• Journal of the Korean Geotechnical Society
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• v.24 no.1
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• pp.119-130
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• 2008

Uncertainties in physical and engineering parameters for the design of shallow foundations arise from various aspects such as inherent variability and measurement error. This paper aims at investigating and reducing uncertainty from deterministic method by using the reliability-based design of shallow foundations accounting for the variation of various design parameters. A probability distribution type and statistics of random variables such as unit weight, cohesion, infernal friction angle and Young's modulus in geotechnical engineering are suggested to calculate the ultimate bearing capacities and immediate settlements of foundations. Reliability index and probability of failure are estimated based on the distribution types of random variables. Widths of foundation are calculated at target reliability index and probability of failure. It is found that application and analysis of the best-fit distribution type for each random variables are more effective than adoption of the normal distribution type in optimizing the reliability-based design of shallow foundations.

• Journal of Computational Design and Engineering
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• v.3 no.4
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• pp.337-348
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• 2016

An experimental approach is presented for the measurement of wear that is common in the threading of cold-forged steel. In this work, the first objective is to measure wear on various types of roll taps manufactured to tapping holes in microalloyed HR45 steel. Different geometries and levels of wear are tested and measured. Taking their geometry as the critical factor, the types of forming tap with the least wear and the best performance are identified. Abrasive wear was observed on the forming lobes. A higher number of lobes in the chamber zone and around the nominal diameter meant a more uniform load distribution and a more gradual forming process. A second objective is to identify the most accurate data-mining technique for the prediction of form-tap wear. Different data-mining techniques are tested to select the most accurate one: from standard versions such as Multilayer Perceptrons, Support Vector Machines and Regression Trees to the most recent ones such as Rotation Forest ensembles and Iterated Bagging ensembles. The best results were obtained with ensembles of Rotation Forest with unpruned Regression Trees as base regressors that reduced the RMS error of the best-tested baseline technique for the lower length output by 33%, and Additive Regression with unpruned M5P as base regressors that reduced the RMS errors of the linear fit for the upper and total lengths by 25% and 39%, respectively. However, the lower length was statistically more difficult to model in Additive Regression than in Rotation Forest. Rotation Forest with unpruned Regression Trees as base regressors therefore appeared to be the most suitable regressor for the modeling of this industrial problem.

• Journal of the Korean Data and Information Science Society
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• v.20 no.3
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• pp.515-526
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• 2009

Pricing based on proper risk has been one of main issues in auto insurance. In this paper, we review how the techniques of pricing in auto insurance have been developed and suggest a better approach which meets the existing risk statistically by comparison. The generalized linear model (GLM) method is discussed for pricing with different distributions. With GLM approach, the distribution of error assumed plays an main role for the best fit corresponding to the characteristics of dependent variables. Tweedie distribution is considered as one of error distributions in addition to widely used Gamma and Poisson distribution. With these different types of error assumption for estimating the proper premium in auto insurance, various modeling approaches are possible. In this paper, various modeling approaches with different assumptions for estimating proper risk is discussed and also real example is given by assuming different.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.4
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• pp.487-496
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• 2005

Chlorine bulk decay tests were carried out by bottle test under controlled conditions in a laboratory. Experiments were performed at different temperatures: $5^{\circ}C$, $15^{\circ}C$, $25^{\circ}C$, and the water temperatures when samples were taken from the effluent just before entering to its distribution system. 38 bulk tests were performed for water of Al (water treatment plant), 4 bulk tests for A2 (large service reservoir), and A3(pumping station). Residual chlorine concentrations in the amber bottles were measured over time till about 100 hours and bulk decay coefficients were evaluated by assuming first-order, parallel first-order, second-order. and $n^{th}-order$ reaction. The $n^{th}-order$ coefficients were obtained using Fourth-order Runge-Kutta Method. A good-fit by the average coefficient of determination ($R^2$) was first-order ($R^2=0.90$) < parallel first-order ($R^2{_{fast}}=0.92$, $R^2{_{slow}}=0.95$) < second-order ($R^2=0.95$) < $n^{th}-order$ ($R^2=0.99$). But if fast reaction of parallel first-order bulk decay were applied to the effluent of large service reservoir with ca. 20 hours of travel time and slow reaction in the water distribution system following the first 20 hours, parallel first-order bulk decay would be best and easy for application of water quality modeling technique.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.14 no.3
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• pp.209-221
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• 2002

In the present paper, a method which enhances the circulation of harbor waters by using wave energy was investigated. The overflow levee was selected as a coastal structure helping the harbor circulation, and was applied to Jeju-outer-port site so as to estimate its effectiveness quantitatively in probabilistic point of view. It was assumed that sea water influx rate through the overflow levee into the harbor depended upon wave height and tidal level and a functional relationship among them was calculated using the results of hydraulic experiment. The probability distribution of water influx could be obtained from hindcasted wave data and measured tidal elevations at Jeju harbor. The Gamma distribution was appeared to best fit the estimated influx distribution, and the optimal location of the levee was discussed. Finally, water quality purification effect was investigated by computing the contaminant material dispersion according to whether the levee was or not.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.183-198
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• 2011

With the recent development of IT technology, the existing contents have been digitalized through various distribution channels. Accordingly, a lot of studies have been done in order to figure out the distribution and features of digital contents, In these studies, however, categorical characteristics of digital contents were not considered ; most of the previous researchers saw digital contents as only a single item or focused on some contents within particular part such as movie, music, etc. So, this study divides digital contents into movies, music and texts. I was going to study which factors affect Customer Satisfaction in relation with the kind of contents. With SERVQUAL as independent variables, which affect the Customer satisfaction, I used five factors :Design Quality, Information Quality, Security Quality, Communication Quality and Transaction Quality. As for the detailed items, I corrected them with Open-End Question and Pre Survey Research, which are more fit into the features of digital contents. This research conducted Principle Component Analysis, Reliability Test, Correlation Analysis and Regression Analysis. I verified that each factor of Service Qualities has a positive effect on Customer Satisfaction. Moreover, the factors of the effect are different according to the kind of digital contents. This paper was added Exploratory Study to find the best distribute channel. For the study, I search the possible distribute channel in each digital contents and their characteristic.

• Journal of Korea Water Resources Association
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• v.41 no.5
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• pp.527-544
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• 2008

Generalized Pareto distribution (GPD) is frequently applied in hydrologic extreme value analysis. The main objective of statistics of extremes is the prediction of rare events, and the primary problem has been the estimation of the threshold and the exceedances which were difficult without an accurate method of calculation. In this paper, to obtain the threshold or the exceedances, four methods were considered. For this comparison a GPD model was used to estimate parameters and quantiles for the seven durations (1, 2, 3, 6, 12, 18 and 24 hours) and the ten return periods (2, 3, 5, 10, 20, 30, 50, 70, 80 and 100 years). The parameters and quantiles of the three-parameter generalized Pareto distribution were estimated with three methods (MOM, ML and PWM). To estimate the degree of fit, three methods (K-S, CVM and A-D test) were performed and the relative root mean squared error (RRMSE) was calculated for a Monte Carlo generated sample. Then the performance of these methods were compared with the objective of identifying the best method from their number.

• The Korean Journal of Applied Statistics
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• v.29 no.2
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• pp.331-344
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• 2016

Whole Crop Barley (WCB) is a representative self-sufficient winter annual forage crop, along with Italian Ryegrass (IRG), in Korea. In this study, we examined the path relationship between WCB yield and climate factors such as temperature, precipitation, and sunshine duration using a structural equation model. A Bayesian approach was considered to overcome the limitations of the small WCB sample size. As prior distribution of parameters in Bayesian method, standard normal distribution, the posterior result of structural equation model for WCB, and the posterior result of structural equation model for IRG (which is the most popular winter crop) were used. Also, Heywood case correction in prior distribution was considered to obtain the posterior distribution of parameters; in addition, the best prior to fit the characteristics of winter crops was identified. In our analysis, we found that the best prior was set by using the results of a structural equation model to IRG with Heywood case correction. This result can provide an alternative for research on forage crops that have hard to collect sample data.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.44 no.4
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• pp.390-396
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• 2011

Southern rough shrimp Trachysalambria curvirostris is exploited mainly by small shrimp beam trawl in coastal regions of Korea. To determine the size selectivity of a shrimp beam trawl for this species, a series of comparative fishing experiments was conducted in the sea adjacent to Geoje Island off the southern cost of Korea in June and November, 2010, using codends with four different mesh sizes(14.2, 17.8, 25.5, and 35.3 mm). The extended Share Each Length's Catch Total(SELECT) analysis method, based on a multinomial distribution, was applied to the fishing data to obtain a master selection curve. The model with the estimated split parameters fit the catch data best. The master selection curve was estimated to be: s(R)=exp(15.183R-7.872)/[1+exp(15.183R-7.872)], where the relative carapace length, R, is the ratio of carapace length to mesh size. The relative carapace length for 50% retention was 0.518, and the selection range was 0.145. The results suggest that codends with a larger mesh size allow more small-sized shrimps to escape.

• Journal of Information Processing Systems
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• v.10 no.3
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• pp.395-411
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• 2014

Temporal medical data is often collected during patient treatments that require personal analysis. Each observation recorded in the temporal medical data is associated with measurements and time treatments. A major problem in the analysis of temporal medical data are the missing values that are caused, for example, by patients dropping out of a study before completion. Therefore, the imputation of missing data is an important step during pre-processing and can provide useful information before the data is mined. For each patient and each variable, this imputation replaces the missing data with a value drawn from an estimated distribution of that variable. In this paper, we propose a new method, called Newton's finite divided difference polynomial interpolation with condition order degree, for dealing with missing values in temporal medical data related to obesity. We compared the new imputation method with three existing subspace estimation techniques, including the k-nearest neighbor, local least squares, and natural cubic spline approaches. The performance of each approach was then evaluated by using the normalized root mean square error and the statistically significant test results. The experimental results have demonstrated that the proposed method provides the best fit with the smallest error and is more accurate than the other methods.