• Journal of Korean Society of Forest Science
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• v.107 no.4
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• pp.351-360
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• 2018

This study was conducted to analyze the responses of chlorophyll contents and growth of Pinus densiflora and Quercus variabilis seedlings on distance from the well and $CO_2$ flux after the artificial $CO_2$ release. From June 1 to 30, 2016, $CO_2$ gas was injected at the rate of $6L\;min^{-1}$ at the study site in Eumseong. Chlorophyll content was analyzed in the middle of July, 2016, and root collar diameter (RCD), height (H), and biomass were measured in May and December, 2016 after planting 2-year-old P. densiflora and 1-year-old Q. variabilis seedlings in May, 2015. The chlorophyll content of P. densiflora seedlings did not show a significant correlation with $CO_2$ flux, whereas the chlorophyll content of Q. variabilis seedlings showed a significant negative correlation with increasing $CO_2$ flux (P<0.05). The RCD and H growth rates of both species showed the significant difference in the distance from the well of the $CO_2$ anthropogenic release treatment. In particular, the RCD and H growth rate of P. densiflora seedlings and the RCD growth rate of Q. variabilis seedlings increased significantly as the seedlings were closer to the well, but the H growth rate of Q. variabilis seedlings decreased significantly. In addition, as the $CO_2$ concentration in the ground increases, ${\Delta}R/S$ ratio increases in both species, suggesting that the high $CO_2$ concentration in the soil promotes carbon distribution relative to the root part. The results of this study can be used as data necessary to monitor the $CO_2$ leakage and physiological and growth responses of both species to leakage of stored $CO_2$ in the future.

• Korean Journal of Heritage: History & Science
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• v.41 no.2
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• pp.79-97
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• 2008

Four Wangs' landscape style (四王山水畵風), which had appeared in Beijing in the early 18th century, widely spread to Korea and Japan in the 19th century and became a significant basis for developing new painting styles in both countries. It was first introduced to Korea by Shin Wi (申緯) and Kim Jeong-hee (金正喜) who associated with literary men of the Qing Dynasty. Being influenced by them directly or indirectly, Shin Myeong-yeon (申命淵), Yi Han-cheol (李漢喆), Yu Suk (劉淑), Changv Seung-eop (張承業), An Choog-sik (安中植), and Jo Seok-jin (趙錫晋) attempted to adapt Four Wangs' landscape style and it later became a main Stream painting style of the Korean painting circles. Based on Four Wangs' landscape style, their landscape paintings had something in common in that they captured natural features from a short distance using the Down-Up prospective and placed guardian mountains across mountain streams by making a tall tree in the right or left bottom of the canvas as the starting point. However, recently unveiled court painter An Geon-yeong (1841~1876)'s the Landscape Screen is remarkable in that it is based on Four Wangs' style, which was in fashion in the late 19th century, but shows different aspects from other Four Wangs' style paintings in terms of feature capturing, brush stroke and colors. While most of An Geon-yeong's existing paintings are small ones, this folding screen is a big piece consisting of six-fold landscape paintings. In particular, it shows new aspects by creating a serene and calm atmosphere through the description of various landscape scenes with thin brush strokes using glossy ink, by showing a macroscopic view in some paintings through feature capture using a birds-eye view method, and by giving life to the canvas through smoke and clouds. This painting style is considered to be linked with those of Wang Xue-hao (王學浩, 1754~1832), Tang Yifen (湯貽汾, 1778~1853) and Dai Xi (戴熙, 1801~1860), based on Four Wangs' style in the early 19th century's Jiangnan Circle (江南 畵壇), who tried to express the energy and vitality of real landscapes by going around China's well-known mountains and complementing painting styles with drawing from nature. Therefore, An Geon-yeong's six-fold Landscape Screen is very significant as a rare case proving the introduction and reception of Jiangnan Circle's Four Wangs' landscape style which was different in many aspects from Beijing Circle in the 19th century.

• Clean Technology
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• v.25 no.3
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• pp.245-255
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• 2019

Pressurized oxy-fuel combustion is a promising technology for $CO_2$ capture with a benefit of improving power plant efficiency compared with atmospheric oxy-fuel combustion. Prior to $CO_2$ compression in this process, a flue gas condenser (FGC) is used to remove $H_2O$ while recovering the latent heat. At the same time, the FGC has a potential for high-efficiency removal of $SO_x$ and $NO_x$ by exploiting their good solubility in water. In this study, experiments were carried out in a lab-scale, direct contact FGC under different pressures varying between 1 and 20 bar to evaluate the removal efficiency of $SO_2$ and $NO_x$ for individual gases and their mixture. In the tests for individual gases, 20% and 76% of $NO_x$ was removed at 1 bar and 10 bar, respectively. Even higher removal efficiencies were achieved for $SO_2$, and also these were maintained for longer as the pressure increased. In the tests for $SO_2$ and $NO_x$ mixture, the removal efficiency of $NO_x$ increased from 13% at 1 bar to 56% at 20 bar because of higher solubility at elevated pressures. $SO_2$ in the mixture was initially dissolved almost completely and then increased by 1,219 ppm at 1 bar and by 165 ppm at 20 bar. Overall, the removal efficiency of $SO_2$ and $NO_x$ was increased at elevated pressures, but it was lower in the mixture compared with individual gases at identical conditions because of a lower pH and associated chemical reactions in water.

• International Area Studies Review
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• v.21 no.1
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• pp.97-117
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• 2017

This research highlights the process of adopting cloud computing technology from users' perspective. Concentrating on perceived mechanism from employees side that lead to job performance at work. Cloud computing, the new player in our modern business environment, authors employ diffusion of innovation theory to capture how this new technology affect employees in workplace in terms of job performance. Education for this new system and managerial support by firm were used as moderating variable to test dependent variable, job performance. Research was done through survey from total 284 people working in metropolitan area at South Korea. The result shows that cloud computing system affect positively on work efficiency, and the extent of diffusion factors that influence from the most to least are as follow: 1. Users' Skill, 2. System Quality, 3. Information Quality, 4. Group Awareness, 5. Attitude towards New System. To test diffusion factors of cloud computing and job performance, South Korean people actually felt that cloud computing help their job performance and the extent of diffusion factors that influence from the most to least are as follow: 1. Users' Skill, 2. System Quality, 3. Information Quality, 4. Attitude towards New System, 5. Group Awareness. As for diffusion factors of cloud computing and productivity, result proved that cloud computing really helps firms, and the extent of diffusion factors that influence from the most to least are as follow: 1. Information Quality, 2. Attitude towards New System, 3. Group Awareness, 4. System Quality, 5. Users' Skill. Two moderating variables, employee education and managerial support were tested to prove whether these two variables affect the job performance and the result displays positive affect for both two factors. To conclude, adopting cloud computing helps firms by increase employees' work efficiency and job performance. In order to accelerate the process employees education really matters because users' skill is the most crucial among diffusion factors.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.151-176
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• 2021

As the information technology industry develops, various kinds of data are being created, and it is now essential to process them and use them in the industry. Analyzing and utilizing various digital data collected online and offline is a necessary process to provide an appropriate experience for customers in the industry. In order to create new businesses, products, and services, it is essential to use customer data collected in various ways to deeply understand potential customers' needs and analyze behavior patterns to capture hidden signals of desire. However, it is true that research using data analysis and UX methodology, which should be conducted in parallel for effective service development, is being conducted separately and that there is a lack of examples of use in the industry. In thiswork, we construct a single process by applying data analysis methods and UX methodologies. This study is important in that it is highly likely to be used because it applies methodologies that are actively used in practice. We conducted a survey on the topic to identify and cluster the associations between factors to establish customer classification and target customers. The research methods are as follows. First, we first conduct a factor, regression analysis to determine the association between factors in the happiness data survey. Groups are grouped according to the survey results and identify the relationship between 34 questions of psychological stability, family life, relational satisfaction, health, economic satisfaction, work satisfaction, daily life satisfaction, and residential environment satisfaction. Second, we classify clusters based on factors affecting happiness and extract the optimal number of clusters. Based on the results, we cross-analyzed the characteristics of each cluster. Third, forservice definition, analysis was conducted by correlating with keywords related to happiness. We leverage keyword analysis of the thumb trend to derive ideas based on the interest and associations of the keyword. We also collected approximately 11,000 news articles based on the top three keywords that are highly related to happiness, then derived issues between keywords through text mining analysis in SAS, and utilized them in defining services after ideas were conceived. Fourth, based on the characteristics identified through data analysis, we selected segmentation and targetingappropriate for service discovery. To this end, the characteristics of the factors were grouped and selected into four groups, and the profile was drawn up and the main target customers were selected. Fifth, based on the characteristics of the main target customers, interviewers were selected and the In-depthinterviews were conducted to discover the causes of happiness, causes of unhappiness, and needs for services. Sixth, we derive customer behavior patterns based on segment results and detailed interviews, and specify the objectives associated with the characteristics. Seventh, a typical persona using qualitative surveys and a persona using data were produced to analyze each characteristic and pros and cons by comparing the two personas. Existing market segmentation classifies customers based on purchasing factors, and UX methodology measures users' behavior variables to establish criteria and redefine users' classification. Utilizing these segment classification methods, applying the process of producinguser classification and persona in UX methodology will be able to utilize them as more accurate customer classification schemes. The significance of this study is summarized in two ways: First, the idea of using data to create a variety of services was linked to the UX methodology used to plan IT services by applying it in the hot topic era. Second, we further enhance user classification by applying segment analysis methods that are not currently used well in UX methodologies. To provide a consistent experience in creating a single service, from large to small, it is necessary to define customers with common goals. To this end, it is necessary to derive persona and persuade various stakeholders. Under these circumstances, designing a consistent experience from beginning to end, through fast and concrete user descriptions, would be a very effective way to produce a successful service.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.69-77
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• 2022

The 3D spatial model is an analysis framework for solving urban problems and is used in various fields such as urban planning, environment, land and housing management, and disaster simulation. The utilization of drones that can capture 3D images in a short time at a low cost is increasing for the construction of 3D spatial model. In terms of building a virtual city and utilizing simulation modules, high location accuracy of aerial survey and precision of 3D spatial model function as important factors, so a method to increase the accuracy has been proposed. This study analyzed location accuracy of aerial survey and precision of 3D spatial model by each condition of aerial survey for urban areas where buildings are densely located. We selected Daerim 2-dong, Yeongdeungpo-gu, Seoul as a target area and applied shooting angle, shooting altitude, and overlap rate as conditions for the aerial survey. In this study, we calculated the location accuracy of aerial survey by analyzing the difference between an actual survey value of CPs and a predicted value of 3D spatial Model. Also, We calculated the precision of 3D spatial Model by analyzing the difference between the position of Point cloud and the 3D spatial Model (3D Mesh). As a result of this study, the location accuracy tended to be high at a relatively high rate of overlap, but the higher the rate of overlap, the lower the precision of 3D spatial model and the higher the shooting angle, the higher precision. Also, there was no significant relationship with precision. In terms of baseline-height ratio, the precision tended to be improved as the baseline-height ratio increased.

• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.393-404
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• 2022

Reliable terrestrial rainfall observations from satellites at finer spatial resolution are essential for urban hydrological and microscale agricultural demands. Although various traditional "top-down" approach-based satellite rainfall products were widely used, they are limited in spatial resolution. This study aims to assess the potential of a novel "bottom-up" approach for rainfall estimation, the parameterized SM2RAIN model, applied to the C-band SAR Sentinel-1 satellite data (SM2RAIN-S1), to generate high-spatial-resolution terrestrial rainfall estimates (0.01° grid/6-day) over Central South Korea. Its performance was evaluated for both spatial and temporal variability using the respective rainfall data from a conventional reanalysis product and rain gauge network for a 1-year period over two different sub-regions in Central South Korea-the mixed forest-dominated, middle sub-region and cropland-dominated, west coast sub-region. Evaluation results indicated that the SM2RAIN-S1 product can capture general rainfall patterns in Central South Korea, and hold potential for high-spatial-resolution rainfall measurement over the local scale with different land covers, while less biased rainfall estimates against rain gauge observations were provided. Moreover, the SM2RAIN-S1 rainfall product was better in mixed forests considering the Pearson's correlation coefficient (R = 0.69), implying the suitability of 6-day SM2RAIN-S1 data in capturing the temporal dynamics of soil moisture and rainfall in mixed forests. However, in terms of RMSE and Bias, better performance was obtained with the SM2RAIN-S1 rainfall product over croplands rather than mixed forests, indicating that larger errors induced by high evapotranspiration losses (especially in mixed forests) need to be included in further improvement of the SM2RAIN.

• Journal of Naturopathy
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• v.9 no.1
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• pp.22-26
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• 2020

Purposes: The purposes of this study were to investigate the relationship between the standing position of the subject and the normal standing position(NSP) and the straight standing position(SSP) and to investigate the possibility of different body shape test results depending on the status of the image inspection apparatus. Methods: The images of the NSP and SSP were compared with each other by body line BLS system. Results: At the time of examination, the position of the camera was captured at a position 2.3 m vertically from the posterior position 45 cm behind the subject. This is a privacy protection method for covering the breast of the subject. Results: The physiological characteristics of the anatomical position of the body align image test are the living body. NSP and SSP tests showed different shapes of the pelvis AS(antero-supero) and pelvis rotation in the transverse plane. Shoulder and arm displacement was observed in the trunk extension image capture. Conclusions: In the body alignment test, the pelvis position test images of NSP and SSP are evaluated differently for pelvis rotation, AS, and PS. At the extension position of the trunk, a test of the maximal extension range showed that the left and right shortening of the shoulder anterior muscles could be observed. Inducing and testing the trunk extension is also useful.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.281-298
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• 2023

Continuous research efforts are being devoted to unmanned mobile platforms for lunar exploration. There is an ongoing demand for real-time information processing to accurately determine the positioning and mapping of areas of interest on the lunar surface. To apply deep learning processing and analysis techniques to practical rovers, research on software integration and optimization is imperative. In this study, a foundational investigation has been conducted on real-time analysis of virtual lunar base construction site images, aimed at automatically quantifying spatial information of key objects. This study involved transitioning from an existing region-based object recognition algorithm to a boundary box-based algorithm, thus enhancing object recognition accuracy and inference speed. To facilitate extensive data-based object matching training, the Batch Hard Triplet Mining technique was introduced, and research was conducted to optimize both training and inference processes. Furthermore, an improved software system for object recognition and identical object matching was integrated, accompanied by the development of visualization software for the automatic matching of identical objects within input images. Leveraging satellite simulative captured video data for training objects and moving object-captured video data for inference, training and inference for identical object matching were successfully executed. The outcomes of this research suggest the feasibility of implementing 3D spatial information based on continuous-capture video data of mobile platforms and utilizing it for positioning objects within regions of interest. As a result, these findings are expected to contribute to the integration of an automated on-site system for video-based construction monitoring and control of significant target objects within future lunar base construction sites.