• Water for future
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• v.6 no.2
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• pp.6-11
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• 1973

This paper include the hydrometeorological analyses of evapotranspiration which is import factor concerning the estimate of water budgest over a certain basin. Evapotranspiration model mode by the multiple regression analysis between the evapotranspiration measured on various kinds of ground cover (water, bare soil and lawn) and the other meteorological elements affecting the evapotranspiration process, and the simple regression analysis between the evapo transpiration measured on each ground cover and the evapotranspiration on water and vegetables calculated from the Penman equation. It is expected that the evapotranspiration models are a very useful formulae estimating ten days amounts or a month's amounts.

• Tunnel and Underground Space
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• v.9 no.4
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• pp.315-327
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• 1999

Rock fracture mechanics has been widely applied to blasting, hydraulic fracturing, rock slope and many other practical problems in rock engineering. But a measuring method for the fracture toughness of rock, one of the mort important parameters in fracture mechanics as an intrinsic property of rock, has not been yet well established. To obtain mode I rock fracture toughness, the more favorable disc-typed specimens such as CCNBD, SCB, chevron-notched SCB and BDT were used in this study. Rock fracture toughness under mixed-mode and mode II conditions was measured by using the STCA applied to the CCNBD specimen. Size effects such as specimen thickness, diameter and notch length on fracture toughness were investigated. From the mixed-mode results, fracture envelops were obtained by applying various regression curves. The mixed-mode results were also compared with three mixed-mode failure criteria. In each fracture toughness test, acoustic emission was measured to get the data for determining the load levels of different crack propagation patterns.

• Journal of the Ergonomics Society of Korea
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• v.6 no.1
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• pp.3-8
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• 1987

This paper develops a statistical mode which estimates mental and physical loads of light work from sinus arrhythmia (SA) scores. During experiments, various levels of mental and physical loads (respectively scored by information processing and finger tapping rates) were imposed on subjects and SA scores were measured from the subjects. Two methods were used in developing workload estimation model. One is an algebraic inverse function of a multivariate regression equation, where mental and physical loads are independent variables and SA scores are dependent variables. The other is a statistical multivariate inverse regression. Of the two methods, inverse function resulted in larger mean squqre error in predicting mental and physical loads. Hence, inverse regression model is recommended for precise workload estimation.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2011.05a
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• pp.191-192
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• 2011

The construction projects contain a lot of variables and risk affecting productivity. The duration of the project must be recognized important as for quality, unit cost and safety. There is need for improving work efficiency by investigating relationship of works to prevent delay. This study focuses on analysing the delay factors of steel staircase system to suggest regression model that enables construction productivity estimation. The position of the observers and construction delay factors were expressed by the independent variable of the regression model and productivity was expressed by a dependent variable. This paper suggests quantitative productivity and it is expected that will be helpful estimating application in construction new technologies.

• Korean Journal of Food Science and Technology
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• v.51 no.3
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• pp.227-236
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• 2019

Antioxidant activity in water and ethanol extracts of dried Lycium chinense fruit, as a result of the total phenolic and tannin content, was measured using a number of chemical and biochemical assays for radical scavenging and inhibition of lipid peroxidation, with the analysis being extended by applying a bootstrapping statistical method. Previous statistical analyses mostly provided linear correlation and regression analyses between antioxidant activity and increasing concentrations of phenolics and tannins in a concentration-dependent mode. The present study showed that multiple component or multivariate analysis by applying multiple regression analysis or regression planes proved more informative than linear regression analysis of the relationship between the concentration of individual components and antioxidant activity. In this paper, we represented the multivariate analysis of antioxidant activities of both phenolic and tannin contents combined in the water and ethanol extracts, which revealed the hidden observations that were not evident from linear statistical analysis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.7
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• pp.777-787
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• 2012

The transient analysis for the output voltage of a piezoresistive microaccelerometer takes a relatively high computation time because at least two iterations are required to calculate the piezoresistive-structural coupled response at each time step. In this study, the high computational cost for calculating the transient output voltage is considerably reduced by an approach integrating the mode superposition method and the least square method. In the approach, data on static displacement and output voltage calculated by piezoresistive-structural coupled simulation for three acceleration inputs are used to develop a quadratic regression model, relating the output voltage to the displacement at a certain observation point. The transient output voltage is then approximated by a regression model using the displacement response cheaply calculated by the mode superposition method. A high-impact microaccelerometer subject to several types of acceleration inputs such as 100,000 G shock, sine, step, and square pulses are adopted as a numerical example to represent the efficiency and accuracy of the suggested approach.

• Proceedings of the KWS Conference
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• 1998.05a
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• pp.188-192
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• 1998

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.577-587
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• 2023

Conventional categorical data imputation techniques, such as mode imputation, often encounter issues related to overestimation. If the variable has too many categories, multinomial logistic regression imputation method may be impossible due to computational limitations. To rectify these limitations, we propose a two-stage imputation method. During the first stage, we utilize the Boruta variable selection method on the complete dataset to identify significant variables for the target categorical variable. Then, in the second stage, we use the important variables for the target categorical variable for logistic regression to impute missing data in binary variables, polytomous regression to impute missing data in categorical variables, and predictive mean matching to impute missing data in quantitative variables. Through analysis of both asymmetric and non-normal simulated and real data, we demonstrate that the two-stage imputation method outperforms imputation methods lacking variable selection, as evidenced by accuracy measures. During the analysis of real survey data, we also demonstrate that our suggested two-stage imputation method surpasses the current imputation approach in terms of accuracy.

• Smart Structures and Systems
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• v.14 no.3
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• pp.397-418
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• 2014

In this paper, a simple two-step method for structural vibration-based health monitoring for beam-like structures have been extended to plate-like structures with though-thickness cracks. Crack locations and severities of plate-like structures are detected using a hybrid approach. The interval wavelet transform is employed to extract crack singularity locations from mode shape and support vector regression (SVR) is applied to predict crack serviettes form crack severity detection database (the relationship of natural frequencies and crack serviettes) using several natural frequencies as inputs. Of particular interest is the natural frequencies estimation for cracked plate-like structures using Rayleigh quotient. Only the natural frequencies and mode shapes of intact structures are needed to calculate the natural frequencies of cracked plate-like structures using a simple formula. The crack severity detection database can be easily obtained with this formula. The hybrid method is investigated using numerical simulation and its validity of the usage of interval wavelet transform and SVR are addressed.

• International Journal of Automotive Technology
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• v.4 no.2
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• pp.101-108
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• 2003

There are a lot of factors that influence automotive fuel economy such as average trip time per kilometer, average trip speed, the number of times of vehicle stationary, and so forth. These factors depend on road conditions and traffic environment. In this study, various driving data were measured and recorded during road tests in Seoul. The accumulated road test mileage is around 1,300 kilometers. The objective of the study is to identify the driving patterns of the Seoul metropolitan area and to analyze the fuel economy based on these driving patterns. The driving data which was acquired through road tests was analysed statistically in order to obtain the driving characteristics via modal analysis, speed analysis, and speed-acceleration analysis. Moreover, the driving data was analyzed by multivariate statistical techniques including correlation analysis, principal component analysis, and multiple linear regression analysis in order to obtain the relationships between influencing factors on fuel economy. The analyzed results show that the average speed is around 29.2 km/h, and the average fuel economy is 10.23 km/L. The vehicle speed of the Seoul metropolitan area is slower, and the stop-and-go operation is more frequent than FTP-75 test mode which is used for emission and fuel economy tests. The average trip time per kilometer is one of the most important factors in fuel consumption, and the increase of the average speed is desirable for reducing emissions and fuel consumption.