• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.117-140
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• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.

• Korean Journal of Heritage: History & Science
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• v.49 no.3
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• pp.32-51
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• 2016

This study examines, based on the database of the Institute for the Translation of Korean Classics(ITKC), the garden plants and their symbolism, and the landscape culture recorded in 'Jipkyungjaeyoungsi(the Series of Poems on Gardens Poetry)' in relevance to traditional houses. First, Jipkyungjaeyoungsi had been continuously written since mid-Goryeo dynasty, when it was first brought in, until the late Joseon dynasty. It was mainly enjoyed by the upper class who chose the path of civil servants. 33 pieces of Jaeyoungsi(題詠詩) in 25 books out of a total of 165 books are related to residential gardens. The first person who wrote a poem in relation to this is believed to be Lee GyuBo(1168~1241) in the late Goryeo dynasty. He is believed to be the first person to contribute to the expansion of natural materials and the variation of entertainment in landscape culture with such books as 'Toesikjaepalyoung(退食齋八詠)', 'Gabeunjeungyukyoung(家盆中六詠)'and 'Gapoyukyoung(家圃六詠)'. Second, most of the poems used the names of the guesthouses. Out of the 33 sections, 19(57.5%) used 8 yeong(詠), then it was in the sequence of 4 yeong(詠), 6 yeong, 10 yeong, 14 yeong, 15 yeong, 16 yeong, 36 yeong(詠) and so on. In the poem writing, it appears to break the patterns of Sosangpalkyung(瀟湘八景) type of writings and is differentiated by (1) focusing on the independent title of the scenery, (2) combining the names of the place and landscape, (3) focusing on the name of the landscape. Third, the subtitles were derived from (1) mostly natural landscape focused on nature and garden plants(22 sections, 66.7%), (2) cultural landscape focused on landscape facilities such as guesthouses, ponds and pavilions(3 sections), (3) complex cultural scenery focused on the activities of people in nature(8 sections). Residents enjoy not only their aesthetic preferences and actual view, but the ideation of the scenery. Especially, they display attachment to and preference for vegetables and herbs, which had been neglected. Fourth, the percentage of deciduous tree population(17 species) rated higher(80.9%) compared to the evergreens(4 species). These aspects are similar results with the listed rate in 'Imwonkyungjaeji(林園經濟志)' by Seo YuGu [evergreen 18 species(21.2%) and deciduous trees 67 species(78.8%)] and precedent researches [Byun WooHyuk(1976), Jung DongOh(1977), Lee Sun(2006)]. Fifth, the frequency of the occurrence of garden plants were plum blossoms(14 times), bamboos(14 times), pine trees(11 times), lotus(11 times), chrysanthemum(10 times), willows(5 times), pomegranates(4 times), maple trees(14 times), royal foxglove trees, common crapemyrtle, chestnut trees, peony, plantains, reeds and a cockscombs(2 times). Thus, the frequency were higher with symbolic plants in relations to (1) Confucian norms(pine trees, oriental arbor vitae, plum blossoms, chrysanthemums, bamboos and lotus), (2) living philosophy of sustain-ability(chrysanthemum, willow), (3) the ideology of seclusion and seeking peace of mind(royal foxglove ree, bamboo). Sixth, it was possible to trace plants in the courtyard and outer garden, vegetable and herb garden. Many symbolic plants were introduced in the courtyard, and it became cultural landscape beyond aesthetic taste. In the vegetable and herb garden, vegetables, fruits and medicinal plants are apparently introduced for epigenetic use. The plants that were displayed to be observed and enjoyed were the sweet flag, pomegranate, daphne odora, chrysanthemum, bamboo, lotus and plum blossom. Seventh, it was possible to understand garden culture related to landscaping materials through poetic words such as pavilions, ponds, stream, flower pot, oddly shaped stones, backyard, orchard, herb garden, flower bed, chrysanthemum fence, boating, fishing, passing the glass around, feet bathing, flower blossom, forest of apricot trees, peach blossoms, stroking the pine tree, plum flower blossoming through the snow and frosted chrysanthemum.

• Korean Journal of Heritage: History & Science
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• v.37
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• pp.65-89
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• 2004

Up to now, the studies for a pond of ancient palace of Korea are mainly achieved in a landscape architectural field. In fact, we can't grasp the general aspects but we are only heard about the fragmentary ruins and remains by the people who are in charge of an archaeological excavation. In this thesis, therefore, I attempt to grasp the relational categories of the ponds of an ancient palace of Korea, and find out the ideological backgrounds of the ponds of a palace construction through classify them excavated so far. The ancient ponds of Korea are divided to the class of square ponds(I) and curved ponds(II) according a shapes of planes. The class of square ponds(I) are subdivided to the form IA of the class of square ponds and form IB of the class of square ponds by whether it has an island, artificial hill and ornamental stone or not. And the class of the curved ponds(II) are divided to the form IIC that is only composed of curves in shore and the form IID that is composed of curves and straight lines. According the size, it is divided to a small size that is below the maximal diameter, 20m, and a large size that is more than 45m, after all, the ponds of the ancient palaces are devided to IAa, IAb, IBa, II Ca, IICb, IIDa. The square ponds and the curved ponds are co-exist from the initial stage when a pond of a place was found in our country and are succeeded or changed after Silla unified the three Kingdoms. In other words, we can infer a continuity from the earlier stage from the fact that there is a flat figure ground mainly constituted by the ponds of a palace mixed up of a straight line and a curved line in United Silla Kingdom while it succeeds the ponds of a palace that has a square form of Goguryo in Balhai. Different from the successional relation of the flat figure grounds, in an aspect of the elements of the construction, the site of the arbor at the top of the island and the bridge facilities in a field of a palace those are not exist in three Kingdoms period are appeared in United Silla Kingdom. The point that this aspect is simultaneously appeared in a neighboring country, or Japan, allows us to infer that there may be some motivations cause the changes in a construction of the ponds of a palace of Korea, China and Japan from the latter half of the 7th century to the first half of the 8th century. The ideological backgrounds of the ponds of a palace construction are divided roughly into Taoism and Buddhism. We can recognize that the ponds of a palace made up of the islands, the artificial hills and the garden rocks reflect Taiosm, considering the records of the ponds a palace of Korea and China are all use the term, Taoism, or the concrete statement represents that the islands, the artificial hills and the garden rocks are used in the description of the ponds of a palace of Korea. Both two are, therefore, obviously differentiated from the ponds of a palace that doesn't include them. We can conclude that the ponds of a palace that doesn't include them are colored by Buddhism since they are overtly distinguished from the class of curved ponds that reflect Taoism at the same period and they are identical with the site of an ancient temples in an aspect of their type and construction.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.6
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• pp.49-59
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• 2018

The purpose of this study was to analyze the importance and satisfaction of resources in the mouth of Nakdong River. A Pearson's chi-square test was performed in SPSS 24.0 for statistical analysis and the result of the study was summarized by three points. First, the results of importance analysis on resources in Nakdong estuary found that the importance of ecology resources was the highest with 27.1%, followed by landscape resources (18.5%), waterside leisure resources (6.5%), complex cultural resources (5.4%), and historic and cultural resources (3.3%). The probability values (p-value) of each group had shown significant differences depending on gender, age, and the location of the survey. For instance, women respondents reported a higher preference to ecology resources and complex cultural resources such as museums than men respondents as much as two times and three times, respectively. Meanwhile, men respondents showed a higher preference to waterside leisure resources in three times as much as women respondents. As for the analysis by age, the respondents in their 20s and 30s recorded a higher value than those in other age groups, and people in their 30s reported a higher preference to waterside leisure resources than those in different age groups by three times. Lastly, no significant differences were found in the preference analysis by occupation (p>.05). With regard to the results of satisfaction analysis, the average level of satisfaction on landscape resources was 6.01, and that of ecology resources and complex cultural resource were 5.65 and 5.15, respectively. Also, significant differences were found between landscape and ecology resources in the satisfaction analysis by age, landscape resources by age, ecology resources by region, and between landscape resources and ecology resources by occupation. The p-value of complex cultural resources was p=0.012, although the satisfaction level of landscape resources and ecology resources were reported to have no significant differences by age. As for the level of satisfaction in landscape resources, respondents in their 40s and 50s showed a high level of satisfaction. However, those in their 20s showed a relatively low level of satisfaction in the same category. The survey respondents living in Busan and South Gyeongsang Province and those living outside the regions revealed no significant differences in terms of satisfaction in landscape resources and complex cultural resources. However, the two same groups were found to show significant differences in the satisfaction analysis on ecology resources. In the satisfaction analysis of landscape resources and ecology resources by occupation, significant differences were found among college students, government employees, ordinary citizens, and expert groups. However, they showed no significant differences in the level of satisfaction to complex cultural resources. Third, the results of importance-satisfaction analysis on Nakdong estuary found that the average levels of satisfaction to landscape resources for each group of respondents who considered landscape, ecology, and cultural resources as important was 6.19, 6.08, and 5.67, respectively. Their levels of satisfaction on ecology resources were 5.95, 5.57, and 5.41 for each. Its correlation to the importance was insignificant. However, it was confirmed that the correlation to the level of satisfaction on complex cultural resources had a significant difference (p=0.025). In addition, the results of the analysis on 15 detailed items that was carried out with the aim to improving values and vitalizing resources in the mouth of Nakdong River found that respondents considered that the vitalization of eco-tourism (49.5%) and restoration of reed marsh (47.5%) were important. The results of detailed analysis revealed respondents' high awareness on the need of enhancing values on ecology resources. Also, improving infrastructure nearby the mouth, creating cycling routes, walkways, waterside leisure facilities, and others were considered as the requirements for the vitalization of Nakdong estuary.

• Journal of Nutrition and Health
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• v.52 no.1
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• pp.90-103
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• 2019

Purpose: This study examined the relationship of the nutrition of rice and the positive evaluation of the rice-based meal with the food consumption habits, physical and emotional health status, and learning efficacy of 601 middle and high school students in Jeonju area. Methods: The participants were divided into two groups using cluster analysis in that the participants belonging to the upper groups had a center score of 46.86 (n = 348), while the people belonging to the lower group had a center score of 36.89 (n = 253). Statistical differences were tested for all the relationships between the physical and emotional health symptoms and learning efficacy between the groups at the ${\alpha}=0.05$ level. Results: Significant differences in the physical self-evaluated symptoms were observed in all five items in each cluster (p < 0.05). In the case of the emotional health status, nine out of 10 items showed significant differences between the groups. Similarly, significant differences in all five items in learning efficacy questionnaire were noted (p < 0.05). Positive attitudes of the parents toward having breakfast also showed significant differences among the groups. Conclusion: The nutrition of rice and a positive evaluation of the rice-based meals significantly affect the physical and emotional health status and learning efficacy of juveniles. These findings can be used as baseline information for promoting nutrition education, particularly rice-based breakfast.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 2021

Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.

• Korean Journal of Heritage: History & Science
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• v.53 no.4
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• pp.234-249
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• 2020

The dispute involving the construction of the Tomb of Queen Sindeok (hereinafter "Jeongreung"), King Taejo's wife in Seoul, and the moving of that tomb, represents the most clearly demonstrated case for the collision of new and old ideologies between political powers in the early period of Joseon. Jeongreung, the tomb of Queen Sindeok from the Kang Clan, was built inside the capital fortress, but in 1409, King Taejong forced the tomb to be moved outside the capital, and the stone relics remaining at the original location were used to build the stone bridge, Gwangtong-gyo. In an unofficial story, King Taejong moved the tomb outside the capital and used the stone items there to make the Cheonggyecheon Gwang-gyo so that the people would step upon the area in order to curse Lady Kang. In the final year of King Taejo, Lady Kang and King Taejong were in a politically conflictual relationship, but they were close to being political partners until King Taejo became the king. Sillok records pertaining to the establishment of Jeongreung or Gwangtong-gyo in fact state things more plainly, indicating that the moving of Jeongreung was a result of following the sangeon (a written statement to the king) of Uijeongbu (the highest administrative agency in Joseon), which stated that having the tomb of a king or queen in the capital was inappropriate, and since it was close to the official quarter of envoys, it had to be moved. The assertion that it was aimed at degrading Jeongreung in order to repair Gwangtong-gyo thus does not reflect the factual relationship. This article presents the possibility that the use of stone items from Jeongreung to repair Gwangtong-gyo reflected an emerging need for efficient material procurement that accompanied a drastic increase in demand for materials required in civil works both in- and outside the capital. The cause for constructing Jeongreung within the capital and the cause of moving the tomb outside the capital would therefore be attributable to the heterogeneity of the ideological backgrounds of King Taejo and King Taejong. King Taejo was the ruler of the Confucius state, as he reigned through the Yeokseong Revolution, but he constructed the tomb and Hongcheon-sa, the temple in the capital for his wife Queen Sindeok. In this respect, it is considered that, with the power of Buddhism, there was an attempt to rally supporters and gather the force needed to establish the authority of Queen Sindeok. Yi Seong-gye, who was raised in the Dorugachi clan of Yuan, lived as a military man in the border area, and so he would not have had a high level of understanding in Confucian scholarship. Rather, he was a man of the old system with its 'Buddhist" tendency. On the other hand, King Taejong Yi Bang-won was an elite Confucian student who passed the national examination at the end of the Goryeo era, and he is also known to have held a profound understanding of Neo-Confucianism. To state it differently, it would be reasonable to say that the understanding of symbolic implications for the capital would be more profound in a Confucian state. Since the national system that was ruled by laws had been established following the Three-Kingdom era, the principle of burial outside of the capital that would have seen a grave constructed on the outskirts of the capital was not upheld, without exception. Jeongreung was built inside the capital due to the strong individual desire of King Taejo, but since he was a Confucian scholar prior to becoming king, it would not have been accepted as desirable. After taking the throne, King Taejong took the initiative to begin overhauling the capital in order to reflect his intent to clearly realize Confucian ideology emphasizing 'Yechi' ("ruling with good manners") with the scenic view of the Capital's Hanyang river. It would be reasonable to conclude accordingly that the moving of Jeongreung was undertaken in the context of such a historic background.

• Korean Journal of Heritage: History & Science
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• v.53 no.4
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• pp.150-169
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• 2020

Surveys of Buddhist ruins at Namsan in Gyeongju began in earnest during the Japanese colonial era, undertaken by Japanese scholars. These surveys of Buddhist remains in Namsan made during the colonial period should be seen as previous research which cannot be ignored in any in-depth study of Buddhist ruins in Gyeongju. Full-scale surveys of Buddhist ruins at Namsan began in the 1920s. Previous surveys conducted around the time of the Japanese annexation of Korea in 1910 are generally viewed as only representing preliminary investigations and, thus, have not received much attention. However, these early surveys are significant in that they led to the Buddhist ruins on Namsan becoming widely known in the 1910s and served as the foundations for later studies. The removal of the Seated Medicine Buddha from Samneung Valley in Gyeongju in 1915 and its subsequent exhibition at the Joseon Local Products Expo, which marked the fifth anniversary of the Japanese administration of Korea, was especially important in garnering attention for Namsan's wealth of Buddhist artifacts, as the statue was placed in the main hall of the art museum and attracted a great deal of interest from visitors. It is typically thought that this Seated Medicine Buddha was exhibited in 1915 because it was the most beautiful and well-preserved statue from Namsan. However, the removal of this statue was closely related to the proposed move of the Seokguram statue to Seoul around the time of Korea's annexation. The plan to move Seokguram to Seoul was primarily devised by Terauchi Masatake, and the plan, based on Ilseontongjo-ron ('日鮮同祖論'), a historical theory that prehistoric Korean and Japanese people were of the same blood, and Joseon Jeongcheasoeng-ron ('朝鮮停滯性論'), a historical theory arguing that development had stagnated in Korea, was intended to be a visual demonstration of a new era for Korea. This new era was to proceed under the rule of the Japanese Empire through the dissolution of Gyeongbokgung, the symbol of the Joseon Dynasty, which would be replaced with past glories as symbolized by the statue of Buddha. However, as the plan floundered, the replacement for Seokguram in Seoul ended up being none other than the Seated Medicine Buddha of Samneung Valley. Surveys of the Seated Medicine Buddha began in 1911, administered by Sekino Tadashi, but he likely learned of the statue's location from Moroga Hideo or Kodaira Ryozo, Japanese residents of Gyeongju. It is also probable that these Japanese residents received a request from the Japanese Government General of Korea to find a Buddha statue that was worthy of being displayed at exhibitions. In this way, we can say that the transfer of the Seated Medicine Buddha to Seoul was the result of close cooperation between the Government General, Sekino Tadashi, and Japanese residents of Gyeongju. This also had the effect of removing the magical veil which had shrouded the Buddhist ruins of Namsan. In other words, while the early surveys of Buddhist ruins on Namsan are significant, it is difficult to argue that the surveys were undertaken for purely academic purposes, as they were deeply related to the imperial ambitions of Governor-General Terauchi which encompassed the plans to move Seokguram to Seoul and the successful hosting of the 1915 Expo. It should also be pointed out that the failure of the plan to move Seokguram to Seoul and the preservation of the Seated Stone Buddha of Mireuggok at Namsan was in no small part due to resistance from Korean residents in Gyeongju. Although it is not described in detail in the paper, research is needed which shows that the Korean residents of Gyeongju were not simple bystanders, but agents of history.