• The Korean Journal of Ecology
• /
• v.23 no.6
• /
• pp.435-438
• /
• 2000

Diameter distributions describe forest stand structure information. Prediction equations for percentiles of diameter distribution and parameter recovery procedures for the Weibull distribution function based on four percentile equations were applied to develop prediction system of even-aged slash pine stand structure development in terms of the number of stems per diameter class changes. Four percentiles of the cumulative diameter distribution were predicted as a function of stand characteristics. The predicted diameter distributions were tested against the observed diameter distributions using the Kolmogorov-Smirnov two sample test at the ${\alpha}$=0.05 level. Statistically, no significant differences were detected based on the data from 236 evaluation data sets. This stand level diameter distribution prediction system will be useful in slash pine stand structure modeling and in updating forest inventories for the long-term forest management planning.

• Journal of the Korean Data and Information Science Society
• /
• v.15 no.4
• /
• pp.1019-1031
• /
• 2004

This paper describes a new modeling method for the prediction of transmembrane protein topology. The structural regions of the transmembrane protein have been modeled by means of a multiple state hidden Markov model that has provided for the detailed modeling of the heterogeneous amino acid distributions of each structural region. Grammatical constraints have been incorporated to the prediction method in order to capture the biological order of membrane protein topology. The proposed method correctly predicted 76% of all membrane spanning regions and 92% sidedness of the integration when all membrane spanning regions were found correctly.

• Journal of Power Electronics
• /
• v.11 no.1
• /
• pp.59-63
• /
• 2011

This paper presents the modeling of the sampling effect in the p-type average current mode control. The prediction of the high frequency components near half of the switching frequency in the current loop gain is given for the p-type average current mode control. By the proposed model, the prediction accuracy is improved when compared to that of conventional models. The proposed method is applied to a buck converter, and then the measurement results are analyzed.

• Atmosphere
• /
• v.30 no.2
• /
• pp.115-124
• /
• 2020

The Northern Hemisphere extratropical prediction skill of the Korea Meteorological Administration (KMA) Global Data Assimilation and Prediction System (GDAPS) is examined for January 2019. The real-time prediction skill, evaluated with mean squared skill score (MSSS) of 30-90°N geopotential height field at 500 hPa (Z500), is ~8 days in the troposphere. The MSSS of Z500 considerably decreases after 3 days mainly due to the increasing eddy errors. The eddy errors are largely explained by the eddy-phased errors with minor contribution of amplitude errors. In particular, planetary-scale eddy errors are considered as a main reason of rapidly increasing errors. It turns out that such errors are associated with the blocking highs over North Pacific (NP) and Euro-Atlantic (EA) regions. The model overestimates the blocking highs over NP and EA regions in time, showing dependence of blocking predictability on blocking initializations. This result suggests that the extratropical prediction skill could be improved by better representing blocking in the model.

• Journal of the Korean Statistical Society
• /
• v.35 no.1
• /
• pp.37-47
• /
• 2006

Recently, as a result of the growing interest in modeling stationary processes with discrete marginal distributions, several models for integer valued time series have been proposed in the literature. One of these models is the integer-valued autoregressive (INAR) models. However, when modeling with integer-valued autoregressive processes, the distributional properties of forecasts have been not yet discovered due to the difficulty in handling the Steutal Van Ham thinning operator 'o' (Steutal and van Ham, 1979). In this study, we derive the mean squared error of h-step-ahead prediction from a Poisson INAR(1) process, reflecting the effect of the variability of parameter estimates in the prediction mean squared error.

• Journal of Korea Society of Industrial Information Systems
• /
• v.27 no.2
• /
• pp.35-44
• /
• 2022

In this paper, we propose an intra-picture prediction method by a quadratic surface modeling method for depth video coding. The pixels of depth video are transformed to 3D coordinates using distance information. A quadratic surface with the smallest error is found by least square method for reference pixels. The reference pixel can be either the upper pixels or the left pixels. In the intra prediction using the quadratic surface, two predcition values are computed for one pixel. Two errors are computed as the square sums of differences between each prediction values and the pixel values of the reference pixels. The pixel sof the block are predicted by the reference pixels and prediction method that they have the lowest error. Comparing with the-state-of-art video coding method, simulation results show that the distortion and the bit rate are improved by up to 5.16% and 5.12%, respectively.

• Journal of the Korea Society for Simulation
• /
• v.14 no.3
• /
• pp.91-100
• /
• 2005

Grid computing is widely applicable to various fields of industry including process control and manufacturing, military command and control, transportation management, and so on. In a viewpoint of application area, grid computing can be classified to three aspects that are computational grid, data grid and access grid. This paper focuses on computational grid which handles complex and large-scale computing problems. Computational grid is characterized by system dynamics which handles a variety of processors and jobs on continuous time. To solve problems of system complexity and reliability due to complex system dynamics, computational grid needs scheduling policies that allocate various jobs to proper processors and decide processing orders of allocated jobs. This paper proposes a service prediction-based job scheduling model and present its scheduling algorithm that is applicable for computational grid. The service prediction-based job scheduling model can minimize overall system execution time since the model predicts the next processing time of each processing component and distributes a job to a processing component with minimum processing time. This paper implements the job scheduling model on the DEVS modeling and simulation environment and evaluates its efficiency and reliability. Empirical results, which are compared to conventional scheduling policies, show the usefulness of service prediction-based job scheduling.

• YAKHAK HOEJI
• /
• v.59 no.1
• /
• pp.29-39
• /
• 2015

In recent years, physiologically based pharmacokinetic (PBPK) modeling has been widely used in pharmaceutical industries as well as regulatory health authorities for drug discovery and development. Several application areas of PBPK have been introduced so far including drug-drug interaction prediction, transporter-mediated interaction prediction, and pediatric PK prediction. The purpose of this review is to introduce PBPK and illustrates one of its application areas, particularly pediatric PK prediction by utilizing existing adult PK data and in vitro data. The evaluation of the initial PBPK for adult was done by comparing with experimental PK profiles and the scaling from adult to pediatric was conducted using age-related changes in size such as tissue compartments, and protein binding etc. Sotalol and lorazepam were selected in this review as model drugs for this purpose and were re-evaluated using the PBPK models by GastroPlus$^{(R)}$. The challenges and strategies of PBPK models using adult PK data as well as appropriate in vitro assay data for extrapolating pediatric PK at various ages were also discussed in this paper.

• Convergence Security Journal
• /
• v.14 no.4
• /
• pp.19-26
• /
• 2014

Mobile malicious code is typically spread by the worm, and although modeling techniques to analyze the dispersion characteristics of the worms have been proposed, only macroscopic analysis was possible while there are limitations in predicting on certain viruses and malicious code. In this paper, prediction methods have been proposed which was based on Markov chain and is able to predict the occurrence of future malicious code by utilizing the past malicious code data. The average value of the malicious code to be applied to the prediction model of Markov chain model was applied by classifying into three categories of the total average, the last year average, and the recent average (6 months), and it was verified that malicious code prediction possibility could be increased by comparing the predicted values obtained through applying, and applying the recent average (6 months).

• International Journal of High-Rise Buildings
• /
• v.2 no.3
• /
• pp.179-192
• /
• 2013

The lack of systematic validation for the design process supporting tall buildings motivated the authors' research groups and their collaborators to found the Chicago Full-Scale Monitoring Program over a decade ago. This project has allowed the sustained in-situ observation of a collection of tall buildings now spanning worldwide. This paper overviews this program and the lessons learned in the process, ranging from appropriate technologies for response measurements to the factors influencing accurate prediction of dynamic properties all the way to how these properties then influence the prediction of response using wind tunnel testing and whether this response does indeed correlate with in-situ observations. Through this paper, these wide ranging subjects are addressed in a manner that demonstrates the importance of continued promotion and expansion of full-scale monitoring efforts and the ways in which these programs can provide true value-added to building owners and managers.