• Korean Journal of Fisheries and Aquatic Sciences
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• v.35 no.4
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• pp.356-365
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• 2002

One of the most important factors that cause eutrophication is nutrient materials containing nitrogen and phosphorus which stem from excreation of terrestial sources and release from sediment. Therefore, to improve water quality, the reduction of these nutrients loads should be indispensible. At this study, the three-dimensional numerical hydrodynamic and ecosystem model, which was developed by Institute for Resources and Environment of Japan, were applied to analyze the processes affecting the eutrophication. The residual currents, which were obtained by integrating the simulated tidal currents over 1 tidal cycle, showed the presence of a typical counterclockwise eddies between Gyewha and Garyuk island. Density driven currents were generated westward at surface and eastward at the bottom in Saemankeum area where the fresh waters are flowing into, The ecosystem model was calibrated with the data surveyed in the field of the study area in annual average. The simulated results were fairly good coincided with the observed values within relative error of $30\%$. The simulations of DIN and DIP concentrations were performed using ecosystem model under the conditions of $40\~100\%$ pollution load reductions from pollution sources. In study area, concentration of DIN and DIP were reduced to $59\%$ and $28\%$ in case of the $80\%$ reduction of the input loads from fresh water respectively. But pollution loads from sediment had hardly affected DIN and DIP concentration, The $95\%$ input load abatement is necessary to meet the DIN and DIP concentration of second grade of ocean water quality criteria.

• Journal of Navigation and Port Research
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• v.33 no.1
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• pp.43-50
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• 2009

Recently, many maritime accidents have been increased and the collisions due to human error are given a great deal of proportions out of them We develop the Real-time Collision Risk Monitoring System (CRMS) for the navigational officers to cope with the emergency situation promptly and thus to reduce the probability of casualty. In this study, the risk of collision and grounding is evaluated by two kinds of method. The first method is based on Fuzzy algorithm, which evaluates the risk of collision between traffic ships. The second method is based on Environmental Stress (ES) Model, where the total risk of collision and grounding is evaluated by the environmental stress felt by human. The developed real-time CRMS has been installed to the ship handling simulator system and its capabilities have been tested through simulator experiments.

• Journal of dental hygiene science
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• v.24 no.1
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• pp.22-28
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• 2024

Background: Particulate matter (PM) has been extensively observed due to its negative association with human health. Previous research revealed the possible negative effect of air pollutant exposure on oral health. However, the predictive model between air pollutant exposure and the prevalence of periodontitis has not been observed yet. Therefore, this study aims to propose a predictive model for the number of patients with periodontitis exposed to PM and atmospheric factors in South Korea using deep learning. Methods: This study is a retrospective cohort study utilizing secondary data from the Korean Statistical Information Service and the Health Insurance Review and Assessment database for air pollution and the number of patients with periodontitis, respectively. Data from 2015 to 2022 were collected and consolidated every month, organized by region. Following data matching and management, the deep neural networks (DNN) model was applied, and the mean absolute percentage error (MAPE) value was calculated to ensure the accuracy of the model. Results: As we evaluated the DNN model with MAPE, the multivariate model of air pollution including exposure to PM_2.5, PM₁₀, and other atmospheric factors predict approximately 85% of the number of patients with periodontitis. The MAPE value ranged from 12.85 to 17.10 (mean±standard deviation=14.12±1.30), indicating a commendable level of accuracy. Conclusion: In this study, the predictive model for the number of patients with periodontitis is developed based on air pollution, including exposure to PM_2.5, PM₁₀, and other atmospheric factors. Additionally, various relevant factors are incorporated into the developed predictive model to elucidate specific causal relationships. It is anticipated that future research will lead to the development of a more accurate model for predicting the number of patients with periodontitis.

• Journal of Environmental Science International
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• v.10 no.1
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• pp.21-25
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• 2001

The Keum river has been utilized for drinking water supply of several city including Kunsan city and is deepening pollution state due to numerous municipal and industrial discharges. The concentration BOD in river is affected by the organic loading from a tributary and the algae biomass that largely happen to under eutrophication state. In the eutrophic water mass such as the Keum river, the autochthonous BOD was very important part for making a decision of water quality management, because it was accounted for majority of the total BOD. The predict of water quality has important meaning for management of water quality pollution of the Keum river. The purpose of this study will manage and predict water quality of the Keum river using QUAL-2E model considering the autochthonous BOD. The estimation of autochthonous BOD represented that the relationship between BOD and chlorophyll a. The regression equation was shown to be autochthonous BOD=$\beta$(sub)5$\times$chlorophyll a. The results of this study may be summarized as followed; The QUAL-2E model was calibrated with the data surveyed in the field of the study area in June, 1998. The calculated value by QUAL-2E model are in good agree to measured value within relative error of 7.80~20.33%. Especially, in the case of the considering autochthonous BOD, the calculated value of BOD were fairly good coincided with the observed values within relative error of 15%. But the case of not considering autochthonous BOD, relative error of BOD was shown to be 43.2%. In order to attain II grade of water quality standard in Puyo station which has a intake facility of water supply, we reduced to the pollutants loading of tributaries. In the case of removed 100% BOD of tributaries, the BOD of Puyo station was 4.07mg/$\ell$, belong to III grade of water quality standard. But in the case of removed 88% nutrient of tributaries, it was satisfied to II grade of water quality standard as below 3mg/$\ell$ of BOD. For estimation of autochthonous BOD in Keum river, we are performed simulating in accordance with reduction of nutrient load(50~100%) under conditions removal 90% organic load. Occupancy of autochthonous BOD according to nutrient loading reductions were varied from 25.97~79.51%. Occupancy of autochthonous BOD was shown to be a tendency to increasing in accordance with reduction of nutrient loading. Showing the above results, the nutrient that one of the growing factor of algae was important role in decision of BOD in the Keum river. For the water quality management of the Keum river, therefore, it is necessary to considering autochthonous BOD and to construction of advanced sewage treatment plant for nutrient removal.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.1
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• pp.89-97
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• 2007

Simple regression models for pollutants load estimation of paddy developed by the Ministry of Environment in 1995 were tested with the data (T-N, T-P, $COD_{Mn}$, and SS) collected from Yeongsan and Seomjin river watersheds, and improvement measures were suggested. Overall, the simulated values showed a great difference from the measured values except for T-P according to the statistical analyses (RMSE, root mean square error; RMAE, root mean absolute error; RB, relative bias; EI, efficiency index). Such difference was assumed due to the fact that the models use only hydrologic factors (quantity factor) associated with precipitation and run-off as input parameters, but do not consider other factors which are likely to affect pollutant concentration (quality factor) including days after fertilization. In addition, in terms of accessibility of the models, some parameters in the models such as run-off depth and run-off amount which can not be obtained from the weather database but should be collected by on-site measurements need to be replaced with other variables.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.06a
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• pp.16-19
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• 2011

In 2010 Manila Conference, the revised STCW (International Convention on Standards of Training, Certification and Watch-keeping for Seafarers) of IMO recalled that a large percentage of maritime casualties and pollution incidents are caused by human error. Therefore, education and training improvement will play important role to reduce maritime casualties. From this, we focus on improving safety during sailing through upgrading the education and training for Korean cadets by updating maritime education and training program. In terms of a maritime education program from some of the maritime universities in the world such as United States Merchant Maritime Academy(USMMA) Philippine Merchant Marine Academy(PMMA), are compared to the Maritime University in Korea. As a result, we suggest an effective education system.

• Journal of Environmental Science International
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• v.12 no.9
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• pp.957-966
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• 2003

Gunsan coastal area is one of region increasing pollution problems. To improve water quality, the reduction of these nutrients loads should be indispensible. In this study, the three-dimensional numerical hydrodynamic and ecosystem model were applied to analyze the processes affecting the eutrophication. In field survey, the average concentrations of dissolved inorganic nitrogen (DIN) and dissolved inorganic phosphorus(DIP) at surface waters were found to be 0.43mg/$\ell$ and 0.03mg/$\ell$ respectively, which were exceeding second grade of water quality criteria. In hydrodynamic modelling, the comparison between the simulated and observed tidal ellipses showed fairly good agreement. The ecosystem model was calibrated with the observed data in study area. The simulated results of DIN were fairly good coincided with the observed values within relative error of 32.39%, correlation coefficient(r) of 0.99. In the case of DIP, the simulated results were fairly good coincided with the observed values within relative error of 24.26%, correlation coefficient(r) of 0.82. The simulations of DIN and DIP concentrations using ecosystem model were performed under the conditions of 20∼80% reductions for pollutant loading. At simulation results, concentration of DIN and DIP were reduced to 20∼80% and under 10% in case of the 80% reduction of pollutant loading, respectively.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.137-149
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• 2019

Traffic emissions are the main cause of environmental pollution in cities and respiratory problems amongst people. This study developed a model based on an integration of support vector regression (SVR) algorithm and geographic information system (GIS) to map traffic carbon monoxide (CO) concentrations and produce prediction maps from micro level to macro level at a particular time gap in a day in a very densely populated area (Utara-Selatan Expressway-NKVE, Kuala Lumpur, Malaysia). The proposed model comprised two models: the first model was implemented to estimate traffic CO concentrations using the SVR model, and the second model was applied to create prediction maps at different times a day using the GIS approach. The parameters for analysis were collected from field survey and remote sensing data sources such as very-high-resolution aerial photos and light detection and ranging point clouds. The correlation coefficient was 0.97, the mean absolute error was 1.401 ppm and the root mean square error was 2.45 ppm. The proposed models can be effectively implemented as decision-making tools to find a suitable solution for mitigating traffic jams near tollgates, highways and road networks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1180-1186
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• 2020

One of the Embedded systems Tiny Processing Unit (TPU) usually acts in harsh environments like external shock or insufficient power. In these cases, data could be polluted, and cause critical problems. As a solution to data pollution, many embedded systems are using Error Correcting Code (ECC) to protect and restore data. However, ECC processing in TPU increases the overall processing time by increasing the time of instruction fetch which is the bottleneck. In this paper, we propose an architecture of parallelized ECC block to the reduce bottleneck of TPU. The proposed architecture results in the reduction of time 10% compared to the original model, although memory usage increased slightly. The test is evaluated with a matrix product that has various instructions. TPU with proposed parallelized ECC block shows 7% faster than the original TPU with ECC and was able to perform the proposed test accurately.

• Journal of the Ergonomics Society of Korea
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• v.30 no.1
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• pp.99-108
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• 2011

Almost all companies have paid much attention to the safety management ranging from maintenance to operation even at the stage of designing in order to prevent accidents, but fatal accidents continue to increase throughout the world. In particular, it is essential to systematically prevent such fatal accidents as fire, explosion or leakage of toxic gas at factories in order to not only protect the workers and neighbors but also prevent economic losses and environmental pollution. Though it is well known that accident probability is very low in NPP(Nuclear Power Plants), the reason why many researches are still being performed about the accidents is the results may be so severe. HRA is the main process to make preparation for possibility of human error in designing of the NPP. But those techniques have some problems and limitation as follows; the evaluation sensitivity of those techniques are out of date. And the evaluation of human error is not coupled with the design process. Additionally, the scope of the human error which has to be included in reliability assessment should be expanded. This work focuses on the coincidence of human error and mechanical failure for some important performance shaping factors to propose a method for improving safety effectively of the process industries. In order to apply in these purposes into the thesis, I found 63 critical Performance Shaping Factors of the eight dimensions throughout studies that I executed earlier. In this study, various analysis of opinion of specialists(Personal Factors, Training, Knowledge or Experience, Procedures and Documentation, Information, Communications, HMI, Workplace Design, Quality of Environment, Team Factors) and the guideline for construction of PSF were accomplished. The selected method was AHP which simplifies objective conclusions by maintaining consistency. This research focused on the implementation process of PSF to evaluate the process of PSF at each phase. As a result, we propose an evaluation model of PSF as a tool to find critical problem at each phase and improve on how to resolve the problems found at each phase. This evaluation model makes it possible to extraction of PSF succesfully by presenting the basis of assessment which will be used by enterprises to minimize the trial and error of construction process of PSF.