• Information Systems Review
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• v.21 no.4
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• pp.47-68
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• 2019

As cloud services and deployment models become diverse, there are a growing number of cloud computing selection options. Therefore, financial companies need a methodology to select the appropriated cloud for each financial computing system. This study adopted the Balanced Scorecard (BSC) framework to classify factors for the introduction of cloud computing in financial companies. Using Analytic Hierarchy Process (AHP), the evaluation items are layered into the performance perspective and the cloud consideration factor and a comprehensive decision model is proposed. To verify the proposed research model, a system of financial company is divided into three: account, information, and channel system, and the result of decision making by both financial business experts and technology experts from two financial companies were collected. The result shows that some common factors are important in all systems, but most of the factors considered are very different from system to system. We expect that our methodology contributes to the spread of cloud computing adoption.

• Korean Journal of Ecology and Environment
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• v.57 no.2
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• pp.83-91
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• 2024

This study utilizes association rule learning and clustering analysis to explore the co-occurrence and relationships within ecosystems, focusing on the endangered brackish-water snail Clithon retropictum, classified as Class II endangered wildlife in Korea. The goal is to analyze co-occurrence patterns between brackish-water snails and other species to better understand their roles within the ecosystem. By examining co-occurrence patterns and relationships among species in large datasets, association rule learning aids in identifying significant relationships. Meanwhile, K-means and hierarchical clustering analyses are employed to assess ecological similarities and differences among species, facilitating their classification based on ecological characteristics. The findings reveal a significant level of relationship and co-occurrence between brackish-water snails and other species. This research underscores the importance of understanding these relationships for the conservation of endangered species like C. retropictum and for developing effective ecosystem management strategies. By emphasizing the role of a data-driven approach, this study contributes to advancing our knowledge on biodiversity conservation and ecosystem health, proposing new directions for future research in ecosystem management and conservation strategies.

• Journal of Christian Education in Korea
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• v.77
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• pp.171-201
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• 2024

Purpose of Research : Since ChatGPT's 2022 release, the educational sector faces mixed reactions to generative AI, sparking innovation but raising concerns about student cognition and communication. While Christian colleges employ AI reflecting their values, secular institutions stress ethical usage. This study explores ethical AI use in these settings, aiming to integrate findings into educational practices. Research content and method : Analyzing AI use and ethics guidelines from 50 domestic and international universities, differences between Christian and secular institutions were explored. Data was categorized, conceptualized via open coding, and components were identified through axial coding. The importance of components for Christian colleges' AI guides was assessed based on the initial data and previous research, leading to the development of tailored AI utilization components for Christian universities. Conclusion : Studies revealed secular institutions have six AI guide components, while Christian colleges found seven in both utilization and ethics guides, focusing on truthfulness, responsibility, and diversity. Emphasizing the need for ethical AI use in Christian colleges, the findings advocate developing AI ethics guidelines to aid marginalized groups and establish a new educational paradigm through further research.

• Journal of the Korean Geographical Society
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• v.40 no.1 s.106
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• pp.126-152
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• 2005

In recent years, there are some confusions related to the definition and existence of mountain ranges, which have been described in current geography text books. We contend that these confusions came from the lack of understanding on the geomorphological processes that form the mountain system in Korea. This research attempts to clarify the definition of mountain ranges and offer geological and geomorphological explanations about the formation of them. Based on the analyses of the social and cultural causes underlying the recent debates on the existence of mountain ranges, we tried to identify the relationships among the definition of mountain ranges, geological structure of Korea, and the forming processes of mountain ranges. The current and past mountain range maps were compared with geological structures, geological maps, surface curvature, and hill shade maps. The latter two maps were derived from a Digital Elevation Model of the Korean Peninsular. The results show that we are able to prove the existence of most mountain ranges, which provides a useful framework to understand the geological evolution of Korean peninsular and formation of mountainous landscape of Korea. In terms of their morphological continuity and genesis, however, we identified five different categories of mountain ranges: 1) Uplift mountain ranges(Hamkyeong Sanmaek, Nangrim Sanmaek, Taebaek Sanmaek), which were formed by the uplift processes of the Korean Peninsular during the Tertiary; 2) Falut mountain ranges(Macheonryeong Sanmaek, Sobaek Sanmaek, Buksubaek Sanmaek), whirh were directly related to the uplift processes of the Korean Peninsular during the Tertiary; 3) Trust mountain ranges(Jekyouryeong Sanmaek, Kwangju Sanmaek, Charyeong Sanmaek, Noryeong Sanmaek), which were formed by the intrusion of granite and consequent orogenic processes during the Mesozoic era; 4) Drainage divide type mountain ranges, which were formed by the erosion processes after the uplift of Korean Peninsular; 5) Cross-drainage basin type mountain ranges (Kangnam Sanmaek, Eunjin Sanmaek, Myelak sanmaek), which were also formed by the erosion processes, but the mountain ranges cross several drainage basins as connecting mountains laterally We believe that the current social confusions related to the existence of mountain ranges has partly been caused by the vague definition of mountain ranges and the diversity of the forming processes. In order to overcome theses confusions, it is necessary to characterize the types of them according the genesis, the purpose of usages and also the scale of maps which will explains the mountain systems. It is also necessary to provide appropriate educational materials to increase the general public's awareness and understanding of geomorphological processes.

• Korean Journal of Environmental Biology
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• v.17 no.1
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• pp.35-50
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• 1999

The relationship between floristic composition and soil environmental conditions was investigated in the forest vegetation of Mt. Paekun. The forest vegetation unit of Mt. Paekun was divided into six plant communities by Zurich-Montpellier method, such as Quercus mongelica community (Typical subcommunity, Rhododendron schlippenbaohii subcommunity), Q. variabilis community, Fraxinus rhynchophylla community, Pinus densiflora community, Larix Eeptolepis community and Pinus koraiensis community. Q. mongolica community group was distributed at the altitude over 500 meter, Q. variabilis and P. densiflora communities appeared on the southwestern slope at the altitudes of 600 ~ 700 m and 290 ~ 700 m. However, L. leptolepis and P. koraiensis plantation were distributed at lower altitude, on hillside or around homestead. The DBH class distribution of dominant species in each community showed that Q. mongolica had 10.9 individuals/a at 6~10 cm class, Q. variabilis 2.5 individuals/a at 11~15 cm class, P. densiflora 1.8 individuals/a at 26~30 cm class, F. rhynchophylla 3.3 individuals/a at 2~5 cm class, and L. leptolepis 5.9 individuals/a at 11~ 15 cm class. Q. mongolica and Q. variabilis communities showed a stable bell-shaped pattern of distribution. The contents of organic matters and soil water, and cation exchange capacity of the soil increased, and the pH decreased as the altitude gets higher increased altitude at the each communities. The contents of the soil water and organic matters of the forest soil collected in Q. mongolica community were in the 17.81% to 51.20% and 5.51% to 14.90%, respectively. These tendency is similar to the contents of N, P and K, but those of Ca, Mg, and CEC was lower than in other communities. Cation exchange capacity was suspected to be correlated to the pH. The hypothetical successional sere of the forest vegetation of Mt. Paekun is as follows: Pinus densiflora community longrightarrowQ. variabilis community longrightarrowQ. mongolica community.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.247-264
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• 2016

With the rapid acceleration of low-birth rate and population aging, the employment of the neglected groups of people including the middle aged class is a crucial issue in South Korea. In particular, in the 2010s, the number of the middle aged who want to find a new job after retirement age is significantly increasing with the arrival of the retirement time of the baby boom generation (born 1955-1963). Despite the importance of matching jobs to this emerging middle aged class, private job portals as well as the Korean government do not provide any online job service tailored for them. A gigantic amount of job information is available online; however, the current recruiting systems do not meet the demand of the middle aged class as their primary targets are young workers. We are in dire need of a specially designed recruiting system for the middle aged. Meanwhile, when users are searching the desired occupations on the Worknet website, provided by the Korean Ministry of Employment and Labor, users are experiencing discomfort to search for similar jobs because Worknet is providing filtered search results on the basis of exact matches of a preferred job code. Besides, according to our Worknet data analysis, only about 24% of job seekers had landed on a job position consistent with their initial preferred job code while the rest had landed on a position different from their initial preference. To improve the situation, particularly for the middle aged class, we investigate a soft job matching technique by performing the following: 1) we review a user behavior logs of Worknet, which is a public job recruiting system set up by the Korean government and point out key system design implications for the middle aged. Specifically, we analyze the job postings that include preferential tags for the middle aged in order to disclose what types of jobs are in favor of the middle aged; 2) we develope a new occupation classification scheme for the middle aged, Korea Occupation Classification for the Middle-aged (KOCM), based on the similarity between jobs by reorganizing and modifying a general occupation classification scheme. When viewed from the perspective of job placement, an occupation classification scheme is a way to connect the enterprises and job seekers and a basic mechanism for job placement. The key features of KOCM include establishing the Simple Labor category, which is the most requested category by enterprises; and 3) we design MOMA (Middle-aged Occupation Matching Algorithm), which is a hybrid job matching algorithm comprising constraint-based reasoning and case-based reasoning. MOMA incorporates KOCM to expand query to search similar jobs in the database. MOMA utilizes cosine similarity between user requirement and job posting to rank a set of postings in terms of preferred job code, salary, distance, and job type. The developed system using MOMA demonstrates about 20 times of improvement over the hard matching performance. In implementing the algorithm for a web-based application of recruiting system for the middle aged, we also considered the usability issue of making the system easier to use, which is especially important for this particular class of users. That is, we wanted to improve the usability of the system during the job search process for the middle aged users by asking to enter only a few simple and core pieces of information such as preferred job (job code), salary, and (allowable) distance to the working place, enabling the middle aged to find a job suitable to their needs efficiently. The Web site implemented with MOMA should be able to contribute to improving job search of the middle aged class. We also expect the overall approach to be applicable to other groups of people for the improvement of job matching results.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.1
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• pp.11-21
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• 2014

The purpose of this study was to furnish basic information for forest community ecology and to accumulate vegetational datum related to hierarchy of forest community for the efficient management of forest vegetation in Mt. Mani. Samples were collected and analyzed by 32 releves from August to October in 2010 using phytosociological analysis methodology of Z-M school and importance value analysis. The results were summarized that the forest vegetation was classified into 5 units in total. Importance value at vegetation unit 1 indicated Pinus densiflora 54.31 (18.10%), Quercus mongolica 39.21 (13.07%), Carpinus coreana 37.29 (12.43%), at vegetation unit 2 Quercus mongolica 89.43 (22.23%), Rhododendron mucronulatum 57.75 (14.43%), Carpinus coreana 47.19(11.80%), at vegetation unit 3 Styrax japonica 53.97 (13.50%), Acer mono 33.60 (8.40%), Carpinus coreana 26.48 (6.62%), Quercus serrata 22.51 (5.64%), at vegetation unit 4 Carpinus coreana 47.70 (11.92%), Quercus acutissima 38.40 (9.60%) and at vegetation unit 5 Evodia daniellii 80.59 (20.14%), Robinia pseudoacacia 35.00 (8.74%), Pueraria thunbergiana 28.63 (7.15%), Quercus dentata 28.20 (7.05%) in the order, respectively.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.2
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• pp.21-29
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• 2018

This study was wanted to select a value evaluation item to maintain the authenticity of the Planting Landscape in Hahoe and Yangdong villages. Above all, after checking the suitability of the 43 selected items by the Focus Group Interview, the weight was calculated in the Analytic Hierarchy Process expert questionnaire to establish the importance of the indicators for the development of the assessment items. The expert analysis analyzed the importance of 2 sections, 6 divisions and 11 detailed categories, and summarized the results of the study as follows : First, the comparative importance of each category and selection of the assessment items for the stabilization of the Planting Landscape of Hahoe and Yangdong indicated that cultural values are more important than biological values. In particular, details of the biological values of trees were derived with relatively low estimates, except for the specific characteristics of species and items of type of tree. Second, as a result of verification of the suitability of the 43 items selected by the Focus Group Interview, the source diameter, the collection width, reception, flushing, supersonality, records, memorials, 11 items were selected, Third, the results of the importance evaluation of the value properties for maintaining the resistance of vegetation through the Analytic Hierarchy Process were : specific in biological values (0.187), steady (0.094), and water pipe width (2007). There was relatively little difference in the highest weights, the width of the pipe except for the lowest value received, and the source diameter flushing. Fourth, the results of an evaluation of the importance of a value property aimed at historical values were whether or not the cultural asset was designated (0.134), the record value (0.092), the time (0.088), and the monument (0.063). In terms of the importance of evaluating the historical values of Planting sites consisting of Hahoe and Yangdong, the importance of designation of cultural properties was considered to be relative to the maintenance of the Planting Landscape including culture and history. Based on the assessment items and weighted values of the Planting Landscape of Yangdong Village and the World Cultural Heritage below and below, this study's Analytic Hierarchy Process can be applied to actual criteria for the assessment of the authenticity of trees in the village. Based on the assessment items and weighted values of the Planting Landscape in Hahoe and Yangdong villages, a follow-up study on the assessment standards for the authenticity of trees in the village will be left as a future task.

• Korean Journal of Soil Science and Fertilizer
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• v.6 no.2
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• pp.95-105
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• 1973

Sink (grain)-filling rates of IR667 line (Suwon 213 and 214) and local leading varieties (Jinheung and Paldal) were investigated in relation to sink-source ratio, sink-source distance, forms of photosynthates, and weather factors. The results are as follows. 1. IR667 line have higher maximum filling rate (g. grain/day. ear) and shorter duration to reach maximum filling rate than local varieties. The curve pattern of sink-filling rate was high and steep type in IR667 line and low and broad type in local varieties. 2. Weather factors seem to give little effect on the curve pattern of sink-filling rate. 3. The functional sink-source distance (actual sink-source distance multiplied by the contribution rate of leaf for grain production) was shorter in upper leaves (flag and 2nd leaf) for IR667 line, the upper leaf-dependent type in grain production, and was longer in lower leaves (3rd and 4th) for local varieties, the lower leaf-dependent type. Specially short first internode from top may contribute to the upper leaf depencency of IR667 line. 4. According to free sugar-starch ratio (sugar/starch) in the culm and leaf sheath IR667 line could be classified as the high sugar type and the local varieties as the high starch type. The ratio of transportable form (sugar) to non transportable photosynthate (starch) seems to relate with sink-filling rate. And high sugar type is expected to have higher efficiency for grain production in view of energy balance. 5. A hypothesis that the higher in the uniformity within the series of productive structure the more efficient in grain production is proposed and discussed in relation to productivity. 6. According to the pattern of percent nutrient retention of each leaf blade IR667 showed the central retention type and Jinheung showed the apical retention type and each retention type appears to be a cause of each canopy conservation pattern. 7. From the content and percent distribution of nutrient in various organ IR667 could be classified as the leaf sheath dominant type and Jinheung as the leaf blade dominant type. 8. The fact that the greater the percent translocation of nutrient into grain the greater the percent nutrient retention in leaf blade was held between nitrogen and phosphorus within a variety and between varieties within a nutrient (N, P or K).

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.