• The Korea Journal of Herbology
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• v.21 no.1
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• pp.51-56
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• 2006

Objectives : To clarify the effects of Actinidia polygama and CsA on OVA-induced asthma model, we examined the influence of Actinidia polygama fructus extract (APF) and CsA on the number of regulatory T cells, NKT cells and ${\gamma}{\delta}$ T cells in murine model of asthma. Methods : All mice were immunized on two different days (21 days and 7 days before inhalational exposure) by i.p. injections of OVA in PBS. Seven days after the second sensitization, mice were exposed to aerosolized ovalbumin for 30 min/day on 3 days/week for 12 weeks and APF (400, 40 mg/kg) were orally administered 3 times a week for 8 weeks. Results : The suppressive effects of APF on asthma model were demonstrated by the increase the number of regulatory T cells, ${\gamma}{\delta}$ T cells and by reducing the number of NK T cells. Conclusion : These results indicate that APF has a deep inhibitory effect on airway inflammation and hyperresponsiveness in murine model of asthma by increase the number of regulatory T cells, and ${\gamma}{\delta}$ T cells and by reducing the number of NK T cells.

• Bulletin of the Korean Mathematical Society
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• v.40 no.4
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• pp.677-683
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• 2003

In multi-allelic model $X\;=\;(x_1,\;x_2,\;\cdots\;,\;x_d),\;M_f(t)\;=\;f(p(t))\;-\;{\int_0}^t\;Lf(p(t))ds$ is a P-martingale for diffusion operator L under the certain conditions. In this note, we examine the stochastic differential equation for model X and find the properties using stochastic differential equation.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.9
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• pp.269-274
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• 2016

In this paper We focuses on suggestion to quality model for IoT infrastructure services for Internet of Things. Quality model is suggested on security set out in ISO25000 quality factors and assessment of the existing traditional software application of ISO 9126 quality model. We validated that the proposed model can be realized it was applied to evaluate the 4 elements and related security in Metrics.

• Bulletin of the Korean Chemical Society
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• v.14 no.2
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• pp.255-258
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• 1993

Molecular dynamics (MD) calculations were carried out in order to investigate the effect of MD cell size to predict the melting phenomena of A-type zeolite. We studied two model systems: a pseudocell of $(T_2O_4Na)_n$, (L= 12.264 $^{\AA}$, N= 84) and a true-cell of (SiAlO$_4Na)_n$. (L= 24.528 $^{\AA}$, N= 672), where T is Si or Al. The radial and bond angle distribution functions of T(Si, Al)-O-T(Si, Al) and diffusion coefficients of T and O were reported at various temperatures. For the true-cell model, the melting temperature is below 1500 K and probably around 1000 K, which is about 600-700 K lower than the pseudocell model. Although it took more time (about 30 times longer) to obtain the molecular trajectories of the true-cell model than those of the pseudocell model, the true-cell model gave more realistic structural transition for the A-type zeolite, which agrees with experiment.

• Journal of Korean Society for Atmospheric Environment
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• v.4 no.2
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• pp.72-81
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• 1988

The typical ARIMA model which was developed by Box and Jenkins, was applied to the monthly $SO_2$ data collected at Seoungsoo and Oryudong in metropolitan area over five years, 1982 to 1986. To find out the changing pattern of $SO_2$ concentration, autocorrelation and partial autocorrelation analysis were undertaken. The three steps of time series model building were followed and the residual series was found to be a random white noise. The results of this study is summarized as follows. 1) The monthly $SO_2$ series was found to be a non-stationary series which which has a periodicity of 12 months. After eliminating the periodicity by differencing, the monthly $SO_2$ series became a stationary series. 2) The ARIMA seasonal model of the $SO_2$ was determined to be ARIMA $(1, 0, 0)(0, 1, 0,)_{12}$ model. 3) The model equations based on the prediction were: for Seoungsoodong: $Y_t = 0.5214Y_{t-1} + Y_{t-12} - 0.5214Y_{t-13} + a_t$ for Oryudong: $Y_t = 0.8549Y_{t-1} + Y_{t-12} - 0.8549Y_{t-13} + a_t$ 4) The validity of the model identified was checked by compairing the measured $SO_2$ values and one-month-ahead predicted values. The result of correlation and regression analysis is as follows. Seoungsoodong: $Y = 0.8710X + 0.0062 r = 0.8768$ Oryudong : $Y = 0.8758X + 0.0073 r = 0.9512$

• Journal of Environmental Science International
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• v.18 no.9
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• pp.1027-1033
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• 2009

For the assesment of pollutant loads, a monitoring has been conducted to identify hydrologic conditions and water quality of the Oenam watershed in Juam Lake, and the SWAT model integrated with GIS was applied to the watershed and evaluated for its applicability through calibration and verification using observed data. For the model application, digital maps were constructed for watershed boundary, land-use, soil series, digital elevation, and topographic input data of the Oenam watershed using Arcview. The observed runoff was 832.8 mm while the simulated runoff was 842.8 mm in 2003. The model results showed that the simulated runoff was in a good agreement with the observed data and indicated reasonable applicability of the model. In terms of nutrient load, the simulation results of T-N, T-P showed a similar trend to observed values. The observed T-N load was 10.8 kg/ha and the simulated T-N load was 7.6 kg/ha while the observed T-P load was 0.21 kg/ha and the simulated T-P load was 0.18 kg/ha. In general, SWAT model predicted observed runoff and loads of T-N and T-P after calibration with observed data in acceptable range. Overall, SWAT model was satisfactory in estimation of nutrient pollutant loads of the rural watershed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.4
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• pp.457-465
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• 2010

In this study, a Taylor series (T-S) model based on the Arrhenius, McVetty, and Monkman-Grant equations was developed using a mathematical analysis. In order to reduce fitting errors, the McVetty equation was transformed by considering the first three terms of the Taylor series equation. The model parameters were accurately determined by a statistical technique of maximum likelihood estimation, and this model was applied to the creep data of alloy 617. The T-S model results showed better agreement with the experimental data than other models such as the Eno, exponential, and L-M models. In particular, the T-S model was converted into an isothermal Taylor series (IT-S) model that can predict the creep strength at a given temperature. It was identified that the estimations obtained using the converted ITS model was better than that obtained using the T-S model for predicting the long-term creep life of alloy 617.

• The Korean Journal of Applied Statistics
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• v.34 no.2
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• pp.239-254
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• 2021

This paper studies time series analysis with estimation and forecasting for Korean COVID-19 confirmed cases, based on the approach of a heterogeneous autoregressive (HAR) model with two-piece t (TP-T) distributed errors. We consider HAR-TP-T time series models and suggest a step-by-step method to estimate HAR coefficients as well as TP-T distribution parameters. In our proposed step-by-step estimation, the ordinary least squares method is utilized to estimate the HAR coefficients while the maximum likelihood estimation (MLE) method is adopted to estimate the TP-T error parameters. A simulation study on the step-by-step method is conducted and it shows a good performance. For the empirical analysis on the Korean COVID-19 confirmed cases, estimates in the HAR-TP-T models of order p = 2, 3, 4 are computed along with a couple of selected lags, which include the optimal lags chosen by minimizing the mean squares errors of the models. The estimation results by our proposed method and the solely MLE are compared with some criteria rules. Our proposed step-by-step method outperforms the MLE in two aspects: mean squares error of the HAR model and mean squares difference between the TP-T residuals and their densities. Moreover, forecasting for the Korean COVID-19 confirmed cases is discussed with the optimally selected HAR-TP-T model. Mean absolute percentage error of one-step ahead out-of-sample forecasts is evaluated as 0.0953% in the proposed model. We conclude that our proposed HAR-TP-T time series model with optimally selected lags and its step-by-step estimation provide an accurate forecasting performance for the Korean COVID-19 confirmed cases.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.597-599
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• 2022

When IoT device performs on-device AI, the device is required to use various AI models selectively according to target service and surrounding environment. Also, AI model can be updated by additional training such as federated learning or adapting the improved technique. Hence, for successful on-device AI, IoT device should acquire various AI models selectively or update previous AI model to new one. In this paper, we propose AI model repository to tackle this issue. The repository supports AI model registration, searching, management, and deployment along with dashboard for practical usage. We implemented it using Node.js and Vue.js to verify it works well.

• Asia pacific journal of information systems
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• v.28 no.4
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• pp.320-349
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• 2018

Purpose: The application of IoT is finding continuous acceptance in our daily lives, particularly, smart speakers are making life easier and convenient for consumers. This research aims to develop and test an integrated model of factors influencing consumer's adoption of voice-enabled IoT devices. Design/methodology/approach: Based on the VAM, an integrated voice-enabled IoT device adoption model is proposed. Gender differences on five constructs relating with perceived value (perceived usefulness, perceived enjoyment, perceived security risk, perceived technicality and perceived cost) was also examined through PLS-MGA technique. The usage experience of consumers was also controlled in the integrated VAM. Findings: Result shows that Perceived-Usefulness, Perceived-Enjoyment and Perceived-Cost have a strong effect on Perceived-Value. However, Perceived-Technicality and Perceived-Security-Risk are non-influential and have no significant effect on PV. Additionally, Perceived-Value and Social-Influence plays a significant role in predicting adoption intention. Gender differences also exist in consumers perception of usefulness, enjoyment and cost. In comparison to the basic value-based adoption model, the integrated model provides more insight on consumers adoption of voice-enabled IoT devices. Originality/value: Using an integrated model, this study is one of the first scholarly attempt at modelling the influential factors for adopting smart speakers i.e., voice-enabled IoT devices, with implications for improved adoption.