• Environmental Engineering Research
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• 제23권1호
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• pp.107-113
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• 2018

Air quality and pollution have recently become a major concern; vehicle emissions significantly pollute the air, especially in large and crowded cities. There are various factors that affect vehicle emissions; this research aims to find the most influential factors affecting $CO_2$ and $NO_x$ emissions using Adaptive Neural Fuzzy Inference System (ANFIS) as well as a systematic approach. The modified ANFIS (MANFIS) was developed to enhance modelling and Root Mean Square Error was used to evaluate the model performance. The results show that percentages of $CO_2$ from trucks represent the best input combination to model. While for $NO_x$ modelling, the best pair combination is the vehicle delay and percentage of heavy trucks. However, the final MANFIS structure involves two inputs, three membership functions and nine rules. For $CO_2$ modelling the triangular membership function is the best, while for $NO_x$ the membership function is two-sided Gaussian.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.468-471
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• 2005

The Air Quality Sensor(AQS), located near the fresh air inlet, serves to reduce the amount of pollution entering the vehicle cabin through the HVAC(heating, ventilating, and air conditioning) system by sending a signal to close the fresh air inlet door/ventilation flap when the vehicle enters a high pollution area. One chip sensor module which include above two sensing elements, humidity sensor and bad odor sensor was developed for AQS (air quality sensor) in automobile. With this sensor module, PIC microcontroller was designed with back propagation neural network to reduce detecting error when the motor vehicles pass through the dense fog area. The signal from neural network was modified to control the inlet of automobile and display the result or alarm the situation. One chip microcontroller, Atmega128L (ATmega Ltd., USA) was used. For the control and display. And our developed system can intelligently detect the bad odor when the motor vehicles pass through the polluted air zone such as cattle farm.

• 환경영향평가
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• 제18권1호
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• pp.31-39
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• 2009

A lot of data which are used in environment analysis of air pollution have characteristics that are distributed continuously in space. In this point, the collected data value such as precipitation, temperature, altitude, pollution density, PM10 have spatial aspect. When geostatistical data analysis are needed, acquisition of the value in every point is the best way, however, it is impossible because of the costs and time. Therefore, it is necessary to estimate the unknown values at unsampled locations based on observations. In this study, spatial interpolation method such as local trend surface model, IDW(inverse distance weighted), RBF(radial basis function), Kriging were applied to PM10 annual average concentration of Seoul in 2005 and the accuracy was evaluated. For evaluation of interpolation accuracy, range of estimated value, RMSE, average error were analyzed with observation data. The Kriging and RBF methods had the higher accuracy than others.

• 한국환경과학회지
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• 제27권12호
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• pp.1291-1298
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• 2018

Marine ecosystems are frequently exposed to a variety of chronic and acute pollutants derived from anthropogenic production and consumption activities. Mussels are sessile (can provide location-specific information), medium-sized (have enough tissue matrix for chemical analysis) filter-feeders (show accumulation of pollutant chemicals from seawater). These biological and ecological characteristics make mussels virtually ideal for pollution monitoring. In this study, Korean mussels (Mytilus coruscus) were collected from nine different sites situated along the coasts of the western sea to the eastern sea of Korea in 2017. Total mercury concentration was highest (mean ${\pm}$ standard error, $92.7{\pm}3.5ng/g\;dry$) on Baengnyeongdo Island in the western sea, and the sites in the southern sea showed the lowest mean concentrations (42.3 - 44.5 ng/g dry). These results were discussed in terms of possible pollution sources.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2010년도 춘계학술대회 논문집
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• pp.2048-2051
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• 2010

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. In addition, HRA may be used to detect the human errors which may cause accidents or trace back to any mistake on the part of workers. Usually, HRA technique is used in association with other risk assessment techniques. Moreover, it can serve to enumerate the human errors which may occur during operation or down-time or correct the existing system to reduce the mistakes. This work focuses on the coincidence of human error and mechanical failure for management of human error, and on some important performance shaping factors to propose a method for improving safety effectively of the process industries.

• 대한수학회논문집
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• 제16권3호
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• pp.385-397
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• 2001

Consider an inverse problem of determining of the 2-D temperature distribution from known temperature given at some time T>0. Our aim is to find the temperature for 0

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2004년도 추계학술대회
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• pp.73-80
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• 2004

최근 해난사고가 난로 증가되고 있으며, 특히, 인적과실로 인한 충돌사고의 비중은 $70\%$에 이르고 있다. 본 연구에서는 실시간 충돌위험도 표시 시스템을 개발함으로써, 충돌위험도를 사전에 인지함으로써 비상상황에 효과적으로 대처하고, 인적과실로 인한 충돌위험도를 줄이고자 하였다. 이를 위해 충돌위험도 추정에 있어, 2가지 방법을 비교 검토하였는데, 선박들 간에 충돌위험도를 평가하는 퍼지 알고리즘을 이용한 방법과 항해사가 느끼는 환경스트레스를 이용하여 충돌위험도를 평가하는 방법이다. 개발된 실시간 충돌위험도 표시 시스템을 검증하기 위해 선박운항 시뮬레이터에 설치하고 다양한 시뮬레이션을 수행하였다.

• 한국전자통신학회논문지
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• 제10권1호
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• pp.47-54
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• 2015

최근, 산업화와 도시화로 연료소비가 급격하게 증가하고, 주요 도시들의 대기오염이 심화됨에 따라 대기질 관리를 위해 대기확산모델의 이용 및 개발과 관련된 연구들이 다양하게 진행되고 있다. 본 연구에서는 국내에서 U.S. EPA가 제공하는 대기확산모델의 활용범위 확장을 목적으로 국내 기상자료를 미국 자료체계로의 변환기능과 모델입력용 기상자료의 생성이 가능한 "국내 기상자료 전처리 프로그램"을 개발하고, 사례연구에 적용을 통해서 프로그램의 활용성을 평가하였다. 평가 결과, 국내 기상자료를 미국 자료체계로 정확하게 변환처리하고, 대기질 모델링 과정에서 오류의 발생 없이 예측이 가능하여 향후 국내 기상자료 전처리 도구로 높은 활용성을 나타내었다.

• 한국물환경학회지
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• 제30권6호
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• pp.585-595
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• 2014

The temporal trends of the prioritized toxic water pollutants generated and discharged from the industrial facilities in the Geum-River basin, Korea were analyzed with the results of the nationwide Water Pollution Source Survey conducted in 2001 - 2012. The statistical results indicated rapid increase in the volume of raw toxic wastewaters whereas the amount of each toxic pollutant kept fluctuating for 12 years. Serious discrepancies in the survey data of the same type of industries demonstrated a low reliability of the survey result, which stemmed from several error factors. A unit-load for each type of industrial facility was devised to estimate the amount of prioritized toxic water pollutant based on the total volume of industrial wastewater generated from the same type of industrial facilities. The supplementary measures with an effective permit issuance policy and adding survey parameters of terminal wastewater treatment plants to use them as references to the Water Pollution Source Survey were suggested as means to minimize the errors associated with the false reports from the industries.

• 한국정보전자통신기술학회논문지
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• 제15권1호
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• pp.14-26
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• 2022

최근 대기환경오염의 심각성이 커짐에 따라 대기오염에 대한 관심도가 높아지고 있다. 본 논문에서 제안한 사물 인터넷 기반 미세먼지 모니터링 시스템은 대기환경오염 중 인체에 영향을 미치는 가장 큰 원인인 미세먼지, 휘발성 유기화합물, 이산화탄소 등을 측정하고 모니터링 할 수 있도록 하였다. 미세먼지 모니터링 시스템은 대기환경정보를 측정할 수 있는 측정 장치, 측정된 정보를 저장 및 분석할 수 있는 서버 시스템, 대기환경정보를 실시간으로 시각화 분석이 가능하도록 관리자용 통합 모니터링 관리 시스템과 사용자용 스마트 폰 애플리케이션으로 구성하여 하였다. 또한, 시스템의 응답속도, 센서 데이터의 전송속도, 센서의 측정오차를 이용하여 제안한 사물인터넷 기반 미세먼지 모니터링 시스템의 효율성을 검증하고자 하였다. 사물인터넷 기반 미세먼지 모니터링 시스템은 대기환경정보를 휴대용 미세먼지 측정 장치로 측정한 후 대기오염상태를 시각화함으로써 사용자의 편리성과 시스템의 효율성을 증대시킬 수 있을 것이라 기대한다.