• Journal of Korean Society of Forest Science
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• v.100 no.4
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• pp.672-680
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• 2011

The purpose of this study has been carried to develop a criterion for the selection of evaluation factors on Forest Carbon Cycle Community(F.C.C.C) based on the result of survey of 96 participants who were operation managers on mountain eco village(31), relevant experts(33), and officers of local government(32). For analysis of the results of survey, DHP(Delphi Hierarchy Process) method was used which is a combination of Delphi method and AHP(Analytic Hierarchy Process) method. The key factors on selection of a suitable area to launch F.C.C.C. project of Korea Forest Service was selected under three hierarchical classes. Class 1 comprises 3 indices(Physical resource index, Human resource index, Vision index), and Class 2 which contains 10 indices (Existing resource, Surroundings resource, Forest biomass resource, Humanities Social quality, Local resident participation, Leader's ability, External support, Planning of operation, Capability of operation, and Effect of operation). Class 3 is sub-level class of class which possess 38 indices. From the results of analysis, Consistency Index(C.I) of each index in the 3 classes was used as evaluation factor. In Class 1, index 'human resources' showed highest Consistency Index(0.454). In Class 2, index 'forest biomass resources' was the highest Consistency Index(0.376) in 'physical resources' of Class 1, index 'leader's ability' was the highest Consistency Index(0.326) in 'human resources' of Class 1, and index 'planning of operation' was the highest Consistency Index(0.346) in 'vision' of Class 1. In Class 3, relative importance of 38 index including 'Joint ownership land security(C.I.-0.266)' was evaluated. Based on the result of this study, a criterion for the selection of evaluation factors for F.C.C.C was developed and the evaluation criterion is expected to be use to select of a suitable area to launch F.C.C.C. project since 2011.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.67-86
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• 2020

Recommender Systems have been huge influence users and business more and more. Recently the importance of E-commerce has been reached rapid growth greatly in world-wide COVID-19 pandemic. Recommender system is the center of E-commerce lively. Top ranked E-commerce managers mentioned that recommender systems have a major influence on customer's purchase such as about 50% of Netflix, Amazon sales from their recommender systems. Most algorithms have been focused on improving accuracy of recommender system regardless of novelty, diversity, serendipity etc. Recommender systems with only high accuracy cannot satisfy business long-term profit because of generating sales polarization. In addition, customers do not experience enjoyment of shopping from only focusing accuracy recommender system because customer's preference is changed constantly. Therefore, recommender systems with various values need to be developed for user's high satisfaction. Reranking is the most useful methodology to realize diversity of recommender system. In this paper, diversity of recommender system is represented through constructing high similarity with users who have different preference using each user's purchased item's category algorithm. It is distinguished from past research approach which is changing the algorithm of recommender system without user's diversity preference level. We tried to discover user's diversity preference level and observed the results how the effect was different according to user's diversity preference level. In addition, graph-based recommender system was used to show diversity through user's network, not collaborative filtering. In this paper, Amazon Grocery and Gourmet Food data was used because the low-involvement product, such as habitual product, foods, low-priced goods etc., had high probability to show customer's diversity. First, a bipartite graph with users and items simultaneously is constructed to make graph-based recommender system. However, each users and items unipartite graph also need to be established to show diversity of recommender system. The weight of each unipartite graph has played crucial role changing Jaccard Distance of item's category. We can observe two important results from the user's unipartite network. First, the user's diversity preference level is observed from the network and second, dissimilar users can be discovered in the user's network. Through the research process, diversity of recommender system is presented highly with small accuracy loss and optimalization for higher accuracy is possible controlling diversity ratio. This paper has three important theoretical points. First, this research expands recommender system research for user's satisfaction with various values. Second, the graph-based recommender system is developed newly. Third, the evaluation indicator of diversity is made for diversity. In addition, recommender systems are useful for corporate profit practically and this paper has contribution on business closely. Above all, business long-term profit can be improved using recommender system with diversity and the recommender system can provide right service according to user's diversity level. Lastly, the corporate selling low-involvement products have great effect based on the results.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.1
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• pp.1-18
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• 2021

This study was intended to present measures for the improvement of the apartment house landscaping supervision system by examining the adequacy of landscaping supervision, which is aimed at improving the quality of landscape plants and facilities in apartment house landscaping sites. Additionally, this study aims to identify the problems occurring in the process of the performance of landscaping supervision and to provide the evidence for legislative activities and revision of the laws currently being pushed forward for the mandatory deployment of apartment house landscaping supervision personnel. The results of the analysis showed that no landscaping supervision personnel was deployed to apartment complexes with less than 1,500 households and that the landscaping comprised 19% to 46% of the entire construction process. The civil engineering firm performed the landscaping supervision, which made it impracticable to fully focus on the construction quality in the field of landscaping. The quality control in terms of landscape plants revealed differences in quality control, depending on the competence and experience of the civil engineer supervising the personnel, where the landscaping supervision personnel was not deployed. The apartment houses landscaping supervision activity index was analyzed, and the results showed that the supervision activity index for apartment house A was 72.0, B was 70.4, and apartment houses C to G ranged from 38.7 to 46.9, which suggested that the difference in quality control, process control, and technical support affected the construction quality and occurrence of defects.The improvement of landscaping process quality control and process management will be carried out more smoothly and the rate of defects will be drastically reduced if the landscaping supervision personnel placement threshold is lowered from 1,500 households to 300 households in complexes. The results of this study are expected to be useful in promoting and re-establishing the landscaping industry based on the improvement of construction quality in the field of landscaping in connection with the construction of apartment houses.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.42-51
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• 2020

This study was performed to support the 6th forest basic planning by Korea Forest Service as predicting the change of forestland area by the transition of land use type in the future over 35 years in South Korea. It is very important to analyze upcoming forestland area change for future forest planning because forestland plays a basic role to predict forest resources change for afforestation, production and management in the future. Therefore, the transitional interaction between land use types in future of South Korea was predicted in this study using econometrical models based on past trend data of land use type and related variables. The econometrical model based on maximum discounted profits theory for land use type determination was used to estimate total quantitative change by forestland, agricultural land and urban area at national scale using explanatory variables such as forestry value added, agricultural income and population during over 46 years. In result, it was analyzed that forestland area would decrease continuously at approximately 29,000 ha by 2027 while urban area increases in South Korea. However, it was predicted that the forestland area would be started to increase gradually at 170,000 ha by 2050 because urban area was reduced according to population decrement from 2032 in South Korea. We could find out that the increment of forestland would be attributed to social problems such as urban hollowing and localities extinction phenomenon by steep decrement of population from 2032. The decrement and increment of forestland by unbalanced population immigration to major cities and migration to localities might cause many social and economic problems against national sustainable development, so that future strategies and policies for forestland should be established considering such future change trends of land use type for balanced development and reasonable forestland use and conservation.

• Journal of Korean Society of Forest Science
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• v.111 no.1
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• pp.61-71
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• 2022

Data from an investigation of vulnerable conifer species in the subalpine zone in Korea obtained by the Korea Forest Service in 2017-2018 and monitoring research conducted by the National Institute of Forest Science since 2014 were used to analyze the status of distribution and growing condition of three major conifer species (Abies nephrolepis, Abies koreana, and Picea jezoensis) in the subalpine zone in the Baekdudaegan protected area. The distribution area of the studied species in the Baekdudaegan protected area was ca. 74% (8,035 ha) of the total distribution area in Korea, indicating that Baekdudaegan is a core area for conservation and restoration of subalpine conifer species. From decline index [A. nephrolepis in Mt. Taebaeksan and Mt. Deogyusan increased by 77.3% and 29.6%, respectively; A. koreana in Mt. Jirisan (Chunwangbong Peak) increased by 45.2% in four years; and P. jezoensis in Mt. Jirisan (Chunwangbong Peak) increased by 47.8% in two years] and seedling frequency (lower frequency of newly recruited seedlings than dead seedlings) results, the studied species are expected to face difficulties in sustainability. In contrast, at Mt. Seseoksan and Chunwangbong Peak in Mt. Jirisan, the health of trees and seedling frequency showed a partial tendency to recover and increase. In addition, we identified the relationship between the decline index and seedling frequency. These results will support the implementation of conservation strategies for vulnerable conifer species in the subalpine zone.

• 한국노년학
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• v.41 no.2
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• pp.197-215
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• 2021

This study aims to evaluate Person Centered Care practice and characteristics of care services in Korean long-term care facilities using Dementia Care Mapping as a tool. DCM, systematic observational evaluation tool for measuring dementia patients' QOL, was transformed into self-report rating scale. The process of transforming DCM into a scale of 34 items involves operationalization of DCM concepts and it's adaptation into Korean long-term care practices. Review by research team of Bradford university was added to maintain DCM concept and meaning in this scale. The scale with Cronbach alpha of .88 was surveyed on 343 care workers. Survey result shows PCC value practiced by them is 3.77(of 5 likert scale) and values on each categories of PCC reveal the characteristics of care in Korean facilities; attachment(4.02), comfort(3.95), inclusion(3.89), identity(3.67) and occupation(3.41). Dementia care in Korean facilities focuses on recipients'safety, comfort but lacks individualistic care and the meaningful and fulfilling occupation for patients. Looking at the organizational and individual factors influencing DCM values, the small facilities showed higher PCC values and there are no significant difference in PCC values between public and private facilities. Managers and care workers with career of 1~2 years showed higher PCC values compared to other career ranks and lengthes. This study suggests care practice should be centered on personhood of patients in long-term care facilities, for which introduction of unit care and education of PCC for service providers including support personnel are needed. DCM and Korean DCM scale developed in this study are suggested for the PCC-based assessment on care quality.

• Korean small business review
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• v.43 no.4
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• pp.59-93
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• 2021

This study surveyed 413 small business owners who experienced closure to see how the loss perception experienced by small business owners affects their comeback through fear of failure. The analysis results are as follows. First, the larger the received loss of financial capital, market capital, and social capital, the greater the fear of failure. Second, the greater the fear of failure, the less willingness to re-start-up, but it did not affect the willingness to work. Third, perceived loss of financial capital, market capital, and social capital grew fear of failure, which negatively affected the willingness to re-start. However, as for the willingness to work, only the perception of loss to market competitiveness strengthened the willingness to work through fear of failure. This suggests that if you think you are out of business due to market competitiveness, you are more likely to choose to get a job than to start a business. Fourth, those with higher entrepreneurial self-efficiency had less effect of perceived loss on fair of failure than those with lower entrepreneurial loss. In other words, it can be seen that a person with high entrepreneurial self-efficiency is likely to start-up. It is noteworthy that despite the tendency to fail due to market competition and lack of understanding of risks, small business operators were most aware of the loss of social capital. This is presumed to have had the greatest impact on fear of failure because small business owners try to receive funding or business revitalization support through social networks such as acquaintances and relatives. Based on the above results, this study requires sufficient market research to secure a competitive advantage when preparing for start-ups through policy practice suggestions, and suggests ways to reduce financial loss through the establishment of sophisticated business plans.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.35-43
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• 2023

The purpose of this study is to research digital twin policies for the use of administrative services. The study was conducted through a mobile survey of 1,000 participants, and the results are as follows. First, in order to utilize digital twin technology, it is necessary to first identify appropriate services that can be applied from the perspective of Gyeonggi Province. Efforts to identify digital twin services that are suitable for Gyeonggi Province's field work should be prioritized, and this should lead to increased efficiency in the work. Second, Gyeonggi Province's digital twin administrative services should prevent duplication with central government projects and establish a model that can be connected and utilized. It should be driven around current issues in Gyeonggi Province and the demands of citizens for administrative services. Third, to develop Gyeonggi Province's digital twin administrative services, a standard model development plan through participation in pilot projects should be considered. Gyeonggi Province should lead the project as the main agency and promote it through a collaborative project agreement. It is suggested that a support system for the overall project be established through the Gyeonggi Province Digital Twin Advisory Committee. Fourth, relevant regulations and systems for the construction, operation, and management of dedicated departments and administrative services should be established. To achieve the realization of digital twins in Gyeonggi Province, a dedicated organization that can perform various roles in project promotion and operation, as well as legal and institutional improvements, is necessary. To designate a dedicated organization, it is necessary to consider expanding and reorganizing existing departments and evaluating the operation of newly established departments. The limitation of this study is that it only surveyed participants from Gyeonggi Province, and it is recommended that future research be conducted nationwide. The expected effect of this study is that it can serve as a foundational resource for applying digital twin services to public work.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.