• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.4
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• pp.11-22
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• 2019

The objective of this study was to improve the cross-sectional area and height estimation method using stream width. Stream water levels should be calculated together to simulate inundation of agricultural land. However, cross-sectional survey data of small rural rivers are insufficient. The previous study has developed regression equations between the width and the cross-sectional area and between the width and the height of stream cross-section, but can not be applied to a wide range of stream widths. In this study, cross-sectional survey data of 6 streams (Doowol, Chungmi, Jiseok, Gam, Wonpyeong, and Bokha stream) were collected and divided into upstream, midstream and downstream considering the locations of cross-sections. The regression equations were estimated using the complete data. $R^2$ between the stream width and cross-sectional area was 0.96, and $R^2$ between width and height was 0.81. The regression equations were also estimated using divided data for upstream, midstream and downstream considering the locations of cross-sections. The range of $R^2$ between the stream width and cross-sectional area was 0.86 - 0.91, and the range of $R^2$ between width and height was 0.79 ? 0.92. As a result of estimating the cross-sections of 6 rivers using the regression equations, the regression equations considering the locations of cross-sections showed better performance both in the cross-sectional area and height estimation than the regression equations estimated using the complete data. Hydrologic Engineering Center - River Analysis System (HEC-RAS) was used to simulate the flood stage analysis of the estimated and the measured cross-sections for 50-year, 100-year, and 200-year frequency floods. As a result of flood stage analysis, the regression equations considering the locations of cross-sections also showed better performance than the regression equations estimated using the complete data. Future research would be needed to consider the factors affecting the cross-sectional shape such as river slope and average flow velocity. This study can be useful for inundation simulation of agricultural land adjacent to an unmeasured stream.

• Journal of Aerospace System Engineering
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• v.18 no.1
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• pp.21-28
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• 2024

In this paper, two prediction models based on deep neural network that could predict cross-sectional stiffness of a rotor blade were proposed. Herein, we employed structural and material information of cross-section. In the case of a prediction model that used material properties as the input of the network, it was designed to predict the cross-sectional stiffness by considering elastic modulus of each cross-sectional member. In the case of the prediction model that used structural information as a network input, it was designed to predict the cross-sectional stiffness by considering the location and thickness of cross-sectional members as network input. Both prediction models based on a deep neural network were realized using data obtained by cross-sectional analysis with KSAC2D (Konkuk section analysis code - two-dimensional).

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.9
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• pp.768-773
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• 2005

A new approach for human foot modelling and last design based on the cross sectional method is presented in this paper. The proposed last design method utilizes the dynamic trimmed parametric patches for the foot 3D data and last 3D data. The cross section a surface of 3D foot for the 3D last, design modeling of free form geometric last shapes. The proposed last design scheme wraps the 3D last data surrounding the measured 3D foot data with the effect of deforming the last design rule The last design rule of the FFD is constructed on the FFD lattice based on foot-last shape analysis. In addition, the control points of FFD lattice are constructed with cross sectional data interpolation methods from the a finite set of 3D foot data. The deformed 3D last result obtained from the proposed FFD is saved as a 3D dxf foot data. The experimental results demonstrate that the last designed with the proposed scheme has good performance.

• Journal of Information Technology Services
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• v.12 no.4
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• pp.91-108
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• 2013

In this study, we empirically examine cross-sectional determinants of IT personnel size of Korean listed companies from year 2004 to year 2009. Also, cross-sectional determinants of IT personnel size involved in managing internal control over financial reporting (hereafter, "ICFR") were examined. IT personnel or IT workers are recognized as critical intangible resources comprising firm's IT capability. Although IT personnel are regarded as important resources, there are not much information about factors explaining the size of firms' IT personnel. Fortunately, the Korean governmant regulates that every listed companies should dislclose the number of IT workers and ICFR-related IT personnel in their annual reports. This study utilizes the mandatorily disclosed IT personnel data to analyze cross-sectional determinants of korean listed companies' IT personnel size. Empirical results show that profitability, uncertainty, leverage, industry types are statistically significant factors associated with the size of IT personnel.

• Composites Research
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• v.30 no.6
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• pp.343-349
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• 2017

A multifield variational formulation is developed for the finite element (FE) cross-sectional analysis of composite beams. The cross-sectional warping displacements and sectional stresses are considered to be the primary variables through the application of Reissner's partially mixed principle. The warping displacements are modeled using generic FE shape functions with nonlinear distribution over the beam section. A generalized Timoshenko level stiffness matrix is derived which incorporates the effects of elastic couplings, transverse shear, and Poisson's deformations. The accuracy of the present analysis is validated for the stiffness constants and elastostatic responses of composite box beams which correlate well with the experimental data and other state-of-the-art approaches.

• Journal of Korean Academy of Nursing
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• v.45 no.1
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• pp.129-138
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• 2015

Purpose: The purpose of this study was to report the instrument modification and validation processes to make existing health belief model scales culturally appropriate for Korean Americans (KAs) regarding colorectal cancer (CRC) screening utilization. Methods: Instrument translation, individual interviews using cognitive interviewing, and expert reviews were conducted during the instrument modification phase, and a pilot test and a cross-sectional survey were conducted during the instrument validation phase. Data analyses of the cross-sectional survey included internal consistency and construct validity using exploratory and confirmatory factor analysis. Results: The main issues identified during the instrument modification phase were (a) cultural and linguistic translation issues and (b) newly developed items reflecting Korean cultural barriers. Cross-sectional survey analyses during the instrument validation phase revealed that all scales demonstrate good internal consistency reliability (Cronbach's alpha=.72~.88). Exploratory factor analysis showed that susceptibility and severity loaded on the same factor, which may indicate a threat variable. Items with low factor loadings in the confirmatory factor analysis may relate to (a) lack of knowledge about fecal occult blood testing and (b) multiple dimensions of the subscales. Conclusion: Methodological, sequential processes of instrument modification and validation, including translation, individual interviews, expert reviews, pilot testing and a cross-sectional survey, were provided in this study. The findings indicate that existing instruments need to be examined for CRC screening research involving KAs.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.113-118
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• 2006

A new last design approach based on the Limb line FFD (LFFD) and Scale factor FFD (SFFD) is presented in this paper. The proposed last design method utilizes the dynamic trimmed parametric patches for the measured foot 3D data and last 3D data. Furthermore, the proposed last data generation system utilizes cross sectional data extracted obtained from the measured 3D foot data. First, the last design rule of the LFFD is constructed on the FFD lattice based on foot last shape analysis. Secondly, SFFD is constructed on the LFFD new lattice based on scale factor deformation. The scale factor is constructed on the boundary edges of polygonized patch and the cross section last data boundary edge of the polygon object. Suppose the two boundary curves have been preprocessed so that they run in the same direction and they forms the SF(Scale Factor). In addition, the control points of FFD lattice are derived with cross. sectional data interpolation methods from a finite set of 3D foot data.

• Water Engineering Research
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• v.3 no.4
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• pp.269-278
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• 2002

A cross sectional analysis for residential water demand was conducted to help understand and explain the spatial and temporal variations in per capita water use in the rapidly growing city of Riyadh, Saudi Arabia. The analysis was based on data previously collected from May 1983 to June 1984. 195 randomly selected households were distributed to three groups according to house condition, household income level, and social and cultural factors. The generated models using stepwise multiple regression indicated that plot size and number of males, females and children are the most significant independent variables. Although, coefficients of determination achieved for most of the developed models were low (0.2-0.5), the independent variables could still explain a part of the variations fur such a complex social and cultural structure.

• Survey Research
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• v.12 no.2
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• pp.89-112
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• 2011

This study shows the results of constructing panel data using Farm Household survey and presents some examples of empirical application. This study shows that ex post constructed panel data using repeated cross-sectional survey can be used in various dynamic analyses. This paper also shows that the well known difficult problem of longitudinal weights can be easily solved by using the existing cross-sectional weights in original cross-section data. Based on these results, we propose that the National Statistical Office not only try to construct panel data, but also construct panel data by using existing repeated cross-section data. The benefits of this approach seems to be very big in establishment survey.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.899-907
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• 2010

Several non-response imputation methods are suggested, however, mainly cross-sectional imputations are studied and applied to this analysis. A simple and common imputation method for panel data is the cross-wave regression imputation or carry-over imputation as a special case of cross-wave regression imputation. This study suggests a multiple imputation method combined time series analysis and cross-sectional multiple imputation method. We compare this method and the cross-wave regression imputation method using MSE, MAE, and Bias. The 2008 monthly labor survey data is used for this study.