• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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• pp.210-212
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• 1999

This paper proposes a novel wavelet transform based technique for prediction of System Marginal Price(SMP). In this paper, Daubechies D1(haar), D2, D4 wavelet transforms are adopted to predict SMP and the numerical results reveal that certain wavelet components can effectively be used to identify the SMP characteristics with relation to the system demand in electric power systems. The wavelet coefficients associated with certain frequency and time localisation are adjusted using the conventional multiple regression method and then reconstructed in order to predict the SMP on the next scheduling day through a five-scale synthesis technique. The outcome of the study clearly indicates that the proposed wavelet transform approach can be used as an attractive and effective means for the SMP forecasting.

• Advances in Computational Design
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• 제2권3호
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• pp.225-240
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• 2017

This paper presents the application of multiple linear regression (MLR) and artificial neural network (ANN) techniques for developing the models to predict the unconfined compressive strength (UCS) and Brazilian tensile strength (BTS) of the fiber reinforced cement stabilized fly ash mixes. UCS and BTS is a highly nonlinear function of its constituents, thereby, making its modeling and prediction a difficult task. To establish relationship between the independent and dependent variables, a computational technique like ANN is employed which provides an efficient and easy approach to model the complex and nonlinear relationship. The data generated in the laboratory through systematic experimental programme for evaluating UCS and BTS of fiber reinforced cement fly ash mixes with respect to 7, 14 and 28 days' curing is used for development of the MLR and ANN model. The data used in the models is arranged in the format of four input parameters that cover the contents of cement and fibers along with maximum dry density (MDD) and optimum moisture contents (OMC), respectively and one dependent variable as unconfined compressive as well as Brazilian tensile strength. ANN models are trained and tested for various combinations of input and output data sets. Performance of networks is checked with the statistical error criteria of correlation coefficient (R), mean square error (MSE) and mean absolute error (MAE). It is observed that the ANN model predicts both, the unconfined compressive and Brazilian tensile, strength quite well in the form of R, RMSE and MAE. This study shows that as an alternative to classical modeling techniques, ANN approach can be used accurately for predicting the unconfined compressive strength and Brazilian tensile strength of fiber reinforced cement stabilized fly ash mixes.

• 한국정밀공학회지
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• 제19권11호
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• pp.96-102
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• 2002

This study is on the estimation method of toot temperature for different tool nose radius and cutting conditions in turning. Experimental analysis has been performed in different cutting conditions such as cutting speed, feed rate, and depth of cut for the tool nose radius, 0.4R, 0.8R using SMC workpiece materials. Tool temperature is measured using a thermo-couple which is embedded in the insert tip. Using multiple linear regression method, the tool temperature can be determined as an exponential equation with cutting variables and tool nose diameters for the different tool materials. The equations determined in this study show a good correlation for the cutting conditions and can be used for a tool temperature estimation technique. The result indicates that the tool temperature decreases for increasing the tool nose radius in general. Also, nose radius hardly influences on the tool temperature compared with cutting speed, feed rate and depth of cut. This method will be useful for the estimation of tool life and temperature using limited experimental data for given cutting conditions.

• Near Infrared Analysis
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• 제1권1호
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• pp.37-41
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• 2000

The purpose of this research was to develop a the reflection technique with near infrared (NIR) radiation for estimating soil components. NIR reflectance was scanned at 2nm intervals from 1100 to 2500nm with an InfraAlyzer 500 (Bran & Luebbe Co.). Over 400 soil sample from fields of different crops and land-use over Youngnam and Honam regions were used to obtain mean diffuse reflection of the soil for the calibration and validation of the calibration set in estimating moisture, organic matter (OM) and total nitrogen (T-N) of the soils. Multiple linear regression (MLR) was used to evaluate the correlation of NIR spectroscopy method. Reflection pattern of NIR spectra for finely sized sample (<0.5mm) and coarsely sized soil(<2mm) did not show much difference. The results showed that NIR spectroscopy and coarsely sized soil (<2mm) did not show much difference. The results showed that NIR spectroscopy could be used as a routine soil testing method in estimating OM, moisture, T-N in soil samples simultaneously.

• 한국대기환경학회지
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• 제8권3호
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• pp.179-190
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• 1992

This study was carried out to characterize sources of atmospheric total suspended particulates (TSP) in urban and sub--urban areas of metropolitan taegu. The sources were tentatively identified by a multivariate technique, i.e. principal component analysis (PCA), and the source contributions to the atmospheric concentrations of TSP were further estimated by stepwise multiple regression analysis. A total of 5 sources was identified in the urban area of Taegu (soil dust resuspension, fuel combustion, secondary aerosol, traffic related aerosol, and refuge burning), while 4 sources were found to be significant in the sub--urban area as following: fuel combustion/secondary aerosol, soil dust resuspension, traffic related aerosol, and wood/agricultural burning. The largest contributor to the atmospheric TSP appeared to be the soil dust resuspension in both areas. The source apportionment of the extractable organic matter (EOM) was also carried out for the Taegu data. The EOM was determined with respect to the solvent polarity, i.e. cyclohexane (non-polar), dichloromethane (semi--polar), and acetone (polar). In addition, the source profiles for the TSP in Taegu area were estimated using a PCA-based algorithm, and the validity was evaluated tentatively by comparing the data in the literature.

• International Journal of Automotive Technology
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• 제4권2호
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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.

• 대한간호학회지
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• 제17권3호
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• pp.218-226
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• 1987

This descriptive-correlational study was undertaken in order to examine if there were relationships between family support, compliance and life satisfaction in chronic arthritis patients. The sampling method was a non-probability, purposive sampling technique. The participants of this study were 92 volunteer adults. 1) who have been diagnosed as having chronic arthritis and 2) who were at the medical out patient clinic of one university hospital in Seoul between April 27th to May 12th 1987. The instruments used for this study were the Family Support Scale developed by Kang Hyun Sook, a Compilance Scale developed by the researcher and the Life-Satisfaction Index-Z developed by Wood et.al. Analysis of data was done using t-test, ANOVA, Pearson Correlation Coefficient and Stepwise Multiple Regression Analysis. The results of study were as follows; Hypothesis I; “The higher the family support, the higher the compliance” was accepted. (r＝.2604, p＜.01) Hypothesis II; “The higher the compliance, the higher the life satisfaction,” was rejected. (r＝.1663, p＞0.5) Hypothesis III; “The higher the family support, the higher the life satisfaction” was accepted. (r＝.3914, p＜.01) In addition, by using Stepwise Multiple Regression Analysis it was determined that the main influencing factors on the life satisfaction were family support, the number of inflammatory joints, compliance and pain level. These 4 main variables made it possible to explain 30.8% of the variance in life satisfaction. In conclusion, this study revealed that family support is an important factor that can improve compliance and life satisfaction in chronic arthritis patients.

• 한국조경학회:학술대회논문집
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• 한국조경학회 2007년도 Journal of Landscape Architecture in Asia Vol.3
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• pp.72-77
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• 2007

Civic participation in managing the work of a park is a natural experience, and urban culture has a role in forming and communicating ideas. However, when it comes to managing a copse, there is no clear scenic image. In this study, my intention was to determine a desirable scene involving a copse and suggest a target image for managing work from a scenic perspective. I selected 12 photographs and listed 10 pairs of adjectives that were judged to reflect the effect produced by the copse scene using the repertory grid development technique. In addition, I performed a scenic evaluation using the semantic differential(SD) method with each pair of adjectives. Factor analysis was performed based on questionnaire survey results, such that the scenic structure of the copse had a clear definition. In addition, the physical characteristics of the photographs were analyzed using Adobe Photoshop 6.0 and the correlations between the results of the questionnaire survey were understood using multiple regression analysis. A desirable scenic image of the copse became clear through this process and I was able to suggest various options of scenic images. Taking the aspects of urban culture into consideration, park improvement projects(including their planning stages) should be implemented by involving residents, which will lead to further development of park planning and maintenance theories and projects giving due consideration to residents' opinions.

• 산업경영시스템학회지
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• 제43권4호
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• pp.76-83
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• 2020

Postal logistics organizations are characterized as having high labor intensity and short response times. These characteristics, along with rapid change in mail volume, make load scheduling a fundamental concern. Load analysis of major postal infrastructures such as post offices, sorting centers, exchange centers, and delivery stations is required for optimal postal logistics operation. In particular, the performance of mail traffic forecasting is essential for optimizing the resource operation by accurate load analysis. This paper addresses a traffic forecast problem of postal parcel that arises at delivery stations of Korea Post. The main purpose of this paper is to describe a method for predicting short-term traffic of postal parcel based on self-similarity analysis and to introduce an application of the traffic prediction model to postal logistics system. The proposed scheme develops multiple regression models by the clusters resulted from feature engineering and individual models for delivery stations to reinforce prediction accuracy. The experiment with data supplied by main postal delivery stations shows the advantage in terms of prediction performance. Comparing with other technique, experimental results show that the proposed method improves the accuracy up to 45.8%.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.993-996
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• 2005

High speed machining(HSM) technique is widely used in the appliance, automobile part and mold industries, which has many advantages such as good quality, low cost and rapid machining time. but it also has problems like tool break, smooth tool path, and so on. In particular, small size end mill is easy to break, so it must be changed before interrupting operation. Generally, the tool life of small size end mill is effected by the milling conditions whose evaluated parameters are spindle, feedrate, and width of cut. The experiments are carried out by full factorial design of experiments using and orthogonal array. This paper shows optimal combination and mathematical model for tool life, and the analysis of variance(ANOVA) is employed to analyze the main effects and the interactions of these milling parameters and the second-order polynomial regression model with three independent variables is estimated to predict tool life by multiple regression analysis.