• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.22 no.4
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• pp.253-287
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• 2018

This paper studies the global stability of a class of discrete-time pathogen infection models with latently infected cells. The rate of pathogens infect the susceptible cells is taken as bilinear, saturation and general. The continuous-time models are discretized by using nonstandard finite difference scheme. The basic and global properties of the models are established. The global stability analysis of the equilibria is performed using Lyapunov method. The theoretical results are illustrated by numerical simulations.

• Journal of Korean Institute of Industrial Engineers
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• v.10 no.1
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• pp.41-45
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• 1984

A resource constrained scheduling problem that involves trade-off between resources and time is considered. Models are considered. Models are presented as zero-one integer program and objectives of models include minimum project completion time and minimum total project cost.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.360-366
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• 1989

Reduced order steady state models for separation columns are developed. The accuracy and efficiency of the reduced order models are also demonstrated by comparing the simulation results obtained using the reduced order models with rigorous tray by tray calculations.

• Journal of the Korean Statistical Society
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• v.19 no.1
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• pp.45-53
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• 1990

Factorization models are a generalization of hierarchical loglinear models which apply equally to discrete and continuous distributions. In regular (strictly positive) cases the intersection of two factorization models is another factorization model whose representation is obtained by a simple algorithm. Failure of this result in an irregular case is related to a theorem of Basu on ancillary statistics.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1032-1032
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• 2001

Artificial Neural Network (ANN) calibration techniques have been used commercially for agricultural applications since the mid-nineties. Global models, based on transmission data from 850 to 1050 nm, are used routinely to measure protein and moisture in wheat and barley and also moisture in triticale, rye, and oats. These models are currently used commercially in approx. 15 countries throughout the world. Results concerning earlier European ANN models are being published elsewhere. Some of the findings from that study will be discussed here. ANN models have also been developed for coarsely ground samples of compound feed and feed ingredients, again measured in transmission mode from 850 to 1050 nm. The performance of models for pig- and poultry feed will be discussed briefly. These models were developed from a very large data set (more than 20,000 records), and cover a very broad range of finished products. The prediction curves are linear over the entire range for protein, fat moisture, fibre, and starch (measured only on poultry feed), and accuracy is in line with the performance of smaller models based on Partial Least Squares (PLS). A simple bias adjustment is sufficient for calibration transfer across instruments. Recently, we have investigated the possible use of ANN for a different type of NIR spectrometer, based on reflectance data from 1100 to 2500 nm. In one study, based on data for protein, fat, and moisture measured on unground compound feed samples, dedicated ANN models for specific product classes (cattle feed, pig feed, broiler feed, and layers feed) gave moderately better Standard Errors of Prediction (SEP) compared to modified PLS (MPLS). However, if the four product classes were combined into one general calibration model, the performance of the ANN model deteriorated only slightly compared to the class-specific models, while the SEP values for the MPLS predictions doubled. Brix value in molasses is a measure of sugar content. Even with a huge dataset, PLS models were not sufficiently accurate for commercial use. In contrast an ANN model based on the same data improved the accuracy considerably and straightened out non-linearity in the prediction plot. The work of Mr. David Funk (GIPSA, U. S. Department of Agriculture) who has studied the influence of various types of spectral distortions on ANN- and PLS models, thereby providing comparative information on the robustness of these models towards instrument differences, will be discussed. This study was based on data from different classes of North American wheat measured in transmission from 850 to 1050 nm. The distortions studied included the effect of absorbance offset pathlength variation, presence of stray light bandwidth, and wavelength stretch and offset (either individually or combined). It was shown that a global ANN model was much less sensitive to most perturbations than class-specific GIPSA PLS calibrations. It is concluded that ANN models based on large data sets offer substantial advantages over PLS models with respect to accuracy, range of materials that can be handled by a single calibration, stability, transferability, and sensitivity to perturbations.

• Korean Institute of Interior Design Journal
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• no.28
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• pp.265-265
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• 2001

The perceptual presentation of interior design is to represent an interior space planned by a designer as if people see it in reality. The perceptual presentation methods that have developed are perspectives, full-scale models, small-scale models, photography of models, video taping of models, computer images, computer animation, and virtual reality. The purpose of this study is to investigate limits of those perceptual presentation methods according to their characteristics. The methods have characteristics that are either static or dynamic and either monoscopic or stereoscopic. In terms of representing interior spaces and perceiving interior spaces, the dynamic characteristic is more helpful than the static characteristic because the dynamic characteristic provides consecutively changing views of interior spaces when people walk around within the spaces. The stereoscopic characteristic is more helpful than the monoscopic characteristic because the stereoscopic characteristic provides the binocular depth perception. Full-scale models, small-scale models, virtual reality that have dynamic and stereoscopic characteristics, are most effective. The next effective methods are video taping of models and computer animation that have dynamic and monoscopic characteristics. The last effective methods are perspectives and photography of models that have static and monoscopic characteristics. But the most effective methods can not be said that those are perfect because each of them still has limits. Designers have to consider the limits of each perceptual presentation method to find a way that shows their designs most effectively. To develop the perceptual presentation methods of interior design, researchers should focus on the helpful characteristics that are dynamic and stereoscopic.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.64.3-64.3
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• 2015

We have developed a set of daily solar flare peak flux forecast models for strong flares using multiple linear regression and artificial neural network methods. We consider input parameters as solar activity data from January 1996 to December 2013 such as sunspot area, X-ray flare peak flux and weighted total flux of previous day, and mean flare rates of McIntosh sunspot group (Zpc) and Mount Wilson magnetic classification. For a training data set, we use the same number of 61 events for each C-, M-, and X-class from Jan. 1996 to Dec. 2004, while other previous models use all flares. For a testing data set, we use all flares from Jan. 2005 to Nov. 2013. The best three parameters related to the observed flare peak flux are weighted total flare flux of previous day (r = 0.51), X-ray flare peak flux (r = 0.48), and Mount Wilson magnetic classification (r = 0.47). A comparison between our neural network models and the previous models based on Heidke Skill Score (HSS) shows that our model for X-class flare is much better than the models and that for M-class flares is similar to them. Since all input parameters for our models are easily available, the models can be operated steadily and automatically in near-real time for space weather service.

• Journal of Technologic Dentistry
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• v.41 no.4
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• pp.287-293
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• 2019

Purpose: To evaluate the accuracy of the 3D printed die models and to investigate its clinical applicability. Methods: Stone die models were fabricated from conventional impressions(stone die model; SDM, n=7). 3D virtual models obtained from the digital impressions were manufactured as a 3D printed die models using a 3D printer(3D printed die models;3DM, n=7). Reference model, stone die models and 3D printed die models were scanned with a reference scanner. All dies model dataset were superimposed with the reference model file by the "Best fit alignment" method using 3D analysis software. Statistical analysis was performed using the independent t-test and 2-way ANOVA (α=.05). Results: The RMS value of the 3D printed die model was significantly larger than the RMS value of the stone die model (P<.001). As a result of 2-way ANOVA, significant differences were found between the model group (P<.001) and the part (P<.001), and their interaction effects (P<.001). Conclusion: The 3D printed die model showed lower accuracy than the stone die model. Therefore, it is necessary to further improve the performance of 3D printer in order to apply the 3D printed model in prosthodontics.

• Korean Journal of Biological Psychiatry
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• v.6 no.2
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• pp.161-169
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• 1999

There are a number of approaches in developing experimental models for depression, but there is no such thing as a best model for depressive syndrome. Animal models are subject to the obvious limitations inherent in the assumption that human psychopathology can be represented accurately in lower animals. Recently, the concern increasingly is to develop a variety of experimental paradigms in animals to study selected aspects of human psychopathology, and animal models should be understood as basically experimental preparations that are developed to carry out these objects. Therefore, a battery of a variety of animal models should be applied to permit detailed pathophysiological studies and to develop new antidepressant treatments. Animal models of depression basically consider behavioral isomorphism with the human depression a plus, but not a req-uirement, and the model behavior should be defined operationally in order to be reproduced reliably by other researchers and be responsive to those agents possessing demonstrated clinical efficacy in human depression. In conclusion, animal models of depression have played a significant role in elucidating pathophysiology of depression and developing current treatments for depression, but there is no single comprehensive model for depression until now. Each of the proposed animal model has its advantages and limitations. In other words, certain paradigms are suitable for studying certain phenomena, whereas others are more suitable for studying other aspects. The best model for depression depends upon what the question is.

• Bulletin of the Korean Space Science Society
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• 2011.04a
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• pp.28.3-28.3
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• 2011

Halo coronal mass ejections (HCMEs) are mainly responsible for the most severe geomagnetic storms. To minimize the projection effect of the HCMEs observed by coronagraphs, several cone models have been suggested. These models allow us to determine the geometrical and kinematic parameters of HCMEs : radial speed, source location, angular width, and the angle between the central axis of the cone and the plane of the sky. In this study, we compare these parameters form two representative cone models (the ice-cream cone model and the asymmetric cone model) using well-observed HCMEs from 2001 to 2002. And we obtain the root mean square error (rms error) between observed projection speeds and calculated projection speeds for both cone models. It is found that the average rms speed error (89 km/s) of the asymmetric cone model is a little smaller than that (107 km/s) of the ice-cream cone models, implying that the radial speeds from both models are reasonably estimated. We also find that the radial speeds obtained from two models are similar to each other with the correlation coefficient of about 0.8.