• Journal of dental hygiene science
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• v.17 no.6
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• pp.543-551
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• 2017

The purpose of this study is to analyze the experience of the parents who examined the first infant oral examination and to understand how to improve the practical oral examination business. In-depth interviews were held with 10 parents who did the first infant oral examination, and their children's age was less than 18 to 29 months. The following conclusions were obtained by deriving the concepts and categories of the recorded contents. First, the main reason for the unsatisfactory examination of this study was that it was formal. Parents were disappointed in the fact that they did not look at the mouth of the child at the same time as it was fast and they said because it is carried out free of charge, it is more formal than the examination for general dental treatment. Second, most of the participants questioned whether they should resume infant oral examination. Third, it appears that the tooth number or dental terminology in the result notice is difficult to understand. Fourth, the opinion on the improvement of the infant oral examinations was should provided that the oral health management information after examination and the direct oral health management method education at the examination. In addition, we identified the need for parents' oral health care education for infants. Therefore, it has been confirmed that in order for the infant oral examination and young children to be practically carried out, the problems should be improved by collecting opinions of the parents. Also it is necessary to search for efficient business management method through repeated research related to infant oral examination.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.3
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• pp.125-146
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• 2013

Nowadays, the performance of the mobile game sales is influencing the ranking of game companies listed on KOSDAQ. In the meantime, venture capital companies had focused on online game. Recently, however, they have great interest in mobile games and mobile game companies. In addition, angel investors and accelerators are increasing investment for the mobile game companies. The most important issues for mobile game investor is how to evaluate the mobile game companies and their contents. Therefore, this study derived the evaluation factors for the mobile game company. And research method converged of the opinions of both supply side and demand side of the game industry. Ten professionals who are responsible for the supply of the game industry and CEO group & development experts of game development company were selected for survey in this study. Also ten professionals who are responsible for the demand of the game industry and the investment company were selected for survey in this study. And Delphi technique was performed according to the survey. Management skills, development capabilities, game play, feasibility, operational capabilities has emerged as five evaluation factors to evaluate the mobile game company. And the 20 sub-factors including CEO's reliability were derived. AHP(Analytic Hierarchy Process) theory is applied to analyze the importance of the qualitative elements which were derived by Delphi technique. As a result, the analysis hierarchy of evaluation factors for the mobile game company was created. Pair-wise comparison for each element was performed to analyze the importance. As a result, 'Core fun of the game' (12,2%), 'Involvement of the game' (10.3%), 'Security Reliability' (8.9%), 'Core developers' ability' (7.6%) appeared in order of importance. The significance of this study is offering more objective methodology for realistic assessment and importance of elements to evaluate mobile game company.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.101-116
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• 2015

Recently, due to the development of smart devices and social media, vast amounts of information with the various forms were accumulated. Particularly, considerable research efforts are being directed towards analyzing unstructured big data to resolve various social problems. Accordingly, focus of data-driven decision-making is being moved from structured data analysis to unstructured one. Also, in the field of recommendation system, which is the typical area of data-driven decision-making, the need of using unstructured data has been steadily increased to improve system performance. Approaches to improve the performance of recommendation systems can be found in two aspects- improving algorithms and acquiring useful data with high quality. Traditionally, most efforts to improve the performance of recommendation system were made by the former approach, while the latter approach has not attracted much attention relatively. In this sense, efforts to utilize unstructured data from variable sources are very timely and necessary. Particularly, as the interests of users are directly connected with their needs, identifying the interests of the user through unstructured big data analysis can be a crew for improving performance of recommendation systems. In this sense, this study proposes the methodology of improving recommendation system by measuring interests of the user. Specially, this study proposes the method to quantify interests of the user by analyzing user's internet usage patterns, and to predict user's repurchase based upon the discovered preferences. There are two important modules in this study. The first module predicts repurchase probability of each category through analyzing users' purchase history. We include the first module to our research scope for comparing the accuracy of traditional purchase-based prediction model to our new model presented in the second module. This procedure extracts purchase history of users. The core part of our methodology is in the second module. This module extracts users' interests by analyzing news articles the users have read. The second module constructs a correspondence matrix between topics and news articles by performing topic modeling on real world news articles. And then, the module analyzes users' news access patterns and then constructs a correspondence matrix between articles and users. After that, by merging the results of the previous processes in the second module, we can obtain a correspondence matrix between users and topics. This matrix describes users' interests in a structured manner. Finally, by using the matrix, the second module builds a model for predicting repurchase probability of each category. In this paper, we also provide experimental results of our performance evaluation. The outline of data used our experiments is as follows. We acquired web transaction data of 5,000 panels from a company that is specialized to analyzing ranks of internet sites. At first we extracted 15,000 URLs of news articles published from July 2012 to June 2013 from the original data and we crawled main contents of the news articles. After that we selected 2,615 users who have read at least one of the extracted news articles. Among the 2,615 users, we discovered that the number of target users who purchase at least one items from our target shopping mall 'G' is 359. In the experiments, we analyzed purchase history and news access records of the 359 internet users. From the performance evaluation, we found that our prediction model using both users' interests and purchase history outperforms a prediction model using only users' purchase history from a view point of misclassification ratio. In detail, our model outperformed the traditional one in appliance, beauty, computer, culture, digital, fashion, and sports categories when artificial neural network based models were used. Similarly, our model outperformed the traditional one in beauty, computer, digital, fashion, food, and furniture categories when decision tree based models were used although the improvement is very small.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.61-83
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• 2012

A knowledge map describes the network of related knowledge into the form of a diagram, and therefore underpins the structure of knowledge categorizing and archiving by defining the relationship of the referential navigation between knowledge. The referential navigation between knowledge means the relationship of cross-referencing exhibited when a piece of knowledge is utilized by a user. To understand the contents of the knowledge, a user usually requires additionally information or knowledge related with each other in the relation of cause and effect. This relation can be expanded as the effective connection between knowledge increases, and finally forms the network of knowledge. A network display of knowledge using nodes and links to arrange and to represent the relationship between concepts can provide a more complex knowledge structure than a hierarchical display. Moreover, it can facilitate a user to infer through the links shown on the network. For this reason, building a knowledge map based on the ontology technology has been emphasized to formally as well as objectively describe the knowledge and its relationships. As the necessity to build a knowledge map based on the structure of the ontology has been emphasized, not a few researches have been proposed to fulfill the needs. However, most of those researches to apply the ontology to build the knowledge map just focused on formally expressing knowledge and its relationships with other knowledge to promote the possibility of knowledge reuse. Although many types of knowledge maps based on the structure of the ontology were proposed, no researches have tried to design and implement the referential navigation-enabled knowledge map. This paper addresses a methodology to build the ontology-based knowledge map enabling the referential navigation between knowledge. The ontology-based knowledge map resulted from the proposed methodology can not only express the referential navigation between knowledge but also infer additional relationships among knowledge based on the referential relationships. The most highlighted benefits that can be delivered by applying the ontology technology to the knowledge map include; formal expression about knowledge and its relationships with others, automatic identification of the knowledge network based on the function of self-inference on the referential relationships, and automatic expansion of the knowledge-base designed to categorize and store knowledge according to the network between knowledge. To enable the referential navigation between knowledge included in the knowledge map, and therefore to form the knowledge map in the format of a network, the ontology must describe knowledge according to the relation with the process and task. A process is composed of component tasks, while a task is activated after any required knowledge is inputted. Since the relation of cause and effect between knowledge can be inherently determined by the sequence of tasks, the referential relationship between knowledge can be circuitously implemented if the knowledge is modeled to be one of input or output of each task. To describe the knowledge with respect to related process and task, the Protege-OWL, an editor that enables users to build ontologies for the Semantic Web, is used. An OWL ontology-based knowledge map includes descriptions of classes (process, task, and knowledge), properties (relationships between process and task, task and knowledge), and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. Therefore a knowledge network can be automatically formulated based on the defined relationships, and the referential navigation between knowledge is enabled. To verify the validity of the proposed concepts, two real business process-oriented knowledge maps are exemplified: the knowledge map of the process of 'Business Trip Application' and 'Purchase Management'. By applying the 'DL-Query' provided by the Protege-OWL as a plug-in module, the performance of the implemented ontology-based knowledge map has been examined. Two kinds of queries to check whether the knowledge is networked with respect to the referential relations as well as the ontology-based knowledge network can infer further facts that are not literally described were tested. The test results show that not only the referential navigation between knowledge has been correctly realized, but also the additional inference has been accurately performed.

• The Korean Society of Law and Medicine
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• v.21 no.2
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• pp.75-103
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• 2020

There is a growing voice that medical information should be shared because it can prepare for genetic diseases or cancer by analyzing and utilizing medical information in big data or artificial intelligence to develop medical technology and improve patient care. The utilization and protection of patients' personal information are the same as two sides of the same coin. Medical institutions or medical personnel should take extra caution in handling personal information with high environmental distinct characteristics and sensitivity, which is different from general information processors. In general, the patient's personal information is processed by medical personnel or medical institutions through the processes of collection, creation, and destruction. Still, the use of terms related to personal information in the Medical Service Act is jumbled, or the scope of application is unclear, so it relies on the interpretation of precedents. For the medical personnel or the founder of the medical institution, in the case of infringement of Article 24(4), it cannot be regarded that it means only medical treatment information among personal information, whether or not it should be treated the same as the personal information under Article 23, because the sensitive information of patients is recorded, saved, and stored in electronic medical records. Although the prohibition of information leakage under Article 19 of the Medical Service Act has a revision; 'secret' that was learned in business was revised to 'information', but only the name was changed, and the benefit and protection of the law is the same as the 'secret' of the criminal law, such that the patient's right to self-determination of personal information is not protected. The Privacy Law and the Local Health Act consider the benefit and protection of the law in 'information learned in business' as the right to self-determination of personal information and stipulate the same penalties for personal information infringement such as leakage, forgery, alteration, and damage. The privacy regulations of the Medical Service Act require that the terms be adjusted uniformly because the jumbled use of terms can confuse information subjects, information processors, and shows certain limitations on the protection of personal information because the contents or scope of the regulations of the Medical Service Law for special corporations and the Privacy Law may cause confusion in interpretation. The patient's personal information is sensitive and must be safely protected in its use and processing. Personal information must be processed in accordance with the protection principle of Privacy Law, and the rights such as privacy, freedom, personal rights, and the right to self-determination of personal information of patients or guardians, the information subject, must be guaranteed.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.99-122
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• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.2
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• pp.151-163
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• 2019

In recent years, as the population of ear and aged villages has increased, the problem of conflict between rural residents and urban-to-rural migrants has been widespread. For successful rural community, such conflict resolution is more important than anything else. However, if we look at previous studies. It is true that there are many studies that focus on people who are not rural residents or urban-to-rural migrants. This study was conducted to find out the difference of strategies for conflict resolution between rural residents and urban-to-rural migrants. This study derives the factors of conflict based on the contents of previous studies, To see the difference, five strategies were used from the response strategies that were used in the 'Computer Prisoner's Dilemma Contest' held by Axelrod (2009). I would like to know what kind of strategies of rural residents and urban-to-rural migrants. All analyzes were done using SPSS 22.0 for Windows, and the results of each conflict resolution analysis showed that the indigenous conflicts were low All. Among the causes of conflict, the highest level of conflict was caused by the 'rural residents who did not understand urban culture'. The strategy is the most used, followed by tit for tat Strategy, and all-c strategy, in that order. However, It is not uncommon for employers to use a work-type strategy, and it can be seen that the strategy changes depending on the cause. As can be seen from the above results, The conflict resolution strategies are almost similar strategies. It can be seen that conflict resolution strategy is used differently according to personality. The purpose of this study is to investigate the differences in conflicts in the rural areas. In particular, it is meaningful to examine the choice of solution strategies based on game theory through reviewing prior research and eliciting actual conflict factors in the field. Successful rural settlement can be achieved not through stakeholder competition but through mutual cooperation by gaining cooperation to the other side. Mutual cooperation is more profitable than betrayal in various conflict situations. The secret to maintaining and communicating smoothly is not to use the other person to fill his or her selfish interests, but to reject it for profit, but to draw cooperation from the other party.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.91-121
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• 2008

Electronic commerce, commonly known as e-commerce or eCommerce, has become a major business trend in these days. The amount of trade conducted electronically has grown extraordinarily by developing the Internet technology. Most electronic commerce has being conducted between businesses to customers; therefore, the researches with respect to e-commerce are to find customer's needs, behaviors through statistical methods. However, the statistical researches, mostly based on a questionnaire, are the static researches, They can tell us the dynamic relationships between initial purchasing and repurchasing. Therefore, this study proposes dynamic research model for analyzing the cause of initial purchasing and repurchasing. This paper is based on the System-Dynamic theory, using the powerful simulation model with some restriction, The restrictions are based on the theory TAM(Technology Acceptance Model), PAM, and TPB(Theory of Planned Behavior). This article investigates not only the customer's purchasing and repurchasing behavior by passing of time but also the interactive effects to one another. This research model has six scenarios and three steps for analyzing customer behaviors. The first step is the research of purchasing situations. The second step is the research of repurchasing situations. Finally, the third step is to study the relationship between initial purchasing and repurchasing. The purpose of six scenarios is to find the customer's purchasing patterns according to the environmental changes. We set six variables in these scenarios by (1) changing the number of products; (2) changing the number of contents in on-line shopping malls; (3) having multimedia files or not in the shopping mall web sites; (4) grading on-line communities; (5) changing the qualities of products; (6) changing the customer's degree of confidence on products. First three variables are applied to study customer's purchasing behavior, and the other variables are applied to repurchasing behavior study. Through the simulation study, this paper presents some inter-relational result about customer purchasing behaviors, For example, Active community actions are not the increasing factor of purchasing but the increasing factor of word of mouth effect, Additionally. The higher products' quality, the more word of mouth effects increase. The number of products and contents on the web sites have same influence on people's buying behaviors. All simulation methods in this paper is not only display the result of each scenario but also find how to affect each other. Hence, electronic commerce firm can make more realistic marketing strategy about consumer behavior through this dynamic simulation research. Moreover, dynamic analysis method can predict the results which help the decision of marketing strategy by using the time-line graph. Consequently, this dynamic simulation analysis could be a useful research model to make firm's competitive advantage. However, this simulation model needs more further study. With respect to reality, this simulation model has some limitations. There are some missing factors which affect customer's buying behaviors in this model. The first missing factor is the customer's degree of recognition of brands. The second factor is the degree of customer satisfaction. The third factor is the power of word of mouth in the specific region. Generally, word of mouth affects significantly on a region's culture, even people's buying behaviors. The last missing factor is the user interface environment in the internet or other on-line shopping tools. In order to get more realistic result, these factors might be essential matters to make better research in the future studies.

• Economic and Environmental Geology
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• v.47 no.4
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• pp.363-379
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• 2014

The Haenam Pb-Zn skarn deposit is located at the Hwawon peninsula in the southwestern part of the Ogcheon Metamorphic Belt. The deposit is developed along the contact between limestone of the Ogcheon group and Cretaceous quartz porphyry. Petrography of ore samples, chemical composition of skarn and ore minerals, and geochemistry of the related igneous rocks were investigated to understand the characteristics of the skarn mineralization. Skarn zonation consists of garnet${\pm}$pyroxene${\pm}$calcite${\pm}$quartz zone, pyroxene+garnet+quartz${\pm}$calcite zone, calcite+pyroxene${\pm}$garnet zone, quartz+calcite${\pm}$pyroxene zone, and calcite${\pm}$chlorite zone in succession toward carbonate rock. Garnet commonly shows zonal texture comprised of andradite and grossular. Pyroxene varies from Mn-hedenbergite to diopside as away from the intrusive rock. Chalcopyrite occurs as major ore mineral near the intrusive rock, and sphalerite and galena tend to increase as going away. Electron probe microanalyses revealed that FeS contents of sphalerite become decreased from 5.17 mole % for garnet${\pm}$pyroxene${\pm}$calcite${\pm}$quartz zone to 2.93 mole %, and to 0.40 mole % for calcite+pyroxene${\pm}$garnet zone, gradually. Ag and Bi contents also decreased from 0.72 wt.% and 1.62 wt.% to <0.01 wt.% and 0.11 wt.%, respectively. Thus, the Haenam deposit shows systematic variation of species and chemical compositions of ore minerals with skarn zoned texture. The related intrusive rock, quartz porphyry, expresses more differentiated characteristics than Zn-skarn deposit of Meinert(1995), and has relatively high$SiO_2$ concentration of 72.76~75.38 wt.% and shows geochemical features classified as calc-alkaline, peraluminous igneous rock and volcanic arc tectonic setting.

• Economic and Environmental Geology
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• v.51 no.4
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• pp.345-358
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• 2018

In this study, we have performed electron probe micro analyzer (EPMA), X-ray differaction (XRD), inductively coupled plasma spectroscopy (ICP), Fourier transform Raman spectroscopy (FT-Raman), far-infrared (FIR), nuclear magnetic resonance (NMR), and pH-DO Analyses for characterizing medicinal mineralogy aspect of the black tourmaline (Shantung, china), black and pink tourmaline (Minas Geraris, Brazil), black touemaline (Daeyu mine, Korea). In addition, heating effects of the tourmaline sauna as well as the effects of tourmaline powder-added soap on skin troubles have been investigated. It has been revealed that chemical composition of the tourmaline is either high in Fe-, Al-, B-rich types. Ratio of the K-Ca, Na-K, and Fe-B reflects the component change property of solid solution. $CaO/CaO+Na_2O$ and MgO/FeO+MgO ratio show high positive correlation. When tourmaline reacts with distilled water, extended reaction time DO values approximately decrease and it stabilizes at DO = 10. Otherwise, pH values increase until 6 hours and it stabilizes at pH = 8 after 24 hours. Distilled water changes to alkaline when it reacts with tourmaline powder and particles. Tourmaline showed lower absorption spectrum strength and transmittance at short wave, where absorption spectrum wavelength and strength were determined by the content of the composition elements and characteristics of crystallography. Increase of the Fe content has been confirmed to be the cause for the reduction of irradiation. For the chemical composition and spectral property of the tourmaline particle samples, it has been found that Si and Fe contents show positive correlation with Far-Infrared irradiation, while Al and Mg contents show negative correlation. For tourmaline powder, it has been confirmed that $^{17}O-NMR$ FWHM (full width at half maximum) decreases when reacts with distilled water. Tourmaline sauna (approximately $100^{\circ}C$) was found to increase $0.5-1.5^{\circ}C$ of body temperature, average of 12 heartbeat, and 10mg Hg of blood pressure. Tourmaline soap had very good aesthetic effect to skin and was confirmed to have above the average improvements to skin troubles (e.g., allergy or atopy).