• Korean Journal of Fisheries and Aquatic Sciences
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• v.43 no.3
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• pp.205-210
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• 2010

Dynamic modeling was used to predict the Pseudomonas spp. concentration in Alaska pollack under dynamic temperature conditions in a programmable incubator using Euler's method. The model evaluation showed good agreement between the predicted and measured concentrations of Pseudomonas spp. In the simulation, three kinds of distribution path were assumed: consumers buying from a distribution center (A), manufacturer (B), or direct market (C). Each of these distribution paths consists of six phases: shipping, warehousing/shipment, warehousing/storing, processing, market exhibition, and sale/consumption. Sensitivity analysis of each phase was also implemented. The Pseudomonas concentrations and sensitivities ($S_k$) at the terminal phases of the three paths were estimated to be (A) 11.174 log CFU/g and 10.550 log $S_k$, (B) 10.948 log CFU/g and 10.738 log $S_k$, and (C) 8.758 log CFU/g and 9.602 log $S_k$, respectively. The sensitivities indicated that path A has the highest risk of failure in managing the relevant phases.

• Journal of the Korean Data and Information Science Society
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• v.20 no.3
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• pp.515-526
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• 2009

Pricing based on proper risk has been one of main issues in auto insurance. In this paper, we review how the techniques of pricing in auto insurance have been developed and suggest a better approach which meets the existing risk statistically by comparison. The generalized linear model (GLM) method is discussed for pricing with different distributions. With GLM approach, the distribution of error assumed plays an main role for the best fit corresponding to the characteristics of dependent variables. Tweedie distribution is considered as one of error distributions in addition to widely used Gamma and Poisson distribution. With these different types of error assumption for estimating the proper premium in auto insurance, various modeling approaches are possible. In this paper, various modeling approaches with different assumptions for estimating proper risk is discussed and also real example is given by assuming different.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.126-136
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• 2004

This paper proposes a new content-based image retrieval algorithm using color-spatial information. For the purpose, the paper suggests two kinds of indexing key to prune away irrelevant images to a given query image; MCS(Main Colors' Set), which is related with color information and DBS (Distribution Block Signature), which is related with spatial information. After successively applying these filters to a database, we could get a small amount of high potential candidates that are somewhat similar to the query image. Then we would make use of new QM(Quad modeling) and relevance feedback mechanism to obtain more accurate retrieval. It would enhance the retrieval effectiveness by dynamically modulating the weights of color-spatial information. Experiments show that the proposed algorithm can apply successfully image retrieval applications.

• Proceedings of the Korean Geotechical Society Conference
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• 1999.10a
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• pp.441-448
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• 1999

The load distribution in a ground anchor is very complex because it involves three different materials(soil, grout, and steel), which sometimes act as composite sections (bonded length) or separately (unbounded length). Therefore it is very hard to understand load transfer mechanism on the anchor. In order to understand the load transfer, it is essential to consider the load distribution In the three different materials. On these purposes, full scale anchor test is planned on the geotechnical site at Sunkyunkwan University Prior to the test, modeling and analyses of the load transfer mechanism were performed on the data from the case histories.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.10a
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• pp.24-30
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• 1993

When modeling a complex system we use an event tree to analyze propagation of failure. An event tree cannot represent the statistical interrelationships among parameters, but it can be represented as a statistically identical influence diagram so that parameter updating can be easily performed. After updating parameters we can calculate posterior distribution of the failure rate for each path. But exact distribution requires considerably complex numerical integration. We propose an approximation method to calculate the posterior and derive the predictive distribution of the time to next failure. Finally we introduce the system which implements our methodology.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.6
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• pp.654-662
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• 1988

A simple and useful model of light distribution for the biologhical tissue to the Gaussian beam is proposed. This model assumes that the incident Gaussian beam broadens into two Gaussian beams, travelling in the opposite directions as the result of both isotropic scattering and absorption in the tissue. With this assumption, two-dimensional light intensity of each flux as well as the equations of both absorption and scattering have been derived, and the validity of modeling has been confirmed experimentally. Consequently, the results paved a way for easy evaluation of the light distribution in the biological tissue.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.203-210
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• 2003

In a standard Metropolis-type Monte Carlo simulation, the proposal distribution cannot be easily adapted to "local dynamics" of the target distribution. To overcome some of these difficulties, Duane et al. (1987) introduced the method of hybrid Monte Carlo(HMC) which combines the basic idea of molecular dynamics and the Metropolis acceptance-rejection rule to produce Monte Carlo samples from a given target distribution. In this paper, using the HMC within Gibbs sampler, an asymptotical estimate of the smoothing mean and a general solution to state space modeling in Bayesian framework is obtaineds obtained.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1156-1158
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• 1998

This paper Presents two distribution-feeder models to simplify complicated distribution system calculations. These equivalent models are developed to simulate the total series voltage drop at the end of the given feeder and the total line loss of the given feeder accurately. In addition, the proposed models are bidirectional. This means that power infeed can be at either end and the model is accurate. Also, it is shown that the proposed models are suitable for network reconfiguration.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.6
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• pp.737-743
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• 2013

This paper describes the overvoltage through lightning surge analysis on underground system in DC combined distribution systems. It is considered that operating micro grid including distributed generation with smart grid can make possibility of composing new distribution system different from existing one. However, there are many papers about low voltage DC distribution in grids or buildings but not many about replacement or distributing 22.9kV AC distribution system to DC system. Among many research need for DC system development, overvoltage is studied in this paper. Overvoltage is simulated on DC cable when lightning strikes to overhead grounding wire which is installed at the nearest location from power cable section. Analysis as well as modeling is performed in EMTP/ATPDraw. It is evaluated that analysis results can be used to design of DC underground distribution power cable system.

• Journal of Ecology and Environment
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• v.43 no.4
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• pp.427-437
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• 2019

Background: Climate change is believed to be continuously affecting ticks by influencing their habitat suitability. However, we attempted to model the climate change-induced impacts on future genus Rhipicephalus distribution considering the major environmental factors that would influence the tick. Therefore, 50 tick occuance points were taken to model the potential distribution using maximum entropy (MaxEnt) software and 19 climatic variables, taking into account the ability for future climatic change under representative concentration pathways (RCPs) 4.5 and 8.5, were used. Results: MaxEnt model performance was tested and found with the AUC value of 0.99 which indicates excellent goodness-of-fit and predictive accuracy. Current models predict increased temperatures, both in the mid and end terms together with possible changes of other climatic factors like precipitation which may lead to higher tick-borne disease risks associated with expansion of the range of the targeted tick distribution. Distribution maps were constructed for the current, 2050, and 2070 for the two greenhouse gas scenarios and the most dramatic scenario; RCP 8.5 produced the highest increase probable distribution range. Conclusions: The future potential distribution of the genus Rhipicephalus show potential expansion to the new areas due to the future climatic suitability increase. These results indicate that the genus population of the targeted tick could emerge in areas in which they are currently lacking; increased incidence of tick-borne diseases poses further risk which can affect cattle production and productivity, thereby affecting the livelihood of smallholding farmers. Therefore, it is recommended to implement climate change adaptation practices to minimize the impacts.