• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.284-294
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• 2018

Statistical methods have been widely used to estimate the remaining battery runtime of mobile smart devices, such as smart phones, smart gears, tablets, and etc. However, existing work available in the literature only considers a particular statistical method. Thus, it is difficult to determine whether statistical methods are applicable to estimating thr remaining battery runtime of mobile devices or not. In this paper, we evaluated the performance of statistical methods applicable to estimating the remaining battery runtime of mobile smart devices. The statistical estimation methods evaluated in this paper are as follows: simple and moving average, linear regression, multivariate adaptive regression splines, auto regressive, polynomial curve fitting, and double and triple exponential smoothing methods. Research results presented in this paper give valuable data of insight to IT engineers who are willing to deploy statistical methods on estimating the remaining battery runtime of mobile smart devices.

• Journal of Korean Society on Water Environment
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• v.31 no.6
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• pp.653-664
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• 2015

TPLMS (Total water pollutant load management system) that is the most powerful water-quality protection program have been implemented since 2004. In the implementation of TPLMS, target water-quality and permissible discharged load from each unit watershed can be decided by water-quality modeling. And NPS (Non-point sources) discharge coefficients associated with certain (standard) flow are used on estimation of input data for model. National Institute of Environmental Research (NIER) recommend NPS discharge coefficients as 0.15 (Q₂₇₅) and 0.50 (Q₁₈₅) in common for whole watershed in Korea. But, uniform coefficient is difficult to reflect various NPS characteristics of individual watershed. Monthly NPS discharge coefficients were predicted and estimated using surface flow and water-quality from HSPF watershed model in this study. Those coefficients were plotted in flow duration curve of study area (Palger stream and Geumho C watershed) with monthly average flow. Linear regression analysis was performed about NPS discharge coefficients of BOD, T-N and T-P associated with flow, and R² of regression were distributed in 0.893~0.930 (Palger stream) and 0.939~0.959 (Geumho C). NPS Discharge coefficient through regression can be estimated flexibly according to flow, and be considered characteristics of watershed with watershed model.

• Journal of Korea Water Resources Association
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• v.38 no.8 s.157
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• pp.605-616
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• 2005

In this paper, runoff curve numbers (CN's) for a small forested mountainous catchment are estimated using rainfall-runoff data measured at Sulma experimental catchment every 10 minutes and a new guideline for applying the antecedent rainfall conditions (ARC's) for small mountainous watersheds in Korea is proposed. Sulma experimental catchment is a typical natural mountainous basin with $97\%$ of forested land cover and CN's are estimated to be in the range between 51 and 89 with median value of 72. The test hypothesis stating as 1-day ARC is better than 5-day ARC in determining CN's for a small mountainous watershed is shown to be acceptable. Also, linear regression equations for the estimation of CN's for small mountainous catchments are proposed. As there is no significant investigations available on CN's for small mountainous catchments, the newly proposed relationships between CN's and ARC may be used as a preliminary guideline to assign CN's for the estimation of floods from rainfall data on mountainous regions.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.432-438
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• 2011

The purpose of the present thesis is to develop bankruptcy prediction models capable of being applied to the Korean construction industry and to deduce an optimal model through comparative evaluation of final developed models. A study population was selected as general contractors in the Korean construction industry. In order to ease the sample securing and reliability of data, it was limited to general contractors receiving external audit from the government. The study samples are divided into a bankrupt company group and a non-bankrupt company group. The bankruptcy, insolvency, declaration of insolvency, workout and corporate reorganization were used as selection criteria of a bankrupt company. A company that is not included in the selection criteria of the bankrupt company group was selected as a non-bankrupt company. Accordingly, the study sample is composed of a total of 112 samples and is composed of 48 bankrupt companies and 64 non-bankrupt companies. A financial ratio was used as early predictors for development of an estimation model. A total of 90 financial ratios were used and were divided into growth, profitability, productivity and added value. The MDA (Multivariate Discriminant Analysis) model and BLRA (Binary Logistic Regression Analysis) model were used for development of bankruptcy prediction models. The MDA model is an analysis method often used in the past bankruptcy prediction literature, and the BLRA is an analysis method capable of avoiding equal variance assumption. The stepwise (MDA) and forward stepwise method (BLRA) were used for selection of predictor variables in case of model construction. Twenty two variables were finally used in MDA and BLRA models according to timing of bankruptcy. The ROC-Curve Analysis and Classification Analysis were used for analysis of prediction performance of estimation models. The correct classification rate of an individual bankruptcy prediction model is as follows: 1) one year ago before the event of bankruptcy (MDA: 83.04%, BLRA: 93.75%); 2) two years ago before the event of bankruptcy (MDA: 77.68%, BLRA: 78.57%); 3) 3 years ago before the event of bankruptcy (MDA: 84.82%, BLRA: 91.96%). The AUC (Area Under Curve) of an individual bankruptcy prediction model is as follows. : 1) one year ago before the event of bankruptcy (MDA: 0.933, BLRA: 0.978); 2) two years ago before the event of bankruptcy (MDA: 0.852, BLRA: 0.875); 3) 3 years ago before the event of bankruptcy (MDA: 0.938, BLRA: 0.975). As a result of the present research, accuracy of the BLRA model is higher than the MDA model and its prediction performance is improved.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.279-289
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• 2022

Since the frequency of heavy rainfall is increasing due to climate change, water levels in the river exceed past historical records. The rating-curve is to convert water level into flow dicscharge from the regression analysis of the water level and corresponding flow discharges. However, the rating-curve involves many uncertainties because of the limited data especially when observed water level exceed past historical water levels. In order to compensate for insufficient data and increase the accuracy of flow discharge data, this study estimates the flow discharge in the river computed mathematically using Monte Carlo simulation based on a 1D hydrodynamic numerical model. Based on the existing rating curve, a random combination of coefficients constituting the rating-curve creates a number of virtual rating curve. From the computed results of the hydrodynamic model, it is possible to estimate flow discharge which reproduces best fit to the observed water level. Based on the statistical evaluation of these samples, a method for mathematically estimating the water level and flow discharge of all cross sections is porposed. The proposed methodology is applied to the junction of Yochoen Stream in the Seomjin River. As a result, it is confirmed that the water level reproducibility was greatly improved. Also, the water level and flow discharge can be calculated mathematically when the proposed method is applied.

• Journal of Korean Society on Water Environment
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• v.35 no.6
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• pp.481-496
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• 2019

The Ministry of Environment has measured streamflow at eight-day intervals for the estimation of standard flow of the Total Maximum Daily Loads (TMDL) system. This study identified the availability of the partially measured the eight-day interval data for estimating standard flow and found the optimal extension techniques of standard flow. The study area was selected for the Nakbon-A watershed in the Nakdong River, and four streamflow record extension techniques of standard flow were considered: extension, percentile, drainagearea, and regional regression methods. The flow duration curve (FDC) using the eight-day interval streamflow data indicated very high Nash and Sutcliffe Efficiency (NSE) values above 90 % from FDC-II to FDC-VII compared to FDC-VIII, the standard FDC. This result demonstrates that FDC using daily data of three-six cumulative years could represent standard FDC fairly well. For the streamflow record extension techniques of standard flow, the percentile method was selected as the optimal alternative, showing the minimal difference from FDC-VIII. These results validate the availability of the eight-day interval streamflow data in the standard flow estimation and the application of extension techniques. It seems that these results could reduce the uncertainty of partially measured streamflow data for water quantity and quality management.

• Journal of the Korean Society for information Management
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• v.29 no.2
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• pp.193-204
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• 2012

The characteristics of citation and centrality measures in citation networks can be identified using multiple linear regression analyses. In this study, we examine the relationships between bibliometric indices and centrality measures in an article-level co-citation network to determine whether the linear model is the best fitting model and to suggest the necessity of data transformation in the analysis. 703 highly cited articles in Physics published in 2004 were sampled, and four indicators were developed as variables in this study: citation counts, degree centrality, closeness centrality, and betweenness centrality in the co-citation network. As a result, the relationship pattern between citation counts and degree centrality in a co-citation network fits a non-linear rather than linear model. Also, the relationship between degree and closeness centrality measures, or that between degree and betweenness centrality measures, can be better explained by non-linear models than by a linear model. It may be controversial, however, to choose non-linear models as the best-fitting for the relationship between closeness and betweenness centrality measures, as this result implies that data transformation may be a necessary step for inferential statistics.

• Journal of Aerospace System Engineering
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• v.3 no.2
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• pp.12-19
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• 2009

The research for the fatigue analysis is regarded greatly as important in aerospace field. Moreover, a study on the fatigue characteristic is very actively progressing. In this study, the fatigue life estimation was performed for Flaperon Joint which has FCL(fatigue critical location) of tilt-rotor UAV. The Flaperon Joint should be taken the various loads by several missions profiles of UAV. The fatigue load spectrum of Flaperon Joint is generated by the standard mission segment for the tilt-rotor UAV, and this spectrum is used for the fatigue test and analysis. The in-house fatigue analysis program is applied to calculate the fatigue life based on Stress-Life(S-N) method. The S-N curve is generated from the S-N data of Mil-Handbook by second order polynomial regression method. Moreover, the coefficient of determination is used to ensure how accuracy it has. In addition, the Goodman equation is used to consider the mean stress effect for evaluating more accurate fatigue life. Finally, the result of fatigue analysis is verified by comparing with the fatigue test result for the Flaperon Joint.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.109-121
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• 2006

The road should be designed in the consistent alignment which the driver can drive safely. Also, proper highway environments in order to maintain optimal operational speeds on highway sections should be provided In design stage, for highway environments, it is essential for an operational speed estimation model to different highway environments. If a method which could evaluate the status of the road safety is developed through this operational speed estimation model, it is possible to provide safe and more comfortable highways to road users. In the study factors to effect on operational speeds are classified into three groups horizontal & vertical alignments and traffic operation characteristic factors. Factors are chosen to effect on operational speeds by using collation analysis as classifications of tangent sections, horizontal curve sections and vertical curve sections. In order to develop operational speed estimation models in express highways, multi-regression analysis has been used in this study using the selected factors. This study has meaning that the developed estimation models for operational speeds and evaluation of degree of safety to horizontal and vortical alignments simultaneous. In order to represent whole area of the country with the developed models, the models should be re-analyzed with vast data related with road alignment factors in the near future.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.3
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• pp.37-43
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• 2009

The objective of this study was to investigate the basic relationships between spectral reflectance and varying concentrations of sediment in surface waters. An experimental method for determining suspended sediment concentration (SSC) in the water by use of a spectroradiometer above the water surface, in visible and near-infrared (NIR) wavelengths, is applied. The main advantage of the method is the direct comparison of spectral reflectance and the SSC, but it requires an accurate knowledge of the water body and sediment. Therefore numerous spectroradiometric measurements are carried out in situ measurements, for SSC, ranging from zero to 100 percentage and two types of sediment applied in the water tank. The results indicate that the suspended sediment causes increasing spectral reflectance response in waters. We observed that spectral reflectance increases with SSC, first at the lower wavelengths (430-480 nm), then in the middle wavelengths (570-700 nm), and finally, in the NIR domain (800-820 nm); a characteristic maximum reflectance appears at 400-670 nm. Relationships between the wavelength, integral value, and the SSC were evaluated on the basis of the regression analysis. The regression curve for the relation between the wavelength, integral value, and the SSC were determined ($R^2$>0.98). Finally, the specular wavelength can be estimated to recognize the sediment and to improve SC estimation accuracy in the water.