• Magazine of the Korean Society of Agricultural Engineers
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• v.31 no.4
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• pp.111-122
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• 1989

A multiple box model which is suitable for the prediction of water quality in shallow lakes with active mixing is a water quality model expected to be used widely in estuary reservoir. In this study, a multiple box water quality model for estuary reservoirs (MBQER) was developed arid the applicability of the MBQER was tested by applying data obtained from Asan-estuary reservoir. The results of this study can be summarized as follows. 1. The MBQER, dynamic water quality model, was developed to estimate 10-day water qualities of estuary reservoirs. For the proper analysis and the application of hydraulics needed to build a model, lake hydraulics was simplified by condisering only hydrological inflow and lake mixing currents. The box division in the MBQER is longitudinal one dimension for upper and middle part, and two layers for lower part of the reservoir. 2. The methods of box division for the multiple box model were ekamined and applied to Asan-estuary reservoir. For determining the number of boxes, Pe number and Pk number were used. In case of three boxes, the error by the model simplification would be estimated about 5 % Therefore, in Asan reservoir, the proper number of boxes was three. 3. The MBQER was calibrated and verified using measured data in Asan-estuary reservoir from 1986 to 1988. The Root Mean Squares(RMS) for the differences between measured data and simulated results by the MBQER were 1.10$^{\circ}$C C for water temperature, 75.8mg/1 for salinity, 0.082mg/1 for total-phosphorus showing good estimations. 4. Through the simulation of water temperature and salinity by the MBQER, the exchange flow and the mixing coefficients for the estuary lake were determined. As a result of simulation, the horizontal mixing coefficients in Asan-estuary reservoir were in the range of 1.07X 105 to 1.12X 105 cm$^2$/sec and vertical mixing coefficient was 2.90X 10-1 cm$^2$/sec.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1101-1106
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• 2005

The purpose of this study was to develop a process management system to manage ingot fabrication and the quality of the ingot. The ingot is the first manufactured material of wafers. Operating data (trace parameters) were collected on-line but quality data (measurement parameters) were measured by sampling inspection. The quality parameters were applied to evaluate the quality. Thus, preprocessing was necessary to extract useful information from the quality data. First, statistical methods were employed for data generation, and then modeling was accomplished, using the generated data, to improve the performance of the models. The function of the models is to predict the quality corresponding to the control parameters. The dynamic polynomial neural network (DPNN) was used for data modeling that used the ingot fabrication data.

• Journal of Environmental Health Sciences
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• v.17 no.2
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• pp.1-8
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• 1991

The stochastic variance and structures of time series data on air quality were examined by employing the techniques of autocorrelation function, variance spectrum, fourier series, ARIMA model. Among the air quality properties of atmosphere, SO$_{2}$ is one of the most siginificant and widely measured parameters. In the study, the air quality data were included hourly observations on SO$_{2}$ TSP and O$_{3}$. The data were measured by automatic recording instrument installed in Kwanghwamoon during February and March in 1991. The results of study were as follows 1. Hourly air quality series varied with the domiant 24 hour periodicity and the 12 hour periodic variation was also observed. 2. The correlation coefficients between SO$_{2}$ and O$_{3}$ is -0.4735. 3. In simulating or forecasting variation in SO$_{2}$ ARIMA models are on a useful tools. The multiplicative seasonal ARIMA (1, 1, 0) (0, 2, 1)$_{24}$ model provided satisfactory results for hourly SO$_{2}$ time series.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.66-72
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• 2009

In order to forecast the progress of the track irregularity, we should observe the long-term track quality and divide a track into some separated divisions which have homogeneous property. For this, we define the division of track which has homogeneous property as a 'Segment' and manage the 'TQI(Track Quality Index)' using track induction data based on each segment. In this study, we introduce some methods of estimating track quality and figure out the TQIs of sample section using new FRA TQI method. In addition, we conducted a basic study of the forecasting model for the progress of track irregularity by analyzing track maintenance data.

• Journal of Korea Multimedia Society
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• v.22 no.10
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• pp.1187-1198
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• 2019

In this study, we propose a new $PM_{10}$ forecasting model for Seoul region using DNN(Deep Neural Network) and secondary data. The previous numerical and Julian forecast model have been developed using primary data such as weather and air quality measurements. These models give excellent results for accuracy and false alarms, but POD is not good for the daily life usage. To solve this problem, we develop four secondary factors composed with primary data, which reflect the correlations between primary factors and high $PM_{10}$ concentrations. The proposed 4 models are A(Anomaly), BT(Back trajectory), CB(Contribution), CS(Cosine similarity), and ALL(model using all 4 secondary data). Among them, model ALL shows the best performance in all indicators, especially the PODs are improved.

• Journal of Korea Water Resources Association
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• v.45 no.7
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• pp.685-696
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• 2012

EFDC model, which is capable of handling both hydrodynamic and water quality analysis has come to use for many recent studies. In order to assess the applicability of the EFDC model, it was applied to Nakdong river. Hydrodynamic and water quality analysis were carried out for Nakbon GH and HI sections chosen as the area of study with gaged data from 2008 to 2009. The comparison was made between water quality simulation results and observed data over water temperature, COD, TOC, DO, TN and TP. On the contrary, a conversion formula was derived to calculate BOD which the EFDC model cannot directly calculates and it was compared to measured data. In this study, it was determined that the EFDC model well represents the behavior of both hydrodynamics and water quality. However, further research on COD, TOC and accurate conversion of BOD needs to be conducted for efficient application to domestic water quality analysis.

• International Journal of Quality Innovation
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• v.6 no.3
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• pp.70-94
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• 2005

The IC packaging industry heavily relies on shop floor information, necessitating the development of a model to flexibly define shop floor information and timely handle manufacturing data. This study presents a novel data model of product manufacturing flow to define shop floor information to effectively respond to accelerated developments in IC package industry. The proposed data model consists of four modules: operation template setup, general process setup, enhanced bill of manufacture (EBOMfr) setup, and work-order process setup. The data model can flexibly define the required shop floor information and decision rules for shop floor product manufacturing flow, allowing one to easily adopt changes of the product and on the shop floor. However, to handle floor dynamics of the IC packaging industry, this work also proposes a WIP (i.e. work-in-process) system for monitoring and controlling the product manufacturing flow on the shop floor. The WIP system integrates the data model with a WIP execution module. Furthermore, an illustrative example, the MIRL WIP System, developed by Mechanical Industrial Research Laboratories of Industrial Technology Research Institute, demonstrates the effectiveness of the proposed model.

• Research in Community and Public Health Nursing
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• v.24 no.3
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• pp.302-313
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• 2013

Purpose: The purpose of this study was to identify factors in quality of life and to construct a model of quality of life in longevity region dwelling elders. Methods: Data were collected from January to July, 2010 through direct interviews and a self-reporting questionnaire survey with 171 subjects who were living at the S County (gun). The collected data were analyzed by using the SPSS/WIN 19.0 and AMOS 19.0 programs. Results: Economic status, social support, health behavior and depression were shown to have direct and total effects on quality of life and were statistically significant. Health status had indirect and total effects on quality of life and was statistically significant. And, self-efficacy had direct, indirect and total effects on quality of life and was statistically significant. These variables of the hypothetical model accounted for 41.4% of quality of life. Conclusion: In order to improve quality of life in longevity region dwelling elders, it is necessary to provide economic support and social support services in tandem with social welfare. And, we need to apply interventions strengthening self-efficacy, health behavior, and health status, and decreasing depression.

• Environmental Engineering Research
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• v.14 no.4
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• pp.200-210
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• 2009

The modern era of water quality modeling in the United States began in the 1960s. Pushed by advances in computer technology as well as environmental sciences, water quality modeling evolved through five broad periods: (1) initial model development with mainframe computers (1960s - mid 1970s), (2) model refinement and generalization with minicomputers (mid 1970s - mid 1980s), (3) model standardization and support with microcomputers (mid 1980s - mid 1990s), (4) better model access and performance with faster desktop computers running Windows and local area networks linked to the Internet (mid 1990s - early 2000s), and (5) model integration and widespread use of the Internet (early 2000s - present). Improved computer technology continues to drive improvements in water quality models, including more detailed environmental analysis (spatially and temporally), better user interfaces and GIS software, more accessibility to environmental data from on-line repositories, and more robust modeling frameworks linking hydrodynamics, water quality, watershed and atmospheric models. Driven by regulatory needs and advancing technology, water quality modeling will continue to improve to better address more complicated water bodies and pollutant types, and more complicated management questions. This manuscript describes historical trends in water quality model development in the United States, reviews current efforts, and projects promising future directions.

• Water for future
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• v.17 no.1
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• pp.31-36
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• 1984

This study has performed to investigate and evaluate the simulation model of steam Water Quality and the simulated results have 매내 been compared with the observed data in the Han River. The predicted BOD, Total-N, Coliform concentrations in the downstream of the Chungrang-Cheon are 8.6m/1, 4.5mg/1 and $3.7X10^5$ respectively. It is interesting to note that the results simulated based on the WQRRS model are extremely in good agreement and also are very much comparable with those observed data reported previously references.