• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2993-3002
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• 2018

This case study introduces the process of developing the technology rating evaluation model for investment. The technology evaluation rating model for investment is a project that the Financial Services Commission and the Ministry of Commerce, Industry and Energy collaborated to expand the scope of technology finance from loan to investment. The technology evaluation model for investment was developed with the aim of predicting high growth companies. The model consists of a statistical model and an expert model. Here, statistical models were modeled by using logistic regression analysis. Expert models gathered opinions of experts and identified the weight of each evaluation item and set the model. The rating system of the model is composed of 10 grades. The distribution of the model was consistent with KTRS grade distribution. Interestingly, the emphasis is on technology and marketability. In the technology valuation grade model for the goddess, there is a considerable difference from the emphasis on managerial competence or business performance.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.93-103
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• 2021

Despite the efforts of financial authorities in conducting the direct management and supervision of collection agents and bond-collecting guideline, the illegal and unfair collection of debts still exist. To effectively prevent such illegal and unfair debt collection activities, we need a method for strengthening the monitoring of illegal collection activities even with little manpower using technologies such as unstructured data machine learning. In this study, we propose a classification model for illegal debt collection that combine machine learning such as Support Vector Machine (SVM) with a rule-based technique that obtains the collection transcript of loan companies and converts them into text data to identify illegal activities. Moreover, the study also compares how accurate identification was made in accordance with the machine learning algorithm. The study shows that a case of using the combination of the rule-based illegal rules and machine learning for classification has higher accuracy than the classification model of the previous study that applied only machine learning. This study is the first attempt to classify illegalities by combining rule-based illegal detection rules with machine learning. If further research will be conducted to improve the model's completeness, it will greatly contribute in preventing consumer damage from illegal debt collection activities.

• Journal of Korean Library and Information Science Society
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• v.51 no.4
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• pp.185-210
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• 2020

The library faced an unexpected crisis of COVID-19, and as a countermeasure strategy, non-face-to-face online service has been reinforced. Therefore, this study attempted to present a plan to overcome the challenges arising from rapidly changing external environment and current crisis. To this end, data search, electronic library, library service, cultural event and open space management status of 288 public libraries serviced as an integrated site were investigated. Based on this, the meaning of online services in the post-COVID-19 era and the implication of it were examined. As a result, first, the increase in the use rate of online data search services with the spread of non-face-to-face culture, second, the expansion of the services of the electronic library, third, the diversification of non-face-to-face, online services, fourth, expansion of online cultural event services, fifth, the diversification of open space services were proposed, sixth, Introduced an artificial intelligence system for unattended loan return based on access and the Seventh, expansion of experiential cultural support services and educational contents through VR, AR and MR. It is deemed necessary for the research on the future direction of the library's non-face-to-face services to be conducted by investigating the current status of online services in various types of libraries and the types and case studies of library services in the era of COVID-19.

• Land and Housing Review
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• v.13 no.4
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• pp.13-26
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• 2022

This study analyzes housing choice determinants of the youth and newlyweds households by using housing survey data in Incheon. A multinomial logit model is employed for analysis with the following variables: housing characteristics, housing market characteristics, and residential and neighborhood environment characteristics. The findings from the analysis are as follows. First, for the continued residence of the youth, the important factors were the relief assistance of housing maintenance costs. For the newlyweds, the important factors were the quality improvement of residential environments to ensure residential stability. Second, the housing choice factors to attract the youth were residential support for rent, maintenance costs, and relocation, and the improvements of residential environments such as security, noise levels, and medical facilities. For the newlyweds, the important factors were housing loan assistance for a home purchase or a cheonsei deposit and residential quality improvements for air pollution and parking facilities. Third, the youth were likely to move out due to high rental costs, and the newlyweds were likely to move out for the purchase of a new apartment or higher-quality housing.

• Journal of Korean Library and Information Science Society
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• v.52 no.1
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• pp.155-178
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• 2021

In the era of the 4th industrial revolution, public libraries need a strategy for promoting intelligent library services in order to actively respond to changes in the external environment such as artificial intelligence. Therefore, in this study, based on the concept of artificial intelligence and analysis of domestic and foreign artificial intelligence related trends, policies, and cases, we proposed the future direction of introduction and development of artificial intelligence services in the library. Currently, the library operates a reference information service that automatically provides answers through the introduction of artificial intelligence technologies such as deep learning and natural language processing, and develops a big data-based AI book recommendation and automatic book inspection system to increase business utilization and provide customized services for users. Has been provided. In the field of companies and industries, regardless of domestic and overseas, we are developing and servicing technologies based on autonomous driving using artificial intelligence, personal customization, etc., and providing optimal results by self-learning information using deep learning. It is developed in the form of an equation. Accordingly, in the future, libraries will utilize artificial intelligence to recommend personalized books based on the user's usage records, recommend reading and culture programs, and introduce real-time delivery services through transport methods such as autonomous drones and cars in the case of book delivery service. Service development should be promoted.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.2
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• pp.49-67
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• 2021

The school library provides a mobile web service that allows access to the library catalog system, and provides services that reflect the needs of search and consider the characteristics of mobile devices. Therefore, this study conducted a literature review, an analysis of the current status of school library mobile web services, and a survey of the mobile service user experience of students and teachers to find the contents and service plans for school library mobile app services that meet the school library mobile needs. Based on the survey, the contents and design plan of the school library DLS mobile service was prepared. First, the steps were reduced from step 4 to step 3. In the first step, solution of screen clipping errors in registering as a member and various login platforms for accessibility are needed. In the second step, integrated search and detailed search, provision of materials for use and reading education, post-booking activities, guides and announcements on the use of the affiliated school library, inter-loan, and e-books are provided as main menu. In the third step, it was proposed to provide related functions such as reservations as well as the display of the detailed screen of the search results of the collection. This study can be used not only to develop dedicated mobile app services, but also to change current web-based mobile services.

• Journal of Korean Library and Information Science Society
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• v.52 no.4
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• pp.79-102
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• 2021

This research is based on open data from the National Library Statistics System and Seoul Survey 2020 from Seoul to analyze the Seoul citizens' usage of public libraries. For such purposes, this research compared and diagnosed the condition of public libraries services at 25 districts of Seoul, focusing on objective indicators of library management and general usage records to understand the correlations between the two. Objective indicators such as budgets, human labor, the number of books, and total ground area were compared with usage records of different classes of Seoul citizens, organized by the citizens' place of living, educational background, and monthly household income. As a result of the research, the correlation between the objective indicators and public usage records of different classes was confirmed. Seoul citizens' usage of public libraries and reading tendency were identified. In addition to, a balanced development of the public libraries in Seoul was proposed to overcome regional disparities and leveling the service level by investigating usage behavior and reading tendency of the public libraries in Seoul.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.307-332
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• 2022

One of the most intensively conducted research areas in business application study is a bankruptcy prediction model, a representative classification problem related to loan lending, investment decision making, and profitability to financial institutions. Many research demonstrated outstanding performance for bankruptcy prediction models using artificial intelligence techniques. However, since most machine learning algorithms are "black-box," AI has been identified as a prominent research topic for providing users with an explanation. Although there are many different approaches for explanations, this study focuses on explaining a bankruptcy prediction model using a counterfactual example. Users can obtain desired output from the model by using a counterfactual-based explanation, which provides an alternative case. This study introduces a counterfactual generation technique based on a genetic algorithm (GA) that leverages both domain knowledge (i.e., causal feasibility) and feature importance from a black-box model along with other critical counterfactual variables, including proximity, distribution, and sparsity. The proposed method was evaluated quantitatively and qualitatively to measure the quality and the validity.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.332-342
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• 2022

Kale (Brassica oleracea var. acephala) is one of the most frequently consumed leafy vegetables globally, as it contains numerous nutrients; essential amino acids, phenolics, vitamins, and minerals, and is particularly rich in glucosinolates. However, the differences in the biosynthesis of glucosinolates and related gene expression among kale cultivars has been poorly reported. In this study, we investigated glucosinolates profile and content in three different kale cultivars, including green ('Man-Choo' and 'Mat-Jjang') and red kale ('Red-Curled') cultivars grown in a vertical farm, using transcriptomic and metabolomic analyses. The growth and development of the green kale cultivars were higher than those of the red kale cultivar at 6 weeks after cultivation. High-performance liquid chromatography (HPLC) analysis revealed five glucosinolates in the 'Man-Choo' cultivar, and four glucosinolates in the 'Mat-Jjang' and 'Red-Curled' cultivars. Glucobrassicin was the most predominant glucosinolate followed by gluconastrutiin in all the cultivars. In contrast, other glucosinolates were highly dependent to the genotypes. The highest total glucosinolates was found in the 'Red-Curled' cultivar, which followed by 'Man-Choo' and 'Mat-Jjang'. Based on transcriptome analysis, eight genes were involved in glucosinolate biosynthesis. The overall results suggest that the glucosinolate content and accumulation patterns differ according to the kale cultivar and differential expression of glucosinolate biosynthetic genes.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.6
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• pp.869-877
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• 2022

This study aims to analyze the factors affecting the re-subscription period upon initial termination of the reverse mortgage subscription. The study utilized the Korea Housing Finance Corporation's database to extract the information regarding re-subscribers of the reverse mortgage from July 2007 to June 2021. The ordered logit model was employed and found that a set of user (subscriber) characteristics are influential towards the re-subscription period. Among the individual characteristics, changes in age group, marital status from married to single-living, maintaining single-living, and the initial subscription period were found statistically significant, highlighting that the increase in the initial subscription period decreased the re-subscription period. Among the housing (home equity) characteristics, changes in housing price and ownership type (single and partial ownership) were statistically significant, indicating that the change in ownership type decreases the re-subscription period. Lastly, the variables related to loan terms were found significant, revealing that changes in payout method and schedule were both increasing factors of the re-subscription period. Based on the findings, necessary policy implications can be considered to secure the returning subscribers of the reverse mortgage effectively.