• Journal of the Korean Academy of Child and Adolescent Psychiatry
• /
• v.12 no.2
• /
• pp.275-281
• /
• 2001

This study examined the relationship between psychopathology(depression, anxiety, aggression), maladaptive cognitions(negative cognitive errors, attributional biases), and age of children with ADHD. 40 ADHD children and their mother completed questionnaires assessing depression, anxiety, aggression level and maladaptive cognitions of children. The results showed that maladaptive cognitions of children with ADHD was not significantly associated with their depression, anxiety, aggression level. Age was negatively related to internal stable attributions for negative events that was characteristic in depression, and had significantly effect on internal stable attributions for negative events. As age of ADHD children increased, their internal attribution for negative events reduced. It seems that their depression and anxiety level is associated with current stress event rather than maladaptive cognitions. Suggestions and limitations of this study, and the directions for future study were discussed.

• STI Policy Review
• /
• v.4 no.2
• /
• pp.41-54
• /
• 2013

R&D is inherently an uncertain endeavor, yet now more than ever those performing R&D with public funding are called upon to clarify the utility of their research. Calls for public accountability are mounting with the increase in constraints on government budgets due to the recent worldwide economic recession, in response to which both policymakers and researchers pay much more attention to rigorously assessing publicly funded R&D. A key issue complicating R&D evaluation in these circumstances is how to adequately account for the nature and degree of risk involved in a given R&D program or project. This study deliberates on certain issues involving the measurement of ex-ante risk in public R&D evaluation: (i) information asymmetry between R&D sponsors and performers, (ii) ambiguity in the measurement of returns in both prospective and retrospective evaluation, and (iii) the dilemma between measurement error and omitted variable bias for empirical estimation of R&D performance. The study then presents an analysis of hypothetical evaluation results that apply risk-relevant weights to the annual evaluation outcomes of South Korea's national R&D programs funded during 2006~2012. In this counterfactual re-evaluation of public R&D program performance, high-risk R&D programs turn out to receive higher evaluation than non-high-risk programs. The current study suggests that R&D evaluation ignoring ex-ante risk is not only conceptually invalid since R&D activities are intrinsically uncertain endeavors, but unfair as R&D performers are asked to be accountable for the results that were in fact out of their reach.

• Proceedings of the Korean Vacuum Society Conference
• /
• 1999.07a
• /
• pp.135-135
• /
• 1999

It is well known that Raman spectroscopy is powerful tool in analysis of sp3/sp3 bonding fraction in diamond-like carbon(DLC) films. Raman spectra of DLC film is composed of D-peak centered at 1350cm-1 and G-peak centered at 1530cm-1. The sp3/sp3 fraction is qualitatively acquired by deconvolution method. However, in case of DLC film, it is generally observed that G-peak position shifts toward low wavenumber as th sp3 fraction increases. However, opposite results were frequently observed in ta-C films. ta-C film has much higher residual compressive stress due to its high sp3 fraction compared to the DLC films deposited by CVD method. Effect of residual stress on G-peak position is most recommendable parameter in Raman analysis of ta-C, due to its smallest fitting error among many parameters acquired by peak deconvolution of symmetric spectra. In current study, the effect of residual stress on Raman spectra was quantitatively evaluated by free-hang method. ta-C films of different residual stress were deposited on Si-wafer by modifying DC-bias voltage during deposition. The variation of the G-peak position along the etching depth were observed in the free-hangs of 20~30${\mu}{\textrm}{m}$ etching depth. Mathematical result based on Airy stress function, was compared with experimental results. The more reliable analysis excluding stress-induced shift was possible by elimination of the Raman shift due to residual compressiove stress.

• Food Science of Animal Resources
• /
• v.35 no.1
• /
• pp.108-113
• /
• 2015

The purpose of this study was to develop predictive models for the growth of Listeria monocytogenes in pork Bulgogi at various storage temperatures. A two-strain mixture of L. monocytogenes (ATCC 15313 and isolated from pork Bulgogi) was inoculated on pork Bulgogi at 3 Log CFU/g. L. monocytogenes strains were enumerated using general plating method on Listeria selective medium. The inoculated samples were stored at 5, 15, and $25^{\circ}C$ for primary models. Primary models were developed using the Baranyi model equations, and the maximum specific growth rate was shown to be dependent on storage temperature. A secondary model of growth rate as a function of storage temperature was also developed. As the storage temperature increased, the lag time (LT) values decreased dramatically and the specific growth rate of L. monocytogenes increased. The mathematically predicted growth parameters were evaluated based on the modified bias factor ($B_f$), accuracy factor ($A_f$), root mean square error (RMSE), coefficient of determination ($R^2$), and relative errors (RE). These values indicated that the developed models were reliably able to predict the growth of L. monocytogenes in pork Bulgogi. Hence, the predictive models may be used to assess microbiological hygiene in the meat supply chain as a function of storage temperature.

• Journal of Forest and Environmental Science
• /
• v.24 no.3
• /
• pp.155-158
• /
• 2008

Site index is the essential tool for forest management to estimate the productivity of forest land Generally, site index equation is developed and used by relationship between stand age and dominant tree heights. However, there is a limit to use the site index equation in the application of variable ages, environmental influence, and estimation of site index for unstocked land. Therefore, it was attempted to develop a new site index equations based on various environmental factors including site and topographical variables. This study was conducted to develop regional site index equations based on the relationship between site index and soil factors for Pinus densiflora. Environmental factors that obtained from GIS application, were selected by stepwise-regression. Site index Equation was estimated by multiple regression from selected factors. Four environmental factors were selected in the final site index equations by stepwise regression. It was observed that coefficients of determination for site index equations were ranged from 0.34 which seem to be relatively low but good enough for estimation of forest stand productivity. The site index equations developed in this study were also verified to be useful by three evaluation statistics such as model's estimation bias, model's precision and mean square error type of measure.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.53 no.5
• /
• pp.699-706
• /
• 2020

Predictive models in food microbiology are used for predicting microbial growth or death rates using mathematical and statistical tools considering the intrinsic and extrinsic factors of food. This study developed predictive growth models for Bacillus cereus on dried laver Pyropia pseudolinearis stored at different temperatures (5, 10, 15, 20, and 25℃). Primary models developed for specific growth rate (SGR), lag time (LT), and maximum population density (MPD) indicated a good fit (R²≥0.98) with the Gompertz equation. The SGR values were 0.03, 0.08, and 0.12, and the LT values were 12.64, 4.01, and 2.17 h, at the storage temperatures of 15, 20, and 25℃, respectively. Secondary models for the same parameters were determined via nonlinear regression as follows: SGR=0.0228-0.0069*T₁+0.0005*T₁²; LT=113.0685-9.6256*T₁+0.2079*T₁²; MPD=1.6630+0.4284*T₁-0.0080*T₁² (where T₁ is the storage temperature). The appropriateness of the secondary models was validated using statistical indices, such as mean squared error (MSE<0.01), bias factor (0.99≤B_f≤1.07), and accuracy factor (1.01≤A_f≤1.14). External validation was performed at three random temperatures, and the results were consistent with each other. Thus, these models may be useful for predicting the growth of B. cereus on dried laver.

• Atmosphere
• /
• v.27 no.1
• /
• pp.105-118
• /
• 2017

This study assesses the performance of the Weather Research and Forecasting (WRF) model in reproducing regional climate over CORDEX-East Asia Phase 2 domain with different cumulus parameterization schemes [Kain-Fritch (KF), Betts-Miller-Janjic (BM), and Grell-Devenyi-Ensemble (GD)]. The model is integrated for 27 months from January 1979 to March 1981 and the initial and boundary conditions are derived from European Centre for Medium-Range Weather Forecast Interim Reanalysis (ERA-Interim). The WRF model reasonably reproduces the temperature and precipitation characteristics over East Asia, but the regional scale responses are very sensitive to cumulus parameterization schemes. In terms of mean bias, WRF model with BM scheme shows the best performance in terms of summer/winter mean precipitation as well as summer mean temperature throughout the North East Asia. In contrast, the seasonal mean precipitation is generally overestimated (underestimated) by KF (GD) scheme. In addition, the seasonal variation of the temperature and precipitation is well simulated by WRF model, but with an overestimation in summer precipitation derived from KF experiment and with an underestimation in wet season precipitation from BM and GD schemes. Also, the frequency distribution of daily precipitation derived from KF and BM experiments (GD experiment) is well reproduced, except for the overestimation (underestimation) in the intensity range above (less) then $2.5mm\;d^{-1}$. In the case of the amount of daily precipitation, all experiments tend to underestimate (overestimate) the amount of daily precipitation in the low-intensity range < $4mm\;d^{-1}$ (high-intensity range > $12mm\;d^{-1}$). This type of error is largest in the KF experiment.

• Journal of Korean Society for Geospatial Information Science
• /
• v.23 no.4
• /
• pp.11-16
• /
• 2015

Spatial and temporal information on near-surface air temperature is important for understanding global warming and climate change. In this study, the estimation algorithm of near-surface air temperature in Korea was developed by using spatial homogeneous surface information obtained from satellite remote sensing observations. Based on LST(Land Surface Temperature), NDWI(Normalized Difference Water Index) and NDVI(Normalized Difference Vegetation Index) as independent variables, the multiple regression model was proposed for the estimation of near-surface air temperature. The different regression constants and coefficients for warm and cold seasons were calculated for considering regional climate change in Korea. The near-surface air temperature values estimated from the multiple regression algorithm showed reasonable performance for both warm and cold seasons with respect to observed values (approximately $3^{\circ}C$ root mean-square error and nearly zero mean bias). Thus;the proposed algorithm using remotely sensed surface observations and the approach based on the classified warm and cold seasons may be useful for assessment of regional climate temperature in Korea.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.46 no.5
• /
• pp.401-406
• /
• 2001

The applicability of non-destructive near infrared reflectance spectroscopic (NIRS) method was tested to determine the protein and oil contents of intact soybean [Glycine max (L.) Merr.] seeds. A total of 198 soybean calibration samples and 101 validation samples were used for NIRS equation development and validation, respectively. In the developed non-destructive NIRS equation for analysis of protein and oil contents, the most accurate equation was obtained at 2, 8, 6, 1(2nd derivative, 8 nm gap, 6 points smoothing, and 1 point second smoothing) and 2, 1, 20, 10 math treatment conditions with Standard Normal Variate and Detrend (SNVD) scatter correction method and entire spectrum (400-2500 nm) by using Modified Partial Least Squares (MPLS) regression, respectively. Validation of these non-destructive NIRS equations showed very low bias (protein: 0.060%, oil: -0.017%) and standard error of prediction (SEP, protein: 0.568 %, oil : 0.451 %) as well as high coefficient of determination ($R^2$, protein: 0.927, oil: 0.906). Therefore, these non-destructive NIRS equations can be applicable and reliable for determination of protein and oil content of intact soybean seeds, and non-destructive NIRS method could be used as a mass screening technique for selection of high protein and oil soybean in breeding programs.

• Journal of Microbiology and Biotechnology
• /
• v.17 no.4
• /
• pp.644-649
• /
• 2007

Response surface model was developed for predicting the growth rates of Salmonella enterica sv. Typhimurium in tryptic soy broth (TSB) medium as a function of combined effects of temperature, pH, and NaCl. The TSB containing six different concentrations of NaCl (0, 2, 4, 6, 8, and 10%) was adjusted to an initial of six different pH levels (pH 4, 5, 6, 7, 8, 9, and 10) and incubated at 10 or $20^{\circ}C$. In all experimental variables, the primary growth curves were well $(r^2=0.900\;to\;0.996)$ fitted to a Gompertz equation to obtain growth rates. The secondary response surface model for natural logarithm transformations of growth rates as a function of combined effects of temperature, pH, and NaCl was obtained by SAS's general linear analysis. The predicted growth rates of the S. Typhimurium were generally decreased by basic (9, 10) or acidic (5, 6) pH levels or increase of NaCl concentrations (0-8%). Response surface model was identified as an appropriate secondary model for growth rates on the basis of coefficient determination $(r^2=0.960)$, mean square error (MSE=0.022), bias factor $(B_f=1.023)$, and accuracy factor $(A_f=1.164)$. Therefore, the developed secondary model proved reliable predictions of the combined effect of temperature, NaCl, and pH on growth rates for S. Typhimurium in TSB medium.