis. The existing research concentrated on the business forecast through the interest rate spread focusing on the US market. The previous studies verified the interest rate spread based on the leading indicators of business forecast by moderating the period of long-term/short-term interest rates and analyzing the degree of leading. After the 7th reform of composite indices of business indicators in Korea of 2006, the interest rate spread was included in the items of composing the business leading indicators, which is utilized till today. Nevertheless, there are a few research on stock returns of each industry and interest rate spread in domestic stock market. Therefore, this study analyzed the stock returns of each industry and interest rate spread targeting Korean stock market. This study selected the long-term/short-term interest rates with high causality through the regression analysis, and then understood the correlations with each leading period and industry. To overcome the limitation of the simple linear regression analysis, polynomial linear regression analysis is used, which raised explanatory power. As a result, the high causality was verified when using differences between returns of corporate bond(AA-) without guarantee for three years by leading six months and call rate returns as interest rate spread. In addition, analyzing the stock returns of each industry, the relation between the relevant interest rate spread and returns of the automobile industry was the closest. This study is significant in the aspect of verifying the causality of interest rate spread, business forecast, and stock returns in Korea. Even though it could be limited to forecast the stock price by using only the interest rate spread, it would be working as a strong factor when it is properly utilized with other various factors.

• Journal of Christian Education in Korea
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• v.66
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• pp.179-208
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• 2021

Due to COVID-19, the entire world is facing the unprecedented phenomenon. Amid the threat of the virus, the global community is struggling for life. In such circumstances, churches in Korea have been criticised as selfish groups threatening the community by spreading the virus. With such criticism, they are disregarded by Korean society because their immorality and exclusive attitude towards other religions and cultures were also mentioned in public. There are many reasons for Korean churches to lose trust from people. One of the reasons for that is the quantitative growth of church and expansion of the power of church, which is a direction that has been practised so far as a missionary goal. The zeal for spreading gospel has undermined the trust of church and become a deteriorating factor for mission, which is irony. In such problematic situations, the change of paradigm is required for new mission. The passion for evangelisation should not only focus on the quantitative growth of church; it should change its direction for serving the world in lieu with the plan of God for the activity of redemption on this land. A hint of such mission can be found in ecumenical mission. Ecumenical mission is a new paradigm which was discussed in ecumenical movement led mainly by WCC, and its aim is to participate in activities of redemption of God for life in this world. Christian education has been a tool for the expansion of Christian power in the context of traditional mission. Reflecting on the role of Christian education as such, the change of direction as practical movement for the kingdom of God was tried in ecumenical movement: the beginning of the discussion of Christian education based on ecumenical mission. Due to exclusivity, aggressive mission, and the excessive attention to the system of ecclesiastical authority rather than life, Korean churches, which have lost trust in this society, should recover themselves as the model of the kingdom of God, and the establishment of mission education based on ecumenical mission is required for them to become a community towards life. Furthermore, this is an urgent task for Korean churches to implement such mission education in a church community.

• The Korea Journal of Herbology
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• v.27 no.6
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• pp.115-122
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• 2012

Objectives : This study evaluated activities and ingredient contents concerning extracts according to extraction solvents of Insampaedok-san (IS, Renshen bai du-san). Methods : The herbal constituents of IS were extracted with water and 70% ethanol at $100^{\circ}C$ for 2 hr. Using the HPLC system, the six ingredient contents of different solvent extracts of IS were analyzed. The nitric oxide (NO), prostaglandin $E_2$ ($PGE_2$) production and proinflammatory cytokines were measured in RAW264.7 cells stimulated with lipopolysaccharide (LPS). The macrophage-derived chemokine (MDC/CCL22) and regulated on activation normal T-cell expression and secreted (RANTES/CCL5) production were measured in HaCaT and BEAS-2B cells stimulated tumor necrosis factor-${\alpha}$ (TNF-${\alpha}$) and interferon-${\gamma}$ (IFN-${\gamma}$). The activities of glycerol-3-phosphate dehydrogenase (GPDH) and leptin level were measured in 3T3-L1 cells. Results : The calibration curves showed good linearity ($r^2$=1.0000) for different concentration ranges. The contents of liquiritin, naringin, hesperidin, neohesperirin and glycyrrizin in 70% ethanol extracts of IS were relatively higher than that of water extract, however the content of ferulic acid in 70% ethanol and water extract of IS were similar. The extraction solvents of water and 70% ethanol were evaluated inhibitory effect on the production of NO, $PGE_2$, TNF-${\alpha}$ and IL-6 in RAW 264.7 cells. Their extractions were inhibitory effect on production of MDC/CCL22 and RANTES/CCL5 in HaCaT cell and BEAS-2B cell, respectively. In addition, evaluated reduced on GPDH activity and leptin level in 3T3-L1 preadipocyte cell. Conclusions : Our results suggest that IS extracts were inhibitory effects of disease such as inflammation, allergies and obesity.