• Korean Journal of Environment and Ecology
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• v.36 no.1
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• pp.102-111
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• 2022

Among protected areas, National Parks are rich in biodiversity, and the benefits of ecosystem services provided to human are higher than the others. Ecosystem service evaluation is being used to manage the value of national parks based on objective and scientific data. Ecosystem services are classified into four services: supporting, provisioning, regulating and cultural. The purpose of this study is to evaluate habitat quality among supporting services. Habitat Quality Model of InVEST was used to analyze. The coefficients of sensitivity and habitat initial value were reset by reflecting prior studies and the actual conditions of protected areas. Habitat quality of 21 national parks except Hallasan National Park was analyzed and mapped. The value of habitat quality was evaluated to be between 0 and 1, and the closer it is to 1, the more natural it is. As a result of habitat quality analysis, Seoraksan and Taebaeksan National Parks (0.90), Jirisan and Odaesan National Parks (0.89), and Sobaeksan National Park (0.88) were found to be the highest in the order. As a result of comparing the area and habitat quality of 18 national parks except for coastal-marine national parks, the larger the area, the higher the overall habitat quality. Comparing the value of habitat quality of each zone, the value of habitat quality was high in the order of the park nature preservation zone, the park nature environmental zone, the park cultural heritage zone, and the park village zone. Considering both the analysis of habitat quality and the legal regulations for each zone of use, it is judged that the more artificial acts are restricted, the higher the habitat quality. This study is meaningful in analyzing habitat quality of 21 National Parks by readjusting the parameters according to the situation of protected areas in Korea. It is expected to be easy to intuitively understand through accurate data and mapping, and will be useful in making policy decisions regarding the development and preservation of protected areas in the future.

• Geophysics and Geophysical Exploration
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• v.26 no.1
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• pp.18-30
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• 2023

Submarine mud volcanos are topographic features that resemble volcanoes, and are formed due to eruptions of fluidized or gasified sediment material. They have gained attention as a source of subsurface heat, sediment, or hydrocarbons supplied to the surface. In the continental slope of the Canadian Beaufort Sea, mud volcano exists at various water depths. The MV420, is an active mud volcano erupting at a water depth of 420 meters, and it has been the subject of extensive study. The Korea Polar Research Institute(KOPRI) collected high-resolution seismic data and heat flow data around the caldera of the mud volcano. By analyzing the multi-channel seismic data, we confirmed the reverse-polarity reflector assumed by a gas hydrate-related bottom simulating reflector(BSR). To further elucidate the relationship between the BSR and gas hydrates, as well as the thermal structure of the mud volcano, a numerical geothermal model was developed based on the steady-state heat equation. Using this model, we estimated the base of the gas hydrate stability zone and found that the BSR depth estimated by multi-channel seismic data and the bottom of the gas hydrate stability zone were in good agreement., This suggests the presence of gas hydrates, and it was determined that the depth of the gas hydrate was likely up to 50 m, depending on the distance from the mud conduit. Thus, this depth estimate slightly differs from previous studies.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.1-17
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• 2023

With the recent rapid development of ICT(Information and Communication Technology) and the popularization of digital devices, the size of the online market continues to grow. As a result, we live in a flood of information. Thus, customers are facing information overload problems that require a lot of time and money to select products. Therefore, a personalized recommender system has become an essential methodology to address such issues. Collaborative Filtering(CF) is the most widely used recommender system. Traditional recommender systems mainly utilize quantitative data such as rating values, resulting in poor recommendation accuracy. Quantitative data cannot fully reflect the user's preference. To solve such a problem, studies that reflect qualitative data, such as review contents, are being actively conducted these days. To quantify user review contents, text mining was used in this study. The general CF consists of the following three steps: user-item matrix generation, Top-N neighborhood group search, and Top-K recommendation list generation. In this study, we propose a recommendation algorithm that applies an extended similarity measure, which utilize quantified review contents in addition to user rating values. After calculating review similarity by applying TF-IDF, Word2Vec, and Doc2Vec techniques to review content, extended similarity is created by combining user rating similarity and quantified review contents. To verify this, we used user ratings and review data from the e-commerce site Amazon's "Health and Personal Care". The proposed recommendation model using extended similarity measure showed superior performance to the traditional recommendation model using only user rating value-based similarity measure. In addition, among the various text mining techniques, the similarity obtained using the TF-IDF technique showed the best performance when used in the neighbor group search and recommendation list generation step.

• Korean Journal of Heritage: History & Science
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• v.55 no.4
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• pp.196-209
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• 2022

This study compared and analyzed the spatial division function and role of partitions by comparing the entire space and the spatial changes before and after the installation of partitions in <Donggwoldo>, which was manufactured in the late Joseon Dynasty. As a research method, a set standard was prepared to decompose the space of <Donggwoldo> into a unit space, and the standard was set according to the role and height of the space by classifying it into a main space, sub space, and transition space. Two convex maps were prepared according to before and after the installation of the Panjang, and the values of connectivity, control, and integration, which are spatial syntax variables, were calculated and analyzed. The results of the study are as follows. First, the partition in <Donggwoldo(東闕圖)> did not affect the overall spatial arrangement and control or connection of Donggwol, but the movement and access of space is limited to specific areas. Second, the partition was a facility intensively distributed in Naejeon(內殿) and Donggung(東宮) to be used actively in the way of space utilization. It shows that the unit space increased rapidly due to the installation of the partition. Since the partition was installed in the spaces that were open and under high control in the case of Naejeon(內殿), it helped to secure private spaces as closed ones under low control. On the other hand, for Donggung(東宮), the spaces were compartmented and divided with the partition to guide the movement path through narrow gates of the partition and increase the depth of the space. This helped to create spaces that are free and can be hidden as it increased the number of spaces coming through. Third, In addition to the functions of "eye blocking, space division, and movement path control" revealed in prior research, the partition has created a "space that is easy to control" within a specific area. The installation of the partition reduced the scale through the separation of spaces, but it occurred the expansion of the movement path and space. Also, the partition functioned to strengthen hiding and closure or increase openness as well through space division. This study is significant in that it revealed the value of the spatial control function of panjang through the analysis of spatial control and depth by analyzing the function of the partition with a mathematical model in addition to the analysis and study of the function and role of panjang. In addition, it is valuable in that it has prepared a framework for analysis tools that can be applied to traditional residential complexes similar to palaces by applying space syntax to <Donggungdo> to create convex spaces according to unit space division and connection types of palace architecture and landscape elements.

• Journal of agriculture & life science
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• v.50 no.3
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• pp.1-11
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• 2016

With increasing interest, there have been studies on LiDAR(Light Detection And Ranging)-based DEM(Digital Elevation Model) to acquire three dimensional topographic information. For producing LiDAR DEM with better accuracy, Filtering process is crucial, where only surface reflected LiDAR points are left to construct DEM while non-surface reflected LiDAR points need to be removed from the raw LiDAR data. In particular, the changes of input values for filtering algorithm-constructing parameters are supposed to produce different products. Therefore, this study is aimed to contribute to better understanding the effects of the changes of the levels of GroundFilter Algrothm's Mean parameter(GFmn) embedded in FUSION software on the accuracy of the LiDAR DEM products, using LiDAR data collected for Hwacheon, Yangju, Gyeongsan and Jangheung watershed experimental area. The effect of GFmn level changes on the products' accuracy is estimated by measuring and comparing the residuals between the elevations at the same locations of a field and different GFmn level-produced LiDAR DEM sample points. In order to test whether there are any differences among the five GFmn levels; 1, 3, 5, 7 and 9, One-way ANOVA is conducted. In result of One-way ANOVA test, it is found that the change in GFmn level significantly affects the accuracy (F-value: 4.915, p<0.01). After finding significance of the GFmn level effect, Tukey HSD test is also conducted as a Post hoc test for grouping levels by the significant differences. In result, GFmn levels are divided into two subsets ('7, 5, 9, 3' vs. '1'). From the observation of the residuals of each individual level, it is possible to say that LiDAR DEM is generated most accurately when GFmn is given as 7. Through this study, the most desirable parameter value can be suggested to produce filtered LiDAR DEM data which can provide the most accurate elevation information.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.171-187
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• 2023

When a person's face is recognized through a recording device such as a low-pixel surveillance camera, it is difficult to capture the face due to low image quality. In situations where it is difficult to recognize a person's face, problems such as not being able to identify a criminal suspect or a missing person may occur. Existing studies on face recognition used refined datasets, so the performance could not be measured in various environments. Therefore, to solve the problem of poor face recognition performance in low-quality images, this paper proposes a method to generate high-quality images by performing image quality improvement on low-quality facial images considering various environments, and then improve the performance of facial feature point detection. To confirm the practical applicability of the proposed architecture, an experiment was conducted by selecting a data set in which people appear relatively small in the entire image. In addition, by choosing a facial image dataset considering the mask-wearing situation, the possibility of expanding to real problems was explored. As a result of measuring the performance of the feature point detection model by improving the image quality of the face image, it was confirmed that the face detection after improvement was enhanced by an average of 3.47 times in the case of images without a mask and 9.92 times in the case of wearing a mask. It was confirmed that the RMSE for facial feature points decreased by an average of 8.49 times when wearing a mask and by an average of 2.02 times when not wearing a mask. Therefore, it was possible to verify the applicability of the proposed method by increasing the recognition rate for facial images captured in low quality through image quality improvement.

• The Journal of Bigdata
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• v.8 no.1
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• pp.111-129
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• 2023

With the diffusion of digital innovation, the adoption of innovative medical technologies based on artificial intelligence is increasing in the medical field. This is driving the launch and adoption of AI-based SaMD(Software as a Medical Device), but there is a lack of research on the factors that influence the adoption of SaMD by medical institutions. The purpose of this study is to identify key factors that influence medical institutions' decisions to adopt AI-based SaMDs, and to analyze the weights and priorities of these factors. For this purpose, we conducted Delphi surveys based on the results of literature studies on technology acceptance models in healthcare industry, medical AI and SaMD, and developed a research model by combining HOTE(Human, Organization, Technology and Environment) framework and HABIO(Holistic Approach {Business, Information, Organizational}) framework. Based on the research model with 5 main criteria and 22 sub-criteria, we conducted an AHP(Analytical Hierarchy Process) analysis among the experts from domestic medical institutions and SaMD providers to empirically analyze SaMD adoption factors. The results of this study showed that the priority of the main criteria for determining the adoption of AI-based SaMD was in the order of technical factors, economic factors, human factors, organizational factors, and environmental factors. The priority of sub-criteria was in the order of reliability, cost reduction, medical staff's acceptance, safety, top management's support, security, and licensing & regulatory levels. Specifically, technical factors such as reliability, safety, and security were found to be the most important factors for SaMD adoption. In addition, the comparisons and analyses of the weights and priorities of each group showed that the weights and priorities of SaMD adoption factors varied by type of institution, type of medical institution, and type of job in the medical institution.

• Asia Marketing Journal
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• v.12 no.3
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• pp.43-62
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• 2010

The notion of customer orientation is now importantly considered in the context of banking industries. Despite customer-oriented organizational cultures, there are few studies addressing the relationship between customer orientation and its outcomes. In particular, this study aims at testing the effect of customer orientation as a key marketing effort designed by a bank. This is because interest rate sensitivity is critical for evaluating banking services after raising the base rate. In so doing, first, this study investigates the relationships among customer orientation, interest rate sensitivity, and customer loyalty. Second, this paper examines how the moderating effects of both deposit interest and loan interest rates influence the linkages of customer orientation-interest rate sensitivity and customer orientation-customer loyalty. To test the proposed model, research data are collected from 304 subjects who use banking services(e.g., Shin-Han, Kookmin, the First Bank, Hana, and Woori banks). Each construct was measured by published items and the psychometric properties of the three constructs, excluding two constructs of the moderators, were evaluated by employing the method of confirmatory factor analysis via the use of AMOS. The model fit was also evaluated using the CFI, TLI, and RMSEA fit indices that are recommended based on their relative stability and insensitivity to sample size. The findings show that the relationship between customer orientation and customer loyalty is significant, whereas the relationships between customer orientation and interest rate sensitivity and between interest rate sensitivity and customer loyalty are not supported. Although customer orientation is highly evaluated, customers' interest rate sensitivity that results in the comparison of interest rates plays an important role in reducing the effect of customer orientation. As a consequence, interest rate sensitivity does not influence customer loyalty. First of all, one of interesting results in this study is that the moderating effect of loan interest rate is quite different from deposit interest rate. In the case of deposit interest rate, the linkages both customer orientation-interest rate sensitivity and customer orientation-customer loyalty are insignificant. In the case of loan interest rate, however, the two proposed linkages are supported. As our proposed relationships are still in its infancy in the context of banking industry, our study contributes to enhance scholars' knowledge of bank services and provides insights for practitioners when their marketing strategies, particularly both deposit and interest rates, have to be established. Finally, this research also illuminates the need for further research that considers the influence of customer orientation on consumer's decision-making and bank profits. More specifically, the results are encouraging and will lead us to further investigate this key outcome of the banking deposit/interest rates.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.655-667
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• 2023

Algal bloom outbreaks are frequently reported around the world, and serious water pollution problems arise every year in Korea. It is necessary to protect the aquatic ecosystem through continuous management and rapid response. Many studies using satellite images are being conducted to estimate the concentration of chlorophyll-a (Chl-a), an indicator of algal bloom occurrence. However, machine learning models have recently been used because it is difficult to accurately calculate Chl-a due to the spectral characteristics and atmospheric correction errors that change depending on the water system. It is necessary to consider the factors affecting algal bloom as well as the satellite spectral index. Therefore, this study constructed a dataset by considering water quality, hydrological and meteorological factors, and sentinel-2 images in combination. Representative ensemble models random forest and extreme gradient boosting (XGBoost) were used to predict the concentration of Chl-a in eight weirs located on the Nakdong river over the past five years. R-squared score (R²), root mean square errors (RMSE), and mean absolute errors (MAE) were used as model evaluation indicators, and it was confirmed that R² of XGBoost was 0.80, RMSE was 6.612, and MAE was 4.457. Shapley additive expansion analysis showed that water quality factors, suspended solids, biochemical oxygen demand, dissolved oxygen, and the band ratio using red edge bands were of high importance in both models. Various input data were confirmed to help improve model performance, and it seems that it can be applied to domestic and international algal bloom detection.

• Journal of Venture Innovation
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• v.6 no.3
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• pp.149-164
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• 2023

Today, when innovation and creativity become increasingly important, management of human resources is a key factor for corporate performance and competitive advantage. Corporate are implementing and introducing various types of support methods for members to achieve goals and improve organizational performance. Organizational culture and organizational trust affect the cognitive and emotional state of members. Furthermore, it can bring about changes in organizational performance such as job stress and job satisfaction. From an institutional point of view, work-life balance is also a major factor affecting organizational performance. The imbalance between work and life leads to a decline in organizational performance, such as decreased morale and dissatisfaction with work. In relation to work-life balance, the low birth rate problem intensified and the importance began to emerge. Therefore, the government has implemented various policy support for workers' work-life balance, and the "52-hour workweek" is a representative example. This study analyzed the effect of organizational culture applying the competitive value model on workers' job stress. In addition, the mediating effects of overtime work per week and organizational trust were analyzed. Job stress corresponds to a prerequisite stage that affects job commitment, job satisfaction, and turnover intention. However, research measuring job stress by organizational performance is insufficient. In addition, there are few studies analyzing the relationship between overtime and organizational performance. Considering this, it is necessary to understand the influence relationship. The results of the study are as follows. First, a hierarchical culture increases the job stress of workers. On the other hand, innovation-oriented, relationship-oriented, and competition-oriented corporate culture reduce job stress. Second, a hierarchical culture has reduced trust in the organization, and other organizational cultures have increased trust in the organization. Third, relationship-oriented and competition-oriented organizational culture reduced overtime. Innovation-oriented, hierarchical-oriented culture increased overtime Fourth, organizational trust and overtime have the effect of mediating organizational culture and job stress. Based on these analysis results, this study presented academic and political implications.