• Journal of Climate Change Research
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• v.6 no.4
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• pp.357-366
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• 2015

This study was conducted to estimate carbon stocks of Quercus serrata with drawing volume of trees in each tree height and DBH applying the suitable stem taper equation and tree specific carbon emission factors, using collected growth data from all over the country. Information on distribution area, tree number per hectare, tree volume and volume stocks were obtained from the $5^{th}$ National Forest Inventory (2006~2010), and method provided in IPCC GPG was applied to estimate carbon storage and removals. Performance in predicting stem diameter at a specific point along a stem in Quercus serrata by applying Kozak's model,$d=a_1DBH^{a_2}a_3^{DBH}X^{b_1Z^2+b_2ln(Z+0.001)+b_3{\sqrt{Z}}+b_4e^Z+b_5({\frac{DBH}{H}})}$, which is well known equation in stem taper estimation, was evaluated with validations statistics, Fitness Index, Bias and Standard Error of Bias. Consequently, Kozak's model turned out to be suitable in all validations statistics. Stem volume tables of Quercus serrata were derived by applying Kozak's model and carbon stock tables in each tree height and DBH were developed with country-specific carbon emission factors ($WD=0.65t/m^3$, BEF=1.55, R=0.43) of Quercus serrata. As a result of carbon stock analysis by age class in Quercus serrata, carbon stocks of IV age class (11,358 ha, 36.5%) and V age class (10,432; 33.5%) which take up the largest area in distribution of age class were 957,000 tC and 1,312,000 tC. Total carbon stocks of Quercus serrata were 3,191,000 tC which is 3% compared with total percentage of broad-leaved forest and carbon sequestration per hectare(ha) was 3.8 tC/ha/yr, $13.9tCO_2/ha/yr$, respectively.

• Proceedings of the Korean DIstribution Association Conference
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• 2003.05a
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• pp.71-92
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• 2003

Specialty stores, which have been major channels of Korean cosmetic industry, are bringing out a lot of problems in current distribution channel systems because of its repeated depression of sales. Especially, inefficiency in distribution channel systems is caused by cannibalistic price-off competition between specialty stores, too many launchings of new products, excessive sales promotion, absence or surplus of stock, and so on. Using qualitative methods such as in-depth interview and group discussion, the authors attempt In diagnose fundamental problems of the cosmetic specialty store distribution channels in three viewpoints； achievement of goals, marketing flows in channels, and relationship management. In addition, this paper suggests core strategies for building up the competitiveness of both of the maker and the retailer, The competitive strategies are mainly about securing profitability of retailers, smoothening of marketing flows in channels, and building-up trustful relationships between distribution channel members.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.29-43
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• 2012

Financial data such as stock index returns and exchange rates have the properties of heavy tail and asymmetry compared to normal distribution. When we estimate VaR using the GARCH model (with the conditional return distribution of normal) it shows the tendency of the lower estimation and clustering in the losses over the estimated VaR. In this paper, we argue that this problem can be resolved through the adaptation of the unbounded Johnson distribution as that of the condition return. We also compare this model with the GARCH with the conditional return distribution of normal and student-t. Using the losses exceed the ex-ante VaR, estimates, we check the validity of the GARCH models through the failure proportion test and the clustering test. We nd that the GARCH model with conditional return distribution of unbounded Johnson provides an appropriate estimation of the VaR and does not occur the clustering of violations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.129-134
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• 1997

The purpose of this study is to estimate the distribution rate of R&D input on R&D output in major manufacturing industrial sector. The distribution rate is estimated on time-series data for the period 1980 to 1996. The data used in this study can be divided into the two categories. 1) R&D output data (Patent, Utility) 2) R&D input data (R&D expenditure, R&D workers) The raw data of R&D expenditure is transformed into R&D stock. And the specific production function is used to represent the interaction between R&D input and output. The production function shows the maximum rate of R&D output that can be achieved by certain given, technologically possible, R&D input combinations. The main findings can be summarized as follows. 1) There was a diminishing return between R&D input and output$(\alpha+\beta<1). 2) R&D output growth was more affected by R&D expenditures than R&D workers. 3) R&D workers were more contributed highly to Patent granted than Utility model.

• The Journal of the Korean Society for Microbiology
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• v.17 no.1
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• pp.57-66
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• 1982

The correlation between the serotypes and sensitivity distribution of Pseudomonas aeruginosa was studied with stock strains of department, strains isolated from various clinical sources and strains of haspital environment of the past two years. Two hundred and fifty seven strains were typable and 38 strains were untypable out of 295 clinical sorces. Serotype B was most provalent(27.6%) followed by serotype G(24.9%), serotype E(23.3%) and serotype A(7.8%) among 257 typable strains. However, no serotype J,L and M were observed. Serotype B,G,E and A were isolated from pus, sputum, wound, burn site and urine. Serotypes E were most frequently isolated from nasal discharge and serotypes K were isolated from pus. There were no apparent differences in sensitivity distribution of streptomycin, carbenicillin and ampicillin between the clinical and The environmental origin. However, the strains of environmental origin were found to be relatively more susceptable to tetracycline, gentamicin and fradiomycin than the strains of clinical sources in high concentration. The strains of clinical sources of serotype B,G,E and A showed different resistant patterns to all antimicrobial agents except for carbenicillin. Serotype E showed the highest percentage resistance followed by serotype G,B and A.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.31-37
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• 2017

Recently Drone technology is emerging as an alternative new way of distribution systems services. Amazon, Google which are global network chain distribution companies are developing an idea of Drone based delivery service and applied for patent for Drone distribution systems in USA. In this paper, we investigate a way to adopt Drone system to Air Cargo logistics, in particular, drone system based on combination of Light ID and RFID technology in the management procedure in stock warehouse. Also we explain the expected impact of Drone systems to customs declaration process. In this paper, we address the investigated limitations of Drone by the Korean Aviation Act as well as suggest the directions of future research for application of Drone to Air logistics industry with investigated limitations.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.4
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• pp.41-65
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• 2002

We study a multi-component production/inventory system in which individual components are made to meet various demand types. We assume that the demands arrive according to a Poisson process, but there is a fixed probability that a demand requests a particular kit of different components. Each component is produced by a flow line with several stations in which the processing times of each station follow a two-stage Coxian distribution. The production of each component is operated by an independent base-stock policy with blocking. We assume that the time needed to assemble final products follows a general distribution and the capacity of an assembling facility is sufficiently large. The objective of this study is to obtain key performance measures such as the distribution of the number of each orders for each final product and the mean time of fulfilling a customer order. The basic principle of the proposed approximation method is to decompose the original system into a set of subsystems, each subsystem being associated with a flow line. Each subsystem is analyzed in isolation using a Marie's method. An iterative procedure is then used to determine the unknown parameters of each subsystem. Numerical results show that the accuracy of the approximation method is acceptable.

• Journal of Ecology and Environment
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• v.43 no.4
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• pp.390-399
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• 2019

Background: The Northern Hemisphere forest ecosystem is a major sink for atmospheric carbon dioxide, and the subalpine zone stores large amounts of carbon; however, their magnitude and distribution of stored carbon are still unclear. Results: To clarify the carbon distribution and carbon budget in the subalpine zone at volcanic Jeju Island, Korea, we report the C stock and changes therein owing to vegetation form, litter production, forest floor, and soil, and soil respiration between 2014 and 2016, for three subalpine forest ecosystems, namely, Abies koreana forest, Taxus cuspidata forest, and Juniperus chinensis var. sargentii forest. Organic carbon distribution of vegetation and NPP were bigger in the A. koreana forest than in the other two forests. However, the amount of soil organic carbon distribution was the highest in the J. chinensis var. sargentii forest. Compared to the amount of organic carbon distribution (AOCD) of aboveground vegetation (57.15 t C ha^-1) on the subalpine-alpine forest in India, AOCD of vegetation in the subalpine forest in Mt. Halla was below 50%, but AOCD of soil in Mt. Halla was higher. We also compared our results of organic carbon budget in subalpine forest at volcanic island with data synthesized from subalpine forests in various countries. Conclusions: The subalpine forest is a carbon reservoir that stores a large amount of organic carbon in the forest soils and is expected to provide a high level of ecosystem services.

• The Korean Journal of Financial Management
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• v.23 no.2
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• pp.143-170
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• 2006

We explore how stock returns and volatility have been impacted by securities market stimulating and controlling plans during the 1980-2004 period, using return analysis, event study, and BFL tests. First, we examine effectiveness of the stimulating plans for a depressed market and the controlling plans for an overheated market with respect to different firm sizes and industries as well as the whole market. KOSPI, large-sized, finance, and manufacturing company stock prices significantly rise following stimulating plans, implying that the plans are quite effective. Controlling plans also seem effective as stock prices stop rising and tend to decline following the plans. Second, we test whether securities market plans have any further impact with respect to fun sizes and industries in addition to the impact on the entire market. Only large-sized stocks show additional response to stimulating plans, while small-sized, electrical-electronic equipment, distribution, and manufacturing industries are further impacted by controlling plans. Third, the results of BFL tests show that volatility does not change around the announcement dates of stimulating and controlling plans. It appears that securities market plans have no impact on volatility. Only stock returns respond to the plans.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.257-264
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• 2003

In the context of a dynamic trading environment, the ultimate goal of the financial forecasting system is to optimize a specific trading objective. This paper proposes a two-phase (extraction and filtering) stock trading system that aims at maximizing the rates of returns. Extraction of stocks is performed by searching specific time-series patterns described by a combination of values of technical indicators. In the filtering phase, several rules are applied to the extracted sets of stocks to select stocks to be actually traded. The filtering rules are automatically induced from past data. From a large database of daily stock prices, the values of technical indicators are calculated. They are used to make the extraction patterns, and the distributions of the discretization intervals of the values are calculated for both positive and negative data sets. We assumed that the values in the intervals of distinctive distribution may contribute to the prediction of future trend of stocks, so the rules for filtering stocks are automatically induced from the data in those intervals. We show the rates of returns when using our trading system outperform the market average. These results mean rule induction method using distributional differences is useful.