• Proceedings of the PSK Conference
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• 2003.04a
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• pp.143.2-144
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• 2003

Joins (SKI 306X) is now clinically used for the treatment of osteoarthritis (OA). In previous reports, Joins a natural herbal product extracted from three herbs Clematis Radix. Trichosanthes Radix and Prunella Flos, was shown to have good analgesic and anti-inflammatory effects in several in vivo models. e.g., acetic acid-induced pain, carrageenan-induced paw edema and adjuvant-induced arthritis. (omitted)

• Journal of the Korean Statistical Society
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• v.36 no.3
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• pp.357-365
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• 2007

In this paper we present characterizations of the Pareto, Lomax, exponential and beta models by some properties of their $r^{th}$ partial moment defined as ${\alpha}_r(t)=E[(X-t)^+]^r$, where $(X-t)^+ = max(X-t,0)$. Given the partial moments at a few truncation points, these results enable us to calculate the moments at many other points.

• Proceedings of the Korean Society of Toxicology Conference
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• 2001.10a
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• pp.20-21
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• 2001

Free radicals and oxidative stress playa crucial role in the pathophysiology of a broad spectrum of cardiovascular diseases including congestive heart failure, valvular heart disease, cardiomyopathy, hypertrophy, atherosclerosis and ischemic heart disease. We have demonstrated that IH 636 proanthocyanidin extract (GSPE) provides excellent protection against free radicals in both in vitro and in vivo models, and exhibits significantly better efficacy as compared to vitamins C, E and $\beta$-carotene.(omitted)

• Food Science of Animal Resources
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• v.40 no.6
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• pp.938-945
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• 2020

A dynamic model was developed to predict the Escherichia coli cell counts in pig trotters at changing temperatures. Five-strain mixture of pathogenic E. coli at 4 Log CFU/g were inoculated to cooked pig trotter samples. The samples were stored at 10℃, 20℃, and 25℃. The cell count data was analyzed with the Baranyi model to compute the maximum specific growth rate (μ_max) (Log CFU/g/h) and lag phase duration (LPD) (h). The kinetic parameters were analyzed using a polynomial equation, and a dynamic model was developed using the kinetic models. The model performance was evaluated using the accuracy factor (A_f), bias factor (B_f), and root mean square error (RMSE). E. coli cell counts increased (p<0.05) in pig trotter samples at all storage temperatures (10℃-25℃). LPD decreased (p<0.05) and μ_max increased (p<0.05) as storage temperature increased. In addition, the value of h₀ was similar at 10℃ and 20℃, implying that the physiological state was similar between 10℃ and 20℃. The secondary models used were appropriate to evaluate the effect of storage temperature on LPD and μ_max. The developed kinetic models showed good performance with RMSE of 0.618, B_f of 1.02, and A_f of 1.08. Also, performance of the dynamic model was appropriate. Thus, the developed dynamic model in this study can be applied to describe the kinetic behavior of E. coli in cooked pig trotters during storage.

• Journal of Biomedical Engineering Research
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• v.30 no.1
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• pp.10-17
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• 2009

Accurate electroencephalography (EEG) forward calculation is of importance for the accurate estimation of neuronal electrical sources. Conventional studies concerning the EEG forward problems have investigated various factors influencing the forward solution accuracy, e.g. tissue conductivity values in head compartments, anisotropic conductivity distribution of a head model, tessellation patterns of boundary element models, the number of elements used for boundary/finite element method (BEM/FEM), and so on. In the present paper, we investigated the influence of modeling errors in the boundary element volume conductor models upon the accuracy of the EEG forward solutions. From our simulation results, we could confirm that accurate construction of boundary element models is one of the key factors in obtaining accurate EEG forward solutions from BEM. Among three boundaries (scalp, outer skull, and inner skull boundary), the solution errors originated from the modeling error in the scalp boundary were most significant. We found that the nonuniform error distribution on the scalp surface is closely related to the electrode configuration and the error distributions on the outer and inner skull boundaries have statistically meaningful similarity to the curvature distributions of the boundary surfaces. Our simulation results also demonstrated that the accumulation of small modeling errors could lead to considerable errors in the EEG source localization. It is expected that our finding can be a useful reference in generating boundary element head models.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.6
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• pp.573-584
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• 2015

In this study, the atmospheric dispersion of radioactive material ($^{137}Cs$) was simulated with regard to its impact within a 50-km radius from the Kori Nuclear Power Plant (NKPP) based on two different types of models (the non-steady-state puff model CALPUFF and the lagrangian model HYSPLIT) during the spring of 2012 (May 2012). The dispersion distribution of $^{137}Cs$ calculated in the CALPUFF model was similar to that of the HYSPLIT model, but the magnitudes of differences in its spatio-temporal concentrations between the two models were different. The $^{137}Cs$ concentrations simulated by the CALPUFF were significantly lower than those of the HYSPLIT due to a limitation of puff models (e.g. puff size growth over time). The CALPUFF had the advantage of determining the dispersion of radioactive materials and their impacts on the surrounding regions, compared with the HYSPLIT that had high concentrations of $^{137}Cs$ in only small local areas with the movement of air masses along the local winds.

• International Journal of Automotive Technology
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• v.5 no.1
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• pp.61-67
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• 2004

This paper suggests two simple two-degree-of-freedom models to describe the dynamical interaction between the pad and the disc of a disc brake system. Separate models for in-plane and out -of-plane vibration are described. Although a brake pad and disc have many modes of vibration, the interaction between a single mode of each component is considered as this is thought to be crucial for brake noise. For both models, the pad and the disc are connected by a sliding friction interface having a velocity dependent friction coefficient. In this paper, it is shown that this friction model acts as negative damping in the system that describes the in-plane vibration, and as negative stiffness in system that describes the out-of-plane vibration. Stability analysis is performed to investigate the conditions under which the systems become unstable. The results of the stability analysis show that the damping is the most important parameter for in-plane vibration, whereas the stiffness is the most important parameter for the out-of-plane vibration.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.448-448
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• 2018

In this study, the regression models (Load ESTimator and eight-parameter model) were evaluated to estimate instantaneous pollutant loads under various criteria and optimization methods. As shown in the results, LOADEST commonly used in interpolating pollutant loads could not necessarily provide the best results with the automatic selected regression model. It is inferred that the various regression models in LOADEST need to be considered to find the best solution based on the characteristics of watersheds applied. The recently developed eight-parameter model integrated with Genetic Algorithm (GA) and Gradient Descent Method (GDM) were also compared with LOADEST indicating that the eight-parameter model performed better than LOADEST, but it showed different behaviors in calibration and validation. The eight-parameter model with GDM could reproduce the nitrogen loads properly outside of calibration period (validation). Furthermore, the accuracy and precision of model estimations were evaluated using various criteria (e.g., $R^2$ and gradient and constant of linear regression line). The results showed higher precisions with the $R^2$ values closed to 1.0 in LOADEST and better accuracy with the constants (in linear regression line) closed to 0.0 in the eight-parameter model with GDM. In hence, based on these finding we recommend that users need to evaluate the regression models under various criteria and calibration methods to provide the more accurate and precise results for pollutant load estimations.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.441-446
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• 2001

On global interconnectivity, the activation of real-time and worldwide contents will permeate and impact all aspects of day-to-day life well throughout this century. In managing contents and models, we too will see the impact of this rapidly changing environment. The real time availability of contents pertaining to a companys supply chain through means of the Internet and mobile networks(e.g., the IMT-2000) will necessitate a change in decision-making processes for effective management of contents and models. To increase the availability of many contents and models, a management system should have adaptive function in proving adequate content and model for companies. In the respect of management of contents and models, this paper discusses a production mechanism of meta-knowledge for effectively managing contents and models. Through two experimental analyses with the production mechanism, it is proven that the system enabling adaptive contents and models provision goes beyond existing ones in view of efficiency of management of contents and models in the wire and wireless networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.366-381
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• 2020

Steganography has been successfully employed in various applications, e.g., copyright control of materials, smart identity cards, video error correction during transmission, etc. Deep learning-based steganography models can hide information adaptively through network learning, and they draw much more attention. However, the capacity, security, and robustness of the existing deep learning-based steganography models are still not fully satisfactory. In this paper, three models for different cases, i.e., a basic model, a secure model, a secure and robust model, have been proposed for different cases. In the basic model, the functions of high-capacity secret information hiding and extraction have been realized through an encoding network and a decoding network respectively. The high-capacity steganography is implemented by hiding a secret image into a carrier image having the same resolution with the help of concat operations, InceptionBlock and convolutional layers. Moreover, the secret image is hidden into the channel B of carrier image only to resolve the problem of color distortion. In the secure model, to enhance the security of the basic model, a steganalysis network has been added into the basic model to form an adversarial network. In the secure and robust model, an attack network has been inserted into the secure model to improve its robustness further. The experimental results have demonstrated that the proposed secure model and the secure and robust model have an overall better performance than some existing high-capacity deep learning-based steganography models. The secure model performs best in invisibility and security. The secure and robust model is the most robust against some attacks.