• Anxiety and mood
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• v.16 no.2
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• pp.57-75
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• 2020

Particular matter is steadily increasing due to environmental factors at domestic and abroad such as industry and economy. Recently, the exposure particular matters has been reported to increase the risk not only for morbidity and mortality, but also for diseases of the respiratory system, cardiovascular system and central nervous system/neuropsychiatric disorder. Although the causes of neuropsychiatric diseases are genetic and environmental factors, it is necessary to pay more attention to environmental factors in terms of prevention. We mainly describe environmental factors that affect neuropsychiatric disorders, mainly on particular matter, which is one of harmful environmental substances. In the current study, we reviewed evidence for the presence of particular matter or particular matter related harmful air pollutants-O₃, SO₂, NO₂/NOx, traffic related air pollution, that may represent risk factors for the development of neuropsychiatric disorder.

• Health Policy and Management
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• v.30 no.1
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• pp.50-61
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• 2020

Background: This study aims to analyze the effects of air pollutants, such as particular matter, to the number of outpatient visits for allergic rhinitis in eup, myeon, and dong administrative boundaries. Methods: Dependent variable was the number of outpatient visits for allergic rhinitis per 10,000 people by region. Independent variables were air pollutants such as PM₁₀, PM_2.5, SO₂, O₃, CO₂, NO₂, and temperature that estimated by using Kriging analysis in all eup, myeon, and dong boundaries. Panel analysis was applied for the analysis to prove the relation between outpatient visits and the concentration of air pollutants. Results: Analysis results showed that particular matter concentration varied by regions and season. Panel analysis showed that outpatient visits for allergic rhinitis had positive relationships with PM₁₀, PM_2.5, SO₂, O₃, and CO₂ in all panel models. Conclusion: Regional variation of particular matter concentration should be considered in establishing regional policies for allergic rhinitis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.277-279
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• 2021

There is a problem that learning of a prediction model is not well performed depending on the characteristics of each particular matter concentration. To solve this problem, it is necessary to design a prediction model for low concentration and high concentration separately. Therefore, a classification model is needed to classify the concentration of particular matter into low and high concentrations. This paper proposes a classification model to classify low and high concentrations based on the concentration of particular matter. DNN was used as the classification model algorithm, and the classification model was designed by applying the optimal parameters after searching for hyper parameters. As for the result of evaluating the performance of the model, 97.54% of the low concentration classification was measured. And in the case of high concentration classification, 85.51% was measured.

• Membrane and Water Treatment
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• v.13 no.1
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• pp.29-37
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• 2022

To verify the fate and transport of engineered nanoparticles (ENP), it is essential to understand its interactions with organic matter. Previous research has shown that dissolved organic matter (DOM) can increase particle stability through steric repulsion. However, the majority of the research has been focused on model organic matter such as humic or fulvic acids, lacking the understanding of organic matter found in field conditions. In the current study, organic matter was sampled from wastewater treatment plants to verify the stability of engineered nanoparticles (ENP) under field conditions. To understand how different types of organic matter may affect the fate of ENP, wastewater was sampled and separated based on their size; as small organic particular matter (SOPM) and large organic particular matter (LOPM), and dissolved organic matter (DOM). Each size fraction of organic matter was tested to verify their effects on nano-zinc oxide (nZnO) and nano-titanium oxide (nTiO₂) stability. For DOM, critical coagulation concentration (CCC) experiments were conducted, while sorption experiments were conducted for organic particulates. Results showed that under field conditions, the surface charge of the particles did not influence the stability. On the contrary, surface charge of the particles influenced the amount of sorption onto particulate forms of organic matter. Results of the current research show how the size of organic matter influences the fate and transport of different ENPs under field conditions.

• The Journal of Korean Medicine
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• v.44 no.3
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• pp.163-169
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• 2023

Objectives: This study aimed to review the experimental research trends in asthma caused by particulate matter to conduct further researches, especially in clinical trials. Methods: We searched for the meaningful literature using medicinal herb for asthma through the Pubmed databases. Results: Finally, six studies were finally selected. These studies showed recent trends, from 2018 to 2021 and conducted mostly in South Korea. The type of fine dust and the method of inducing asthma are different for each paper, but the effective mechanism is relatively common. It was commonly confirmed that the ratio and number of eosinophils, th2 cells and related cytokines are decreased in BALF and lung tissue by administration of medicinal herb. Conclusions: Although the method of inducing asthma using fine dust has not yet been standardized, it is thought that more meaningful evaluation results can be derived if a standardized animal model is established in the future. Nevertheless, based on the results that herbal medicine is effective for particular matter induced asthma, it is expected that it will be the basis for expanding into future clinical studies.

• Proceedings of KOSOMES biannual meeting
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• 2018.06a
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• pp.174-174
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• 2018

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.127-133
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• 2020

The international cancer research institute under the WHO designated fine dust as a first-class carcinogen. Particular matter refers to dust that is small enough to be invisible and floating in the air. Particular matter is mainly emitted from the combustion process of fossil fuels such as coal and oil, and is a risk factor that can cause lung disease, pneumonia, and heart disease. The Ministry of Environment recently analyzed the output data of 10 fine dust measuring stations and, as a result, announced that about 60% had an error that the existing atmospheric measurement concentration was higher. In order to accurately predict fine dust, the wind direction and measurement position must be corrected. In this paper, in order to solve these problems, fuzzy rules are used to solve these problems. In addition, in order to calculate the fine particulate sensation index actually felt by pedestrians on the street, a computer simulation experiment was conducted to calculate the fine particulate sensation index in consideration of weather conditions, temperature conditions, humidity conditions, and wind conditions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.280-282
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• 2021

A particular matter prediction model was designed using a deep learning algorithm to solve the problem of particular matter forecast with subjective judgment applied. RNN and LSTM were used among deep learning algorithms, and it was designed by applying optimal parameters by proceeding with hyperparametric navigation. The predicted performance of the two models was evaluated through RMSE and predicted accuracy. The performance assessment confirmed that there was no significant difference between the RMSE and accuracy, but there was a difference in the detailed forecast accuracy.

• Economic and Environmental Geology
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• v.21 no.3
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• pp.319-329
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• 1988

As a factor which can help to understand the genesis of (mata) sedimentary and/or hydrothermal uranium depisits, an interpretation of the role of organic matter associated with uranium mineralization, was attempted with the literature published up to the end of 1986. Laboratory studies, in which diageneis and metamorphism are artificially simulated, can help to elucidate how uranium with particular organic materials are formed and destroyed. Similarly, research involving a variety of techniques is needed to characterize both the soluble organic extracts (bitumen) and the insoluble organic matter (kerogen), separated from uranium ores and associated rocks. In the presence of clay minerals and amorphous oxy-hydroxde minerals, an understanding of the role of organic matter must be prudent and may require the incorporation of multidisciplinary approach (mineralogy, inorganic geochemistry ...).

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.41.2-41.2
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• 2018

The Minkowski Functionals of the matter densityeld, as traced by galaxies, contain information regarding the nature of dark energy and the fraction of dark matter in the Universe. In particular, the genus is a statistic that provides a clean measurement of the shape of the linear matter power spectrum. As the genus is a topological quantity, it is insensitive to galaxy bias and gravitational collapse. Furthermore, as it traces the linear matter power spectrum, it is a conserved quantity with redshift. Hence the genus amplitude is a standard population that can be used to test the distance-redshift relation. In this talk, I show how we can extract the genus from galaxy catalogs, and how we can use its properties to constrain the equation of state of dark energy and the energy content of the Universe.