• Title/Summary/Keyword: addition

Search Result 101,002, Processing Time 0.119 seconds

The Effect of Shading on Pedestrians' Thermal Comfort in the E-W Street (동-서 가로에서 차양이 보행자의 열적 쾌적성에 미치는 영향)

  • Ryu, Nam-Hyong;Lee, Chun-Seok
    • Journal of the Korean Institute of Landscape Architecture
    • /
    • v.46 no.6
    • /
    • pp.60-74
    • /
    • 2018
  • This study was to investigate the pedestrian's thermal environments in the North Sidewalk of E-W Street during summer heatwave. We carried out detailed measurements with four human-biometeorological stations on Dongjin Street, Jinju, Korea ($N35^{\circ}10.73{\sim}10.75^{\prime}$, $E128^{\circ}55.90{\sim}58.00^{\prime}$, elevation: 50m). Two of the stations stood under one row street tree and hedge(One-Tree), two row street tree and hedge (Two-Tree), one of the stations stood under shelter and awning(Shelter), while the other in the sun (Sunlit). The measurement spots were instrumented with microclimate monitoring stations to continuously measure microclimate, radiation from the six cardinal directions at the height of 1.1m so as to calculate the Universal Thermal Climate Index (UTCI) from 24th July to 21th August 2018. The radiant temperature of sidewalk's elements were measured by the reflective sphere and thermal camera at 29th July 2018. The analysis results of 9 day's 1 minute term human-biometeorological data absorbed by a man in standing position from 10am to 4pm, and 1 day's radiant temperature of sidewalk elements from 1:16pm to 1:35pm, showed the following. The shading of street tree and shelter were mitigated heat stress by the lowered UTCI at mid and late summer's daytime, One-Tree and Two-Tree lowered respectively 0.4~0.5 level, 0.5~0.8 level of the heat stress, Shelter lowered respectively 0.3~1.0 level of the heat stress compared with those in the Sunlit. But the thermal environments in the One-Tree, Two-Tree and Shelter during the heat wave supposed to user "very strong heat stress" while those in the Sunlit supposed to user "very strong heat stres" and "exterme heat stress". The main heat load temperature compared with body temperature ($37^{\circ}C$) were respectively $7.4^{\circ}C{\sim}21.4^{\circ}C$ (pavement), $14.7^{\circ}C{\sim}15.8^{\circ}C$ (road), $12.7^{\circ}C$ (shelter canopy), $7.0^{\circ}C$ (street funiture), $3.5^{\circ}C{\sim}6.4^{\circ}C$ (building facade). The main heat load percentage were respectively 34.9%~81.0% (pavement), 9.6%~25.2% (road), 24.8% (shelter canopy), 14.1%~15.4% (building facade), 5.7% (street facility). Reducing the radiant temperature of the pavement, road, building surfaces by shading is the most effective means to achieve outdoor thermal comfort for pedestrians in sidewalk. Therefore, increasing the projected canopy area and LAI of street tree through the minimal training and pruning, building dense roadside hedge are essential for pedestrians thermal comfort. In addition, thermal liner, high reflective materials, greening etc. should be introduced for reducing the surface temperature of shelter and awning canopy. Also, retro-reflective materials of building facade should be introduced for the control of reflective sun radiation. More aggressively pavement watering should be introduced for reducing the surface temperature of sidewalk's pavement.

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
    • /
    • v.27 no.3
    • /
    • pp.95-112
    • /
    • 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.

Location and Construction Characteristics of Imdaejeong Wonlim based on Documentation (기문(記文)을 중심으로 고찰한 임대정원림(臨對亭園林)의 입지 및 조영 특성)

  • Rho, Jae-Hyun;Park, Tae-Hee;Shin, Sang-Sup;Kim, Hyoun-Wuk
    • Journal of the Korean Institute of Traditional Landscape Architecture
    • /
    • v.29 no.4
    • /
    • pp.14-26
    • /
    • 2011
  • Imdaejeong Wonlim is located on the verge of Sangsa Village in Sapyeong-ri, Daepyeong-myeon, Hwasun-gun Gyeongsangnam-do toward Northwest. It was planned by Sa-ae, Minjuhyeon in 1862 on the basis of Gobanwon built by Nam Eongi in 16th century against the backdrop of Mt. Bongjeong and facing Sapyeong Stream. As water flows from west to east in the shape of crane, this area is a propitious site standing for prosperity and happiness. This area shows a distinct feature of Wonlim surrounding the Imdaejeong with multi layers as consisting of 5 districts - front yard where landmark stone with engraved letters of 'Janggujiso of Master Sa-ea' and junipers are harmoniously arranged, internal garden of upper pavilion ranging from a pavilion to square pond with a little island in the middle, Sugyeongwon of under pavilionu consisting of 2 ponds with a painting of three taoist hermits, forest of Mt. Bonggeong and external garden including Sapyeong Stream and farmland. According to documentation and the results of on-site investigation, it is certainly proved that Imdaejeong Wonlim was motivated by Byeoseo Wonlim which realized the idea of 'going back to hometown after resignation' following the motives of Janggujiso, a hideout aimed to accomplish the ideology, 'training mind and fostering innate nature,' on the peaceful site surrounded by water and mountain, as well as motives of Sesimcheo(洗心處) to be unified with morality of Mother Nature, etc. In addition, it implies various imaginary landscapes such as Pihangji, Eupcheongdang, square pond with an island and painting of three Taoist hermits based on a notion that 'the further scent flies away, the fresher it becomes,' which is originated from Aelyeonseol(愛蓮說). In terms of technique of natural landscape treatment, divers techniques are found in Imdaejeong Wonlim such as distant view of Mt. Bongjeong, pulling view with an intention of transparent beauty of moonlight, circle view of natural and cultural sceneries on every side, borrowed scenary of pastoral rural life adopted as an opposite view, looked view of Sulyundaero, over looked view of pond, static view in pavilion and paths, close view of water space such as stream and pond, mushroom-and-umbrella like view of Imdaejeong, vista of pond surrounded by willows, imaginary view of engraved letters meaning 'widen knowledge by studying objectives' and selected view to comprise sunrise and sunset at the same time. In the beginning of construction, various plants seemed to be planted, albeit different from now, such as Ginkgo biloba, Phyllostachys spp., Salix spp., Pinus densiflora, Abies holophylla, Morus bombycis, Juglans mandschurica, Paulownia coreana, Prunus mume, Nelumbo nucifera, etc. Generally, it reflected dignity of Confucianism or beared aspect of semantic landscape implying Taoist taste and idea of Phoenix wishing a prosperity in the future. Furthermore, a diversity of planting methods were pursued for such as liner planting for the periphery of pond, bosquet planting and circle planting adopted around the pavilion, spot planting using green trees, solitary planting of monumentally planted Paulownia coreana and opposite planting presenting the Abies holophylla into yin and yang.

Discussion on the Necessity of the Study on the Principle of 'How to Mark an Era in Almanac Method of Tiāntǐlì(天體曆)' Formed until Han dynasty (한대(漢代) 이전에 형성된 천체력(天體曆) 기년(紀年) 원리 고찰의 필요성에 대한 소론(小論))

  • Seo, Jeong-Hwa
    • (The)Study of the Eastern Classic
    • /
    • no.72
    • /
    • pp.365-400
    • /
    • 2018
  • The signs of $G{\bar{a}}nzh{\bar{i}}$(干支: the sexagesimal calendar system) almanac, which marked each year, month, day and time with 60 ordinal number marks made by combining 10 $Ti{\bar{a}}ng{\bar{a}}ns$(天干: the decimal notation to mark date) and 12 $D{\grave{i}}zh{\bar{i}}s$(地支 : the duodecimal notation to mark date), were used not only as the sign of the factors affecting the occurrence of a disease and treatment in the area of traditional oriental medicine, but also as the indicator of prejudging fortunes in different areas of future prediction techniques.(for instance, astrology, the theory of divination based on topography, four pillars of destiny and etc.) While theories of many future predictive technologies with this $G{\bar{a}}nzh{\bar{i}}$(干支) almanac signs as the standard had been established in many ways by Han dynasty, it is difficult to find almanac discussion later on the fundamental theory of 'how it works like that'. As for the method to mark the era of $Ti{\bar{a}}nt{\check{i}}l{\grave{i}}$(天體曆: a calendar made with the sidereal period of Jupiter and the Sun), which determines the name of a year depending on where $Su{\grave{i}}x{\bar{i}}ng$(歲星: Jupiter) is among the '12 positions of zodiac', there are three main ways of $$Su{\grave{i}}x{\bar{i}}ng-J{\grave{i}}ni{\acute{a}}nf{\check{a}}$$(歲星紀年法: the way to mark an era by the location of Jupiter on the celestial sphere), $$T{\grave{a}}isu{\grave{i}}-J{\grave{i}}ni{\acute{a}}nf{\check{a}}$$ (太歲紀年法: the way to mark an era by the location facing the location of Jupiter on the celestial sphere) and $$G{\bar{a}}nzh{\bar{i}}-J{\grave{i}}ni{\acute{a}}nf{\check{a}}$$(干支紀年法: the way to mark an era with Ganzhi marks). Regarding $$G{\bar{a}}nzh{\bar{i}}-J{\grave{i}}ni{\acute{a}}nf{\check{a}}$$(干支紀年法), which is actually the same way to mark an era as $$T{\grave{a}}isu{\grave{i}}-J{\grave{i}}ni{\acute{a}}nf{\check{a}}$$(太歲紀年法) with the only difference in the name, there are more than three ways, and one of them has continued to be used in China, Korea and so on since Han dynasty. The name of year of $G{\bar{a}}nzh{\bar{i}}$(干支) this year, 2018, has become $W{\grave{u}}-X{\bar{u}}$(戊戌) just by 'accident'. Therefore, in this discussion, the need to realize this situation was emphasized in different areas of traditional techniques of future prediction in which distinct theories have been established with the $G{\bar{a}}nzh{\bar{i}}$(干支) mark of year, month, day and time. Because of the 1 sidereal period of Jupiter, which is a little bit shorter than 12 years, once about one thousand years, 'the location of Jupiter on the zodiac' and 'the name of a year of 12 $D{\grave{i}}zh{\bar{i}}s$(地支) marks' accord with each other just for about 85 years, and it has been verified that recent dozens of years are the very period. In addition, appropriate methods of observing the the twenty-eight lunar mansions were elucidated. As $G{\bar{a}}nzh{\bar{i}}$(干支) almanac is related to the theoretical foundation of traditional medical practice as well as various techniques of future prediction, in-depth study on the fundamental theory of ancient $Ti{\bar{a}}nt{\check{i}}l{\grave{i}}$(天體曆) cannot be neglected for the succession and development of traditional oriental study and culture, too.

A Methodology of Customer Churn Prediction based on Two-Dimensional Loyalty Segmentation (이차원 고객충성도 세그먼트 기반의 고객이탈예측 방법론)

  • Kim, Hyung Su;Hong, Seung Woo
    • Journal of Intelligence and Information Systems
    • /
    • v.26 no.4
    • /
    • pp.111-126
    • /
    • 2020
  • Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

Aspect-Based Sentiment Analysis Using BERT: Developing Aspect Category Sentiment Classification Models (BERT를 활용한 속성기반 감성분석: 속성카테고리 감성분류 모델 개발)

  • Park, Hyun-jung;Shin, Kyung-shik
    • Journal of Intelligence and Information Systems
    • /
    • v.26 no.4
    • /
    • pp.1-25
    • /
    • 2020
  • Sentiment Analysis (SA) is a Natural Language Processing (NLP) task that analyzes the sentiments consumers or the public feel about an arbitrary object from written texts. Furthermore, Aspect-Based Sentiment Analysis (ABSA) is a fine-grained analysis of the sentiments towards each aspect of an object. Since having a more practical value in terms of business, ABSA is drawing attention from both academic and industrial organizations. When there is a review that says "The restaurant is expensive but the food is really fantastic", for example, the general SA evaluates the overall sentiment towards the 'restaurant' as 'positive', while ABSA identifies the restaurant's aspect 'price' as 'negative' and 'food' aspect as 'positive'. Thus, ABSA enables a more specific and effective marketing strategy. In order to perform ABSA, it is necessary to identify what are the aspect terms or aspect categories included in the text, and judge the sentiments towards them. Accordingly, there exist four main areas in ABSA; aspect term extraction, aspect category detection, Aspect Term Sentiment Classification (ATSC), and Aspect Category Sentiment Classification (ACSC). It is usually conducted by extracting aspect terms and then performing ATSC to analyze sentiments for the given aspect terms, or by extracting aspect categories and then performing ACSC to analyze sentiments for the given aspect category. Here, an aspect category is expressed in one or more aspect terms, or indirectly inferred by other words. In the preceding example sentence, 'price' and 'food' are both aspect categories, and the aspect category 'food' is expressed by the aspect term 'food' included in the review. If the review sentence includes 'pasta', 'steak', or 'grilled chicken special', these can all be aspect terms for the aspect category 'food'. As such, an aspect category referred to by one or more specific aspect terms is called an explicit aspect. On the other hand, the aspect category like 'price', which does not have any specific aspect terms but can be indirectly guessed with an emotional word 'expensive,' is called an implicit aspect. So far, the 'aspect category' has been used to avoid confusion about 'aspect term'. From now on, we will consider 'aspect category' and 'aspect' as the same concept and use the word 'aspect' more for convenience. And one thing to note is that ATSC analyzes the sentiment towards given aspect terms, so it deals only with explicit aspects, and ACSC treats not only explicit aspects but also implicit aspects. This study seeks to find answers to the following issues ignored in the previous studies when applying the BERT pre-trained language model to ACSC and derives superior ACSC models. First, is it more effective to reflect the output vector of tokens for aspect categories than to use only the final output vector of [CLS] token as a classification vector? Second, is there any performance difference between QA (Question Answering) and NLI (Natural Language Inference) types in the sentence-pair configuration of input data? Third, is there any performance difference according to the order of sentence including aspect category in the QA or NLI type sentence-pair configuration of input data? To achieve these research objectives, we implemented 12 ACSC models and conducted experiments on 4 English benchmark datasets. As a result, ACSC models that provide performance beyond the existing studies without expanding the training dataset were derived. In addition, it was found that it is more effective to reflect the output vector of the aspect category token than to use only the output vector for the [CLS] token as a classification vector. It was also found that QA type input generally provides better performance than NLI, and the order of the sentence with the aspect category in QA type is irrelevant with performance. There may be some differences depending on the characteristics of the dataset, but when using NLI type sentence-pair input, placing the sentence containing the aspect category second seems to provide better performance. The new methodology for designing the ACSC model used in this study could be similarly applied to other studies such as ATSC.

Deriving adoption strategies of deep learning open source framework through case studies (딥러닝 오픈소스 프레임워크의 사례연구를 통한 도입 전략 도출)

  • Choi, Eunjoo;Lee, Junyeong;Han, Ingoo
    • Journal of Intelligence and Information Systems
    • /
    • v.26 no.4
    • /
    • pp.27-65
    • /
    • 2020
  • Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

The Effect of the Quality of Education Service on the Performance of Education Service through Relationship Commitment in Franchise Beauty Academy: Moderating Effect of Trust Level (프랜차이즈 뷰티 아카데미의 교육서비스 품질이 관계 몰입을 통한 교육 서비스 성과에 미치는 영향 연구: 신뢰 수준의 조절효과)

  • Kim, Chang-Bong;Kim, Hee-Su
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
    • /
    • v.16 no.3
    • /
    • pp.193-211
    • /
    • 2021
  • Recently, interest in Korean Wave craze and K-beauty, led by K-pop, is increasing. In addition, the popularity and influence of the domestic beauty service industry has increased, and the economic and cultural ripple effects have been continuously expanding. The need to professional manpower training in response to the demand for manpower due to the growing development of domestic beauty services is emphasized, and the number of trainees who are actual consumers of beauty academy is increasing. Therefore, the purpose of our study is to examine the importance of quality factors of educational services to achieve educational purposes in the educational services provided by the Beauty Academy and the relationship between relationship commitment and educational service performance. Furthermore, it is to draw the importance of administrative support services, educational programs as well as educational service provision activities. However, the research for professional manpower training according to the provision of beauty services is insufficient compared to the development speed of the beauty industry. Therefore, at the present time when beauty service education is emphasized, our study will examine the relationship between relationship commitment and educational service performance based on the quality of education service by the students of domestic beauty academy. The measurement variables set for our study are program, instructor quality, tuition, external service, service fairness, relationship commitment, trust level, and educational service performance. The variables were analyzed and derived through the survey, and the following contents were derived from the empirical analysis. First, the quality of education service provided by the beauty academy, such as program, external service, service fairness, relationship commitment and trust level, had a significant effect on relationship commitment. Educational services provided by the institute, such as the systematicity and diversity of educational programs, enabled students to have a uniform relationship commitment. The quality of education service itself is to learn the expertise necessary for providing beauty service from the standpoint of the students and play an organic role in the relationship with the institute. Second, the moderating effect of trust level between academies and students was significant in the quality of education service and the relationship commitment. This means that students will feel higher level of service quality through the practical trust relationship of the students about the educational services provided by the institute. Based on the results of the empirical analysis, the implications of our study are to find ways to improve the students' ability and satisfaction represented by the results of educational services. This is because the quality of education services provided by the institute called Beauty Academy will have a great impact on the career choice of educational facilities and students. The characteristics of consistency, convenience, and knowledge orientation of education itself should be considered comprehensively, and a strong market position should be established through image formation through external service factors, which are external environments of academies.Furthermore, in terms of presenting differentiated strategies with competitors, the educational service quality factors play a significant role in the commitment to the relationship with the students, so the role of relationship marketing will be important for the psychological stability experienced by the students by grasping the demand accompanying the behavior of the students in advance.

The oldest Maehyang-bi (埋香碑) of Memorial Inscriptions existing on record; Yeong-am's 'Jeongwon (貞元)' Stone Monument (현존 최고(最古)의 매향비(埋香碑): 영암 정원명(貞元銘) 석비(石碑))

  • Sung, Yungil
    • Korean Journal of Heritage: History & Science
    • /
    • v.54 no.1
    • /
    • pp.70-99
    • /
    • 2021
  • Yeong-am's 'Jeongwon (貞元)' stone monument, designated as the Jeollanam-do Cultural Heritage, is considered to be the oldest of the epigraphs in Jeollanam-do. Immediately after the discovery, the possibility of it being a Maehyangbi of Memorial Inscriptions was mentioned and attracted attention. However, there is an absolute age of the 'Jeongwon (貞元) of 2 years' (786), so despite it is a relatively early epigraph (金石文), there are not many papers on the theme related to this stone monument. I believe that this stone monument is a Maehyangbi (埋香碑). While reviewing and comparing the results of the existing research, I decoded the text from the 42nd character of the 4th line. As a result of the review, that was conducted, it was confirmed that this stone monument is truly a Maehyangbi (埋香碑). In particular, it was recorded in the literature of the late Joseon Dongguk-myungsanggi (東國名山記) that the letters of the Maehyangbi (埋香碑) are not recognizable. However, it is clearly stated that this stone monument is a Maehyangbi (埋香碑). Although there is no common expression for 'bury (埋)' or 'incense burial (埋香)' in the traditional Maehyangbi (埋香碑), which were popular in the late Goryeo and early Joseon Periods, it can be seen that it is a Maehyangbi (埋香碑) from the words "hide (呑藏)" and "10 bundles of fragrant incense (合香十束)" that are engraved on the stone monument with the name 'Jeongwon.' In other words, it is thought that it meant 'hide (呑藏)' instead of 'bury (埋)'. Circumstantial evidence for the monument of Jingamseonsa (眞鑑禪師), built in 888, contains the an epigraph from the Unified Silla Era. There is a phrase on it that says 'Plant incense on the shore (海岸植香)' on the monument of Jingamseonsa (眞鑑禪師), and it conveys its meaning without using the character 'bury (埋)'. As a result of the absence of the character 'bury (埋)' on the stone monument with the name 'Jeongwon', it is not considered as a Maehyangbi (埋香碑). However, there is evidence that the stone monument with the name 'Jeongwon (貞元)' is in fact a Maehyangbi (埋香碑) and it is also in the Geumpyoseok (禁標石; Forbidden Stone) around Gukjangsaeng (國長生) and at the entrance of Dogapsa Temple (道甲寺). The letters written on the gold sign suggest the possibility that the charcoal used to burn incense (香炭) at the royal tombs of King Jeongjo (正祖) was produced around at Dogapsa Temple (道甲寺) in Wolchulsan (月出山). Since the charcoal used to burn incense (香炭) is naturally related to incense (香), it has been shown that the area around Wolchulsan, where Dogapsa Temple is located, has a long history related to incense (香). The letters visible on the stone monument, the record of Dongguk-myungsanggi (東國名山記) in the late Joseon Dynasty, and the letters on the Geompyoseok (禁標石; Forbidden Stone), all show that the stone monument with the name 'Jeongwon (貞元)' is a Maehyangbi (埋香碑). Considering the fact that the earliest Maehyangbi (埋香碑) in existence is the Maehyangbi (埋香碑) in Yeongam (靈巖) Ippam-ri (笠巖里), which has two dates from 1371 at the end of Goryeo and 1410 at the beginning of Joseon, the stone monument with the name 'Jeongwon' which was set up in 786, would be the oldest Maehyangbi (埋香碑) that we know of. In addition, there is a historical significance in that the Maehyangbi (埋香碑) is proven in the record of Dongguk-myungsanggi (東國名山記), a document from the late Joseon period.

Dedicatory Inscriptions on the Amitabha Buddha and Maitreya Bodhisattva Sculptures of Gamsansa Temple (감산사(甘山寺) 아미타불상(阿彌陁佛像)과 미륵보살상(彌勒菩薩像) 조상기(造像記)의 연구)

  • Nam, Dongsin
    • MISULJARYO - National Museum of Korea Art Journal
    • /
    • v.98
    • /
    • pp.22-53
    • /
    • 2020
  • This paper analyzes the contents, characteristics, and historical significance of the dedicatory inscriptions (josanggi) on the Amitabha Buddha and the Maitreya Bodhisattva statues of Gamsansa Temple, two masterpieces of Buddhist sculpture from the Unified Silla period. In the first section, I summarize research results from the past century (divided into four periods), before presenting a new perspective and methodology that questions the pre-existing notion that the Maitreya Bodhisattva has a higher rank than the Amitabha Buddha. In the second section, through my own analysis of the dedicatory inscriptions, arrangement, and overall appearance of the two images, I assert that the Amitabha Buddha sculpture actually held a higher rank and greater significance than the Maitreya Bodhisattva sculpture. In the third section, for the first time, I provide a new interpretation of two previously undeciphered characters from the inscriptions. In addition, by comparing the sentence structures from the respective inscriptions and revising the current understanding of the author (chanja) and calligrapher (seoja), I elucidate the possible meaning of some ambiguous phrases. Finally, in the fourth section, I reexamine the content of both inscriptions, differentiating between the parts relating to the patron (josangju), the dedication (josang), and the prayers of the patrons or donors (balwon). In particular, I argue that the phrase "for my deceased parents" is not merely a general axiom, but a specific reference. To summarize, the dedicatory inscriptions can be interpreted as follows: when Kim Jiseong's parents died, they were cremated and he scattered most of their remains by the East Sea. But years later, he regretted having no physical memorial of them to which to pay his respects. Thus, in his later years, he donated his estate on Gamsan as alms and led the construction of Gamsansa Temple. He then commissioned the production of the two stone sculptures of Amitabha Buddha and Maitreya Bodhisattva for the temple, asking that they be sculpted realistically to reflect the actual appearance of his parents. Finally, he enshrined the remains of his parents in the sculptures through the hole in the back of the head (jeonghyeol). The Maitreya Bodhisattva is a standing image with a nirmanakaya, or "transformation Buddha," on the crown. As various art historians have pointed out, this iconography is virtually unprecedented among Maitreya images in East Asian Buddhist sculpture, leading some to speculate that the standing image is actually the Avalokitesvara. However, anyone who reads the dedicatory inscription can have no doubt that this image is in fact the Maitreya. To ensure that the sculpture properly embodied his mother (who wished to be reborn in Tushita Heaven with Maitreya Bodhisattva), Kim Jiseong combined the iconography of the Maitreya and Avalokitesvara (the reincarnation of compassion). Hence, Kim Jiseong's deep love for his mother motivated him to modify the conventional iconography of the Maitreya and Avalokitesvara. A similar sentiment can be found in the sculpture of Amitabha Buddha. To this day, any visitor to the temple who first looks at the sculptures from the front before reading the text on the back will be deeply touched by the filial love of Kim Jiseong, who truly cherished the memory of his parents.