• Health Policy and Management
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• v.18 no.4
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• pp.85-110
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• 2008

In this study, we explore the long-term demand forecasting of high-price medical equipments based on logistic and Bass diffusion model. We analyze the specific pattern of each equipment's diffusion curve by interpreting the parameter estimates of Bass diffusion model. Our findings are as follows. First, ultrasonic imaging system, CT are in the stage of maturity and so, the future demands of them are not too large. Second, medical image processing unit is between growth stage and maturity stage and so, the demand is expected to increase considerably for two or three years. Third, MRI is in the stage of take-off and Mammmography X-ray system is in the stage of maturity but, estimates of the potential number of adopters based on logistic model is considerably different to that based on Bass diffusion model. It means that additional data for these two equipments should be collected and analyzed to obtain the reliable estimates of their demands. Fourth, medical image processing unit have the largest q value. It means that the word-of-mouth effect is important in the diffusion of this equipment. Fifth, for MRI and Ultrasonic system, q/p values have the relatively large value. It means that collective power has an important role in adopting these two equipments.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.361-368
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• 2013

This research aims to offer the information required for demand increase on marketing strategy level by investigating Mudeungsan visitors' demographic characteristics and social economical variables. To accomplish this study, the proper analyzing model needs to be applied because a grave error of parameters will be led if regression model appropriate for analyzing the data of a continuous probability variable is applied, in case that dependent variable is a discrete random variable which have a discrete probability distribution. Therefore data analysis was performed with Poisson model. However, as the data was showing an overdispersion, parameter was estimated with the Binomial Poisson model able to cover the problem. As a result, some explanatory variables turned out to be significant such as visitor's age, occupation, preferred season to visit, type of company, five days working, and preferring type of tourism. Author could offer to the national park the information about characteristics of core market revealed and marketing strategy for it, based on those influential variables.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.730-737
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• 2016

Electric utilities may face new threats with increase in electric vehicles (EVs) in the personal automobile market. The peak demand will increase which may stress the distribution network equipment. The focus of this paper is on an adaptive control of smart household appliances by using an intelligent load management system (ILMS). The main objectives are to accomplish consumer needs and prevent overloading of power grid. The stress from the network is released by limiting the peak demand of a house when it exceeds a certain point. In the proposed strategy, for each smart appliance, the customers will set its order/rank according to their own preferences and then system will control the household loads intelligently for consumer reliability. The load order can be changed at any time by the customer. The difference between the set and actual value for each load's specific parameter will help the utility to estimate the acceptance of this intelligent load management system by the customers.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.617-628
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• 2021

Drought is a major natural disaster that causes serious social and economic losses. Local drought forecasts can provide important information for drought preparedness. In this study, we propose a new machine learning model that predicts drought by using historical drought indices and meteorological data from 10 sites from 1981 to 2020 in the southeastern part of the Korean Peninsula, Busan-Ulsan-Gyeongnam. Using Bayesian optimization techniques, a hyper-parameter-tuned Random Forest, XGBoost, and Light GBM model were constructed to predict the evaporative demand drought index on a 6-month time scale after 1-month. The model performance was compared by constructing a single site model and a regional model, respectively. In addition, the possibility of improving the model performance was examined by constructing a fine-tuned model using data from a individual site based on the regional model.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.844-847
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• 1997

In this paper, scheduling problem is dealt for the minimization of due date penalty for the customer order. Multiproduct batch processes have been dealt with for their suitability for high value added low volume products. Their scheduling problems take minimization of process operation for objective function, which is not enough to meet the customer satisfaction and the process efficiency simultaneously because of increasing requirement of fast adaptation for rapid changing market condition. So new target function has been suggested by other researches to meet two goals. Penalty function minimization is one of them. To present more precisely production scheduling, we develop new scheduling model with penalty function of earliness and tardiness We can find many real cases that penalty parameters are divergent by the difference between the completion time of operation and due date. That is to say, the penalty parameter values for the product change by the customer demand condition. If the order charges different value for due date, we can solve it with the due date period. The period means the time scope where penalty parameter value is 0. If we make use of the due date period, the optimal sequence of our model is not always same with that of fixed due date point. And if every product have due date period, due date of them are overlapped which needs optimization for the maximum profit and minimum penalty. Due date period extension can be enlarged to makespan minimization if every product has the same abundant due date period and same penalty parameter. We solve this new scheduling model by simulated annealing method. We also develop the program, which can calculate the optimal sequence and display the Gantt chart showing the unit progress and time allocation only with processing data.

• Journal of Korean Society on Water Environment
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• v.21 no.5
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• pp.511-515
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• 2005

CBOD(carbonaceous BOD) decay rate was investigated for the execution of water quality model in Nakdong-Rive basin. Estimation of laboratory-derived CBOD decay rate, $k_l$ and CBOD decay rate in natural waters, $k_d$ were carried out. Hydraulic factors were applied for the calculation of $k_d$. Values of biochemical oxygen demand were investigated in Weagwan, Koreong, Jeokpo, Namgi and Mulgeom sites for the four times. The ranges of $k_l$ value were $0.04{\pm}0.01{\sim}0.14{\pm}0.03$. The values of $k_l$ in upstream sites were much larger than those in the downstream sites. The values of $k_d$ were 0.025, 0.036, 0.005 and 0.001 at Weagwan, Jeokpo, Namgi and Mulgeom, respectively, indicating that values of $k_d$ were generally larger than those of $k_l$.

• International Area Studies Review
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• v.14 no.3
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• pp.35-60
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• 2010

In this paper, we develop a dynamic structural model based on a dynamic supergame and measure market power for the Dallas-Forth Worth fluid milk market in the U.S. In particular, we compare the conduct parameter estimates from a static model with that from the dynamic model and illustrate bias in the market-power measure in a static model. And we also analyze the cyclical behavior of firm conduct. We find that the conduct parameter in a static model underestimates true market power if firms' behaviors are posited by a dynamic oligopoly game. We also verify that firm conduct in the Dallas-Forth Worth fluid milk market is countercyclical against demand shocks and expected future cost shocks. Our results indicate that the firms' conduct in the Dallas-Forth Worth fluid milk market is consistent with what dynamic oligopoly models predict. This implies that the firms consider not only the contemporary reactions of the other firms' but also future market competition. Therefore, the measurement of market power requires the specification of fully dynamic pricing relationship.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.87.2-87.2
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• 2010

The steady and dynamic process model for an internal reforming molten carbonate fuel cell power plant is discussed in this paper. The dominant thermal and chemical dynamic processes are modeled for the stack module and balance-of-plant, including cathode gas preparation, heat recovery, heat loss (Each heat loss amount for the stack and MBOP is obtained from real plant data) and fuel processing. Based on dynamic model and control demand, PID controllers are designed in the whole system. By applying these controllers we can obtain temperature balance of stack and control system depending on changing steam to carbon ratio, air feed amount, and transient condition.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.1
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• pp.341-348
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• 1991

An efficient tool to deal with a multi-dimensional radiative heat transfer is in strong demand to analyze various thermal problems combined either with other modes of heat transfer or with combustion phenomena. The current study examined the discrete ordinates method (DOM) for a coupled radiative and conductive heat transfer in rectangular enclosures in which either nonscattering or scattering medium is present. The results were compared with the other benchmarked approximate solution. The efficiency and accuracy of the DOM were thus validated.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.3
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• pp.154-160
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• 1998

Ride quality of medium truck became a very important factor in the suspension design, to the demand of more comfortable ride of passengers. This study describes how to determine and evaluate design parameters related to the chassis suspension system with time and frequency analysis. The spring stiffness and damping force of the chassis suspension system were obtained by observing the vertical acceleration PSD. The simulation was carried out on various road profiles, which was suggested by ISO. The pitching motion of the medium size truck was observed to improve the ride quality. A computer simulated truck model was constructed using DADS, a commercial dynamic analysis software, in order to simulate the truck motions. From the analyzed process of suspension parameters, it was concluded that the spring and the shock absorbers affect the pitching of the vehicle. In order to validate the computer simulated truck model, a physical prototype was constructed and tested.