• Journal of the Economic Geographical Society of Korea
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• v.18 no.3
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• pp.335-347
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• 2015

Music industry is considered as a creative industry, which tends to locate within a city. However, there is very few paper analysing spatial patterns of music industry in Korea. This study aims to understand music industry's value chain and its location pattern; whether it is clustered or dispersed. In detail, music industry contains five sub-industry: planning, manufacturing, distribution, sales and performance. Locational pattern of each sub-industry is tested by GIS and hot spot analysis. There are several findings from this research. First, value chain of music industry make clusters and have a spatial autocorrelation. Second, the result shows that music industry makes a hotspot area at Gangnam, Guro, Mapo and Jongro-Junggu.

• Journal of Environmental Health Sciences
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• v.41 no.2
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• pp.90-101
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• 2015

Objective: This study was conducted to develop a chemical oxygen demand (COD) regression model using water quality monitoring data (January, 2014) obtained from the Han River auto-monitoring stations. Methods: Surface water quality data at 198 sampling stations along the six major areas were assembled and analyzed to determine the spatial distribution and clustering of monitoring stations based on 18 WQPs and regression modeling using selected parameters. Statistical techniques, including combined genetic algorithm-multiple linear regression (GA-MLR), cluster analysis (CA) and principal component analysis (PCA) were used to build a COD model using water quality data. Results: A best GA-MLR model facilitated computing the WQPs for a 5-descriptor COD model with satisfactory statistical results ($r^2=92.64$,$Q{^2}_{LOO}=91.45$,$Q{^2}_{Ext}=88.17$). This approach includes variable selection of the WQPs in order to find the most important factors affecting water quality. Additionally, ordination techniques like PCA and CA were used to classify monitoring stations. The biplot based on the first two principal components (PCs) of the PCA model identified three distinct groups of stations, but also differs with respect to the correlation with WQPs, which enables better interpretation of the water quality characteristics at particular stations as of January 2014. Conclusion: This data analysis procedure appears to provide an efficient means of modelling water quality by interpreting and defining its most essential variables, such as TOC and BOD. The water parameters selected in a COD model as most important in contributing to environmental health and water pollution can be utilized for the application of water quality management strategies. At present, the river is under threat of anthropogenic disturbances during festival periods, especially at upstream areas.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.435-444
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• 2013

ATSC terrestrial DTV system can support high data rates for HDTV(High Definition Television) service, but it suffers from significant performance degradation caused by multipath fading. Thus, it is necessary to analyze multipath fading effects in order to enhance the DTV reception performance. Generally, DTV channel profile can be obtained by auto-correlation between reference pseudo random signal and received DTV signal. However, in the ATSC terrestrial DTV system, the estimation performance of DTV channel profile may be decreased due to the VSB modulation features. In this paper, improved DTV channel profile measurement technique is analyzed and proposed.

• Archives of Plastic Surgery
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• v.35 no.3
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• pp.303-308
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• 2008

Purpose: The purpose of this study is to develop three-dimensional computerized anthropometry(3DCA) and to compare its reliability and accuracy 3DCA with manual anthropometry(MA) for measurement of lips and nasal deformities in unilateral cleft lips and palate(UCLP) patients. Methods: Samples were consisted of six UCLP patients whose facial plaster models were available immediately before and 3 months after the cleft lip surgery. MA of the facial plaster models was carried out using an electronic caliper. In 3DCA, three-dimensional auto-measuring program was used to digitize landmarks and to measure three-dimensional virtual facial models (3DVFM), which was generated with a laser scanner and 3D virtual modeling program. Intraclass correlation coefficients(ICC) were calculated to evaluate reliability and reproducibility of the variables in both methods, and Wilcoxon's signed rank test was done to investigate the difference in values of the same variables of facial models of each patient between two methods. Results: All ICC values were higher than 0.8, so both methods could be considered reliable. Although most variables showed statistical differences between two methods(p<0.05), differences between mean values were very small and could be considered not significant in clinical situation. Conclusion: In clinical situation, 3DCA can be an objective, reliable and accurate tool for evaluation of lips and nasal deformities in the cleft patients.

• Water for future
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• v.15 no.3
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• pp.23-36
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• 1982

The stochastic variations and structures of time series data on water quality were examined by employing the techniques of autocorrelation function, variance spectrum, Fourier series, autoregressive model and ARIMA model. These time series included hourly and daily observation on DO, turbidity, conductivity pH and water temperature. The measurement was made by automatic recording instrument at Noryangjin and Dook-do located in the downstream part of Han River during 1975 and 1976. Hourly water quality time series varied with the dominant 24-hour periodicity, and the 12-hour periodicity was also observed. An important factor affecting 24-hour periodic variation of DO is believed to be photosynthesis by algae. These phenomena might be attributable to periodic discharges of municipal sewage. Noryangjin site showed the more distinct 12-hour periodicity than Dook-do site did, and tidal effect might be responsible for the difference. The water quality, as measured by DO and turbidity, was better in the afternoon compared with the quality in the morning. This change can be explained by the periodic variation of DO, temperature and the amount of municipal wewage discharge. It was also observed that the water temperature at Noryangjin was higher than the temperature at Dook-do. This difference might have been caused by the pollutants that were added to the section between two sites. The correlation coefficients between some of the variables were fairly high. For example, the coefficient was -0.88 between DO and water temperature, 0.75 between turbidity and river flow, and 0.957 between water temperature and air temperature. The lag time of heat transfer from the air to the water was estimated as 24 days. The first order auto-regressive model was appropriate for explaning standardized hourly DO time series. The ARIMA model of (1, 0, 0) type provided relatively satisfactory results for daily DO time series after the removal of significant harmonic value.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.3
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• pp.233-238
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• 2001

This paper deals with demand forecasting of parts in an automobile model which has been extinct. It is important to estimate how much inventory of each part in the extinct model should be stocked because production lines of some parts may be replaced by new ones although there is still demands for the model. Furthermore, in some countries, there is a strong regulation that the automobile manufacturing company should provide customers with auto parts for several years whenever they are requested. The major characteristic of automobile parts demand forecasting is that there exists a close correlation between the number of running cars and the demand of each part. In this sense, the total demand of each part in a year is determined by two factors, the total number of running cars in that year and the failure rate of the part. The total number of running cars in year k can be estimated sequentially by the amount of shipped cars and proportion of discarded cars in years 1, 2,$\cdots$, i. However, it is very difficult to estimate the failure rate of each part because available inter-failure time data is not complete. The failure rate is, therefore, determined so as to minimize the mean squared error between the estimated demand and the observed demand of a part in years 1, 2,$\cdots$, i. In this paper, data obtained from a Korean automobile manufacturing company are used to illustrate our model.

• Journal of Korean Ophthalmic Optics Society
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• v.18 no.2
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• pp.173-178
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• 2013

Purpose: This study is to predict refractive errors according to uncorrected visual acuity using uncorrected visual acuity of the first glasses wearers. Methods: For 886 children who visited an ophthalmic clinic, subjective refraction was carried out with maintain refraction (MR) and cycloplegic refraction (CR), and objective refraction was carried out using auto-refractometer. Uncorrected visual acuity and corrected visual acuity were tested using on a trial lens and a Han's visual acuity chart. Results: In correlation between with the uncorrected visual acuity and refractive the myopia was the highest (r=0.774) and followed by hyperopia (r=0.670), simple astigmatism (r=0.623), simple with-the-rule astigmatism (r=0.604)and simple against-the-rule astigmatism (r=0.508). Conclusions: There were differences in the predictions between uncorrected visual acuity and refractive error according to the types of refractive error and astigmatism.

• The Journal of Industrial Distribution & Business
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• v.10 no.9
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• pp.53-60
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• 2019

Purpose - The objective of this paper is to discover if there exists a relationship between the economic index and distribution industry index in Korean. Because of the distribution industry boom in the recent years, a lot of interest in the relationship between the economic index and distribution industry index in Korean and the economy has been generated. This article examine on the mutual influence between economic index and distribution industry index in Korean. Research design, data, and methodology - For this purpose, we use the vector-auto regression model, impulse response function and variance decomposition of the economic index and distribution industry index, Granger causality test using weekly data on the economic index and distribution industry price index in korea. The sample period is covering from January 2, 2010 to August 31, 2019. The VAR model can also be linked to cointegration analysis. Cointegration Analysis makes possible to find a mechanism causing x and y to move around a long-run equilibrium (Engle and Granger, 1987). This equilibrium means that external shocks may separate the series temporarily at any particular time, but there will be an overall tendency towards some type of long-run equilibrium. If variables are found to have this tendency they are said to be cointegrated and a long-run relationship between these series is established. These econometric tools have been applied widely into economics and business areas to analyze intertemporal linkages between different time series. Results - This research showed following main results. First, from the basic statistic analysis of the economic index and distribution industry index in Korean, the economic index and the distribution industry index in korea have unit roots. Second, there is at least one cointegration between the economic index and distribution industry index in Korean. Finally, the correlation between of the economic index and the distribution industry index in korea is (+) 0.528876. Conclusions - We find that the distribution industry price index Granger cause the economic index in korea. As a consequence, the distribution industry index affect the economic index in Korean. The distribution industry index to the economic index is stronger than that from the economic index to the distribution industry index.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11A
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• pp.1079-1086
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• 2008

In this paper, we propose a Cyclic-Prefix Code Division Multiple Access system that uses Sequences with Good Autocorrelation property(GAS-CP-CDMA) and analyze the uplink signal-to-noise ratio performance of that system. Phase-shifted sequences are used for differentiating users. The signals of the GAS-CP-CDMA system experience no (or very little) interferences from co-cell signals because of the good autocorrelation property, but user signals of adjacent cells may yield interferences. The frequency reuse factor in the ordinary CDMA system is around 0.6 and the interference from adjacent cells is about 40 percent of the total interference in the conventional CDMA system. Our numerical analysis shows that the frequency reuse factor and user capacity versus signal-to-noise ratio of the GAS-CP-CDMA system are improved comparing to the conventional CDMA system. The uplink user capacity of the proposed system can be increased up to about twice of that of the conventional CDMA system.

• Journal of Korean Society of Water and Wastewater
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• v.21 no.5
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• pp.601-607
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• 2007

In order to maintain constant residual chlorine in sedimentation basin, It is necessary to develop real time prediction model of residual chlorine considering water treatment plant data such as water qualities, weather, and plant operation conditions. Based on the operation data acquired from K water treatment plant, prediction models of residual chlorine in sediment basin were accomplished. The input parameters applied in the models were water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage. The multiple regression models were established with linear and non-linear model with 5,448 data set. The corelation coefficient (R) for the linear and non-linear model were 0.39 and 0.374, respectively. It shows low correlation coefficient, that is, these multiple regression models can not represent the residual chlorine with the input parameters which varies independently with time changes related to weather condition. Artificial neural network models are applied with three different conditions. Input parameters are consisted of water quality data observed in water treatment process based on the structure of auto-regressive model type, considering a time lag. The artificial neural network models have better ability to predict residual chlorine at sediment basin than conventional linear and nonlinear multi-regression models. The determination coefficients of each model in verification process were shown as 0.742, 0.754, and 0.869, respectively. Consequently, comparing the results of each model, neural network can simulate the residual chlorine in sedimentation basin better than mathematical regression models in terms of prediction performance. This results are expected to contribute into automation control of water treatment processes.