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Relationship between Insomnia and Depression in Type 2 Diabetics (2형 당뇨병 환자에서 불면증과 우울 증상의 관련성)

  • Lee, Jin Hwan;Cheon, Jin Sook;Choi, Young Sik;Kim, Ho Chan;Oh, Byoung Hoon
    • Korean Journal of Psychosomatic Medicine
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    • v.27 no.1
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    • pp.50-59
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    • 2019
  • Objectives : Many of the patients with type 2 diabetes are associated with sleep problems, and the rate of insomnia is known to be higher in the general population. The aims of this study were to know the frequency and clnical characteristics of insomnia, and related variables to insomnia in patients diagnosed with type 2 diabetes. Methods : For 99 patients from 18 to 80 years of age (65 males and 34 females) with type 2 diabetes, interviews were performed. Total sleep time and sleep latency was evaluated. Insomnia was evaluated using the Korean Version of the Insomnia Severity Index (ISI-K). Severity of depressive symptoms were evaluted using the Korean version of the Hamilton Depression Scale (K-HDRM). According to the cutoff score of 15.5 on the ISI-K, subjects were divided into the group of type 2 diabetics with insomnia (N=34) and those without insomnia (N=65) at first, and then statistically analyzed. Results : TInsomnia could be found in 34.34% of type 2 diabetics. Type 2 diabetics with insomnia had significantly more single or divorced (respectively 11.8%, p<0.05), higher total scores of the K-HDRS ($11.76{\pm}5.52$, p<0.001), shorter total sleep time ($5.35{\pm}2.00hours$, p<0.001), and longer sleep latency ($50.29{\pm}33.80minutes$, p<0.001). The all item scores of the ISI-K in type 2 diabetics with insomnia were significantly higher than those in type 2 diabetics without insomnia, that is, total ($18.38{\pm}2.69$), A1 (Initial insomnia) ($2.97{\pm}0.76$), A2 (Middle insomnia) ($3.06{\pm}0.69$), A3 (Terminal insomnia) ($2.76{\pm}0.61$), B (Satisfaction) ($3.18{\pm}0.72$), C (Interference) ($2.09{\pm}0.97$), D (Noticeability) ($2.12{\pm}1.09$) and E (Distress) ($2.21{\pm}0.81$) (respectively p<0.001). Variables associated with insomnia in type 2 diabetics were as following. Age had significant negative correlation with A3 items of the ISI-K (${\beta}=-0.241$, p<0.05). Total scores of the K-HDRS had significant positive correlation, while total sleep time had significant negative correlation with all items of the ISI-K (respectively p<0.05). Sleep latency had significant positive correlation with total,, A1, B and E item scores of the ISI-K (respectively p<0.05). Conclusions : Insomnia was found in about 1/3 of type 2 diabetics. According to the presence of insomnia, clinical characteristics including sleep quality as well as quantity seemed to be different. Because depression seemed to be correlated with insomnia, clinicians should pay attention to early detection and intervention of depression among type 2 diabetics.

How to improve the accuracy of recommendation systems: Combining ratings and review texts sentiment scores (평점과 리뷰 텍스트 감성분석을 결합한 추천시스템 향상 방안 연구)

  • Hyun, Jiyeon;Ryu, Sangyi;Lee, Sang-Yong Tom
    • Journal of Intelligence and Information Systems
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    • v.25 no.1
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    • pp.219-239
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    • 2019
  • As the importance of providing customized services to individuals becomes important, researches on personalized recommendation systems are constantly being carried out. Collaborative filtering is one of the most popular systems in academia and industry. However, there exists limitation in a sense that recommendations were mostly based on quantitative information such as users' ratings, which made the accuracy be lowered. To solve these problems, many studies have been actively attempted to improve the performance of the recommendation system by using other information besides the quantitative information. Good examples are the usages of the sentiment analysis on customer review text data. Nevertheless, the existing research has not directly combined the results of the sentiment analysis and quantitative rating scores in the recommendation system. Therefore, this study aims to reflect the sentiments shown in the reviews into the rating scores. In other words, we propose a new algorithm that can directly convert the user 's own review into the empirically quantitative information and reflect it directly to the recommendation system. To do this, we needed to quantify users' reviews, which were originally qualitative information. In this study, sentiment score was calculated through sentiment analysis technique of text mining. The data was targeted for movie review. Based on the data, a domain specific sentiment dictionary is constructed for the movie reviews. Regression analysis was used as a method to construct sentiment dictionary. Each positive / negative dictionary was constructed using Lasso regression, Ridge regression, and ElasticNet methods. Based on this constructed sentiment dictionary, the accuracy was verified through confusion matrix. The accuracy of the Lasso based dictionary was 70%, the accuracy of the Ridge based dictionary was 79%, and that of the ElasticNet (${\alpha}=0.3$) was 83%. Therefore, in this study, the sentiment score of the review is calculated based on the dictionary of the ElasticNet method. It was combined with a rating to create a new rating. In this paper, we show that the collaborative filtering that reflects sentiment scores of user review is superior to the traditional method that only considers the existing rating. In order to show that the proposed algorithm is based on memory-based user collaboration filtering, item-based collaborative filtering and model based matrix factorization SVD, and SVD ++. Based on the above algorithm, the mean absolute error (MAE) and the root mean square error (RMSE) are calculated to evaluate the recommendation system with a score that combines sentiment scores with a system that only considers scores. When the evaluation index was MAE, it was improved by 0.059 for UBCF, 0.0862 for IBCF, 0.1012 for SVD and 0.188 for SVD ++. When the evaluation index is RMSE, UBCF is 0.0431, IBCF is 0.0882, SVD is 0.1103, and SVD ++ is 0.1756. As a result, it can be seen that the prediction performance of the evaluation point reflecting the sentiment score proposed in this paper is superior to that of the conventional evaluation method. In other words, in this paper, it is confirmed that the collaborative filtering that reflects the sentiment score of the user review shows superior accuracy as compared with the conventional type of collaborative filtering that only considers the quantitative score. We then attempted paired t-test validation to ensure that the proposed model was a better approach and concluded that the proposed model is better. In this study, to overcome limitations of previous researches that judge user's sentiment only by quantitative rating score, the review was numerically calculated and a user's opinion was more refined and considered into the recommendation system to improve the accuracy. The findings of this study have managerial implications to recommendation system developers who need to consider both quantitative information and qualitative information it is expect. The way of constructing the combined system in this paper might be directly used by the developers.

An Analytical Approach Using Topic Mining for Improving the Service Quality of Hotels (호텔 산업의 서비스 품질 향상을 위한 토픽 마이닝 기반 분석 방법)

  • Moon, Hyun Sil;Sung, David;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
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    • v.25 no.1
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    • pp.21-41
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    • 2019
  • Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.

Major Class Recommendation System based on Deep learning using Network Analysis (네트워크 분석을 활용한 딥러닝 기반 전공과목 추천 시스템)

  • Lee, Jae Kyu;Park, Heesung;Kim, Wooju
    • Journal of Intelligence and Information Systems
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    • v.27 no.3
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    • pp.95-112
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    • 2021
  • In university education, the choice of major class plays an important role in students' careers. However, in line with the changes in the industry, the fields of major subjects by department are diversifying and increasing in number in university education. As a result, students have difficulty to choose and take classes according to their career paths. In general, students choose classes based on experiences such as choices of peers or advice from seniors. This has the advantage of being able to take into account the general situation, but it does not reflect individual tendencies and considerations of existing courses, and has a problem that leads to information inequality that is shared only among specific students. In addition, as non-face-to-face classes have recently been conducted and exchanges between students have decreased, even experience-based decisions have not been made as well. Therefore, this study proposes a recommendation system model that can recommend college major classes suitable for individual characteristics based on data rather than experience. The recommendation system recommends information and content (music, movies, books, images, etc.) that a specific user may be interested in. It is already widely used in services where it is important to consider individual tendencies such as YouTube and Facebook, and you can experience it familiarly in providing personalized services in content services such as over-the-top media services (OTT). Classes are also a kind of content consumption in terms of selecting classes suitable for individuals from a set content list. However, unlike other content consumption, it is characterized by a large influence of selection results. For example, in the case of music and movies, it is usually consumed once and the time required to consume content is short. Therefore, the importance of each item is relatively low, and there is no deep concern in selecting. Major classes usually have a long consumption time because they have to be taken for one semester, and each item has a high importance and requires greater caution in choice because it affects many things such as career and graduation requirements depending on the composition of the selected classes. Depending on the unique characteristics of these major classes, the recommendation system in the education field supports decision-making that reflects individual characteristics that are meaningful and cannot be reflected in experience-based decision-making, even though it has a relatively small number of item ranges. This study aims to realize personalized education and enhance students' educational satisfaction by presenting a recommendation model for university major class. In the model study, class history data of undergraduate students at University from 2015 to 2017 were used, and students and their major names were used as metadata. The class history data is implicit feedback data that only indicates whether content is consumed, not reflecting preferences for classes. Therefore, when we derive embedding vectors that characterize students and classes, their expressive power is low. With these issues in mind, this study proposes a Net-NeuMF model that generates vectors of students, classes through network analysis and utilizes them as input values of the model. The model was based on the structure of NeuMF using one-hot vectors, a representative model using data with implicit feedback. The input vectors of the model are generated to represent the characteristic of students and classes through network analysis. To generate a vector representing a student, each student is set to a node and the edge is designed to connect with a weight if the two students take the same class. Similarly, to generate a vector representing the class, each class was set as a node, and the edge connected if any students had taken the classes in common. Thus, we utilize Node2Vec, a representation learning methodology that quantifies the characteristics of each node. For the evaluation of the model, we used four indicators that are mainly utilized by recommendation systems, and experiments were conducted on three different dimensions to analyze the impact of embedding dimensions on the model. The results show better performance on evaluation metrics regardless of dimension than when using one-hot vectors in existing NeuMF structures. Thus, this work contributes to a network of students (users) and classes (items) to increase expressiveness over existing one-hot embeddings, to match the characteristics of each structure that constitutes the model, and to show better performance on various kinds of evaluation metrics compared to existing methodologies.

The Present Status and the Preservation Method of the Rice Terrace as Scenic Sites Resources in Northeast Asia (동북아시아 계단식 논의 명승지정 현황 및 보전방안)

  • Youn, Kyung-Sook;Lee, Chang-Hun;Kim, Hyung-Dae;Seo, Woo-Hyun;Lee, Jae-Keun
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.29 no.4
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    • pp.111-123
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    • 2011
  • This study aims to present the basic materials, which lead us to preserve the Korea Rice Terrace as scenic sites resources and study it continuously, through researching about the present status and the preservation method of the Rice Terrace in Korea, China and Japan. The results of this study are as follows. First, The Rice Terrace has a traditional agricultural technique which minimizing the damage of the scenic view while cultivating the slope. And also, it has the value of one of the Korea unique traditional scenic views. However, The no cultivation land or disappearing desert land of rice terrace were increasing by the disadvantage of operation in land cultivation. Therefore, The Government must need preparing the base of scene resources excavation by executed the established of Korea Rice Terrace Database for preserving of Korea traditional scene. however it is getting to disappearance. And also, The High valued of Rice Terrace by cultural and scenic view which is must managed by designation of scenic sites or monument. Second, The internal and external reference book researched and analyzed results are as followings for understanding about Korea Rice Terrace feature. First of all, The Rice Terrace's dictionary meaning is just difference by each nations. However, Generally speaking that It means the terraced land by cultivated of sloped land. The Rice Terrace has cross relation with mountain valley and piedmont slope cultivation in location of condition. It occurred era is before approximately estimated from 3000 of years until 6000 of years. It can divide two type by topography shape those are slope and valley type. However, The natural element of forest has very big position in this part. But, The Rice Terrace is just managed and designated by the scenic sites with the Cultural Properties Protection Law. It must needs more binding force and effectiveness for the Rice Terrace scenic view plan establishment by scenic laws and farming and fishing village laws etc. I think that it must need the Rice Terrace related law establishment as soon as possible for efficient preservation and management of the Rice Terrace. Third, The Rice Terrace were researched and analyzed results are as followings those were executed at the Korea, China and Japan. The Korea and Japan have good Rice Terrace Characteristic. And also, The high valued scenic sites area were good managed by the Cultural Properties Protection Law as well as the superior scenic valued Rice Terrace in China. Those are also managed by designated scenic sites for protection and preservation positively. Those were managed by each autonomous district management Department. The each nation's related laws of Rice Terrace protection were just little bit different. However, The basic purpose is same. for example, it based on superior scenic view preservation and protection. Especially, The Japan's Cultural Properties Law and Scenic law linkage, and China Autonomous district legislation and effectiveness. The Korea Government must need above elements for Korea Rice Terrace culture and scenic view preservation. Fourth, We need inducing the owner system and the policy of Rice Terrace preservation promotion association for efficient preservation of Rice Terrace in japan. The owner system in japan gives the owner of the land a permission to rent the land to Rice Terrace preservation promotion association and the local government. In this system the village would be revitalized by commons in the way of the management of the terraces, beautifying the area around the terraces and etc. And also, Making the each village management operating system for Rice Terrace management through educating civilization. The civilization could receive quick help from a consultative body comprised of experts such as representatives of Cultural Heritage Administration and professors. And it is in a hurry to solve the problem of revitalization of the region by exchange between cities and the village.

A Study on the Ideal Leadership whole person of Confucian philosophy (유가(儒家)의 전인적(全人的) 지도자상(指導者像) 고찰(考察))

  • Kim, Kyeong-Mi
    • (The)Study of the Eastern Classic
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    • no.62
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    • pp.145-176
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    • 2016
  • This paper aims to define the leadership of Gunja (君子, translated into prince, gentleman, or ideal man) based on Confucian Classics which offer the general values and norms of individuals' virtue and social virtuous acts. Thus, humanitarianism is regarded as true value, and the values of a virtuous person who properly practices social human relationships are discussed. The real worth of Gunja image is discussed as a true human image of "self-completion and completion of all things" (成己成物) which involves the convergence of truth, good and beauty where there is a sense of harmony and balance, where there is stern self discipline and self cultivation and where win-win values of human relationships are created. Confucian saint (聖人), wise man (賢人), great man (大人), and gentleman (君子) mean social leaders. They practice human morals, enlighten and beautify society with teachings, and are indicated as equipped with mental and material harmony, good character and competence, and economic power and morality. People today pursue their own personal growth according to their material preferences rather than pure intellectual cultural values, and are engrossed in visually beautiful external unlimited competition. In this digital age, we are supposed to demonstrate our individuality, but many people are obsessed with appearance, go on severe diet, and lose their health beauty, and consequently suffer mental stress. This trend fuels obsession with appearance and the sick practice of valuing appearance. As an alternative method to overcome this phenomenon, we need a leader image with the convergence of truth, good and beauty, which is characterized by internal self cultivation, external professionalism, and handsome and solid character. Confucian thoughts consist in practicing the Way of disciplining oneself for governing others (修己治人). Self discipline involves developing personal virtuous ability for cultivating a virtuous character, and governing others involves interacting to work together in society and to have right human relationships. Thus, leaders should impress not only themselves but also others. Self discipline for governing others means cultivating virtue for oneself and leading others. A true leader has self introspection and establishes himself through self discipline so that he can govern others or reach the realm of settling others where people live together. As all things have a value and a virtue, humans endeavor to cultivate character and virtue by learning and studying for securing their professionalism, reliability, character and ability, so as to create their own brand value. Personal character does not come from a high position, wealth and power. Character is a personal virtue, and is cultivated as immaculate and fresh through self discipline. As such, it well matches with a clean and clear spirit. This offers the ideal leader as the Guja image who has an extremely humane character, as well as being equipped with inherent virtues of intellect, benevolence and courage. Self development can foster virtue and self management through self leadership and self discipline. The leader in the relationship area can practice his virtue through virtuous acts, in other words, even think from another person's perspective. Such leader is mentioned as the principle of measuring square in the Great Learning. In our viewpoint, the beauty of character can breed the seed of virtue through intellect, benevolence and courage, the beauty of win-win can realize the right virtue by showing exemplary acts to others through considerateness, and the beauty of harmony can love and care for others like me through the principle of measuring square, thereby realizing the universal principle of virtue and harmony, which is like my mind. As such, the ideal leader, when his virtue and mind of being considerate of others all blending well, can exercise his ability to the full, can live together and coexist with many people, and can grow again into a triumphant relationship.

An Essay in a Research on Gwonwu Hong Chan-yu's Poetic Literature - Focussing on Classical Chinese Poems in Gwonwujip (권우(卷宇) 홍찬유(洪贊裕) 시문학(詩文學) 연구(硏究) 시론(試論) - 『권우집(卷宇集)』 소재(所載) 한시(漢詩)를 중심(中心)으로 -)

  • Yoon, Jaehwan
    • (The)Study of the Eastern Classic
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    • no.50
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    • pp.55-88
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    • 2013
  • Gwonwu Hong Chan-yu is one of the modern and contemporary Korean scholars of Sino-Korean literature and one of the literati of his era, so is respected as a guiding light by academic descendants. Gwonwu was a teacher of his era, who experienced all the turbulence of Korean society, such as the Japanese occupation by force, the Korean War, the military dictatorship, and the struggle for democracy, and who educated and led young scholars of his time. However, academia has not payed attention to his life and achievements since his death. This paper is to examine the poetry of Gwonwu Hong Chan-yu, one of the representative modern and contemporary scholar of Sini-Korean literature, which has not yet been discussed by academia. The minimal meaning of this paper is that it is a first work based on his anthology, which has not been discussed by academia, and a first full-scale study on Gwonwu Hongchan-yu. For the reason, this paper aims at the detailed inspection of his poetic pieces recorded in his anthology. Nonetheless, despite such intentions, some limits cannot be avoided here and there in this paper for the insufficient knowledge and academic capability of this paper's writer and for the lack of academic sources. Gwonwu's poetry examined through his anthology shows the characteristic which is that his poems focus on exposing his own internal emotions. Such a characteristic says that his idea of poetic literature payed attention more to individuality, that is exposition of private emotions, than to social utility of poems. Gwonwu's such an idea of poetic literature can be generally affirmed throughout his poetry. Accordingly, Gwonwu preferred classical Chinese poems to archaistic poems, and single poems to serial poems; and avoided writing poems within social relations such as farewell-poems, bestowal-poems, and mourning-poems. When the characteristics of Gwonwu's poetic literature get summarized as such, however, some questions remain. The preferential question is whether the poems in his anthology are the whole poetry of him. Although Gwonwu's poetic pieces that the writer of this paper have checked out till now are all in his anthology, it is very much questionable whether Gwonwu's poetry can be summed up only with these poems. The next question is what is the writing method for taking joy(spice), sentiment, and full-heart into his poems if Gwonwu's poems focus on exposing his internal emotions, and if poems exposing joy and poems exposing sentiment and full-heart appear coherently in various different spaces and circumstances of writing. The final question is what are the meanings of Gwonwu's poems if his poetry checked out through his anthology directly shows either the reality carried in his poems or the reality of a time in his life. The questions listed above are thought to be resolved by the synchronizing process of stereoscopic searches both for Gwonwu as an individual and for the era of his life. Especially, spurring deeper researches toward a new direction regarding Gwonwu's poetry has an important meaning for construction of a complete modern and contemporary history of Sino-Korean literature and for procurement of continuous research on Sino-Korean literature and its history. For the reason, it is thought that more efforts of researchers are required.

Different Look, Different Feel: Social Robot Design Evaluation Model Based on ABOT Attributes and Consumer Emotions (각인각색, 각봇각색: ABOT 속성과 소비자 감성 기반 소셜로봇 디자인평가 모형 개발)

  • Ha, Sangjip;Lee, Junsik;Yoo, In-Jin;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.27 no.2
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    • pp.55-78
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    • 2021
  • Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of today's robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing "robot development methodology" or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robot's appearance has an important influence in the process of forming user's perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumer's attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumer's emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.

The Prediction of Export Credit Guarantee Accident using Machine Learning (기계학습을 이용한 수출신용보증 사고예측)

  • Cho, Jaeyoung;Joo, Jihwan;Han, Ingoo
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.83-102
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    • 2021
  • The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.

Virtuous Concordance of Yin and Yang and Tai-Ji in Joseon art: Focusing on Daesoon Thought (조선 미술에 내재한 음양합덕과 태극 - 대순사상을 중심으로 -)

  • Hwang, Eui-pil
    • Journal of the Daesoon Academy of Sciences
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    • v.35
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    • pp.217-253
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    • 2020
  • This study analyzes the principles of the 'Earthly Paradise' (仙境, the realm of immortals), 'Virtuous Concordance of Yin and Yang' (陰陽合德), and the 'Reordering Works of Heaven and Earth' (天地公事) while combining them with Joseon art. Therefore, this study aims to discover the context wherein the concept of Taiji in 'Daesoon Truth,' deeply penetrates into Joseon art. Doing so reveals how 'Daesoon Thought' is embedded in the lives and customs of the Korean people. In addition, this study follows a review of the sentiments and intellectual traditions of the Korean people based on 'Daesoon Thought' and creative works. Moreover, 'Daesoon Thought' brings all of this to the forefront in academics and art at the cosmological level. The purpose of this research is to vividly reveal the core of 'Daesoon Thought' as a visual image. Through this, the combination of 'Daesoon Thought' and Joseon art will secure both data and reality at the same time. As part of this, this study deals with the world of 'Daesoon Thought' as a cosmological Taiji principle. This concept is revealed in Joseon art, which is analyzed and examined from the viewpoint of art philosophy. First, as a way to make use of 'Daesoon Thought,' 'Daesoon Truth' was developed and directly applied to Joseon art. In this way, reflections on Korean life within 'Daesoon Thought' can be revealed. In this regard, the selection of Joseon art used in this study highlights creative works that have been deeply ingrained into people's lives. For example, as 'Daesoon Thought' appears to focus on the genre painting, folk painting, and landscape painting of the Joseon Dynasty, attention is given to verifying these cases. This study analyzes 'Daesoon Thought,' which borrows from Joseon art, from the perspective of art philosophy. Accordingly, attempts are made to find examples of the 'Virtuous Concordance of Yin and Yang' and Tai-Ji in Joseon art which became a basis by which 'Daesoon Thought' was communicated to people. In addition, appreciating 'Daesoon Thought' in Joseon art is an opportunity to vividly examine not only the Joseon art style but also the life, consciousness, and mental world of the Korean people. As part of this, Chapter 2 made several findings related to the formation of 'Daesoon Thought.' In Chapter 3, the structures of the ideas of 'Earthly Paradise' and 'Virtuous Concordance of Yin and Yang' were likewise found to have support. And 'The Reordering Works of Heaven and Earth' and Tai-Ji were found in depictions of metaphysical laws. To this end, the laws of 'The Reordering Works of Heaven and Earth' and the structure of Tai-Ji were combined. In chapter 4, we analyzed the 'Daesoon Thought' in the life and work of the Korean people at the level of the convergence of 'Daeesoon Thought' and Joseon art. The analysis of works provides a glimpse into the precise identity of 'Daesoon Thought' as observable in Joseon art, as doing so is useful for generating empirical data. For example, works such as Tai-Jido, Ssanggeum Daemu, Jusachaebujeokdo, Hwajogi Myeonghwabundo, and Gyeongdodo are objects that inspired descriptions of 'Earthly Paradise', 'Virtuous Concordance of Yin and Yang,' and 'The Reordering Works of Heaven and Earth.' As a result, Tai-Ji which appears in 'Daesoon Thought', proved the status of people in Joseon art. Given all of these statements, the Tai-Ji idea pursued by Daesoon Thought is a providence that follows change as all things are mutually created. In other words, it was derived that Tai-Ji ideology sits profoundly in the lives of the Korean people and responds mutually to the providence that converges with 'Mutual Beneficence.'