• (The)Study of the Eastern Classic
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• no.32
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• pp.103-128
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• 2008

King Jeongjo had lost his father, Sado-Seja(Prince Sado) by Noron(Older Faction). Especially those who tried to kill Sado-Seja and king Jeongjo consisted of king's family-in-law of king Youngjo and Sado-Seja. Therefore king Jeongjo's first goal was to strengthen his kingship than other things because he could gain the throne overcoming the strong hinderance of Noron and king's family-in-law. King Jeongjo requested his subjects to be "Kukbyon-In"(國邊人: a person for king) pointing out the harm of the king's family-in-law and "Tangpyong-Dang"(蕩平黨: the strongest faction consisted under the rule of king Youngjo). For the purpose, king Jeongjo built up "Gyujang-Gak". Gyujang-Gak was spoken to contain and protect the writings of earlier kings superficially, but in reality, it was an apparatus to gain and train the friendly subjects for king Jeongjo. Like that, it was the most important for king Jeongjo to suppress the king's family-in-low and to win Neo-Confucian lterati over to himself's side. Until now, the politics of Joseon Dynasty had been mainly explained on the point of view of "Seonghak-Non"(聖學論). "Seonghak-Non" means that Neo-Confucian lterati were treated as real hero, not kings in the political space of Joseon Dynasty and the role of factions were recognized important. But king Jeongjo denied these ideological stream and tried to change that political system. King Jeongjo wanted to strengthen the throne through the method which insisted the king as a hero in politics. For the purpose, king Jeongjo criticized the Neo-Confucian literati's viewpoint about politics and learning at that time and anticipated to be sole leader of politics and learning on that critique. King Jeongjo aimed to destroy the dignity of "Salim"(山林: Neo-Confucian Sages) with attacking their wrong behaviors. King Jeongjo also criticized the period of king Injo when the regime of "Sarim"(士林: pure Neo-Confucian lterati) faction fully appeared as the starting period when the factional harms were getting worse. King Jeongjo wanted to previously block the oppositions to win subjects over to himself's side with criticizing the period of king Injo and to take away the initiative from his opponents with insisting "Salim-Muyongnon"(山林無用論: a theory ignoring Neo-Confucian Sages). King Jeongjo's critique was not limited just on the system of factional politics. "Seonghak-Non" eventually took root in Neo-Confucianism. Therefore king Jeongjo criticized Neo-Confucianism. He insisted that the essence of Chinese Classics was pragmatical learning, not Neo-Confucianism. Through that critique, king Jeongjo aimed to destroy the ideological base of his opponents. However, king Jeongjo failed to be a sole leader of his subjects in the both boundaries of politics and learning even though he criticized the Neo-Confucian lterati's viewpoint about politics and learning. Because he abruptly died leaving his reformational scheme behind as well as his loyal subjects guarding himself against Noron Byeok-Pa(老論 ?派: the opposing party in Older Faction) were gone behind himself. The politics of Joseon Dynasty returned to more powerful politics for king's family-in-law after king Jeongjo's death.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Journal of the Korean Society of Earth Science Education
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• v.16 no.2
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• pp.247-260
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• 2023

In this study, when applying the 'geological structure' content element of high school earth science I developed according to the 2015 curriculum to the STEAM program using a web-based expert system using 3D data of Google Earth and drones, the creative problem-solving ability of high school students, attitudes toward STEAM, and the results of this study are as follows. First, after applying the STEAM program, high school students' creative problem-solving ability showed meaningful results at the p<.001 level. Second, STEAM attitudes showed a significant value at the p<.001 level, confirming that they had a positive impact on high school students' attitudes towards STEAM. It was judged that web-based class activities using Google Earth and drones were useful for integrated thinking such as learners' sense of efficacy and value recognition for usefulness of knowledge. High school students' satisfaction with the STEAM program was 3.251, showing a slightly high average. It was confirmed that web-based class activities such as drones and Google Earth had a positive impact on learners' class satisfaction. However, it was interpreted that the lack of time for class activities limited the ability of the learners to increase their interest in class. The proposal of this research is as follows. First of all, in consideration of the production of presentation materials and practical training in the STEAM program, activities such as block time and advance instruction for class understanding before class are necessary. Secondly, in order to revitalize STEAM education in the high school curriculum, we judge that research on the development of various integrated education programs that can be applied to the high school grade system is necessary.

• The Journal of Korean Medicine
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• v.44 no.1
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• pp.65-75
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• 2023

Objectives: Objectives: In this study, we define a medical service type that combines Western medicine, Korean medicine, and complementary and alternative medicine (CAM) as an integrated medical service. This study, as part of tertiary hospital-based integrated medical service model and clinical field application, aims to collect status and opinions on integrated medical service for medical staff in the field. Methods: This is a survey study, and was conducted on doctors from Kyung Hee University Hospital and Korean medicine doctors from Kyung Hee University Korean Medicine Hospital. Respondents were recruited on a first-come, first-served basis until the number of respondents reached 120. The investigation was conducted for a total of 16 days from October 4, 2021 to October 19, 2021 by e-mail. Results: Recognition of integrated medical services was confirmed to be 45.8%, and 49.2% responded positively to the necessity of it. As a group of diseases that require the establishment of integrated medical services in the future, 'disorders of musculoskeletal systems and connective tissues' was the highest. The most expected advantages of providing integrated medical services were 'increased satisfaction of patients and guardians' and 'increased treatment effects.' Conclusions: In this study, we investigated the perception of doctors and Korean medicine doctors on integrated medical services that combine Western medicine, Korean medicine, and CAM. It has been confirmed that medical staff generally have a positive perception of integrated medical services, and if the scientific basis for the effect of integrated medical services is supported, the rate of positive perception is expected to increase.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.287-310
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• 2022

Companies' interest in developing AI-based intelligent new products is increasing. Recently, the main concern of companies is to innovate customer experience and create new values by developing new products through the effective use of Artificial intelligence technology. However, due to the nature of products based on radical technologies such as artificial intelligence, intelligent products differ from existing products and development methods, so it is clear that there is a limitation to applying the existing development methodology as it is. This study proposes a new research method based on KANO-TOPSIS for the successful development of AI-based intelligent new products by using car voice assistants as an example. Using the KANO model, select and evaluate functions that customers think are necessary for new products, and use the TOPSIS method to derives priorities by finding the importance of functions that customers need. For the analysis, major categories such as vehicle condition check and function control elements, driving-related elements, characteristics of voice assistant itself, infotainment elements, and daily life support elements were selected and customer demand attributes were subdivided. As a result of the analysis, high recognition accuracy should be considered as a top priority in the development of car voice assistants. Infotainment elements that provide customized content based on driver's biometric information and usage habits showed lower priorities than expected, while functions related to driver safety such as vehicle condition notification, driving assistance, and security, also showed as the functions that should be developed preferentially. This study is meaningful in that it presented a new product development methodology suitable for the characteristics of AI-based intelligent new products with innovative characteristics through an excellent model combining KANO and TOPSIS.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.6
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• pp.13-24
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• 2022

The purpose of this study is to examine whether the existence of related personnel in KOSDAQ technology special listed firms has a signal effect on the market and affects performance when listed. The KOSDAQ technology special listing system is a system introduced to enable future growth by securing financing through corporate public offering based on the technology and marketability of technology-based startups and venture companies. As a result of analyzing 135 special technology companies listed from 2005 to 21 (excluding SPAC mergers and foreign companies) whether or not related personnel affect corporate value and listing period when they are listed, it was analyzed that the presence of related personnel did not significantly affect corporate value or listing period. The same was found in the results of the verification by reducing the scope to related personnel such as public officials and related agencies. However, under certain conditions, significant results were derived from the presence of related personnel on the listing of companies listed in special technology cases. It was found that the presence of related personnel and VC investment had a significant effect on corporate value, and in the case of bio-industry, there was a slight significant effect on the duration of listing. This study is significant in that it systematically analyzed the signal effect of the existence of related personnel for the first time for all 135 companies. In addition, as a result of the analysis, the results suggest that internalized efforts to secure technology and marketability are more important, such as parallel to VC investment, rather than simply recruiting related personnel.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.1-10
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• 2013

RFID(Radio Frequency Identification) system is non-contact identification technology. A basic RFID system consists of a reader, and a set of tags. RFID tags can be divided into active and passive tags. Active tags with power source allows their own operation execution and passive tags are small and low-cost. So passive tags are more suitable for distribution industry than active tags. A reader processes the information receiving from tags. RFID system achieves a fast identification of multiple tags using radio frequency. RFID systems has been applied into a variety of fields such as distribution, logistics, transportation, inventory management, access control, finance and etc. To encourage the introduction of RFID systems, several problems (price, size, power consumption, security) should be resolved. In this paper, we proposed an algorithm to significantly alleviate the collision problem caused by simultaneous responses of multiple tags. In the RFID systems, in anti-collision schemes, there are three methods: probabilistic, deterministic, and hybrid. In this paper, we introduce ALOHA-based protocol as a probabilistic method, and Tree-based protocol as a deterministic one. In Aloha-based protocols, time is divided into multiple slots. Tags randomly select their own IDs and transmit it. But Aloha-based protocol cannot guarantee that all tags are identified because they are probabilistic methods. In contrast, Tree-based protocols guarantee that a reader identifies all tags within the transmission range of the reader. In Tree-based protocols, a reader sends a query, and tags respond it with their own IDs. When a reader sends a query and two or more tags respond, a collision occurs. Then the reader makes and sends a new query. Frequent collisions make the identification performance degrade. Therefore, to identify tags quickly, it is necessary to reduce collisions efficiently. Each RFID tag has an ID of 96bit EPC(Electronic Product Code). The tags in a company or manufacturer have similar tag IDs with the same prefix. Unnecessary collisions occur while identifying multiple tags using Query Tree protocol. It results in growth of query-responses and idle time, which the identification time significantly increases. To solve this problem, Collision Tree protocol and M-ary Query Tree protocol have been proposed. However, in Collision Tree protocol and Query Tree protocol, only one bit is identified during one query-response. And, when similar tag IDs exist, M-ary Query Tree Protocol generates unnecessary query-responses. In this paper, we propose Adaptive M-ary Query Tree protocol that improves the identification performance using m-bit recognition, collision information of tag IDs, and prediction technique. We compare our proposed scheme with other Tree-based protocols under the same conditions. We show that our proposed scheme outperforms others in terms of identification time and identification efficiency.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.233-243
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• 2008

Recognition for the importance and roles of public transportation is increasing because of traffic problems in many cities. In spite of this paradigm change, previous researches related with public transportation trip assignment have limits in some aspects. Especially, in case of multimodal public transportation networks, many characters should be considered such as transfers. operational time schedules, waiting time and travel cost. After metropolitan integrated transfer discount system was carried out, transfer trips are increasing among traffic modes and this takes the variation of users' route choices. Moreover, the advent of high-technology public transportation card called smart card, public transportation users' travel information can be recorded automatically and this gives many researchers new analytical methodology for multimodal public transportation networks. In this paper, it is suggested that the methodology for establishment of brand new multimodal public transportation networks based on computer programming methods using transportation card data. First, we propose the building method of integrated transportation networks based on bus and urban railroad stations in order to make full use of travel information from transportation card data. Second, it is offered how to connect the broken transfer links by computer-based programming techniques. This is very helpful to solve the transfer problems that existing transportation networks have. Lastly, we give the methodology for users' paths finding and network establishment among multi-modes in multimodal public transportation networks. By using proposed methodology in this research, it becomes easy to build multimodal public transportation networks with existing bus and urban railroad station coordinates. Also, without extra works including transfer links connection, it is possible to make large-scaled multimodal public transportation networks. In the end, this study can contribute to solve users' paths finding problem among multi-modes which is regarded as an unsolved issue in existing transportation networks.

• Korean journal of food and cookery science
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• v.17 no.6
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• pp.542-548
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• 2001

Hazard Analysis Critical Control Point(HACCP) is becoming an important component of food safety worldwide. The aim of this study was to investigate comprehensively the education and knowledge level of food service managers on HACCP as well as applying HACCP system to industrial foodservice. Total 247 foodservice managers participated in the survey and 159 responses were used for analysis. The results were as follows: 1) 89% of foodservice managers were educated about HACCP, and 40.9% felt they did fully understand HACCP and 47.8% did half. 2) The score for the implementation of HACCP was in the order of apparatus and facility sanitation, personal sanitation, and time-temperature/etc. sanitation. 3) Foodservice managers who were taught HACCP kept a deep attention to food and personal sanitation, compared with those without education(p＜0.05). However, the education time on HACCP affected conducting safety management. The results suggest that education and understanding of HACCP are positively related, and understanding of HACCP has a positive influence on conducting safety management.