• Journal of Korean Society for Geospatial Information Science
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• v.8 no.1 s.15
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• pp.51-63
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• 2000

Dynamic traffic assignment(DTA) has been a topic of substantial research during the past decade. While DTA is gradually maturing, many aspects of DTA still need improvement, especially regarding its formulation and solution algerian Recently, with its promise for In(Intelligent Transportation System) and GIS(Geographic Information System) applications, DTA have received increasing attention. This potential also implies higher requirement for DTA modeling, especially regarding its solution efficiency for real-time implementation. But DTA have many mathematical difficulties in searching process due to the complexity of spatial and temporal variables. Although many solution algorithms have been studied, conventional methods cannot iud the solution in case that objective function or constraints is not convex. In this paper, the genetic algorithm to find the solution of DTA is applied and the Merchant-Nemhauser model is used as DTA model because it has a nonconvex constraint set. To handle the nonconvex constraint set the GENOCOP III system which is a kind of the genetic algorithm is used in this study. Results for the sample network have been compared with the results of conventional method.

• Journal of Wetlands Research
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• v.7 no.3
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• pp.75-85
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• 2005

The Construction of industrial complex areas means the increase of imperviousness rate and the increase of nonpoint pollutant emissions during a rainfall. Generally the retention basin can become the alternative for removing and controling these nonpoint pollutants. Recently Ministry of Environment are trying to change the purpose of retention basins from flooding control to nonpoint pollutant control. In order to propel the stormwater management program, administration plan of stormwater management is enacted in Spring, 2005. Hereafter, in a newly developing area, the best management practices should be established to control the nonpoint pollutant. Landuses of the research area are classified to the categories of the 1st manufacturing industry, metal industry, fiber and chemical product manufacturing industry, etc. Therefore, this research was performed to understand washed-off characteristics of stormwater and to suggest the controling method of nonpoint pollutants. The optimum capacity of the retention basin can be determined by analyzing the relationships among data of rainfall, runoff, washed-off pollutants from the areas. The rainfall analysis using the data of normal year, recent 2, 5 and 10 years shows that the 80% rainfall frequency was occurred on 10mm accumulated rainfall, but which is not considered the first flush effect. However, by considering the first flush effect, the appropriate treatment capacity of rainfall can be decreased to 4-5mm accumulated rainfall. Using the criteria, the optimum capacity of retention basin is determined to $12,000m^3$ in the research area. The washed-off nonpoint pollutant loading from the areas have beeb calculated to 435ton/yr for TSS, 238ton/yr for COD, 8,518kg/yr for TKN and 1,816kg/yr for TP. The mass of 78.3ton/yr for TSS, 20.4ton/yr for BOD, 128.6ton/yr for COD, 4.6ton/yr for TKN and 980kg/yr for TP can be reduced by constructing the retention basin. The sediment accumulation rate is also calculated by $6.53kg/m^2-hr$.

• Korean Journal of Organic Agriculture
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• v.15 no.3
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• pp.319-330
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• 2007

This study analyzed physical and chemical characteristics of peat soil to use peat soil as the materials fur pot media and investigated seedling quality of horticultural plants in order to use peat soil as the raw materials fur pot media. The summary of the results is as follows; The chemical characteristics of peat soil, which is main ingredient of pot media are as follows; pH was 4.9, EC was less than $2.0ds{\cdot}m^{-1}$, which interferes the growth of the plant and organic ingredient was 33%. When looking into the germination characteristics of plants according to the mixture of pot media, red pepper showed 54.2% speed of germination and 97% germination rate in peat soil single treatment. Therefore the peatsoil was appropriate for the pot media for red pepper. In case of cucumbers, in the 50 : 50 treatment of main ingredient (peat soil) and auxiliary ingredients (vermiculite, peat moss and perlite) they showed 100% speed of germination and 100% germination rate. Therefore 50 : 50 treatment was appropriate fur the pot media for cucumbers. In case of chinese cabbage, peat soil, perlite and peat moss mixture (50 : 25 : 25) treatment showed the highest speed of germination (77.5%), while the germination rate was a little lower (92.15%) than comparative soil. However, it was appropriate for the pot media for chinese cabbage. In case of watermelon, germination was bad because of the influence of EC when the teat soil ingredient is over 80%. However, in the mixture of peat soil and vermiculite (50:50) treatment, they showed 91.6% speed of germination and 100% germination rate. Therefore it was appropriate for the pot media for watermelon. When looking into the growth of the plants according to the mixture of ingredients, peat soil and perlite (50:50) mixture showed excellent seedling quality for cucumbers, peat soil and perlite (50:50) mixture showed excellent seedling quality and it was proven to be appropriate for the pot media for cucumbers. In case of watermelon, peat soil, peat moss and perlite (80 : 10 : 10) mixture showed excellent seedling quality and it was proven to be appropriate for the pot media for watermelon.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.6
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• pp.719-730
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• 2017

Recently, oceanic research has been carried out investigating global scientific interests and the territorial management of national marine jurisdictional waters, including exclusive economic zones (EEZ) and the open seas. To meet the needs of ocean researchers pursuing these - objectives, acquiring advanced research infrastructure, including research vessels, large facilities, and equipment, is a top priority in ocean science. However, ocean science is a similar to space science, and securing resources and state-of-the-art technology can be expensive. Faced with these challenges, our study focused on establishing a strategy for the efficient operation and management of research vessels, attempting to establish benchmarks from foreign examples that can be adapted to suit the target context. The results of this study provide ways to identify operating systems that could increase the efficiency of joint-use research vessels. The different systems examined in this study included a joint-use committee-based management system (JCMS, Type 1), private enterprise entrusted operating system (PEOS, Type 2), institutional investment operating system (IIOS, Type 3), and commissioned executive operating system (CEOS, Type 4). The efficiencies of JCMS, PEOS, IIOS and CEOS were 9.17, 5.82, 11.2 and -1.72 %, respectively. Given the total costs involved, the most affordable operating system was IIOS. JCMS was the most cost-effective system based on a quantitative cost-benefit analysis, but IIOS also had an acceptable cost-benefit balance. An operational committee would be required and regulations and guidelines shoulde be established to employ, JCMS, while a strategy to yield independent revenue would be needed to utilize an IIOS system.

• Food Engineering Progress
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• v.14 no.4
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• pp.335-341
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• 2010

The extraction of polyphenol and flavonoid from black rice bran was performed by diverse extraction methods using the sugar solution, ethanol, hot water ($80^{\circ}C$), and by subcritical water extraction (SWE) method. By SWE under operating conditions of $190^{\circ}C$, 1,300 psi, and 10 min, the maximum yields of total polyphenolic compounds (35.06${\pm}$1.28 mg quercetin equivalent (QE)/g dried material and flavonoids (7.08${\pm}$0.31 mg QE/g dried material) could be obtained. These results were over 11.77- and 12.21-fold higher than those of the ethanol extraction, which showed the highest extraction efficiency among tested conventional methods in total polyphenols (2.98${\pm}$0.74 mg QE/g dried material) and flavonoids (0.58${\pm}$0.21 mg QE/g dried material), respectively. Though the highest antioxidant activity (87.14${\pm}$1.14%) was observed at the dried extract obtained from ethanol method, the relative antioxidant activity per 1 g dried black rice bran by SWE ($190^{\circ}C$, 10 min) was over 11.53-fold higher than that by the ethanol extraction.

• Journal of Life Science
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• v.34 no.7
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• pp.476-484
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• 2024

Although two-dimensional (2D) monolayer cell culture models are still widely used as the optimal models for anticancer activity research, three-dimensional (3D) multicellular tumor spheroid (3D MTS) models that can better approximate the tumor environment can offer an alternative to bridge the gap between in vitro and animal model studies. Isoalantolactone is among the sesquiterpene lactones found in medicinal plants, including the roots of Elecampane (Inula helenium L.), and is known to have various pharmacological activities, including anticancer activity. In this study, we investigated whether the anticancer activity of isoalantolactone observed in 2D models could be reproduced in a 3D MTS model derived from human hepatocellular carcinoma (HCC) Hep3B cells. According to our results, isoalantolactone inhibited the formation of MTSs in a manner dependent on the treatment concentration, which was accompanied by an increase in reactive oxygen species (ROS) generation. In particular, as isoalantolactone treatment and the culture time increased, the area of proliferating cells was replaced by cells in which apoptosis was induced. Additionally, in MTSs, isoalantolactone increased the expression of death-receptor-related proteins and the activity of caspase-3, and it decreased the expression of the Bax/Bcl-2 expression ratio and total poly(ADP-ribose) polymerase. However, when the production of ROS was artificially blocked, all these changes caused by isoalantolactone were attenuated and the cell survival rate of MTS cells was restored. Therefore, the results of this study suggest that the induction of apoptosis in Hep3B cell-derived MTSs by isoalantolactone is achieved through the activation of extrinsic and intrinsic pathways and is ROS-dependent.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.9
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• pp.3856-3868
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• 2011

Until recently, research trend in real estate has been focused on real estate market and the market analysis. But the studies on real estate training program development for real estate agents to improve their job performance are relatively short in numbers. Thus, this study shows empirical analysis of the needs for the training programs for real estate agents in Cheonan to improve their job performance. The results are as follows. First, in the survey of asking what educational contents they need in order to improve real estate agents' job performance, most of the respondents show their needs for the analysis of house's value, legal knowledge, real estate management, accounting, real estate marketing, and understanding of the real estate policy. This is because they are well aware that the best way of responding to the changing clients' needs comes from training programs. Secondly, asked about real estate marketing strategies, most of respondents showed their awareness of new strategies to meet the needs of clients. This is because new forms of marketing strategies including internet ads are needed in the field as the paradigm including Information Technology changes. Thirdly, asked about the need for real estate-related training programs, 92% of the respondents answered they need real estate education programs run by the continuing education centers of the universities. In addition, the survey showed their needs for retraining programs that utilize the resources in the local universities. Other than this, to have effective and efficient training programs, they demanded running a training system by utilizing the human resources of the universities under the name of the department of 'Real Estate Contract' for real estate agents' job performance. Fourthly, the survey revealed real estate management(44.2%) and real estate marketing(42.3%) is the most chosen contents they want to take in the regular course for improving real estate agents' job performance. This shows their will to understand clients' needs through the mind of real estate management and real estate marketing. The survey showed they prefer the training programs as an irregular course to those in the regular one. Despite the above results, this study chose subjects only in Cheanan and thus it needs to research more diverse areas. The needs of programs to improve real estate agents job performance should be analyzed empirically targeting the real estate agents not just in Cheonan but also cities like Pyeongchon, Ilsan and Bundang in which real estate business is booming, as well as undergraduate and graduate students whose major is real estate studies. These studies will be able to provide information to help develop the customized training programs by evaluating elements that real estate agents need in order to meet clients satisfaction and improve their job performance. Many variables of the program development learned through these studies can be incorporated in the curriculum of the real estate studies and used very practically as information for the development of the real estate studies in this fast changing era.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.167-194
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• 2019

This research starts from the four basic concepts of incentive incompatibility, limited information, myopia and decision variable which are confronted when making decisions in keyword bidding. In order to make these concept concrete, four framework approaches are designed as follows; Strategic approach for the incentive incompatibility, Statistical approach for the limited information, Alternative optimization for myopia, and New model approach for decision variable. The purpose of this research is to propose the statistical optimization model in constructing the portfolio of Sponsored Search Advertising (SSA) in the Sponsor's perspective through empirical tests which can be used in portfolio decision making. Previous research up to date formulates the CTR estimation model using CPC, Rank, Impression, CVR, etc., individually or collectively as the independent variables. However, many of the variables are not controllable in keyword bidding. Only CPC and Rank can be used as decision variables in the bidding system. Classical SSA model is designed on the basic assumption that the CPC is the decision variable and CTR is the response variable. However, this classical model has so many huddles in the estimation of CTR. The main problem is the uncertainty between CPC and Rank. In keyword bid, CPC is continuously fluctuating even at the same Rank. This uncertainty usually raises questions about the credibility of CTR, along with the practical management problems. Sponsors make decisions in keyword bids under the limited information, and the strategic portfolio approach based on statistical models is necessary. In order to solve the problem in Classical SSA model, the New SSA model frame is designed on the basic assumption that Rank is the decision variable. Rank is proposed as the best decision variable in predicting the CTR in many papers. Further, most of the search engine platforms provide the options and algorithms to make it possible to bid with Rank. Sponsors can participate in the keyword bidding with Rank. Therefore, this paper tries to test the validity of this new SSA model and the applicability to construct the optimal portfolio in keyword bidding. Research process is as follows; In order to perform the optimization analysis in constructing the keyword portfolio under the New SSA model, this study proposes the criteria for categorizing the keywords, selects the representing keywords for each category, shows the non-linearity relationship, screens the scenarios for CTR and CPC estimation, selects the best fit model through Goodness-of-Fit (GOF) test, formulates the optimization models, confirms the Spillover effects, and suggests the modified optimization model reflecting Spillover and some strategic recommendations. Tests of Optimization models using these CTR/CPC estimation models are empirically performed with the objective functions of (1) maximizing CTR (CTR optimization model) and of (2) maximizing expected profit reflecting CVR (namely, CVR optimization model). Both of the CTR and CVR optimization test result show that the suggested SSA model confirms the significant improvements and this model is valid in constructing the keyword portfolio using the CTR/CPC estimation models suggested in this study. However, one critical problem is found in the CVR optimization model. Important keywords are excluded from the keyword portfolio due to the myopia of the immediate low profit at present. In order to solve this problem, Markov Chain analysis is carried out and the concept of Core Transit Keyword (CTK) and Expected Opportunity Profit (EOP) are introduced. The Revised CVR Optimization model is proposed and is tested and shows validity in constructing the portfolio. Strategic guidelines and insights are as follows; Brand keywords are usually dominant in almost every aspects of CTR, CVR, the expected profit, etc. Now, it is found that the Generic keywords are the CTK and have the spillover potentials which might increase consumers awareness and lead them to Brand keyword. That's why the Generic keyword should be focused in the keyword bidding. The contribution of the thesis is to propose the novel SSA model based on Rank as decision variable, to propose to manage the keyword portfolio by categories according to the characteristics of keywords, to propose the statistical modelling and managing based on the Rank in constructing the keyword portfolio, and to perform empirical tests and propose a new strategic guidelines to focus on the CTK and to propose the modified CVR optimization objective function reflecting the spillover effect in stead of the previous expected profit models.