• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.317-324
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• 2015

GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (T_m), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.

• Journal of Distribution Science
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• v.9 no.3
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• pp.5-14
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• 2011

One of the new roles of modern retail stores is to supply consumers with a memorable experience. In Korea, enhancing a store's environment so that customers remember a unique shopping experience is recognized as a sound strategy for strengthening the store's competitiveness. Motivated by this incentive, awareness of the experience-store concept is starting to increase in various categories of the retail industry. However, many experience stores, except in a few cases, have yet to derive a significant profit, explaining why Korean consumers are somewhat unfamiliar with, yet fascinated by, the experience stores that now exist in the country. Consumer satisfaction directly, and indirectly, affects a company's future profit and potential financial gain; customer satisfaction also affects loyalty. Therefore, knowing the significant factors that increase satisfaction and loyalty is essential for any company, in any field, to be able to effectively differentiate itself from the competition. Intrigued by increased competition opportunities, most Korean companies have adopted experience-store marketing strategies. When establishing the most effective processes for increasing sales and achieving a sustainable competitive advantage of a new concept, companies should consider certain factors that influence consumers' ability to accept new concepts and ideas. The Technology Acceptance Model (TAM) is a theory that models how people accept new concepts. TAM proposes the following two factors that influence a person's decisions about how, and when, he or she will use a new product: "perceived usefulness" and "perceived ease of use." Much of the existing research has suggested that a person's character also affects the process for accepting new ideas. Such personal character attributes as individual preferences, self-confidence, and a person's values, traits, and/or skills affect the process for willingly consenting to try something new. It will be meaningful to establish how the TAM theory's components, as well as personal character, affect individuals accepting the experience-store concept. To that end, as it pertains to an experience store, the first goal of the study is to examine the influence of innovative factors (perceived usefulness and perceived ease of use) on satisfaction and loyalty. The second objective is to define the moderate effect of consumers' personal characteristics on the model. The proposed model was tested on 149 respondents who were engaged in leisure sports activities and bought sports outdoor garments and equipment. According to the study's findings, the satisfaction and loyalty of an experience store can be explained by perceived usefulness and perceived ease of use, with the study's results demonstrating the stronger of the two factors being "perceived ease of use." The study failed to explain the effects of a person's character on the model. In conclusion, when the companies that operate the experience stores execute their marketing and promotion strategies, they should stress the stores' "ease of use" product components. Additionally, it can be extrapolated from the study data that since the experience-store idea is still relatively unfamiliar to Korean consumers, most customers are not yet able to evaluate, nor take a position regarding, their respective attitudes toward experience stores.

• The Journal of Korean Philosophical History
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• no.31
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• pp.87-111
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• 2011

In moral instruction, one of the important purposes is cultivate students' meaningful moral knowing. To obtain this purpose, generally systems approach has been adopted and used in moral instruction. Systems approach has emphasized efficient designs which do not occur incidental learning that does not contribute to obtain learning objectives. However, moral meaning may occur to the subject of knowing, then occurrence of coincidence can not be excluded. If we approach to moral instruction with operative and engineering ways, we may convey the learning object but it won't be received meaningfully. Because of such problem, moral instruction has been required an alternative perspective contrary to the systems approach. Above all we need to reconsider the logic of explanation based on the systems approach. Because the moral instruction is understood that it is a systematic and operative act according to the logic of explanation. According to the logic of explanation, education is an act that conveys the teachers' knowledge to students who have inferior knowledge to teachers'. During this process, students' interpretation has been overlooked. In moral instruction, the teachers' interpretation of moral meaning can occur and extend by students' interpretation. When we understand moral instruction as the course of alliance between interpretation, it could be stood out that teaching as a symbol, constitution of teaching text as a vacuum, learning as a coincidence. When we stand out these aspects, the moral instruction could be understand as a poetic act. And based on such understanding, we can abstract specific resemblances between the poetic act and the moral instruction. There are semantic invariants and semantic variants in the teaching text of moral instruction. The semantic variants premise uncertainty. The limitation, that is, semantic invariants and the openness which is possible within semantic variants are changed to the moral instruction by students' response. It is essential that a selective attention as esthetic transaction that could be changed from text to poet. Like this, we need to take notice of instructive aspects not to means for reaching learning objectives but to act for being possible disinterested experiential learning.

• The Critical Review of Religion and Culture
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• no.31
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• pp.141-172
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• 2017

The objectives of this paper are to investigate hunting, stock raising, sacrifice recorded in the oracle bone inscriptions of Shang Dynasty. I want to raise two basic questions. First, what were the functions of hunting, stock raising, sacrifice, which constructed the world of life in Shang Dynasty? Second, what were the relationships of gods, men, animals derived from them? These questions are brought up to how the commoners of Shang Dynasty build the world and perceive it. I adopted positively prevalent theories for answering those questions. I am particularly provided with Michael J. Puett's insightful remarks in this presentation. He criticizes the previous viewpoint that the relationships of gods and men in ancient China were harmonious and mutually respondent. According to him, in the ancient way of thinking of China the world of gods was full of whimsical and unpredictable power and also contained the risks, which led to disaster to the human world. So it is needed to be controled in a certain way. The sacrifice and the divination must have been instruments for controlling it in ancient China. In the same vein his arguments can be applied to the special connotations of hunting and stock raising, by the benefit of which I developed my own ideas in this paper. The conclusions are as follows. First, Shang dynasty tried to suppress the latent danger of two worlds. The nature represented by animals and the world of gods were respectively considered as the unknown domains, which is to threatening human life. Hunting, stock raising, sacrifice were the ways and means of controlling these two domains of power, which cause chaos in life. Second, the relationships among gods, men, animals had various functions and changed their status role, depending on the circumstances. Hunting and stock raising were important methods to domesticate animals with violence. In this domestication process animals became "victims" but animals are also to be the messengers to gods through being slain in the sacrifice. In this way animals are both inferior and superior to men and hold a unique status between gods and men.

• The Critical Review of Religion and Culture
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• no.31
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• pp.255-287
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• 2017

This paper analyzes the religious circuit of suicidal concept based on verbal expression and ritual acts, which are found in the suicide discourse of Korean Catholic Church and Protestant Church. In the relationship of suicide and religion, it is easily overlooked the religious circuit and its construction that forms the concept of suicide among the religious laymen. It is assumed that the belief system of traditional religions prohibits suicide and the laymen accordingly construct a perception or concept of suicide along with this belief system. Various studies on this subject have proved it. However, in order to understand the religious way of constructing the concept of suicide on a personal level, it is necessary to pay attention to the religious environment in which the concepts and emotions of suicide circulate. The laymen do not passively and perfectly accept the finely established suicide concept provided by the doctrine or the theology. Rather, the laymen tend to collect the pieces of concept over the suicide that are drifting in the religious environment of his/her daily routine life and to make an concept of suicide in an incomplete form. We can find the unstable and imperfect traits of such a suicide concept through the experience of suicide survivors who have a religious background. For the suicide survivors with religious beliefs, they resist the formal doctrinal and theological provisions to suicide, or try to understand the notion of suicide in their own contexts. In terms of linguistic expressions and ritual acts relating to suicide, the attentions are differently directed in the public and the private domain among the religious groups. Considering on the high rates of suicide in Korean society, the Korean Catholic Churches are increasingly tolerant over the suicide and accept it in the public sphere. It is unlikely when comparing to the negative attitudes of the suicide in the past. However, such tolerance does not go beyond the doctrinal and ethical judgment that defines suicide as a serious sin. The once-committed lay believer's speech and gestures usually contain the various emotions, such as sadness, grief, anxiety, regretfulness, eagerness, and pain in the private spheres. The language and gestures with these emotions have been activated in the religious circuits of suicide, being extended to the religious apparatus for the person who died of suicide. In case of Protestantism, the institutional organizations, such as the particular denominations and the individual-churchism of the Korean Protestant Churches, and their own interpretations of the Bible have in the private sphere strongly effected on the linguistic expressions and the rituals related to the suicide. The religious-ethical judgment of the suicide is varied how the suicide is interpreted by the theologians and the pastors. And the ritual acts for healing the complex feelings and the psychological wounds of the suicide survivors are not actively explored and adopted yet. It makes harder to approach and heal the protestant followers since they emphasize the innermost belief and the salvation assurance faith.

• Korean Journal of Heritage: History & Science
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• v.52 no.2
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• pp.292-307
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• 2019

Buddhists have always tended to adorn and embellish Buddhist statues and their surrounding spaces in order to exhibit the grandeur and sublime nature of the Buddha. The various kinds of splendid instruments and implements used in such ornamentation are collectively called jangeomgu in Korean. Thus, the term jangeomgu encompasses articles used to decorate Buddhist statues, halos, and baldachin, as well as Buddhist banners and wind chimes, which are generally hung outside a building. Wind chimes are still widely used at Buddhist temples. In China, judging from various structures such as the Wooden Stupa of Yongningsi in Luoyang and the Dunhuang Caves, wind chimes began to be used around the sixth century. As for Korea, Buddhism was first introduced from China during the Three Kingdoms Period, and Koreans accordingly began to build Buddhist temples and buildings. It would appear that wind chimes came to be used around the time that the first temples were built. The oldest extant wind chime in Korea is the gilt-bronze wind chime of Baekje, discovered at the Mireuksa Temple Site in Iksan. In general, Korean wind chimes dating from the Three Kingdoms Period are classified into two general types according to their shape and elevation, i.e., those shaped like a Buddhist bell and those shaped like a trapezoid. As these two forms of wind chimes have influenced each other over time, those made during the Goryeo dynasty, having inherited the style, structure, and design of the preceding period, display such features. At the same time, the artisans who produced wind chimes pursued technical development and adopted free, yet not extravagant, designs. In particular, Goryeo wind chimes are characterized by original designs created through exchanges with other Buddhist art forms of the same period, such as the embossed lotus design band of Goryeo bells; the bullmun design, which served to display the grandeur of the royal family; the samhwanmun design, which consisted of decorating the interior of a Goryeo incense burner with three holes; Sanskrit designs; and designs inspired by the windows and doors of stone pagodas. In this way, the production of Goryeo wind chimes developed with a focus on purpose while being free of formal constraints. This study started out from the fact that the largest number of Korean wind chimes were produced during the Goryeo dynasty. Therefore, research on wind chimes should be based on those of the Goryeo dynasty, especially since fewer relevant studies have been conducted compared to studies on other forms of Buddhist art. For the purposes of this study, the reasons for the production of wind chimes will be examined first, followed by an examination of the various styles of Korean wind chimes. Then, based on the findings of this investigation, the development and characteristics of the wind chimes produced during the Goryeo dynasty will be explored for each period.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.127-137
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• 2019

Recidivism prediction has been a subject of constant research by experts since the early 1970s. But it has become more important as committed crimes by recidivist steadily increase. Especially, in the 1990s, after the US and Canada adopted the 'Recidivism Risk Assessment Report' as a decisive criterion during trial and parole screening, research on recidivism prediction became more active. And in the same period, empirical studies on 'Recidivism Factors' were started even at Korea. Even though most recidivism prediction studies have so far focused on factors of recidivism or the accuracy of recidivism prediction, it is important to minimize the prediction misclassification cost, because recidivism prediction has an asymmetric error cost structure. In general, the cost of misrecognizing people who do not cause recidivism to cause recidivism is lower than the cost of incorrectly classifying people who would cause recidivism. Because the former increases only the additional monitoring costs, while the latter increases the amount of social, and economic costs. Therefore, in this paper, we propose an XGBoost(eXtream Gradient Boosting; XGB) based recidivism prediction model considering asymmetric error cost. In the first step of the model, XGB, being recognized as high performance ensemble method in the field of data mining, was applied. And the results of XGB were compared with various prediction models such as LOGIT(logistic regression analysis), DT(decision trees), ANN(artificial neural networks), and SVM(support vector machines). In the next step, the threshold is optimized to minimize the total misclassification cost, which is the weighted average of FNE(False Negative Error) and FPE(False Positive Error). To verify the usefulness of the model, the model was applied to a real recidivism prediction dataset. As a result, it was confirmed that the XGB model not only showed better prediction accuracy than other prediction models but also reduced the cost of misclassification most effectively.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.199-230
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• 2021

Innovative new products and services are being launched through the convergence between heterogeneous industries, and social interest and investment in convergence industries such as AI, big data-based future cars, and robots are continuously increasing. However, in the process of commercialization of convergence new products and services, there are many cases where they do not conform to the existing regulatory and legal system, which causes many difficulties in companies launching their products and services into the market. In response to these industrial changes, the current government is promoting the improvement of existing regulatory mechanisms applied to the relevant industry along with the expansion of investment in new industries. This study, in these convergence industry trends, aimed to analysis the existing regulatory system that is an obstacle to market entry of innovative new products and services in order to preemptively predict regulatory issues that will arise in emerging industries. In addition, it was intended to establish a regulatory impact analysis system to evaluate adequacy and prepare improvement measures. The flow of this study is divided into three parts. In the first part, previous studies on regulatory impact analysis and evaluation systems are investigated. This was used as basic data for the development direction of the regulatory impact framework, indicators and items. In the second regulatory impact analysis framework development part, indicators and items are developed based on the previously investigated data, and these are applied to each stage of the framework. In the last part, a case study was presented to solve the regulatory issues faced by actual companies by applying the developed regulatory impact analysis framework. The case study included the autonomous/electric vehicle industry and the Internet of Things (IoT) industry, because it is one of the emerging industries that the Korean government is most interested in recently, and is judged to be most relevant to the realization of an intelligent information society. Specifically, the regulatory impact analysis framework proposed in this study consists of a total of five steps. The first step is to identify the industrial size of the target products and services, related policies, and regulatory issues. In the second stage, regulatory issues are discovered through review of regulatory improvement items for each stage of commercialization (planning, production, commercialization). In the next step, factors related to regulatory compliance costs are derived and costs incurred for existing regulatory compliance are calculated. In the fourth stage, an alternative is prepared by gathering opinions of the relevant industry and experts in the field, and the necessity, validity, and adequacy of the alternative are reviewed. Finally, in the final stage, the adopted alternatives are formulated so that they can be applied to the legislation, and the alternatives are reviewed by legal experts. The implications of this study are summarized as follows. From a theoretical point of view, it is meaningful in that it clearly presents a series of procedures for regulatory impact analysis as a framework. Although previous studies mainly discussed the importance and necessity of regulatory impact analysis, this study presented a systematic framework in consideration of the various factors required for regulatory impact analysis suggested by prior studies. From a practical point of view, this study has significance in that it was applied to actual regulatory issues based on the regulatory impact analysis framework proposed above. The results of this study show that proposals related to regulatory issues were submitted to government departments and finally the current law was revised, suggesting that the framework proposed in this study can be an effective way to resolve regulatory issues. It is expected that the regulatory impact analysis framework proposed in this study will be a meaningful guideline for technology policy researchers and policy makers in the future.