• Journal of Korean Society of Forest Science
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• v.109 no.4
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• pp.477-483
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• 2020

We constructed a stand yield table for Chamaecyparis obtusa based on data from an actual forest. The previous stand yield table had a number of disadvantages because it was based on actual forest information. In the present study we used data from more than 200 sampling plots in a stand of Chamaecyparis obtusa. The analysis included theestimation, recovery and prediction of the distribution of values for diameter at breast height (DBH), and the result is a valuable process for the preparation ofstand yield tables. The DBH distribution model uses a Weibull function, and the site index (base age: 30 years), the standard for assessing forest productivity, was derived using the Chapman-Richards formula. Several estimation formulas for the preparation of the stand yield table were considered for the fitness index, and the optimal formula was chosen. The analysis shows that the site index is in the range of 10 to 18 in the Chamaecyparis obtusa stand. The estimated stand volume of each sample plot was found to have an accuracy of 62%. According to the residuals analysis, the stands showed even distribution around zero, which indicates that the results are useful in the field. Comparing the table constructed in this study to the existing stand yield table, we found that our table yielded comparatively higher values for growth. This is probably because the existing analysis data used a small amount of research data that did not properly reflect. We hope that the stand yield table of Chamaecyparis obtusa, a representative species of southern regions, will be widely used for forest management. As these forests stabilize and growth progresses, we plan to construct an additional yield table applicable to the production of developed stands.

• Atmosphere
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• v.31 no.2
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• pp.229-240
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• 2021

The Global Ocean Data Assimilation and Prediction System (GODAPS) in operation at the KMA (Korea Meteorological Administration) is introduced. GODAPS consists of ocean model, ice model, and 3-d variational ocean data assimilation system. GODAPS assimilates conventional and satellite observations for sea surface temperature and height, observations of sea-ice concentration, as well as temperature and salinity profiles for the ocean using a 24-hour data assimilation window. It finally produces ocean analysis fields with a resolution of 0.25 ORCA (tripolar) grid and 75-layer in depth. This analysis is used for providing a boundary condition for the atmospheric model of the KMA Global Seasonal Forecasting System version 5 (GloSea5) in addition to monitoring on the global ocean and ice. For the purpose of evaluating the quality of ocean analysis produced by GODAPS, a one-year data assimilation experiment was performed. Assimilation of global observing system in GODAPS results in producing improved analysis and forecast fields with reduced error in terms of RMSE of innovation and analysis increment. In addition, comparison with an unassimilated experiment shows a mostly positive impact, especially over the region with large oceanic variability.

• 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 Life Science
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• v.33 no.3
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• pp.277-286
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• 2023

Sarcopenia is the age-related loss of muscle mass and function. It is a natural part of aging and can lead to decreased mobility and increased frailty. The ubiquitin-proteasome pathway, which is involved in muscle protein degradation, is closely linked to sarcopenia. Germinated Rhynchosia nulubilis hydrolysate (GRH) has been reported to have anti-inflammatory and antioxidant properties, but there have been no reports on its inhibitory effect on muscle reduction. However, no study has yet explored the relationship between GRH and muscle loss inhibition. In this study, we evaluated the effects of GRH on muscle atrophy inhibitory activity in dexamethasone (Dexa)-induced muscle atrophy C2C12 myotubes and mouse models. Moreover, we identified a molecular pathway underlying the effects of GRH on skeletal muscle. May Grunwald-Giemsa staining showed that the length and area of myotubes increased in the groups treated with GRH. In addition, the GRH-treated group significantly reduced the expression of muscle ring finger protein 1 and muscular atrophy F-box (MAFbx) in the Dexa-induced muscular atrophy C2C12 model. GRH also improved muscle strength in C57BL/6 mice with Dexa-induced muscle atrophy, resulting in prolonged running exhaustive time and increased grip strength. We found that muscle strengthening by GRH was correlated with a decreased expression of the MAFbx gene in mouse muscle tissue. In conclusion, GRH can attenuate Dexa-induced muscle atrophy by inhibiting the ubiquitin-proteasome pathway via downregulation of the MAFbx gene expression.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.103-119
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• 2023

Since the Korean government has decided to apply the policy of BIM (Building Information Modeling) to the entire construction industry, it has experienced a positive trend in adoption and utilization. BIM can reduce workloads by building model objects into libraries that conform to standards and enable consistent quality, data integrity, and compatibility. In the domestic architecture, civil engineering, and the overseas landscape architecture sectors, many BIM library standardization studies have been conducted, and guidelines have been established based on them. Currently, basic research and attempts to introduce BIM are being made in Korean landscape architecture field, but the diffusion has been delayed due to difficulties in application. This can be addressed by enhancing the efficiency of BIM work using standardized libraries. Therefore, this study aims to provide a starting point for discussions and present a classification system for objects and attribute information that can be referred to when creating landscape libraries in practice. The standardization of landscape BIM library was explored from two directions: object classification and attribute information items. First, the Korean construction information classification system, product inventory classification system, landscape design and construction standards, and BIM object classification of the NLA (Norwegian Association of Landscape Architects) were referred to classify landscape objects. As a result, the objects were divided into 12 subcategories, including 'trees', 'shrubs', 'ground cover and others', 'outdoor installation', 'outdoor lighting facility', 'stairs and ramp', 'outdoor wall', 'outdoor structure', 'pavement', 'curb', 'irrigation', and 'drainage' under five major categories: 'landscape plant', 'landscape facility', 'landscape structure', 'landscape pavement', and 'irrigation and drainage'. Next, the attribute information for the objects was extracted and structured. To do this, the common attribute information items of the KBIMS (Korean BIM Standard) were included, and the object attribute information items that vary according to the type of objects were included by referring to the PDT (Product Data Template) of the LI (UK Landscape Institute). As a result, the common attributes included information on 'identification', 'distribution', 'classification', and 'manufacture and supply' information, while the object attributes included information on 'naming', 'specifications', 'installation or construction', 'performance', 'sustainability', and 'operations and maintenance'. The significance of this study lies in establishing the foundation for the introduction of landscape BIM through the standardization of library objects, which will enhance the efficiency of modeling tasks and improve the data consistency of BIM models across various disciplines in the construction industry.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• 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 Nutrition and Health
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• v.56 no.3
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• pp.264-276
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• 2023

Purpose: Food environmental factors related to food insecurity affect household food intake in several socio-ecological aspects. This study explores the relationship between food environment factors and food insecurity in households with married immigrant women. Methods: From November 2018 to February 2020, a survey was conducted enrolling 249 married immigrant women residing in the metropolitan areas of South Korea. In the final analysis, 229 subjects were divided into 2 groups classified as food security (n = 154) and food insecurity (n = 75), as assessed by the score of food security. Three aspects of food environments were measured: built·natural, political·economic, and socio-cultural Results: Food environments were significantly different between food security and food insecurity groups, as follows: the number of foods market and their distance from the home and food status for the last week at home in the built·natural domain; monthly cost of food purchase and experience for food assistance in the political·economic domain; total score of social support, parenting, and cooking skills in the socio-cultural domain. A stepwise multivariate linear regression model showed a negative association between the food insecurity score with social support from family and food inventory status in the last week. After adjusting for confounders, a positive association was obtained between the experience of a food support program. The final regression model explains about 30% of the relationship obtained in the three food environment domains and food insecurity (p < 0.001). Conclusion: Not only economic factors, which are common determinants of household food insecurity, but socio-cultural factors such as social support also affect household food insecurity. Therefore, plans for implementing a food assistance program to improve food insecurity for households with immigrant women should consider financial support as well as other comprehensive aspects, including socio-cultural domain such as social support from family and community.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.121-137
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• 2022

The purpose of this study is to present the necessary success factors and strategies for high-tech social ventures and stakeholders in the related ecosystem by empirically identifying factors that affect their sustainable performance. Based on prior research, the dimensions of three performance factors were presented: core technology competency, core business competency, and social mission orientation. Then, such sub-dimensions such as technology innovation orientation, R&D capability, business model, customer orientation, social network, and social mission pursuit were derived. For empirical analysis, a survey was conducted on domestic high-tech social ventures, and the significance of the hypothesis was tested through PLS-structural equation analysis of the collected 243 valid data. As a result, it was found that the technology innovation orientation was embedded as an abstract organizational and cultural characteristic in the high-tech social venture, which is a research sample, and thus did not significantly affect the dependent variable. In other words, aiming for the latest cutting-edge technology alone cannot affect performance, and it is a result of proving the need for substantial influencing factors that can strengthen it. On the other hand, the business model had a significant effect only on social performance, which is presumed to be the limitation of measurement tools developed for social enterprises, and the results of additional multi-group analysis to determine the cause also supported the basis for this estimation. Excluding the previous two performance factors, R&D competency, customer orientation, social network, and social mission pursuit were all found to have a significant positive (+) effect on social and economic performance. This study laid a foundation for related research by identifying high-tech social ventures emerging in the ecosystem of a social economy and expanded empirical research models related to the performance of existing social enterprises and social ventures. However, in the research method or process, there were limitations such as factor derivation or verification for balance of dual performance, subjective measurement method, and sample representativeness. It is expected that more in-depth follow-up studies will continue by supplementing future limitations and designing improved research models.

• Journal of Nutrition and Health
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• v.57 no.1
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• pp.53-64
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• 2024

Purpose: Mitochondria play a crucial role in preserving skeletal muscle mass, and damage to mitochondria leads to muscle mass loss. This study investigated the effects of oxypeucedanin hydrate, a furanocoumarin isolated from Angelica dahurica radix, on myogenesis and mitochondrial function in vitro and in zebrafish models. Methods: C2C12 myotubes cultured in media containing 0.1, 1, 10, or 100 ng/mL oxypeucedanin hydrate were immunostained with myosin heavy chain (MHC), and then multinucleated MHC-positive cells were counted. The expressions of markers related to muscle differentiation, muscle protein degradation, and mitochondrial function were determined by quantitative reverse transcription polymerase chain reaction. To investigate the effects of oxypeucedanin hydrate on mitochondrial dysfunction, Tg(Xla.Eef1a1:mito-EGFP) zebrafish embryos were treated with 5-fluorouracil, leucovorin, and irinotecan (FOLFIRI) with or without oxypeucedanin hydrate and analyzed for mito-EGFP intensity and mitochondrial length. Results: Oxypeucedanin hydrate significantly increased MHC-positive multinucleated myotubes (≥ 3 nuclei) and increased the expression of the myogenic marker myosin heavy chain 4. However, it decreased the expressions of muscle-specific RING finger protein 1 and muscle atrophy f-box (markers of muscle protein degradation). Furthermore, oxypeucedanin hydrate enhanced the expressions of markers of mitochondrial biogenesis (peroxisome proliferator-activated receptor-gamma coactivator 1 alpha, transcription factor a mitochondrial, succinate dehydrogenase complex flavoprotein subunit A, and cytochrome c oxidase subunit 1) and mitochondrial fusion (optic atrophy 1). However, it reduced the expression of dynamin-related protein 1 (a mitochondrial fission regulator). Consistently, oxypeucedanin hydrate reduced FOLFIRI-induced mitochondrial dysfunction in the skeletal muscles of zebrafish embryos. Conclusion: The study indicates that oxypeucedanin hydrate promotes myogenesis by improving mitochondrial function, and thus, suggests oxypeucedanin hydrate has potential use as a nutritional supplement that improves muscle mass and function.