• Journal of Korean Society of Water and Wastewater
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• v.34 no.6
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• pp.503-512
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• 2020

Identifying the water circulation status is one of the indispensable processes for watershed management in an urban area. Recently, various water circulation models have been developed to simulate the water circulation, but it takes a lot of time and cost to make a water circulation model that could adapt the characteristics of the watershed. This paper aims to develop a water circulation state estimation model that could easily calculate the status of water circulation in an urban watershed by using multiple linear regression analysis. The study watershed is a watershed in Seoul that applied the impermeable area ratio in 1962 and 2000. And, It was divided into 73 watersheds in order to consider changes in water circulation status according to the urban characteristic factors. The input data of the SHER(Similar Hydrologic Element Response) model, a water circulation model, were used as data for the urban characteristic factors of each watershed. A total of seven factors were considered as urban characteristic factors. Those factors included annual precipitation, watershed area, average land-surface slope, impervious surface ratio, coefficient of saturated permeability, hydraulic gradient of groundwater surface, and length of contact line with downstream block. With significance probabilities (or p-values) of 0.05 and below, all five models showed significant results in estimating the water circulation status such as the surface runoff rate and the evapotranspiration rate. The model that was applied all seven urban characteristics factors, can calculate the most similar results such as the existing water circulation model. The water circulation estimation model developed in this study is not only useful to simply estimate the water circulation status of ungauged watersheds but can also provide data for parameter calibration and validation.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.31-39
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• 2014

Seasonal influenza epidemics cause 3 to 5 millions severe illness and 250,000 to 500,000 deaths worldwide each year. To prepare better controls on severe influenza epidemics, many studies have been proposed to achieve near real-time surveillance of the spread of influenza. Korea CDC publishes clinical data of influenza epidemics on a weekly basis typically with a 1-2-week reporting lag. To provide faster detection of epidemics, recently approaches using unofficial data such as news reports, social media, and search queries are suggested. Collection of such data is cheap in cost and is realized in near real-time. This research aims to develop regression models for early detecting the outbreak of the seasonal influenza epidemics in Korea with keyword query information provided from the Naver (Korean representative portal site) trend services for PC and mobile device. We selected 20 key words likely to have strong correlations with influenza-like illness (ILI) based on literature review and proposed a logistic regression model and a multiple regression model to predict the outbreak of ILI. With respect of model fitness, the multiple regression model shows better results than logistic regression model. Also we find that a mobile-based regression model is better than PC-based regression model in estimating ILI percentages.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.4
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• pp.129-134
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• 2018

Recently, the artificial neural network (ANN) model is a promising technique in the prediction, numerical control, robot control and pattern recognition. We predicted the outside temperature of greenhouse using ANN and utilized the model in greenhouse control. The performance of ANN model was evaluated and compared with multiple regression model(MRM) and support vector machine (SVM) model. The 10-fold cross validation was used as the evaluation method. In order to improve the prediction performance, the data reduction was performed by correlation analysis and new factor were extracted from measured data to improve the reliability of training data. The backpropagation algorithm was used for constructing ANN, multiple regression model was constructed by M5 method. And SVM model was constructed by epsilon-SVM method. As the result showed that the RMSE (Root Mean Squared Error) value of ANN, MRM and SVM were 0.9256, 1.8503 and 7.5521 respectively. In addition, by applying the prediction model to greenhouse heating load calculation, it can increase the income by reducing the energy cost in the greenhouse. The heating load of the experimented greenhouse was 3326.4kcal/h and the fuel consumption was estimated to be 453.8L as the total heating time is $10000^{\circ}C/h$. Therefore, data mining technology of ANN can be applied to various agricultural fields such as precise greenhouse control, cultivation techniques, and harvest prediction, thereby contributing to the development of smart agriculture.

• Journal of Korean Society of Transportation
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• v.33 no.4
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• pp.393-404
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• 2015

Gravity model has had the major problem that the model explains the characteristics of travel behavior with only deterrence factors such as travel time or cost. In modern society, travel behavior can be affected not only deterrence factors but also zonal characteristics or transportation service. Therefore, those features have to be considered to estimate the future travel demand accurately. In this regard, there are two primary aims of this study: 1. to identify the characteristics of inter-zonal travel, 2. to develop the new type of calibration method. By employing accessibility variable which can explain the manifold pattern of trip, we define the zonal travel behavior newly. Furthermore, we suggest 2-phase calibration method, since existing calibration method cannot find the optimum solution when organizing the deterrence function with the new variables. The new method proceeds with 2 steps; step 1.estimating deterrence parameter, step 2. finding balancing factors. The validation results with RMSE, E-norm, C.R show that this study model explains the inter-zonal travel pattern adequately and estimate the O/D pairs precisely than existing gravity model. Especially, the problem with estimation of short distance trip is overcomed. In conclusion, it is possible to draw the conclusion that this study suggests the possibility of improvement for trip distribution model.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.7-19
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• 2005

Mode choice Analysis is essential analysis stage in transportation demand forecasting process. Therefore, methods for calibration and forecasting of mode choice model in aspect of practical view need to be discussed in depth. Since 1980s, choice models, especially Logit model, are spread widely and rapidly over academic area, research institutes and consulting firms in Korea like other developed countries in the world. However, the process of calibration and parameter estimation for practical application was not clearly explained in previous papers and reports. This study tried to explain clearly the calibration process of mode choice step by step and suggested a forecasting mode choice model that can be applicable in real policy analysis by using household survey data of Pusan metropolitan are. The study also suggested a way of estimating attributes which was not observed during the household survey commonly such as travel time and cost of unchosen alternative modes. The study summarized the statistical results of model specification for four different Logit models as a process to upgrade model capability of explanation for real traveler's choice behaviors. By using the analysis results, it also calculated the value of travel time and compared them with the values of other previous studies to test reliability of the estimated model.

• Proceedings of the KOR-KST Conference
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• 1996.02a
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• pp.59-86
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• 1996

Current methods for evaluating unsignalized intersections, and estimating level-of-service (LOS) is determined from efficiency-based criteria such as little or no delay to very long delays. At present, similar procedures to evaluate intersections using safety-based criteria do not exist. The improvement of sight distances at intersections is the most effective way of improving intersection safety. However, a set of procedures is necessary to account for the limitations in current methodology. Such an approach would build upon such methods, but also account for: deficiencies in the current deterministic solution for the determination of intersection sight distances; opportunity for an accident and severity of an accident; and cost-effectiveness of attaining various levels of sight distances. In this research, a model that estimates the degree of safety at two-way stop-controlled intersections is described. Only crossing maneuvers are considered in this study because accidents caused by the crossing maneuvers are the dominate type among intersection accidents. Monte Carlo methods are used to estimate the hazard at an intersection as a function of roadway features and traffic conditions. Driver`s minimum gap acceptance in the crossing vehicles and headway distribution on the major road are used in the crossing vehicles and headway distribution on the major road are used in the model to simulate the real intersectional maneuvers. Other random variables addressed in the model are: traffic speeds; preception-reaction times of both drivers in the crossing vehicles and drivers in oncoming vehicles on the major road; and vehicles on the major roads. The developed model produces the total number of conflicts per year per vehicle and total potential kinetic energy per year per vehicle dissipated during conflicts as measurements of safety at intersections. Based on the results from the developed simulation model, desirable sight distances for various speeds were determined as 350 feet, 450 feet and 550 feet for 40 mph, 50 mph and 60 mph prevailing speed on the major road, respectively. These values are seven to eight percent less than those values recommended by AASHTO. A safety based level-of-service (LOS) is also developed using the results of the simulation model. When the total number of conflicts per vehicle is less than 0.05 at an intersection, the LOS of the intersection is `A' and when the total number of conflicts per vehicle is larger than 0.25 at an intersection, the LOS is `F'. Similarly, when the total hazard per vehicle is less than 350, 000 1b-ft2/sec2, the LOS is `F'. Once evaluation of the current safety at the intersection is complete, a sensitivity analysis can be done by changing one or more input parameters. This will estimate the benefit in terms of time and budget of hazard reduction based upon improving geometric and traffic characteristics at the intersection. This method will also enable traffic engineers in local governments to generate a priority list of intersection improvement projects.

• Management & Information Systems Review
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• v.28 no.1
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• pp.71-97
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• 2009

In this study, I compare the ability of alternative accounting method for employee stock option to reflect firm value using the Ohlson's(1995) valuation model for 200 firms. The each methods, I compare are employee stock option expense recognition based on the K-GAAP disclosures, and asset recognition at the grant date based on the SFAS No. 123 Exposure Draft: Accounting for stock-based compensation. The model include: (1) a model that uses reported earnings, equity book value, and compensation expense based on the K-GAAP disclosures; (2) a model that uses pro-forma earnings, equity book value and adds a measure of the unrecognized asset arising form granting of employee stock options. Finding form estimating equations that the K-GAAP method for calculating compensation has no explanatory power, and the SFAS No.123 Draft Exposure method for arising asset and fair value compensation better captures than market's perception of the economic impact of stock options on firm values. However, the correlation of employee stock option compensation expense is positive. These results suggest that incentive benefits derived from employee stock option plans outweigh the cost associated with plan. In addition, I couldn't find evidence that company in KOSDAQ that have high growth potential benefit more from employee stock option plan compared to lager, more mature firm in SEC.

• Environmental and Resource Economics Review
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• v.22 no.4
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• pp.817-841
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• 2013

The purpose of this study is to examine feasibility of the 'Master Plan of 2013 Slow Food Expo(2013 AsiO Gusto), Korea' and to analyze the following economic effect. To this end, we used existing data and statistics, and estimated the demand by means of survey for people's traveling and questionnaires for ordinary Koreans. For examining financial feasibility for hosting the Expo, BC ratio (Benefit-Cost Ratio) and NPV (Net Present Value) was applied. For estimating the economic effect following the Expo, the effect on all over the country and the Gyeong-gi province was analyzed, using the MRIO (Model of Regional Input-Output). Specifically, with the net effect of Expo, the economic feasibility test shows 1.04~2.15 BC ratio with 10% free admission, and 1.02~2.27 BC ratio in Finance analysis. Furthermore, the Expo feeds through Gyeong-gi (including Nam-yang-ku) regional economies with production induction effect, value-added induction effect, and employment induction effect. The amounts of regional effects are 373.6~738.7 billion won, 166.2~327.4 billion won, and 1,971~2,009 persons, respectively. Also, the "2013 Slow Food Expo, Korea" was analyzed profitable in general. Residents in Nam-yang-ju expects the Expo to bring vitalities into their hometown. The Expo is highly related to the positive economic effectiveness of Nam-yang-ju.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.1-12
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• 2017

The Seoul metropolitan transportation card's high value lies in its recording of total population movements of the public transit system. In case of recorded information on transit by bus, even though route information utilized by each passenger is accurate, the lack of passenger transfer information of the urban railway makes it difficult to estimate correct routes taken by each passenger. Therefore, pinpointing passenger path selection patterns arising in the metropolitan railway network and using this as part of a path movement estimation model is essential. This research seeks to determine that features of passenger movement routes in the urban railway system is comprised of M-similar routes with increasing number of transfer reflected as additional costs. In order to construct the path finding conditions, an M-similar route searching method is proposed, embedded with non additive path cost which appears through inclusion of the stepwise transportation parameter. As well, sensitivity of the M-similar route method based on transportation card records is evaluated and a stochastic trip assignment model using M-similar path finding is constructed. From these, link trip and transfer trip results between lines of the Seoul metropolitan railway are presented.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.96-106
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• 2005

The ability of remote sensing and GIS technique, which used to provide valuable informations in the time and space domain, has been known to be very useful in providing permanent records by mapping and monitoring flooded area. In 2000, floods were at the worst stage of devastation in Tonle Sap Lake, Mekong River Basin, for the second time in records during July and October. In this study, Landsat ETM+ and RADARSAT imagery were used to obtain the basic information on computation of the inundation area and volume using ISODATA classifier and segmentation technique. However, the extracted inundatton area showed only a small fraction than the actually inundated area because of clouds in the imagery and complex ground conditions. To overcome these limitations, the cost-distance method of GIS was used to estimate the inundated area at the peak level by integrating the inundated area from satellite imagery in corporation with digital elevation model (DEM). The estimated inundation area was simply converted with the inundation volume using GIS. The inundation volume was compared with the volume based on hydraulic modeling with MIKE 11. which is the most poppular among the dynamic river modeling system. The method is suitable for estimating inundation volume even when Landsat ETM+ has many clouds in the imagery.