• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.9
• /
• pp.73-81
• /
• 2020

This study demonstrated the effect of IT Ssupports for Iintegration Ccompetency(ITSIC) on organizational performance by using organizational temperance and absorption capacity as medium. The research model was verified with Smart PLS 3.0 based on the survey conducted overa total a total of of 126 pparticipantseople's surveys for the employees. First, the ITSIC had a positive effect on both the alignment and adaptability and also on absorption capacity. Second, it was confirmed that organizational temperance hads a positive effect on absorption capacity. Third, when the organizational temperance was mediated in the relationship between ITSIC and absorption capacity, it had a indicated a positive effect. Fourth, absorption capacity had a positive impact on organizational performance. The implications of this study differ from the existing studies through by validating validation of correlations correlations by extending IT technology and organizational performance to organizational ethical factors. In addition, it has been established that the ethical factors of the organization also act as leading factors of absorption capacity. ITSIC helps managers make balanced decision-making, which can contribute to improving absorption capacity by giving members a positive perception, ultimately having a positive impact on organizational performance. It suggests the importance of building appropriate IT infrastructure and cultivating organizational virtues in order to improve the performance of organizations in which absorption capacity is essential.

• KIPS Transactions on Software and Data Engineering
• /
• v.9 no.4
• /
• pp.137-144
• /
• 2020

Delirium is among the most common mental disorders encountered in patients with a temporary cognitive impairment such as consciousness disorder, attention disorder, and poor speech, particularly among those who are older. Delirium is distressing for patients and families, can interfere with the management of symptoms such as pain, and is associated with increased elderly mortality. The purpose of this paper is to generate useful clinical knowledge that can be used to distinguish the outcomes of patients with delirium in long-term care facilities. For this purpose, we extracted the clinical classification knowledge associated with delirium using a local covering rule acquisition approach with the rough lower approximation region. The clinical applicability of the proposed method was verified using data collected from a prospective cohort study. From the results of this study, we found six useful clinical pieces of evidence that the duration of delirium could more than 12 days. Also, we confirmed eight factors such as BMI, Charlson Comorbidity Index, hospitalization path, nutrition deficiency, infection, sleep disturbance, bed scores, and diaper use are important in distinguishing the outcomes of delirium patients. The classification performance of the proposed method was verified by comparison with three benchmarking models, ANN, SVM with RBF kernel, and Random Forest, using a statistical five-fold cross-validation method. The proposed method showed an improved average performance of 0.6% and 2.7% in both accuracy and AUC criteria when compared with the SVM model with the highest classification performance of the three models respectively.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.34 no.4
• /
• pp.567-571
• /
• 2005

In this study, the effects of varying the amount of water, soaking time at $25^{\circ}C$ and drying time after soaking at $45^{\circ}C$ on the induction of resveratrol were evaluated to optimize the soaking treatment by response surface methodology (RSM). After response surface regression (RSREG), the second-order polynomial equation was fitted to the experimental data. The analysis of variance showed that the model appeared to be adequate $(R^2=0.9547)$ with no significant lack of fit (p>0.1). From statistical analysis, amount of water and soaking time were found to be significant factors. On the other hand, drying time was not significant. Ridge analysis showed that the optimized parameters were $67.15\%$ for amount of water, 19.58 hr for soaking time, 65.56 hr for drying time. It was confirmed that resveratrol content was increased from $0.1\;{\mu}g/g$ to $4.55\;{\mu}g/g$ under the optimized conditions. In addition, the experimental values at the optimized condition agreed with values predicted by ridge analysis. The analytical method validation parameters such as accuracy, precision, and specificity were calculated to ensure the method's validity.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.55 no.4
• /
• pp.284-291
• /
• 2010

A simulation modeling for predicting the harvesting date with high potato solids consists of development of mathematical models. The mathematical model on potato growth and its development should be obtained by using agricultural elements which analyze relations of solar radiation quantity, temperature, photon quantity, carbon dioxide exchange rate, water stress and loss, relative humidity, light intensity, and wind etc. But more reliable way to predict harvesting date against climatic change employs in vivo energy consumption for growth and induction shape in a slight environmental adaptation. Therefore, to calculate in vivo energy loss, we take a concept of estimate of the amount of basal metabolism in each tuber on the basis of $Wm={\int}^m_tf(x)dt$ and $Tp=\frac{Tm{\cdot}Wm^{Tp}}{Wm^{Tm}}$. In the validation experiments, results of measuring solid accumulation of potato harvested at simulated date agreed fairly well with the actual measured values in each regional field during the growth period of 2005-2009. The calculation method could be used to predict an appropriate harvesting date for a production of high potato solids according to weather conditions.

• Korean Journal of Remote Sensing
• /
• v.32 no.5
• /
• pp.435-452
• /
• 2016

Land Surface Temperature (LST) has been operationally retrieved from the Communication, Ocean, and Meteorological Satellite (COMS) data by the spilt-window method (CSW_v2.0) developed by Cho et al. (2015). Although the CSW_v2.0 retrieved the LST with a reasonable quality compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) LST data, it showed a relatively poor performance for the strong inversion and lapse rate conditions. To solve this problem, the LST retrieval algorithm (CSW_v2.0) was updated using the simulation results of radiative transfer model (MODTRAN 4.0) by considering the diurnal variations of air temperature. In general, the upgraded version, CSW_v3.0 showed a similar correlation coefficient between the prescribed LSTs and retrieved LSTs (0.99), the relatively smaller bias (from -0.03 K to-0.012 K) and the Root Mean Square Error (RMSE) (from 1.39 K to 1.138 K). Particularly, CSW_v3.0 improved the systematic problems of CSW_v2.0 that were encountered when temperature differences between LST and air temperature are very large and/or small (inversion layers and superadiabatic lapse rates), and when the brightness temperature differences and surface emissivity differences were large. The bias and RMSE of CSW_v2.0 were reduced by 10-30% in CSW_v3.0. The indirect validation results using the MODIS LST data showed that CSW_3.0 improved the retrieval accuracy of LST in terms of bias (from -0.629 K to -0.049 K) and RMSE (from 2.537 K to 2.502 K) compared to the CSW_v2.0.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.29 no.1
• /
• pp.31-36
• /
• 2009

This study was conducted to find out an alternative way of rapid and accurate analysis of forage quality. Near reflectance infrared spectroscopy (NIRS) was used to evaluate the possibility of forage analysis and collect 258 samples such as barley for whole crop silage, forage corn and sudangrass from 2002 to 2007. The samples were analyzed for CP (crude protein), CF (crude fiber), ADF (acid detergent fiber), NDF (neutral detergent fiber) and IVTD (in vitro true digestibility), and also scanned using NIRSystem with wavelength from $400{\sim}2,400nm$. Multiple linear regression was used with wet analysis data for developing the calibration model and validate unknown samples. The important index In this experiment was SEC and SEP $r^2$ for CF, CP, NDF, ADF and IVTD in calibration set were 0.70, 0.86, 0.94, 0.94 and 0.89, also 0.47, 0.39, 0.89, 0.90 and 0.61 in validation sample, respectively. The results of this experiment indicates that NIRS was reliable analytical method to assess forage quality, specially in CF, ADF and IVTD, sample should be included for respective forage samples to get accurate result. More robust calibrations can be made to cover every forage samples if added representative sample set.

• Journal of the Korean GEO-environmental Society
• /
• v.9 no.5
• /
• pp.45-52
• /
• 2008

The present study has extended OpenSees, which is an open-source software framework DOS program for developing applications to idealize geotechnical and structural problems, for the static analysis of axial load capacity and settlement of single piles in MS Windows environment. The Windows version of OpenSees as improved by this study has enhanced the DOS version from a general purpose software program to a special purpose program for driven and bored pile analysis with additional features of pre-processing and post-processing and a user friendly graphical interface. The method used in the load capacity analysis is the numerical methods based on load transfer functions combined with finite elements. The use of empirical nonlinear T-z and Q-z load transfer curves to model soil-pile interaction in skin friction and end bearing, respectively, has been shown to capture the nonlinear soil-pile response under settlement due to load. Validation studies have shown the static load capacity and settlement predictions implemented in this study are in fair agreement with reference data from the static loading tests.

• Journal of Radiation Protection and Research
• /
• v.38 no.4
• /
• pp.208-213
• /
• 2013

The suitability of the site criteria is a basic requirement for securing safety of nuclear power plants. The suitability should be confirmed through the estimation of environmental radiation effects at the exclusion area boundary under the severe weather conditions. In this study, field tracer experiments over short range of 1 km radius under severe weather conditions were conducted at flat area in Daejeon. Severe weather conditions are represented with stable atmospheric condition and low wind speed. In general, the condition is appeared at clean night time with weak wind. The analysis of the measured distribution of the released tracer gas shows two big differences between the results of the past experiments conducted under the favorable weather conditions. One is the difficulty of finding the typical distribution of the released tracer gas with peak concentration in the downwind direction. The other one is the appearance of the contour of the concentration of tracer gas at several hundred meters even though the gas released at 10 m height over the ground.

• Korean Chemical Engineering Research
• /
• v.48 no.6
• /
• pp.717-724
• /
• 2010

The flash point is one of the most important physical properties used to determine the potential for fire and explosion hazards of flammable liquids. Despite the needs of the experimental flash point data for the design and construction of chemical plants, there is often a significant gap between the demands for the data and their availability. This study have built and compared two models of partial least squares(PLS) and support vector machine(SVM) to predict the experimental flash points of 893 organic compounds out of DIPPR 801. As the independent variables of the models, 65 functional groups were chosen based on the group contribution method that was oriented from the assumption that each fragment of a molecule contributes a certain amount to the value of its physical property, and the logarithm of molecular weight was added. The prediction errors calculated from cross-validation were employed to determine the optimal parameters of two models. And, an optimization technique should be used to get three parameters of SVM model. This work adopted particle swarm optimization that is one of heuristic optimization methods. As the selection of training data can affect the prediction performance, 100 data sets of randomly selected data were generated and tested. The PLS and SVM results of the average absolute errors for the whole data range from 13.86 K to 14.55 K and 7.44 K to 10.26 K, respectively, indicating that the predictive ability of the SVM is much superior than PLS.

• Journal of Korea Water Resources Association
• /
• v.37 no.8
• /
• pp.643-651
• /
• 2004

In this paper, the Hydrologic Simulation Program-Fortran (HSPF) was validated to estimate the pollutant loads from rural small watershed. The study watershed was the HP#6 subwatershed in Balhan reservoir watershed, located southwest from Suwon. The drainage area of HP#6 study watershed was 3.85$\textrm{km}^2$. Parameters of the HSPF model related to hydrology and water quality were calibrated from 1996 to 1997, and validated from 1999 to 2000 using observed hydrologic and water quality data. The average simulated runoff ratio for the calibration period was 0.579 and the measured runoff ratio was 0.583. The root mean square error (RMSE) for runoff during the calibration period was 2.1mm and correlation coefficient ($R^2$) was 0.92. Regarding the total nitrogen simulation, the RMSE was 0.086kg/ha/day and $R^2$ was 0.81 for the calibration period. In the case of total phosphorus, the RMSE was 0.012kg/ha/day and $R^2$ was 0.70 for the calibration period.