• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.4
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• pp.375-382
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• 2011

There is no system to obtain the basic data and proceed data and user input interface is complex, thus there are some limitation to utilize the oil spill prediction model. It is difficult to build the scientific response strategy in order to respond oil spill accident rapidly because it is impossible to operate the oil spill prediction model any time. In this study, the optimum operational system for oil spil prediction model has been developed considering the present system. External real time data has been linked because of impossibility of building all basic data and minimum database has been build in this study. Through this data system, real time oil spill prediction model can be utilized. And the user interface has been designed to reduce the error of the interface between user and model and the output interface has been proposed to analyze the result of modeling at multidimensional aspect. While the system for oil spill prediction model as the result of this study has some uncertainties because of depending on external data, the thing that we can predict oil spill using operate the model rapidly as soon as the accident occurred can be meaning in the response field.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.674-682
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• 2020

Recently, the problem of air pollution has become a global concern due to industrialization and overcrowding. Air pollution can cause various adverse effects on human health, among which respiratory diseases such as asthma, which have been of interest in this study, can be directly affected. Previous studies have used clinical data to identify how air pollutant affect diseases such as asthma based on relatively small samples. This is high likely to result in inconsistent results for each collection samples, and has significant limitations in that research is difficult for anyone other than the medical profession. In this study, the main focus was on predicting the actual asthmatic occurrence, based on data on the atmospheric environment data released by the government and the frequency of asthma outbreaks. First of all, this study verified the significant effects of each air pollutant with a time lag on the outbreak of asthma through the time-lag Pearson Correlation Coefficient. Second, train data built on the basis of verification results are utilized in Deep Learning algorithms, and models optimized for predicting the asthmatic occurrence are designed. The average error rate of the model was about 11.86%, indicating superior performance compared to other machine learning-based algorithms. The proposed model can be used for efficiency in the national insurance system and health budget management, and can also provide efficiency in the deployment and supply of medical personnel in hospitals. And it can also contribute to the promotion of national health through early warning of the risk of outbreak by atmospheric environment for chronic asthma patients.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.79-90
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• 2006

The partitioning level of a catchment becomes an issue if the calculated results from different levels show the same performance regardless of the levels. This study aims to identify the proper processing level of spatial resolution for the SWMM model application in an urban area. Using GIS overlaying technique, the division of subcatchments as a hydrologic similarity unit (HSU) is achieved with a comprehensive consideration of surface slope conditions, flow directions of storm sewers, and current land cover situation. Three surface-sewer alternatives are made on the basis of three different levels of surface divisions as well as the number of sewer connections and used as runoff simulation fields for the application of SWMM. As the result, it is found that the effect of a spatial resolution on the surface runoff results is not significant. On the other hand, the accumulated pollution load from an unit subcatchment, which is built by aggregation of several unit subcatchments consisting of various land cover conditions is reduced through the deterioration of surface spatial resolution. Although overall runoff pattern and accumulated runoff are little affected by spatial resolution, the simulated runoff from sewer outlet shows slight difference at the peak appearance time. The gap between surface pollution load accumulated and it discharged from the sewer outlet in a surface-sewer alternative during runoff period is monitored but the level of error is less than 5-10% except the lowest spatial resolution case.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.383-400
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• 2023

Air pollution-related diseases are escalating worldwide, with the World Health Organization (WHO) estimating approximately 7 million annual deaths in 2022. The rapid expansion of industrial facilities, increased emissions from various sources, and uncontrolled release of odorous substances have brought air pollution to the forefront of societal concerns. In South Korea, odor is categorized as an independent environmental pollutant, alongside air and water pollution, directly impacting the health of local residents by causing discomfort and aversion. However, the current odor management system in Korea remains inadequate, necessitating improvements. This study aims to enhance the odor management system by analyzing 1,010,749 data points collected from odor sensors located in Osong, Chungcheongbuk-do, using an Ensemble-Based Multi-Region Integrated Odor Concentration Prediction Model. The research results demonstrate that the model based on the XGBoost algorithm exhibited superior performance, with an RMSE of 0.0096, significantly outperforming the single-region model (0.0146) with a 51.9% reduction in mean error size. This underscores the potential for increasing data volume, improving accuracy, and enabling odor prediction in diverse regions using a unified model through the standardization of odor concentration data collected from various regions.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.639-643
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• 2001

Recently, photovoltaic system has been studied widely as a renewable energy system, because it does not produce environmental pollution and it has infinity energy source from the sun. A study on photovoltaic system has a lot of problems like as reappearance and repetition of some situation in the laboratory experiment for development of MPPT algorithm and islanding detection algorithm, because output characteristics of solar cell are varied by irradiation and surface temperature of solar cell. And this system is consisted a lot of solar cell unit. Therefore, the assistant equipment which emulates the solar cell characteristics which can be controlled arbitrarily by researcher is require to the researchers for reliable experimental data. In this paper, the virtual implement of solar cell (VISC) system is proposed to solve these problems and to achieve reliable experimental result on photovoltaic system. VISC system emulates the solar cell output characteristics, and this system can substitute solar cell in laboratory experiment system. To realize the VISC, mathematical model of solar cell is studied for driving converter and the DC/DC converters are compared in viewpoint of tracking error using computer simulation. And then analysis of parallel and series characteristics was done for combination of VISC model.

• Journal of Korean Society for Atmospheric Environment
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• v.17 no.4
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• pp.313-319
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• 2001

The development of ozone SRP (Standard Reference Photometer) designated as a G-7 project by the Korean Ministry of Environment began 1997 and is now nearly completed. With the completion of the ozone SRP we will not only acquire a qualification to participate in the international ozone calibration system but also enhance calibration credibility of ozone similarly to that of other ambient air pollution monitors. As the ozone SRP uses highly cleaned blank air that can be distinguished from general ozone analyzer, it is possible to reduce errors associated with the determination of ozone via elongation of the absorption length as long as 1 meter In addition, gas chopping method hat been adopted to cut down interference of other substances and time drift. Furthermore, the system has also been modified to minimize the strayed ultra-violet noise along the light path. In this paper, a new method for uncertainty evaluation has been introduced, which is guided by the ISO (International Standard Organization) GUM (Guide to the Expression of Uncertainty in Measurement) through assessments of the uncertainty type B (that was impossible to estimate before) as well as the uncertainty type A (based on statistics).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.10
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• pp.2766-2770
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• 2009

Recently, the Green IT is noticed because of the effects of greenhouse gas emissions, a drain on natural resources and pollution. In this paper, Visible Light Communication (VLC) systems with Turbo Coded scheme using LED is proposed and simulated in an optical wireless channel. As a forward error correction scheme to reduce information losses, turbo coding was employed. To decode the codewords, The Map (Maximum a Posteriori) algorism and SOVA (Soft Output Viterbi Algorithm) is used. The above mentioned schemes are described and simulation results are analyzed. As using turbo codes scheme, BER performance of proposed VLC systems is improved about 5 [dB].

• Journal of Korean Society on Water Environment
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• v.21 no.6
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• pp.549-563
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• 2005

The study was carried out to develop and standardize the analytical method of 1,4-dioxane in water. The National Institute of Environmental Research in Korea has monitored for 1,4-dioxane in water since 1998 and it has been detected in environmental water occasionally. But the environmental pollution and analytical method in water is not well known over the world. The trace analytical method at low-${\mu}/L$ level is prerequisite in order to evaluate the residue of 1,4-dioxane in water. Evaluation of the method was demonstrated by comparing and analyzing with liquid-liquid extraction, solid-phase extraction and purge & trap technique. As a result of experiment by standard solutions and raw samples, the precision and accuracy for three methods were obtained within error rate of about 10%. Therefore, three methods were standardized as official monitoring method in Korea. Also, a convenient and simple liquid-liquid extraction method for the analysis of 1,4-dioxane in water was developed by combined with gas chromatography/mass spectrometry and applied to the water samples in Korea

• Journal of Korean Society on Water Environment
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• v.30 no.3
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• pp.304-310
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• 2014

The conventional methods for total residual chlorine such as iodometry and DPD colorimetric can cause secondary pollution due to additional agents, also have a wide error range. As for alternative, electrochemical method can measure TRC(Total residual chlorine), and is not required as additional agents, also very suitable for using the fields of ballast water because test time is relatively fast. Therefore, this study was investigated for changing charge by agitation, salt concentration, and temperature change. Charge showed differences based on changes of reduction peak with or without agitation. In contrast, TRC and charge were well correlated in constant agitation speed. As TRC and charge were analyzed with high correlations in constant salinity and temperature of ocean, thereby conductivity was firstly measured, and charge had high correlation for TRC in spite of changing salinity and temperature Pt electrode revealed high reliability ($r^2=0.960$) because it was rarely effected by TRC, On the other hand, Au electrode appeared inadequate ($r^2=0.767$) to use sensor in less than 1.0 ppm of TRC. For high accuracy and detection of TRC, Pt and Au electrodes for test time were, respectively, 14 and 22 seconds. As a result, Pt electrode was more valuable than Au electrode in terms of response time.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.6
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• pp.738-748
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• 2005

Considering pollution source is transferred by discharge, it is very important to analyze the correlation between discharge and water quality. And temperature also influent to the water quality. In this paper, it is used water quality data that was measured DO (Dissolved Oxygen), TOC (Total Organic Carbon), TN (Total Nitrogen), TP (Total Phosphorus) at Dalchun real time monitoring stations in Namhan river. These characteristics were analyzed with the water quality of rainy and nonrainy periods. Input data of the water quality forecasting models that they were constructed by neural network and neuro-fuzzy was chosen as the reasonable data, and water quality forecasting models were applied. LMNN (Levenberg-Marquardt Neural Network), MDNN (MoDular Neural Network), and ANFIS (Adaptive Neuro-Fuzzy Inference System) models have achieved the highest overall accuracy of TOC data. LMNN and MDNN model which are applied for DO, TN, TP forecasting shows better results than ANFIS. MDNN model shows the lowest estimation error when using daily time, which is qualitative data trained with quantitative data. If some data has periodical properties, it seems effective using qualitative data to forecast.