• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.713-727
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• 2005

Among different regression approaches, nonparametric procedures perform well under different conditions. In practice it is very hard to identify which is the best procedure for the data at hand, thus model combination is of practical importance. In this paper, we focus on one dimensional regression with fixed design. Polynomial regression, local regression, and smoothing spline are considered. The data are split into two parts, one part is used for estimation and the other part is used for prediction. Prediction performances are used to assign weights to different regression procedures. Simulation results show that the combined estimator performs better or similarly compared with the estimator chosen by cross validation. The combined estimator generates a similar risk to the best candidate procedure for the data.

• Journal of the Korea Safety Management & Science
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• v.11 no.2
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• pp.117-126
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• 2009

We develop methods for propagating and analyzing EPCI(Extended Process Capability Index) by using the error type that classifies into accuracy and precision. EPCI developed in this study can be applied to the three combined processes that consist of production, measurement and calibration. Little calibration work discusses while a great deal has been studied about SPC(Statistical Process Contol) and MSA(Measurement System Analysis). EPCI can be decomposed into three indexes such as PPCI(Production Process Capability Index), PPPI(Production Process Performance Index), MPCI(Measurement PCD, and CPCI(Calibration PCI). These indexs based on the type of error classification can be used with various statistical techniques and principles such as SPC control charts, ANOVA(Analysis of Variance), MSA Gage R&R, Additivity-of-Variance, and RSSM(Root Sum of Square Method). As the method proposed is simple, any engineer in charge of SPC. MSA and calibration can use efficientily in industries. Numerical examples are presentsed. We recommed that the indexes can be used in conjunction with evaluation criteria.

• Journal of the Korean Statistical Society
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• v.27 no.3
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• pp.305-318
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• 1998

Smoothing tests based on an L$_2$ error between a truncated courier series estimator and a true function have shown good powers for a wide class of alternatives, These tests have the same form of the Neyman smooth test whose performance depends on the selected order, a basis, the farm of estimators. We construct flexible data driven Neyman smooth tests by changing a basis, combining model selection criteria and different series estimators. A simulation study shows that the generalized Neyman smooth test with the best basis provides good power for a wider class of alternatives compared with other data driven Neyman smooth tests based on a fixed form of estimator, a fixed basis and a fixed criterion.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.27 no.6
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• pp.407-416
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• 2014

Five factors are identified, which affect the performance of optical filter: 1) type of optical glass, 2) existence of Fe, 3) photo pic coating type, 4) coating form, and 5) coating thickness. If we consider all the levels of five factors, there are 360 possible candidates. We determined five evaluation criteria, which can be used to evaluate possible candidates. For the performance measures we selected white-state avearge voltage, black-state average voltage, and black-state error rate. And we added economic criterion and quality and maintenance criterion. Through the two-step statistical analysis of white-state avearge voltage, black-state average voltage, and black-state error rates, we selected final four candidates. Based on the five criteria we finally determined optimal optical filter using AHP.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.595-612
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• 2011

Most organizations use performance appraisal system to evaluate the effectiveness and efficiency of their employees. In evaluating staff performance, performance appraisal usually involves awarding numerical values or linguistic labels to employees performance. These values and labels are used to represent each staff achievement by reasoning incorporated in the arithmetical or statistical methods. However, the staff performance appraisal may involve judgments which are based on imprecise data especially when a person (the superior) tries to interpret another person's (his/her subordinate) performance. Thus, the scores awarded by the appraiser are only approximations. From fuzzy logic perspective, the performance of the appraisee involves the measurement of his/her ability, competence and skills, which are actually fuzzy concepts that can be captured in fuzzy terms. Accordingly, fuzzy approach can be used to handle these imprecision and uncertainty information. Therefore, the performance appraisal system can be examined using Fuzzy Logic Approach, which is carried out in the study. The study utilized a Cascaded fuzzy inference system to generate the performance qualities of some University non-teaching staff that are based on specific performance appraisal criteria.

• Korean Journal of Human Ecology
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• v.16 no.3
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• pp.563-576
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• 2007

The purpose of this study is to analyze the financial performance according to the economic environment change. The data of 4,577 households in 2003 and 3994 households in 2000 is from the Korean Labor and Income Panel Study. The data were analyzed by various statistical methods such as frequency, mean-test, Duncan's multiple range test, k-mean cluster analysis. Findings were as follows; First, the classified household financial strategy types were Residual(44.3%), Financial Assets(24.0%), Informal Institutional(19.7%), Diversified Portfolio(7.6%), Real Estate(4.5%). Second, the criteria of classification of the financial strategies were relative, not absolute. Third, the rate of economic growth was high and the index of the current money was low in 2000. Fourth, households that employed a diversified portfolio strategy had the greatest net wealth.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.151-162
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• 1990

Occupational disease among typists such as Carpal Tunnel Syndrome(CTS) and tendonitis has increased along with rapid expansion of office automation. During typing, the posture can be defined as forearm pronation, ulnar abduction, wrist extension and finger flexion. The CTS results from awkward posture between forearm-wrist-hand and the keyboard arrangement. Therefore, ergonomic principles should be emphasized in keyboard design. The objective of the study is to improve keyboard design by analyzing anatomical posture of forearm and hand during typing. An experimental study was performed to investigate relationships between a keyboard and typing performance. Results showed that typing performance is dependent to angles and slopes of a keyboard. Statistical analysis indicated that the suggested ergonomic keyboard improved typing speed significantly(17%).

• Geomechanics and Engineering
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• v.33 no.1
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• pp.1-9
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• 2023

The unconfined compression strength (UCS) of soils is commonly used either before or during the construction of geo-structures. In the pre-design stage, UCS as a mechanical property is obtained through a laboratory test that requires cumbersome procedures and high costs from in-situ sampling and sample preparation. As an alternative way, the empirical model established from limited testing cases is used to economically estimate the UCS. However, many parameters affecting the 1D soil compression response hinder employing the traditional statistical analysis. In this study, gene expression programming (GEP) is adopted to develop a prediction model of UCS with common affecting soil properties. A total of 79 undisturbed soil samples are collected, of which 54 samples are utilized for the generation of a predictive model and 25 samples are used to validate the proposed model. Experimental studies are conducted to measure the unconfined compression strength and basic soil index properties. A performance assessment of the prediction model is carried out using statistical checks including the correlation coefficient (R), the root mean square error (RMSE), the mean absolute error (MAE), the relatively squared error (RSE), and external criteria checks. The prediction model has achieved excellent accuracy with values of R, RMSE, MAE, and RSE of 0.98, 10.01, 7.94, and 0.03, respectively for the training data and 0.92, 19.82, 14.56, and 0.15, respectively for the testing data. From the sensitivity analysis and parametric study, the liquid limit and fine content are found to be the most sensitive parameters whereas the sand content is the least critical parameter.

• International Journal of Highway Engineering
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• v.14 no.2
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• pp.165-174
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• 2012

In this study, a method for evaluating the performance of speed measurements was developed to assess the qualities of a vehicle detector. The evaluation method considers measurement errors that are reflected in a reference speed. For this, the concept of uncertainty in measurement was applied to the development method. Other factors such as precedent study, statistical processing techniques, and speed measurement performance method of traffic enforcement equipment and vehicle detection systems were also reviewed. Through this process, the problems of the existing evaluation methods were derived and developed for the new performance evaluation method. Vehicle detectors that are installed in the field were evaluated using the traditional assessment methods and the developed method. As a result, for traditional assessment methods, it was found that evaluation criteria are acceptable, while developed method's criteria are not acceptable. This means that traditional assessment methods do not sufficiently consider errors in measurement, so it has potential to over-estimate for performance of evaluation equipment. On the other hand, it was represented that the developed method should include variable factor such as errors in measurement and more precise compared to traditional assessment methods.

• International Journal of Concrete Structures and Materials
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• v.9 no.2
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• pp.185-206
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• 2015

This paper presents statistical models developed to study the influence of key mix design parameters on the properties of lightweight self-consolidating concrete (LWSCC) with expanded shale (ESH) aggregates. Twenty LWSCC mixtures are designed and tested, where responses (properties) are evaluated to analyze influence of mix design parameters and develop the models. Such responses included slump flow diameter, V-funnel flow time, J-ring flow diameter, J-ring height difference, L-box ratio, filling capacity, sieve segregation, unit weight and compressive strength. The developed models are valid for mixes with 0.30-0.40 water-to-binder ratio, high range water reducing admixture of 0.3-1.2 % (by total content of binder) and total binder content of $410-550kg/m^3$. The models are able to identify the influential mix design parameters and their interactions which can be useful to reduce the test protocol needed for proportioning of LWSCCs. Three industrial class ESH-LWSCC mixtures are developed using statistical models and their performance is validated through test results with good agreement. The developed ESH-LWSCC mixtures are able to satisfy the European EFNARC criteria for self-consolidating concrete.