• Sleep Medicine and Psychophysiology
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• v.19 no.2
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• pp.68-76
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• 2012

Objectives: Sleep disorders cause changes of autonomic nervous system (ANS) which affect cardiovascular system. Primary insomnia (PI) makes acceleration of sympathetic nervous system (SNS) tone by sleep deficiency and arousal. Obstructive sleep apnea syndrome (OSAS) sets off SNS by frequent arousals and hypoxemias during sleep. We aimed to compare the changes of heart rate variability (HRV) indices induced by insomnia or sleep apnea to analyze for ANS how much to be affected by PI or OSAS. Methods: Total 315 subjects carried out nocturnal polysomnography (NPSG) were categorized into 4 groups - PI, mild, moderate and severe OSAS. Severity of OSAS was determined by apnea-hypopnea index (AHI). Then we selected 110 subjects considering age, sex and valance of each group's size [Group 1 : PI (mean age=$41.50{\pm}13.16$ yrs, AHI <5, n=20), Group 2 : mild OSAS (mean age=$43.67{\pm}12.11$ yrs, AHI 5-15, n=30), Group 3 : moderate OSAS (mean age $44.93{\pm}12.38$ yrs, AHI 16-30, n=30), Group 4 : severe OSAS (mean age=$45.87{\pm}12.44$ yrs, AHI >30, n=30)]. Comparison of HRV indices among the four groups was performed with ANCOVA (adjusted for age and body mass index) and Sidak post-hoc test. Results: We found statistically significant differences in HRV indices between severe OSAS group and the other groups (PI, mild OSAS and moderate OSAS). And there were no significant differences in HRV indices among PI, mild and moderate OSAS group. In HRV indices of PI and severe OSAS group showing the most prominent difference in the group comparisons, average RR interval were $991.1{\pm}27.1$ and $875.8{\pm}22.0$ ms (p=0.016), standard deviation of NN interval (SDNN) was $85.4{\pm}6.6$ and $112.8{\pm}5.4$ ms (p=0.022), SDNN index was $57.5{\pm}5.2$ and $87.6{\pm}4.2$ (p<0.001), total power was $11,893.5{\pm}1,359.9$ and $18,097.0{\pm}1,107.2ms^2$(p=0.008), very low frequency (VLF) was $7,534.8{\pm}1,120.1$ and $11,883.8{\pm}912.0ms^2$ (p=0.035), low frequency (LF) was $2,724.2{\pm}327.8$ and $4,351.6{\pm}266.9ms^2$(p=0.003). Conclusions: VLF and LF which were correlated with SNS tone showed more increased differences between severe OSAS group and PI group than other group comparisons. We could suggest that severe OSAS group was more influential to increased SNS activity than PI group.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.39-55
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• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Journal of the Korean Society of Food Science and Nutrition
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• v.39 no.6
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• pp.909-919
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• 2010

The purpose of this study was to investigate the demand and use of fresh-cut produce in school foodservice and restaurant industries. The subjects of this survey study were 200 school nutritionists and 70 cooks or managers in the restaurant industry nationwide. The data were collected by means of self-administered or e-mail questionnaires. Data analysis was completed using the SPSS window (ver. 12.0) program including frequency, $\chi^2$-test and t-test. Survey questions assessed the general characteristic of respondents, and the supply, use, and demand of fresh-cut produce in school foodservice and restaurant industries. Over 74% of the subjects have used fresh-cut produce. Most of the school foodservice (84.0%) kept fresh-cut produce for one day, while restaurant industry (28.3%) kept them up to three days. The nutritionists of school foodservice and managers of restaurant industry considered origin and date of production as the most important factor, respectively, when fresh-cut produce were being used. Fresh-cut root vegetable, such as potato and carrot was used mostly. The main reason not to use the fresh cut produce was due to the distrust of the fresh-cut produce safety in school foodservice and cost in restaurant industry. The main problem in fresh-cut produce use was the need of rewashing (29.9%) in school foodservice and irregular size (39.0%) in restaurant industry. These results indicate that the quality standard and size specification must be prepared with production guideline of safe fresh-cut produce.

• Investigative Magnetic Resonance Imaging
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• v.8 no.2
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• pp.100-108
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• 2004

Purpose : Early degeneration of articular cartilage is accompanied by a loss of glycosaminoglycan (GAG) and the consequent change of the integrity. The purpose of this study was to biochemically quantify the loss of GAG, and to evaluate the $Gd(DTPA)^{2-}$-enhanced, and T1, T2, rho relaxation map for detection of the early degeneration of cartilage. Materials and Methods : A cartilage-bone block in size of $8mm\;\times\;10mm$ was acquired from the patella in each of three pigs. Quantitative analysis of GAG of cartilage was performed at spectrophotometry by use of dimethylmethylene blue. Each of cartilage blocks was cultured in one of three different media: two different culture media (0.2 mg/ml trypsin solution, 1mM Gd $(DTPA)^{2-}$ mixed trypsin solution) and the control media (phosphate buffered saline (PBS)). The cartilage blocks were cultured for 5 hrs, during which MR images of the blocks were obtained at one hour interval (0 hr, 1 hr, 2 hr, 3 hr, 4 hr, 5 hr). And then, additional culture was done for 24 hrs and 48 hrs. Both T1-weighted image (TR/TE, 450/22 ms), and mixed-echo sequence (TR/TE, 760/21-168ms; 8 echoes) were obtained at all times using field of view 50 mm, slice thickness 2 mm, and matrix $256\times512$. The MRI data were analyzed with pixel-by-pixel comparisons. The cultured cartilage-bone blocks were microscopically observed using hematoxylin & eosin, toluidine blue, alcian blue, and trichrome stains. Results : At quantitation analysis, GAG concentration in the culture solutions was proportional to the culture durations. The T1-signal of the cartilage-bone block cultured in the $Gd(DTPA)^{2-}$ mixed solution was significantly higher ($42\%$ in average, p<0.05) than that of the cartilage-bone block cultured in the trypsin solution alone. The T1, T2, rho relaxation times of cultured tissue were not significantly correlated with culture duration (p>0.05). However the focal increase in T1 relaxation time at superficial and transitional layers of cartilage was seen in $Gd(DTPA)^{2-}$ mixed culture. Toluidine blue and alcian blue stains revealed multiple defects in whole thickness of the cartilage cultured in trypsin media. Conclusion : The quantitative analysis showed gradual loss of GAG proportional to the culture duration. Microimagings of cartilage with $Gd(DTPA)^{2-}$-enhancement, relaxation maps were available by pixel size of $97.9\times195\;{\mu}m$. Loss of GAG over time better demonstrated with $Gd(DTPA)^{2-}$-enhanced images than with T1, T2, rho relaxation maps. Therefore $Gd(DTPA)^{2-}$-enhanced T1-weighted image is superior for detection of early degeneration of cartilage.

• Radiation Oncology Journal
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• v.13 no.2
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• pp.181-189
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• 1995

Pupose: Radiation therapy(RT) is conventionally standard treatment for locally advanced stage for uterine cervix cancer. Recently to improve treatment results, combined chemotherapy and radiation therapy was tried We retrospectively analysed our experience of 122 patients. Comparision of the results in 45 patients treated with RT alone and 77 patients treated with RT plus chemotherapy was made Materials and Mathods: From January 1985 to December 1991 122 patients with cervix cancer were treated with whole pelvic external RT and ICR(34 1 ICR, 77 2 ICR, 11 high dose rate ICR) in our department. Forty five patients were treated with RT alone, and 77 patients were treated with combined RT plus chemotherapy Mean age was 58 years(range:29-81). Histologic types were 111 squamous cell carcinoma, 5 large cell carcinoma, 3 adenocarcinoma, and 2 adenosquamous cell carcinoma. According to the FIGO stage 6 had stage $IA(4.9\%),$ 11 had $IIA(9.0\%),$ 37 had $IIB(30.3\%),$ 3 had $IIIA(2.5\%),$ 63 had $IIIB(51.6\%).$ and 2 had stage $IV(1.6\%).$ In 77 patients with RT Plus chemotherapy, 36 patients were treated with VBP(vinblastin, bleomycin, cisplatinum) , 39 patients with cisplatinum plus 5-FU and 2 patients with 5-FU. Results: Complete response after external RT (3960cGy-5500cGy) was achieved in 61 patients$(50\%).$ The actuarial 5 year and 9 rear survival rate was $57.8\%\;and\;53.9\%,$ respectively. Five rear actuarial survival rate was $63.1\%$with RT alone(n=45) and $55.9\%$ with RT plus chemotherapy(n=77). The 5 rear survival rate was $35.5\%$ for 1 course of ICR and $67\%$ for 2 courses of ICR. There was statistically significant advantage of survival with RT alone group who were treated with 2 courses of ICR and dose to the A Point)=8000cGy (4/25 died). In RT plus chemotherapy group, dose response was not seen and there was no difference in 5 year survival between 1 course and 2 course of ICR $(50\%\;vs\;56.8\%),$ and dose to point A less than 8000 cGy and more than 8000 $cGy(55.6\%\;vs\;55.7\%).$ There was no significant difference in survival between RT alone and RT plus chemotherapy for patients with tumor size greater than 3cm in size. Five year survival rate for early stage (Stage IB and IIA) with RT alone group and with RT Plus chemotherapy group was $60\%\;and\;77.0\%,$ respectively In advanced stage (stage IIB, IIIA, IIIB, IVA) the 5 year actuarial survival rate were $62.6\%,$ for RT alone group vs $53.6\%$ for RT plus chemotherapy group. Conclusion: Present study demonstrates that there is no survival advantage with adding chemotherapy in advanced stage of uterine cervix cancer. RT alone is considered as treatment of choice for patients with locally advanced cervix cancer. There was increased survival in RT alone group treated with RT dose above 8000 cGy to point A and 2 course of ICR. but 2 course of ICR and RT dose above 8000 cGy to point A did not affect survival advantage in RT plus chemotherapy group.

• Horticultural Science & Technology
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• v.34 no.6
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• pp.886-897
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• 2016

The physical properties of rooting media for the establishment of plugs in a greenhouse are modified according to variations in the greenhouse environment throughout the season. In this study, we established a standard for rooting media for the production of plug seedlings for each growing season (summer, winter and spring fall). Eight types of peatmoss (PM) and 4 types of perlite (PL) commonly used in Korea were collected and blended with the ratio of 7 parts PM to 3 parts PL (v/v) to make 32 different rooting media blends. We determined the total porosity (TP), container capacity (CC), air-filled porosity (AFP), pH, and electrical conductivity (EC) of the 32 media blends, and 6 media blends were selected for seasonal use. We also conducted additional analyses for plant easily available water (EAW), buffering water (BW), cation exchange capacity (CEC), and nutrient contents in the 6 media blends. The TP, CC, and AFP of the 32 media blends ranged from 64.7 to 96.0%, 42.9 to 90.1%, and 1.3 to 27.8%, respectively, indicating that the physical properties were strongly influenced by the type of PM and PL. The pH and EC of the PMs ranged from 2.96 to 3.81 and 0.08 to $0.47dS{\cdot}m^{-1}$, respectively. However, after blending the PM with the PL the pH was raised and the EC was lowered The media blends selected for the summer growing season were Blonde Golden peatmoss (BG) + No. 1 perlite size < 1 mm (PE1) and Latagro 0-10 mm (L1) + No. 2 perlite size 1-2 mm (PE2). These two media blends had 89.8-90.9% of TP, 80.8-81.3% of CC, and 9.0-9.7% of AFP. The media blends selected for the winter growing season were Sfagnumi Turvas (ST) + PE2 and Latagro 20-40 mm (L3) + PE2. These media blends had 79.9-86.7% of TP, 60.4-74.9% of CC, and 11.8-19.6% of AFP. The TP, CC, and AFP of two media blends, BG + No.3 perlite 2-5 mm (PE3) and Orange peatmoss (O) + PE3, selected for the spring and fall growing seasons, respectively, were 85.2-87.3%, 77.9%, and 7.4-9.4%, respectively. The percentage of EAW of the media blends selected for the spring, summer, and winter growing seasons ranged from 24.2-24.9%, 22.0-28.6%, and 18.0-21.8%, respectively, but the percentages of BW were not significantly different among the selected root media blends. The pH, EC, and CEC of the 6 selected media blends ranged from 3.11-3.97, $0.06-0.26dS{\cdot}m^{-1}$, and $97-119meq{\cdot}100g^{-1}$, respectively.

• Journal of the Korean Society of Groundwater Environment
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• v.7 no.3
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• pp.103-115
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• 2000

The formation of brown-colored precipitates is one of the serious problems frequently encountered in the development and supply of groundwater in Korea, because by it the water exceeds the drinking water standard in terms of color. taste. turbidity and dissolved iron concentration and of often results in scaling problem within the water supplying system. In groundwaters from the Pajoo area, brown precipitates are typically formed in a few hours after pumping-out. In this paper we examine the process of the brown precipitates' formation using the equilibrium thermodynamic and kinetic approaches, in order to understand the origin and geochemical pathway of the generation of turbidity in groundwater. The results of this study are used to suggest not only the proper pumping technique to minimize the formation of precipitates but also the optimal design of water treatment methods to improve the water quality. The bed-rock groundwater in the Pajoo area belongs to the Ca-$HCO_3$type that was evolved through water/rock (gneiss) interaction. Based on SEM-EDS and XRD analyses, the precipitates are identified as an amorphous, Fe-bearing oxides or hydroxides. By the use of multi-step filtration with pore sizes of 6, 4, 1, 0.45 and 0.2 $\mu\textrm{m}$, the precipitates mostly fall in the colloidal size (1 to 0.45 $\mu\textrm{m}$) but are concentrated (about 81%) in the range of 1 to 6 $\mu\textrm{m}$in teams of mass (weight) distribution. Large amounts of dissolved iron were possibly originated from dissolution of clinochlore in cataclasite which contains high amounts of Fe (up to 3 wt.%). The calculation of saturation index (using a computer code PHREEQC), as well as the examination of pH-Eh stability relations, also indicate that the final precipitates are Fe-oxy-hydroxide that is formed by the change of water chemistry (mainly, oxidation) due to the exposure to oxygen during the pumping-out of Fe(II)-bearing, reduced groundwater. After pumping-out, the groundwater shows the progressive decreases of pH, DO and alkalinity with elapsed time. However, turbidity increases and then decreases with time. The decrease of dissolved Fe concentration as a function of elapsed time after pumping-out is expressed as a regression equation Fe(II)=10.l exp(-0.0009t). The oxidation reaction due to the influx of free oxygen during the pumping and storage of groundwater results in the formation of brown precipitates, which is dependent on time, $Po_2$and pH. In order to obtain drinkable water quality, therefore, the precipitates should be removed by filtering after the stepwise storage and aeration in tanks with sufficient volume for sufficient time. Particle size distribution data also suggest that step-wise filtration would be cost-effective. To minimize the scaling within wells, the continued (if possible) pumping within the optimum pumping rate is recommended because this technique will be most effective for minimizing the mixing between deep Fe(II)-rich water and shallow $O_2$-rich water. The simultaneous pumping of shallow $O_2$-rich water in different wells is also recommended.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.6
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• pp.149-153
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• 2008

The pollutant capacity occurred before and after the development of a watershed should be quantitatively estimated and controlled for the minimization of water contamination. The Ministry of Environment suggested a guideline for the legal management of nonpoint source from 2006. However, the rational method for the determination of treatment capacity from nonpoint source proposed in the guideline has the problem in the field application because it does not reflect the project based cases and overestimates the pollutant load to be reduced. So, we perform the standard rainfall analysis by analytical probabilistic method for the estimation of an additional pollutant load occurred by a project and suggest a methodology for the estimation of contaminant capacity instead of a simple rational method. The suggested methodology in this study could determine the reasonable capacity and efficiency of a treatment facility through the estimation of pollutant load from nonpoint source and from this we can manage the watershed appropriately. We applied a suggested methodology to the projects of housing land development and a dam construction in the watersheds. When we determine the treatment capacity by a rational method without consideration of the types of projects we should treat the 90% of pollutant capacity occurred by the development and to do so, about 30% of the total cost for the development should be invested for the treatment facility. This requires too big cost and is not realistic. If we use the suggested method the target pollutant capacity to be reduced will be 10 to 30% of the capacity occurred by the development and about 5 to 10% of the total cost can be used. The control of nonpoint source must be performed for the water resources management. However it is not possible to treat the 90% of pollutant load occurred by the development. The proper pollutant capacity from nonpoint source should be estimated and controlled based on various project types and in reality, this is very important for the watershed management. Therefore the results of this study might be more reasonable than the rational method proposed in the Ministry of Environment.

• 한국산학경영학회:학술대회논문집
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• 2004.11a
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• pp.55-72
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• 2004

Before 2003 the companies In Korea should capitalize the interest expenses that are attributable to the acquisition, construction or production of a qualifying assets. However, according to the revised standard which should be applied from 2003, the companies can either capitalize the interest expenses or recognize as an expense when they are incurred. Therefore almost all the companies confronted with the decision making of accounting choices on the interest capitalization. This paper empirically examines which financial characteristics of the companies affect the accounting choice by using logistic regression model and reviews the sufficiency of the foot notes disclosures regarding the capitalized interest. The variables of the financial characteristics are change of debt-equity ratio, borrowing ratio, qualifying assets ratio, firm sire and income smoothing. The results of this study are summarized as follows. First, among the financial characteristics, only qualifying asset ratio has the significant difference between capitalized companies and expensing companies. Second, the results of logistic regression indicate that qualifying asset ratio and firm size have the significant influence on the accounting choices. Therefore, I cannot find the evidence supporting that the companies use the accounting choice to manage the financial ratios.