• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.300-300
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• 2023

기후변화의 영향 중 하나인 무강우일수의 증가는 우리의 삶에 다양한 피해를 야기하고 있다. 영산강·섬진강권역은 2001년 이후 가장 심한 가뭄을 겪고 있으며, 이로 인해 하천의 건천화, 수질악화, 농업피해 등이 발생하고 있다. 무강우일수의 증가로 인한 피해는 농업지역에만 국한되지 않는다. 도시지역에 무강우가 지속될 경우 공기 중의 미세먼지가 효과적으로 제거되지 못하는 문제가 발생한다. 미세먼지로 인한 환경문제는 특정 배출지역에 국한되지 않고 기상조건에 따라 오염물질이 이동할 수 있으므로 타지역 및 타국가와의 갈등을 유발할 수 있다. 따라서, 정확한 분석을통해 원인을 규명하고 해결방안을 강구하는 것은 중요한 일이다. 이를 위해 본 연구에서는 먼저 한국환경공단에서 운영 중인 523개의 도시대기 측정소에서 관측된 PM₁₀ 시단위 자료를 이용하여 미세먼지의 추세를 분석하였다. 다음으로 미세먼지의 이동과 소멸과 연관성이 있을 것으로 판단되는 강우량, 습도, 풍속 등의 기상요소 및 무강우일수와 미세먼지 농도의 관련성을 분석하였다. 무강우일수는 전국에 분포된 103개 지상관측소의 시단위 강우자료를 통해 계산하였으며, 무강우일수와 미세먼지 농도의 관계는 각각의 무강우일수에 대응되는 미세먼지의 농도분포를 통해 년단위 및 월단위로 지역별로 분석하였다.

• Journal of the Korean earth science society
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• v.36 no.1
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• pp.125-135
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• 2015

The purpose of this study were to sample particulate matter and analyze its elements and microorganisms for secondary school science project. The particulate matter was sampled on the rooftop a four-store building at a university in Chungju province. A simplified capturing system was developed with the parts, motor-pump, innet, $1.0{\mu}m$ teflon filter, filter-holder, etc. Using the system, this study had sampled particulate matter during Dec., 2013-Jun., 2014. Then, this study analyzed the elements and microorganisms of the sampled particulate matter. Results have been shown that the particulate matter derived China urban area is mainly consisted of the artificial pollutant, such as Cu, Zn, Cd, Ni, Pb. In addition, this study has been shown that microorganisms, such as bacteria and fungi, are included in the particulate matter. Therefore, this study suggests a new systemic investigation and monitoring about the particulate matter, specially originated from China. Also, this study provides a sample for secondary school science experiment.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.281-290
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• 2018

Concerns regarding health problems due to fine dust have rapidly grown in Korea. However, studies on fine dust cognition, knowledge and attitudes were not performed actively. The purpose of this study is to examine college students' cognition, knowledge, and attitudes regarding fine dust in Korea, and to identify the relating factors including self efficacy on theses variables. This study was descriptive research, and 206 college students of 1 university were interviewed with a structured questionnaires. We found that the fine dust cognition score was the highest, and the knowledge and attitude scores were low among college student. According to the logistic regression analysis, grade, past respiratory disease, and self-efficacy were affecting fine dust cognition, and grade, self-efficacy were affecting fine dust knowledge. It is needed to provide educational program for college students to enhance the fine dust knowledge and attitude. It is necessary to include strategy increasing the self-efficacy to the education program.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.11a
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• pp.1435-1435
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• 2017

미세먼지 문제는 이미 우리 생활 속에서 국민들을 불안에 떨게 만드는 존재로 인식되고 있다. 미세먼지와 관련된 정책들을 부처에서 쏟아내고 있지만 법에 근거하지 않는 문제로 지속적인 저감 효과를 불러일으키기에는 부족하다는 평이다, 이에 미세먼지와 관련된 현행 법안들을 검토하여 본 문제에 대한 해결 방안을 제시하고자 한다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.429-430
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• 2022

본 논문에서는 일산화탄소 센서와 미세먼지 센서를 이용하여 연기농도에 따른 감도시험을 수행하였다. 일산화탄소 센서와 미세먼지 센서는 광전식감지기 감도시험 챔버 내에서 발생시킨 연기농도에 따라 감지반응이 있었으며, 다양한 화재정보를 제공을 위해 가스 센서 및 미세먼지 센서가 기술기준 도입이 필요할 것으로 사료된다.

• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.285-292
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• 2023

Recently, the impact of fine dust on health has become a major topic. Fine dust is dangerous because it can penetrate the body and affect the respiratory system, without being filtered out by the mucous membrane in the nose. Since fine dust is directly related to the industry, it is practically impossible to completely remove it. Therefore, if the concentration of fine dust can be predicted in advance, pre-emptive measures can be taken to minimize its impact on the human body. Fine dust can travel over 600km in a day, so it not only affects neighboring areas, but also distant regions. In this paper, wind direction and speed data and a time series prediction model were used to predict the concentration of fine dust in Seoul, and the correlation between the concentration of fine dust in Seoul and the concentration in each region was confirmed. In addition, predictions were made using the concentration of fine dust in each region and in Seoul. The lowest MAE (mean absolute error) in the prediction results was 12.13, which was about 15.17% better than the MAE of 14.3 presented in previous studies.

• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.45-55
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• 2020

Recently, as the awareness of fine dust has increased in Korea, various countermeasures have been suggested. This study examines the current status of fine dust free zones at home and abroad in order to analyze changes in guest space according to the occurrence of fine dust and to find activity patterns. I would like to predict and find implications. The purpose of this study is to forecast demand centering on domestic and foreign countermeasures for dust and domestic industry. In order to secure competitiveness for the smart city in the era of the 4th Industrial Revolution, the research is aimed at proposing a strategic plan to cope with the fine dust that is a threat to urban space. The research method is described in the following order.

• Proceedings of the KAIS Fall Conference
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• 2011.05a
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• pp.300-302
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• 2011

본 논문에서는 울산지역의 79개 고등학교 238개 교실을 대상으로 측정한 미세먼지($PM_{10}$)의 농도를 학교, 교실, 지역별로 평가하였다. 울산지역 고등학교 미세먼지($PM_{10}$)의 평균농도는 $63.8 \;{\mu}g/m^3$이었고 일반계가 $64.9 \;{\mu}g/m^3$으로 전문계 고등학교 미세먼지($PM_{10}$)의 평균농도에 비해 높게 나타났으며, 사립고등학교가 공립 고등학교 미세먼지($PM_{10}$)의 평균농도 보다 높았다. 또한, 남녀공학 교실의 미세먼지($PM_{10}$) 평균농도가 남고와 여고에 비해 높았으나 통계적인 유의성은 없었다. 학생들의 활동이 많은 일반교실의 평균 미세먼지($PM_{10}$) 농도가 특별실 보다 통계적으로 유의하게 높게 나타났고 유지기준 초과율도 특별실에 비해 약 2배 이상 높았다. 학년별로는 1학년 교실의 미세먼지($PM_{10}$) 농도가 2학년에 비해 통계적으로 유의하게 높았다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.623-625
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• 2018

As the issue of particulate matter spreads, services for providing particulate matter information in real time are increasing. However, when a sensor node for collecting particulate matter is defective, a corresponding service may not be provided. To solve these problems, it is necessary to predict and deduce particulate matter. In this paper, a particulate matter prediction model is designed using artificial neural network algorithm based on past particulate matter and meteorological data to predict particulate matter. Also, the prediction results are compared by learning the input data of the model in the design stage.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.540-542
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• 2019

With many announcements on air pollution and human effects from particulate matters, particulate matter forecasts are attracting a lot of public attention. As a result, various efforts have been made to increase the accuracy of particulate matter forecasting by using statistical modeling and machine learning technique. In this paper, the particulate matter AQI index prediction is performed using the multilayer perceptron neural network for particulate matter prediction. For this purpose, a prediction model is designed by using the meteorological factors and particulate matter concentration values commonly used in a number of studies, and the accuracy of the particulate matter AQI prediction is compared.