• 품질경영학회지
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• 제18권1호
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• pp.84-95
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• 1990

The objective of this study is to understand the effect of measurement-related investment. That is, this study aims at verifying the correlation between the measurement-related investment and inferiority rate of products by statistical analysis. The samples of this study are 376 industrial companies in Korea, and the research data was analysed on inferiority state of industrial companies with a measurement standard laboratory. The analysis was made by the elementary statistics, the correlation analysis and the regression analysis. The results are summarized as follows : First, the inferioriy rate of the industrial companies with a measurement standard laboratory was relatively lower than that of the other companies without the laboratory by statistical significance. Second, the increment on measurement-related investment had a negative correlation with the increment of inferiority rate, and the increase of measurement-related investment showed decrease of the inferiority rate by regression analysis.

• 대한산업공학회지
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• 제41권6호
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• pp.579-587
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• 2015

Semiconductor manufacturing industry is a high density integration industry because it generates a vest number of data that takes about 300~400 processes that is supervised by numerous production parameters. It is asked of engineers to understand the correlation between different stages of the manufacturing process which is crucial in reducing production costs. With complex manufacturing processes, and defect processing time being the main cause. In the past, it was possible to grasp the corelation among manufacturing process stages through the engineer's domain knowledge. However, It is impossible to understand the corelation among manufacturing processes nowadays due to high density integration in current semiconductor manufacturing. in this paper we propose a canonical correlation analysis (CCA) using both wafer test voltage variables and fail bit counts variables. using the method we suggested, we can increase the semiconductor yield which is the result of the package test.

• 산업경영시스템학회지
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• 제37권2호
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• pp.27-34
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• 2014

In this paper, we investigate the statistical correlation of the time series for temperature measured at the heat box in the automobile drying process. We show, in terms of the sample variance, that a significant non-linear correlation exists in the time series that consist of absolute temperature changes. To investigate further the non-linear correlation, we utilize the volatility, an important concept in the financial market, and induce volatility time series from absolute temperature changes. We analyze the time series of volatilities in terms of the de-trended fluctuation analysis (DFA), a method especially suitable for testing the long-range correlation of non-stationary data, from the correlation perspective. We uncover that the volatility exhibits a long-range correlation regardless of the window size. We also analyze the cross correlation between two (inlet and outlet) volatility time series to characterize any correlation between the two, and disclose the dependence of the correlation strength on the time lag. These results can contribute as important factors to the modeling of forecasting and management of the heat box's temperature.

• International Journal of Internet, Broadcasting and Communication
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• 제14권4호
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• pp.228-239
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• 2022

Many countries around the world using ICT technologies have various technologies to keep pace with the 4th industrial revolution, and various algorithms and systems have been developed accordingly. Among them, many industries and researchers are investing in unmanned automation systems based on AI. At the time when new technology development and algorithms are developed, decision-making by big data analysis applied to AI systems must be equipped with more sophistication. We apply, Pearson's correlation analysis is applied to six independent variables to find out the job satisfaction that office workers feel according to their job characteristics. First, a correlation coefficient is obtained to find out the degree of correlation for each variable. Second, the presence or absence of correlation for each data is verified through hypothesis testing. Third, after visualization processing using the size of the correlation coefficient, the degree of correlation between data is investigated. Fourth, the degree of correlation between variables will be verified based on the correlation coefficient obtained through the experiment and the results of the hypothesis test

• 지역연구
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• 제8권1호
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• pp.31-50
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• 1992

The aim of this paper is to define major factors influencing land development of each of major uses (residential, commercial, industrial) in the process of rapid urban expansion. The main hypothesis of this study is that land use changing patterns are directed by supply side of land managed to public policies rather than demand side. The graphic analysis is applied to relationships between urban growth and land development process of each use and between land development project managed to public policies and land development process. Public and land development projects and zonning protection seem to be major roles of land supply and main determinants of urban spatial structure. Location factors for land development of each uses are selected in 23 variables. Factor analysis is applied to test correlation between variables in 1971 and 1981. Factor structure between two years is similar, but progressive processing of functional separation is derived such as intensive land use is grouped, different location between residential and industrial use is deep. Dependent variables are standardized to logarithm of land development of each use per unit vacant land in two periods, between 1971 and 1980 year and between 1981 year. Correlation analysis between 6 dependent variables and 23 location factors in each years are applied. Major factors of each use are selected in criteria such as high correlation with dependent variables, low correlation between independent variables and common application in two periods. As the result, major factors for residential land development are Land Readjustment Project (LRP), percent of total zoned area in residential zone, residential floor space density per available area, percent of total area in industrial use; for commercial development is distance to CBD, percent of total area in commercial use, residential floor space density per available area in each year, and volumn rate of industrial use; for industrial use is percent of total area of industrial use is percent of total area of industrial use, Industrial Estate Project (IES), LRP, and distance from CBD. Land development pattern of each use between two periods are slightly different. So 6 equation is derived from appling backward method of regession. Adjusted multiple R squares of all is more than 0.5 and those equation is statistically significant and valuable to assist urban land use forecasting.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2004년도 추계학술대회 논문집
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• pp.15-15
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• 2004

• 품질경영학회지
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• 제48권3호
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• pp.511-520
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• 2020

Purpose: The purpose of this study was to devise an accurate machine learning model for predicting silica concentrations following the addition of impurities, through time series analysis of mining data. Methods: The mining data were preprocessed and subjected to time series analysis using the machine learning model. Through correlation analysis, valid variables were selected and meaningless variables were excluded. To reflect changes over time, dependent variables at baseline were treated as independent variables at later time points. The relationship between independent variables and the dependent variable after n point was subjected to Pearson correlation analysis. Results: The correlation (R2) was strongest after 3 hours, which was adopted as a dependent variable. According to root mean square error (RMSE) data, the proposed method was superior to the other machine learning methods. The XGboost algorithm showed the best predictive performance. Conclusion: This study is important given the current lack of machine learning studies pertaining to the domestic mining industry. In addition, using time series analysis in mining data will show further improvement. Before establishing a predictive model for the proposed method, predictions should be made using data with time series characteristics. After doing this work, it should also improve prediction accuracy in other domains.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.86.4-86
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• 2001

This paper presents the results of a visualization analysis of the correlation between the fiber orientation and flow pattern in injection molding using the Gate-magnetization method developed for the precise visualization of melt flow. The results of the comparisons of the fiber orientation angles with the flow patterns by the Gate-Magnetization method for GPPS mixed with glass fibers show the strong correlation between the flow patterns and fiber orientation angles. According to forward movement of the flow, the fiber orientation patterns move toward the side walls following the flow patterns. These results elucidate that fibers are oriented in the expansion process of the melt, and ...

• KIEAE Journal
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• 제14권3호
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• pp.87-95
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• 2014

The purpose of this study is to evaluate the correlation coefficients between the airtightness and sound insulation performance of Han-style windows in New Han-ok. To achieve these goals, field measurements were accomplished in 18 bedrooms of 16 Han-oks in which actual residents were living, and then lab measurements were proceeded in the reverberation lab for evaluating the sound insulation performance. Followings are results. The results of the correlation analysis between the airtightness(Air change per hour at 50 Pa, ACH50) and sound insulation performance(Sound reduction index, Rw) in bedrooms of actual Han-oks, it was found that there were no significant correlation between two evaluating values. On the other hand, it was analyzed that the correlation coefficients of total 24 structures(double casement windows, single casement window, casement and sliding windows, single sliding window, 6 types per each structure) were located on 0.6757 exponentially and 0.4154 lineary in the lab evaluating conditions. But, The results of evaluating 4 structure classificatorily, it was found that there were high correlation coefficients(0.8665~0.9273 at ACH50, 0.8414~0.9346 at Rw). These results were signified that the correlation coefficients were changed according to the each structure and case by case analysis were necessary at the same time.

• 산업기술연구
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• 제34권
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• pp.53-59
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• 2014

The single regression method was used to analyze the correlationship between the compression index with mechanical properties for reclaimed marine clays in the southern coast of Korea. As results of performing regression analysis for 200 samples about reclaimed marine clays in the southern coast of Korea, linear regression lines between compression index and natural water content, void ratio in situ, and liquid limit respectively wer obtained. The changed properties of soil due to disturbance during dredging and reclaiming could be investigated by comparing with the existing empirical correlation equations for the original ground where dredging was performed. These regression equations might be rationally used in the preliminary evaluation of settlement of dredged and reclaimed marine clayey ground in the southern coast of Korea.