• Journal of Korean Society of Forest Science
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• v.104 no.3
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• pp.421-426
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• 2015

The objective of this paper is to look into the growth of Cryptomeria japonica stand in South Korea along with the evaluation on their yields, followed by their carbon stocks and removals. A total of 106 sample plots were selected from Jeonnam, Gyeongnam, and Jeju, where the groups of standard are grown. We only used 92 plots data except outlier. As part of the analysis, the Weibull diameter distribution was applied. In order to estimate the diameter distribution, the growth estimation equation for each of the growth factors including the height, the diameter at breast height, and the basal area was drafted out and the verification for each equation was examined. The site index for figuring out the forest productivity of Cryptomeria japonica stand for each district was also developed as a Schumacher model and 30yr was used as a reference age for the estimation of the site index. It was found that the site index for Cryptomeria japonica stand in South Korea ranges from 10 to 16 and this result was used as a standard for developing the stand yield table. According to the site 14 in the stand yield table, the mean annual increment (MAI) of the Cryptomeria japonica reaches $7.6m^3/ha$ on its 25yr and its growing stock is estimated to be at $190.1m^3/ha$. This volume is about $20m^3$ as high as that of the Chamaesyparis obtusa. Furthermore, the annual carbon absorptions for a Cryptomeria japonica stand reached the peak at 25yr, which is 2.14 tC/ha/yr, $7.83tCO_2/ha/yr$. When compared to the other conifers, this rate is slightly higher than that of a Chamaecyparis obtusa ($7.5tCO_2/ha/yr$) but lower than that of the Pinus koraiensis ($10.4tCO_2/ha/yr$) and Larix kaempferi ($11.2tCO_2/ha/yr$). With such research result as a base, it is necessary to come up with the ways to enhance the utilization of Cryptomeria japonica as timbers, besides making use of their growth data.

• Journal of Korean Society of Forest Science
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• v.97 no.6
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• pp.605-610
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• 2008

This study was carried out to investigate the short-term (3 years) effect of thinning on aboveground carbon storage for 34-year-old (site 1) and 45-year-old (site 2) Korean pine (Pinus koraiensis Siebold et Zuccarini) plantations with different diameter class and site quality located in Gwangneung experimental forest. Thinning was manually carried out in consideration of basal area in 2004 (site 1 : 30% and 60% of basal area removed and site 2 : 60% of basal area removed). In 2004 and 2007, DBH and tree height were measured to analyze the changes in carbon storage after thinning. In the sites of 60% of basal area removed, although the mean DBH of site 1 was higher than that of site 2, mean annual carbon storage increment in site 2 ($6.5Mg\;C\;ha^{-1}yr^{-1}$) was about 3 times higher than that in site 1 ($2.3Mg\;C\;ha^{-1}yr^{-1}$). The reason for this result was probably due to higher stem density and site quality in site 2 compared to site 1. In site 2, mean annual carbon storage increment in thinned plot ($6.5Mg\;C\;ha^{-1}yr^{-1}$) was about 1.3 times higher than that in control ($5.2Mg\;C\;ha^{-1}yr^{-1}$). The results suggest that the stem density and site quality may be much more related to the aboveground carbon storage compared to diameter class. In addition, it is needed to consider these two factors for determining whether thinning is a feasible management alternative for the increase in aboveground carbon sequestration.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• The Journal of Small Business Innovation
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• v.19 no.2
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• pp.53-68
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• 2016

Motivation and activities for technological learning, entrepreneurship, innovation, and creativity are driving forces of economic development in Asian countries. In the early stages of technological development, technological learning and entrepreneurship are efficient ways in which to catch up with advanced countries because firms can accumulate skills and knowledge quickly at relatively low risk. In the later stages of technological development, however, innovation and creativity become more important. This study aims to identify a) the factors (learning capabilities) that influence technological learning performance and b) barriers to enhancing innovation capabilities for the creative economy and organizations. The major part of this study is related to learning capabilities in the post-catch-up era. Based on a literature review and observations from Korean experiences, this study proposes a technological learning model composed of various influencing factors on technological learning. Three hypotheses are derived, and data are collected from Korean machine tool manufacturers. Intense interviews with CEOs and R&D directors are conducted using structured questionnaires. Statistical analysis, such as correlation and ANOVA are then carried out. Furthermore, this study addresses how to enhance innovation capabilities to move forward. Innovation enablers and barriers are identified by case studies and policy analysis. The results of the empirical study identify several levels of firms' learning capabilities and activities such as a) stock of technology, b) potential of technical labor, c) explicit technological efforts, d) readiness to learn, e) top management support, f) a formal technological learning system, g) high learning motivation, h) appropriate technology choice, and i) specific goal setting. These learning capabilities determine firms' learning performance, especially in the early stages of development. Furthermore, it is found that the critical factors for successful technological learning vary along the stages of technology development. Throughout the statistical and policy analyses, this study confirms that technological learning can be understood as an intrinsic principle of the technology development process. Firms perform proactive and creative learning in the late stages, while reactive and imitative learning prevails in the early stages. In addition, this study identifies the driving forces or facilitating factors enhancing innovation performance in the post catch-up era. The results of the preliminary case studies and policy analysis show some facilitating factors such as a) the strategic intent of the CEO and corporate culture, b) leadership and change agents, c) design principles and routines, d) ecosystem and collaboration with partners, and e) intensive R&D investment.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.143-159
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• 2017

Due to the rapid development of IT in recent years, not only personal information but also the key technologies and information leakage that companies have are becoming important issues. For the enterprise, the core technology that the company possesses is a very important part for the survival of the enterprise and for the continuous competitive advantage. Recently, there have been many cases of technical infringement. Technology leaks not only cause tremendous financial losses such as falling stock prices for companies, but they also have a negative impact on corporate reputation and delays in corporate development. In the case of SMEs, where core technology is an important part of the enterprise, compared to large corporations, the preparation for technological leakage can be seen as an indispensable factor in the existence of the enterprise. As the necessity and importance of Information Security Management (ISM) is emerging, it is necessary to check and prepare for the threat of technology infringement early in the enterprise. Nevertheless, previous studies have shown that the majority of policy alternatives are represented by about 90%. As a research method, literature analysis accounted for 76% and empirical and statistical analysis accounted for a relatively low rate of 16%. For this reason, it is necessary to study the management model and prediction model to prevent leakage of technology to meet the characteristics of SMEs. In this study, before analyzing the empirical analysis, we divided the technical characteristics from the technology value perspective and the organizational factor from the technology control point based on many previous researches related to the factors affecting the technology leakage. A total of 12 related variables were selected for the two factors, and the analysis was performed with these variables. In this study, we use three - year data of "Small and Medium Enterprise Technical Statistics Survey" conducted by the Small and Medium Business Administration. Analysis data includes 30 industries based on KSIC-based 2-digit classification, and the number of companies affected by technology leakage is 415 over 3 years. Through this data, we conducted a randomized sampling in the same industry based on the KSIC in the same year, and compared with the companies (n = 415) and the unaffected firms (n = 415) 1:1 Corresponding samples were prepared and analyzed. In this research, we will conduct an empirical analysis to search for factors influencing technology leakage, and propose an early warning system through data mining. Specifically, in this study, based on the questionnaire survey of SMEs conducted by the Small and Medium Business Administration (SME), we classified the factors that affect the technology leakage of SMEs into two factors(Technology Characteristics, Organization Characteristics). And we propose a model that informs the possibility of technical infringement by using Support Vector Machine(SVM) which is one of the various techniques of data mining based on the proven factors through statistical analysis. Unlike previous studies, this study focused on the cases of various industries in many years, and it can be pointed out that the artificial intelligence model was developed through this study. In addition, since the factors are derived empirically according to the actual leakage of SME technology leakage, it will be possible to suggest to policy makers which companies should be managed from the viewpoint of technology protection. Finally, it is expected that the early warning model on the possibility of technology leakage proposed in this study will provide an opportunity to prevent technology Leakage from the viewpoint of enterprise and government in advance.

• Journal of Animal Environmental Science
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• v.11 no.3
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• pp.197-206
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• 2005

This study was carried out to investigate the concentration and characteristics of dust originating from windowless broiler building in each season. 12.0m width and 46m tenth with side wall height of 3.0m was investigated and capacity was 12,800 birds at a stock density of 23.2 birds per square meter. Dust concentrations in terms of total suspended particles (TSP), and particulate matter of sizes $10{\mu}m(PM10),\;2.5{\mu}m (PM2.5),\;and\;1{\mu}m(PM1)$ were measured at 30-minute intervals. On the basis of broiler age, the average dust concentration in summer in TSP as follows: 1,229 904.5 558.8 and $1,053{\mu}g/m^3$ on the broilers' first to fourth week of age, respectively. But during winter, the average dust concentration showed an increasing pattern, as follows: 465.4, 1,401, 4,497, 5,097 and $6,873{\mu}g/m^3$ on the broilers' first to fifth week of age, respectively. The maximum dust concentration of $11,132{\mu}g/m^3$ was observed on the fifth week. On a daily basis, the maximum dust concentration during summer was detected in early morning, and the minimum in the afternoon. The aerial dust particle size of $0.05\~0.35{\mu}m$ was the highest in number. But on volume basis, particle size of 16~99 un had the largest percentage in the broiler house. Crude protein of the dust $(42.8\~65.2\%)$, on dry matter basis, was higher than that $(20.5\~24.5\%)$ fed to the broilers. Heavy metal concentration of the dust also had high levels compared with that of the feed.

• Korean Journal of Environmental Agriculture
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• v.19 no.3
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• pp.194-200
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• 2000

The amount of swine wastewater reaches about $197,000m^3$ per day at live-stock houses in the whole country. A half of the swine wastewater resources are too small to be restricted legally. This untreated wastewater causes the eutrophication in the water bodies. In case of swine wastewater treatment, the solid-liquid separation must be performed because feces(solid phase) and urine(liquid phase) have large differences in nitrogen and phosphorus concentration. It is necessary to assess exactly the concentration of the pollutants in swine wastewater for planning the wastewater treatment facilities. A full-scale operation was carried out in K city and the plant is consists of conventional plant, the supplementary flocculation basin of chemical treatment process and $anaerobic{\cdot}aerobic$ basin for nitrogen removal. The improved full-scale swine wastewater treatment plant removed the $1,500{\sim}3,000mg/l$ of total-nitrogen(T-N) to 120mg/l of T-N and $131{\sim}156mg/l$ of total-phosphorus(T-P) to $0.15{\sim}1.00mg/l$ of T-N. Accordingly, as a results of operational improvement, the removal efficiencies of T-N and T-P were over $92{\sim}96%$, 99%, respectively. The continuous supply of organic carbon sources and the state of pH played important roles for the harmonious metabolism in anaerobic basin and the pH value of anaerobic basin maintained at about 9.0 for the period of the study.

• Korean Journal of Poultry Science
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• v.39 no.1
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• pp.71-76
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• 2012

This study was carried out to investigate the performance of growing period of two-crossbred of Korean Native Chickens. A total of four hundred eighty female 2-crossbred chicks that restored strains and were aboriginal at National Institute of Animal Science. Treatments were four crossbreds (4 replications/crossbred, 30 birds/replication) as A) C strain ${\times}$ S strain, B) C strain ${\times}$ H strain, C) R strain ${\times}$ S strain, and D) L strain ${\times}$ H strain, respectively. Livability of C crossbred was the highest as over 90% and that of B crossbred was the lowest as 73~78% during growing period (P<0.05). Body weight of A crossbred was the highest at the 4 week and that of D strain was the lowest at the 4 and 8 week (P<0.05). Weekly body weight of B and C crossbreds were higher than A and D crossbreds (P<0.05). There was no significant difference among four crossbreds. Weekly feed intake of D crossbred was the highest among all crossbreds at 0~4 weeks (P<0.05). These results suggested the basic data on the record of growing phase of 2-crossbreed Korean Native Chickens.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.105-118
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• 2016

The purpose of this study is to improve the classification system of sub-divided land cover map among the land cover maps provided by the Ministry of Environment. To accomplish the purpose, first, the overseas country land cover map classification items were examined in priority. Second, the area ratio of each item established by applying the previous sub-divided classification system was analyzed. Third, the survey on the improvement of classification system targeting the users (experts and general public) who actually used the sub-divided land cover map was carried out. Fourth, a new classification system which improved the previous system by reclassifying 41 classification items into 33 items was finally established. Fifth, the established land cover classification items were applied on study area, and the land cover classification result according to the improvement method was compared with the previous classification system. Ilsan area in Goyang city where there are diverse geographic features with various land surface characteristics such as the urbanization area and agricultural land were distributed evenly were selected as the study area. The basic images used in this study were 0.25 m aerial ortho-photographs captured by the National Geographic Information Institute (NGII), and digital topographic map, detailed stock map plan, land registration map and administrative area map were used as the relevant reference data. As a result of applying the improved classification system into the study area, the area of culture-sports, leisure facilities was $1.84km^2$ which was approximately more than twice larger in comparison to the previous classification system. Other areas such as transportation and communication system and educational administration facilities were not classified. The result of this study has meaningful significance that it reflects the efficiency for the establishment and renewal of sub-divided land cover map in the future and actual users' needs.

• Korean Journal of Soil Science and Fertilizer
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• v.30 no.4
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• pp.361-369
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• 1997

A microbiological nitrate determination method by E. coli is modified in Korea, using K12 wildtype, KCTC 1116, for the quantitative reduction of $NO_3{^-}$ to $NO_2{^-}$. The nitrate in plant, soil or water sample is determined spectrophotometrically after being diazotized with sulfaniamide and N-(1-naphthl)-ethlenediamine. The modified E. coli cell method and principle for nitrate determination using Korean wildtype E. coli strain is described, and cell culture and preparation of stock suspension for E. coli as well. This modified E. coli cell method can be managed simply and fast, it is suitable for the investigation of the large serials, it can be also automated and has a high degree of sensitivity up to 0.01ppm $NO_3{^-}-N$ in the sample solution. The applicability of the modified E. coli cell method has been tested for plant, soil and water analysis on a wide range of different samples. Recovery rates of added nitrate have been determined and comparisons with other standard nitrate analytical procedures have been carried out. The results with the modified E. coli cell method show high correlation ($r^2=0.98$) with those gained by the standard analytical procedures. The advantages and disadvantages of the method are also discussed to other nitrate determination methods.