• 디지털산업정보학회논문지
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• 제8권3호
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• pp.199-212
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• 2012

This study focuses on the influence of followership on leadership and empowerment, and to verify based on the control variables taken in IT SME's to enhance competitiveness through innovation and improvement plan that have been taken. Because there can be a lot of information to be taken, the laws of Moderated Regression Multiple analysis(MMR) were used. Amos, due to the moderating effect of Structural Equation Modeling(SEM) has been employed to re-verify the results seen with Moderated Regression Multiple analysis. The paper focuses on determining whether transformational leadership or transactional leadership is effective as shown by the levels of empowerment derived from these two types of leadership under study. As a result, both the Moderated Regression Multiple analysis and structural equation model searched information on transformational and followership for empowerment having moderating effects. In the Moderated Regression Multiple analysis, results showed that empowerment for leadership in business in the regulation of followership role appeared not to be seen. However, using the structural equation modeling, moderating effects have been found.

• 한국농공학회논문집
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• 제65권3호
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• pp.15-28
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• 2023

The compaction properties of the soil change depending on the physical properties, and are also affected by crushing of the particles. Since the particle size distribution of soil affects the engineering properties of the soil, it is necessary to analyze the material properties to understand the compaction characteristics. In this study, the size of each sieve was classified into four in the particle size analysis as a material property, and the compaction characteristics were evaluated by multiple regression and maximum dry unit weight. As a result of maximum dry unit weight prediction, multiple regression analysis showed R² of 0.70 or more, and DNN analysis showed R² of 0.80 or more. The reliability of the prediction result analyzed by DNN was evaluated higher than that of multiple regression, and the analysis result of DNN-T showed improved prediction results by 1.87% than DNN. The prediction of maximum dry unit weight using particle size distribution seems to be applied to evaluate the compacting state by identifying the material characteristics of roads and embankments. In addition, the particle size distribution can be used as a parameter for predicting maximum dry unit weight, and it is expected to be of great help in terms of time and cost of applying it to the compaction state evaluation.

• 동아시아식생활학회지
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• 제17권6호
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• pp.963-971
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• 2007

This research aimed to determine the relationship between hotel restaurants' SCM activities and their results. The samples are included exclusive high-end hotels located in the seoul area. To analyze the data, frequency analysis, reliability analysis, factor analysis, and regression analysis were applied. Multiple regression analysis showed that SCM activities (${\beta}$=.342, p<.000), information sharing (${\beta}$=.136, p<.006), and cooperative activities (${\beta}$=.120, p<.015) had a significant impact on financial performance. The explanatory power of this model was 14%, and there was statistical significance in the regression model. SCM activities(${\beta}$=.221, p<.000), information sharing (${\beta}$=.475, p<.000), and cooperative activities (${\beta}$=.172, p<.000) also had a significant impact on non-financial performance, and the explanatory power of this model was 29%, with statistical significance in the regression model.

• Journal of the Korean Data and Information Science Society
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• 제15권1호
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• pp.251-261
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• 2004

The paper focuses primarily on the standard linear multiple regression model where the parameter of interest is a ratio of two regression coefficients. The general model includes the calibration model, the Fieller-Creasy problem, slope-ratio assays, parallel-line assays, and bioequivalence. We provide an orthogonal transformation (cf. Cox and Reid (1987)) of the original parameter vector. Also, we give some remarks on the difficulties associated with likelihood based confidence interval.

• Journal of the Korean Data and Information Science Society
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• 제13권2호
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• pp.271-284
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• 2002

In this paper we consider the robust inference for the parameter of linear regression model based on weighted least squares. First we consider the sequential test of multiple outliers. Next we suggest the way to assign a weight to each observation $(x_i,\;y_i)$ and recommend the robust inference for linear model. Finally, to check the performance of confidence interval for the slope using proposed method, we conducted a Monte Carlo simulation and presented some numerical results and examples.

• 한국농공학회:학술대회논문집
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• 한국농공학회 1999년도 Proceedings of the 1999 Annual Conference The Korean Society of Agricutural Engineers
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• pp.387-392
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• 1999

In this paper, we attempted to eatablish questionnaire items for evaluation of residential satisfaction level by factor analysis, and the model was developed as a function of primary component of questionnaire items. For development of residential satisfaction model, items are selected by factor analysis adn regression coefficient is estimated by the multiple linear regression analysis.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2000년도 학술발표회 발표논문집
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• pp.412-418
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• 2000

The purpose of this study is estimation of daily runoff in the watershed with insufficient hydrological data using tank model. In order to estimate, twentysix watersheds were selected to calibrate tank model parameters that were defined by a trial and error method. Results were correlated with characteristics of watershed. Relationships between the parameters and the watershed characteristics were derived by a multiple regression analysis. The simulation results were in agreement with the observed data.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1525-1525
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• 2001

Non-destructive determination of soluble solids(Brix) in harvested fruits using near infrared(hereafter, NIR) spectroscopy has been reported by many researchers. We have just reported on non-destructive estimation of Brix in harvested melons using a NIR Systems Model 6500 spectrophotometer(Ito et al., 2000). There is a melon cultivar that is difficult to judge the harvest time from the external appearance. If we can determine Brix in growing fruits non-destructively in the field, immature fruits will not be harvested. A portable m spectrophotometer for field use has been just developed by Kubota Corporation. The spectral data of growing melons were measured by the portable spectrophotometer. A commercial program was used for multiple linear regression analysis. Brix in growing melons could be estimated by a multiple regression equation calibrated with harvested melons. Absorbances of 906 and 874 nm were included as the independent variables in the multiple regression equation, and these wavelengths are key wavelengths for non-destructive Brix determination.

• 한국환경과학회지
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• 제7권6호
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• pp.827-831
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• 1998

Statistical $SO_2$ forecasting technique by multiple regression analysis was designed and developed to predict $SO_2$ concentration in Wonju City. $SO_2$ concentration data measured from air pollution monitoring system and meteorological factors data such as : wind speed, atmospheric stability, surface temperature, relative humidity and precipitation were used in Wonju City during the 1996~1997. As the results, correlation model for forecasting was well fitted with some parameters including minimum temperature, wind speed and the $SO_2$ concentration of the previous day.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2000년도 춘계 학술대회 및 국제 감성공학 심포지움 논문집 Proceeding of the 2000 Spring Conference of KOSES and International Sensibility Ergonomics Symposium
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• pp.240-243
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• 2000

An apparel products retrieval system was proposed in which users can refer to products using Kansei evaluation values. The system adopts relevance feedback using history of the retrieval to learn the tendency of user evaluation. The system is based on a vector space retrieval model using products images expression as semantic scales. The system makes a query from user inputting information and retrieves closest products from the database. Revising algorithms of the difference method. linear multiple regression performed to investigate the effectiveness and criteria of the search. As a result of evaluation of the accuracy, it was found that the linear multiple regression and the neural network models are effective for the retrieval considering the individual Kansei.