• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.43-61
• /
• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Land and Housing Review
• /
• v.12 no.3
• /
• pp.11-26
• /
• 2021

With the increasing demand for office space, there have been questions on how office rent distribution produces a change in the urban spatial structure in Seoul. The purpose of this paper is to investigate a relative price gradient and to present a time-series model that can quantitatively explain the dynamic changes in the urban spatial structure. The analysis was dealt with office rent above 3,306 m² for the past 10 years from 1Q 2010 to 4Q 2019 within Seoul. A modified repeat sales model was employed. The main findings are briefly summarized as follows. First, according to the estimates of the office price gradient in the three major urban centers of Seoul, the CBD remained at a certain level with little change, while those in the GBD and the YBD continued to increase. This result reveals that the urban form of Seoul has shifted from monocentric to polycentric. This shows that the spatial distribution of companies has gradually accelerated decentralized concentration implying that the business networks have become significant. Second, contrary to small and medium-sized office buildings that have undertaken no change in the gradient, large office buildings have seen an increase in the gradient. The relative price gradients in small and medium-sized buildings were inversely proportional among the CBD, the GBD, and the YBD, implying their heterogeneous submarkets by office rent movements. Presumably, those differences in the submarkets were attributed to investment attraction, industrial competition, and the credit and preference of tenants. The findings are consistent with the hierarchical system identified in the Seoul 2030 Plan as well as the literature about Seoul's urban form. This research claims that the proposed method, based on the modified repeat sales model, is useful in understanding temporal dynamic changes. Moreover, the findings can provide implications for urban growth strategies under rapidly changing market conditions.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.24 no.2
• /
• pp.12-28
• /
• 2021

Based on the global smart city promotion trend, in 2018, the "Fourth Industrial Revolution Committee" selected "sustainability" and "people-centered" as keywords in relation to the direction of domestic smart city policy. Accordingly, the Living Lab program, which is an active citizen-centered innovation methodology, is applied to each stage of the domestic smart city construction project. Through the Living Lab program, and in collaboration with the public and experts, the smart city discovers local issues as it focuses on citizens, devises solutions to sustainable urban problems, and formulates a regional development plan that reflects the needs of citizens. However, compared to citizen participation in urban regeneration projects that have been operated for a relatively long time, participation in smart city projects was found to significantly differ in level and sustainability. Therefore, this study conducted a comparative analysis of the characteristics of citizen participation at each stage of an urban regeneration project and, based on Arnstein's "Participation Ladder" model, examined the level of citizen participation activities in the Living Lab program carried out in a smart city commercial area from 2018 to 2019. The results indicated that citizen participation activities in the Living Lab conducted in the smart city project had a great influence on selecting smart city services, which fit the needs of local residents, and on determining the technological level of services appropriate to the region based on a relatively high level of authority, such as selection of smart city services or composition of solutions. However, most of the citizen participation activities were halted after the project's completion due to the one-off recruitment of citizen participation groups for the smart city construction project only. On the other hand, citizens' participation activities in the field of urban regeneration were focused on local communities, and continuous operation and management measures were being drawn from the project planning stage to the operation stage after the project was completed. This study presented a plan to revitalize citizen participation for the realization of a more sustainable smart city through a comparison of the characteristics and an examination of the level of citizen participation in such urban regeneration and smart city projects.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.177-190
• /
• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• Journal of Christian Education in Korea
• /
• v.70
• /
• pp.37-74
• /
• 2022

COVID-19, which occurred in Wuhan, China, made it difficult for Korean churches to face to face worship, therefore metaverse emerged as an alternative to solving these problems. metaverse is forming various platforms through technology expressed in 3I(Immersion, Interactive, virtual Image). The purpose of this study is to analyze the application plan of Christian education by applying metaverse technologies to Christian education. In order to achieve the purpose of this study, first, the definition, type, platform, and technology of the metaverse are presented to examine the key of the metaverse, second, in order to analyze the church from the theological educational aspect, the essence of the church, the mission of the church, and the metaverse church are examined, third in order to apply the metaverse to Christian education, it is classified into worship through the metaverse, education through the metaverse, service through the metaverse, the christian relationship through the metaverse, and missions through the metaverse. The application plan of the metaverse for Christian education is that first, worship can be held through metaverse. Second, education can be performed through the metaverse. Third, the metaverse can be used to fulfill the mission of service. Fourth, through the metaverse, christian can fellowship through the metaverse. Fifth, the missionary mission can be carried out through the metaverse. In conclusion, metaverse is still in the development stage, but various programs should be developed to achieve the purpose of Christian education by utilizing various platforms developed so far and utilizing the advantages of the platform. In particular, the Korean church will be able to utilize various programs such as Sunday worship, Sunday school, youth retreat, QT, Bible school, and pilgrimage through the metaverse to make good use of the characteristics of the metaverse. In addition, metaverse is an extended reality(XR) that integrates VR, AR, and MR, and its strength is an engagement in creative Christian educational activities out of the original Christian education. In the future, metaverse technology can be applied to Christian education in various ways as the fourth industrial technology is developing.

• Journal of Navigation and Port Research
• /
• v.46 no.1
• /
• pp.1-10
• /
• 2022

This study aims to investigate changes in the demand for ship officers in response to changes in the shipping industry environment in which Maritime Autonomous Surface Ships (MASS) emerge according to the application of the fourth industrial revolution technology to ships, and it looks into changes in the skill of ship officer. It also analyzes and proposes a plan for nurturing ship officers accordingly. As a result of the degree of recognition and AHP analysis, this study suggests that a new training system is required because the current training and education system may cover the job competencies of emergency response, caution and danger navigation, general sailing, cargo handling, seaworthiness maintenance, emergency response, and ship maintenance and management, but tasks such as remote control, monitoring diagnosis, device management capability, and big data analysis require competency for unmanned and shore-based control. By evaluating the importance of change factors in the duties of ship officers in Maritime Autonomous Surface Ships, this study provides information on ship officer educational institutions' response strategies for nurturing ship officers and prioritization of resource allocation, etc. The importance of these factors was compared and evaluated to suggest changes in the duties of ship officers and methods of nurturing ship officers according to the introduction of Maritime Autonomous Surface Ships. It is expected that the findings of this study will be meaningful as it systematically derives the duties and competency factors of ship officers of Maritime Autonomous Surface Ships from a practical point of view and analyzed the perception level of each relevant expert to diagnose expert-level responses to the introduction of Maritime Autonomous Surface Ships.

• Journal of Christian Education in Korea
• /
• v.74
• /
• pp.107-134
• /
• 2023

The purpose of this study is to provide a foundation for establishing the correct direction of education that utilizes artificial intelligence, a key technology of the Fourth Industrial Revolution, in the context of Christian education. To achieve this, theoretical and literature research was conducted. First, the research analyzed the historical development of artificial intelligence to understand its characteristics. Second, the research analyzed the use of artificial intelligence in convergence education from an educational perspective and examined the current policy direction in South Korea. Through this analysis, the research examined the direction of Christian education in the era of artificial intelligence. In particular, the research critically examined the perspectives of continuity and change in the context of Christian education in the era of artificial intelligence. The research reflected upon the fundamental educational purposes of Christian education that should remain unchanged despite the changing times. Furthermore, the research deliberated on the educational curriculum and teaching methods that should adapt to the changing dynamics of the era. In conclusion, this research emphasizes that even in the era of artificial intelligence, the fundamental objectives of Christian education should not be compromised. The utilization of artificial intelligence in education should serve as a tool that fulfills the mission permitted by God. Therefore, Christian education should remain centered around God, rooted in the principles of the Bible. Moreover, Christian education should aim to foster creative and convergent Christian nurturing. To achieve this, it is crucial to provide learners with an educational environment that actively utilizes AI-based hybrid learning environments and metaverse educational platforms, combining online and offline learning spaces. Moreover, to enhance learners' engagement and effectiveness in education, it is essential to actively utilize AI-based edutech that reflects the aforementioned educational environments. Lastly, in order to cultivate Christian learners with dynamic knowledge, it is crucial to employ a variety of teaching and learning methods grounded in constructivist theories, which emphasize active learner participation, collaboration, inquiry, and reflection. These approaches seek to align knowledge with life experiences, promoting a holistic convergence of faith and learning.

• Asia Marketing Journal
• /
• v.13 no.3
• /
• pp.25-53
• /
• 2011

This study probes the effect of loyalty program on the customer retention based on the real transaction data(n=2,892) acquired from education service industry. We try to figure out the outcomes of reward program through more than 1 year-long data gathered and analyzed according to quasi-experimental design(i.e., before and after design). We adopt this kinds of research scheme in regard that previous studies measured the effect of loyalty program by dividing the customers into two group(i.e., members vs. non-members) after the firms or stores had started the program. We believe that it might not avoid the self-selection bias. The research questions of this study could be explained such as: First, most research said that the loyalty programs could increase the customer loyalty and contribute to the sustainable growth of company. But there are little confirmation that this promotional tool could be justified in terms of financial perspective. Thus, we are interested in both the retention rate and financial outcomes caused by the introduction of loyalty programs. Second, reward programs target mainly current customer. Especially CRM(customer relationship management) said that it is more profitable for company to build positive relationship with current customer instead of pursuing new customer. And it claims that reward program is excellent means to achieve this goal. For this purpose, we check in this study whether there is a interaction effect between loyalty program and customer type in retaining customer. Third, it is said that dis-satisfied customers are more likely to leave the company than satisfied customers. While, Bolton, Kannan and Bramlett(2000) claimed that reward program could contribute to minimize the effect of negative service by building emotional link with customer, it is not empirically confirmed. This point of view explained that the loyalty programs might work as exit barrier to current customer. Thus, this study tries to identify whether there is a interaction effect between loyalty program and service experience in keeping customer. To achieve this purpose, this study adopt both Kaplan-Meier survival analysis and Cox proportional hazard model. The research outcomes show that the average retention period is 179 days before introducing loyalty program but it is increased to 227 days after reward is given to the customers. Since this difference is statistically significant, it could be said that H1 is supported. In addition, the contribution margin coming from increased transaction period is bigger than the cost for administering loyalty programs. To address other research questions, we probe the interaction effect between loyalty program and other factors(i.e., customer type and service experience) affecting it. The analysis of Cox proportional hazard model said that the current customer is more likely to engage in building relationship with company compared to new customer. In addition, retention rate of satisfied customer is significantly increased in relation to dis-satisfied customer. Interestingly, the transaction period of dis-satisfied customer is notably increased after introducing loyalty programs. Thus, it could be said that H2, H3, and H4 are also supported. In summary, we found that the loyalty programs have values as a promotional tool in forming positive relationship with customer and building exit barrier.

• Journal of Practical Engineering Education
• /
• v.15 no.1
• /
• pp.119-126
• /
• 2023

Today, in order to improve fuel efficiency and dynamic behavior of automobiles, an era of light weight and simplification of automobile parts is being formed. In order to simplify and design and manufacture the shape of the product, various components are integrated. For example, in order to commercialize three products into one product, product processing is occurring to a very narrow area. In the case of existing parts, precision die casting or casting production is used for processing convenience, and the multi-piece method requires a lot of processes and reduces the precision and strength of the parts. It is very advantageous to manufacture integrally to simplify the processing air and secure the strength of the parts, but if a deep and narrow pocket part needs to be processed, it cannot be processed with the equipment's own spindle. To solve a problem, research on cutting processing is being actively conducted, and multi-axis composite processing technology not only solves this problem. It has many advantages, such as being able to cut into composite shapes that have been difficult to flexibly cut through various processes with one machine tool so far. However, the reality is that expensive equipment increases manufacturing costs and lacks engineers who can operate the machine. In the five-axis cutting processing machine, when producing products with deep and narrow sections, the cycle time increases in product production due to the indirectness of tools, and many problems occur in processing. Therefore, dedicated machine tools and multi-axis composite machines should be used. Alternatively, an angle spindle may be used as a special tool capable of multi-axis composite machining of five or more axes in a three-axis machining center. Various and continuous studies are needed in areas such as processing vibration absorption, low heat generation and operational stability, excellent dimensional stability, and strength securing by using the angle spindle.

• Journal of Venture Innovation
• /
• v.3 no.2
• /
• pp.1-21
• /
• 2020

Recently, the emergence of new technologies caused by the Fourth Industrial Revolution caused a great change not only in the overall society but also in the retail industry. In the retail industry, unmanned stores based on new technologies have emerged, changing the consumption behavior of consumers. In particular, the global pandemic caused by COVID-19, which appeared in December 2019, raised social risks, and as a result of this, the beginning of the non-face-to-face era, interest in unmanned stores is increasing. In this study, the effects of benefits factors (perceived usefulness, perceived economics, perceived enjoyment, relative advantages) and sacrifice factors (perceived risk, technicality) perceived by unmanned store users on continuous use intention through perceived value. In addition, it is a study to test through empirical analysis what role the social risk from COVID-19 plays in the process of consumption through unmanned stores. The purpose of this study is to provide strategic implications for the activation of unmanned stores in the non-face-to-face era. In this study, a total of 293 copies of data were collected for users of unmanned stores for hypothesis testing. In addition, the collected data was analyzed using SPSS 21.0 and AMOS 21.0 statistical programs. The results of the study are summarized as follows. First, it was found that the perceived benefits (perceived usefulness, perceived economics, perceived playfulness, and relative advantages) of unmanned stores all had a significant positive effect on perceived value. Second, it was found that all perceived sacrifices (perceived risk, technicality) of unmanned stores had a significant negative effect on perceived value. Third, it was found that the perceived value of unmanned stores had a significant positive effect on the intention to continue use. Finally, the social risk from COVID-19 has been shown to play a moderating role when the perceived sacrifice of unmanned stores affects the perceived value.