• Journal of Environmental Science International
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• v.24 no.7
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• pp.961-968
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• 2015

The production of highly concentrated $PM_{10}$ is in the spotlight as a social issue, and it increases the attack rate of Asthma. This study aimed to analyze the characteristics of concentration and distribution for $PM_{10}$ from 2000 to 2011, and investigate its correlation with the death from Asthma. Furthermore, this study was designed to analyze it by dividing into two cases like including Asian dust and excluding Asian dust because it presented the high concentration when Asian dust was occurred in the spring. This study has found that the annual average concentration distribution of $PM_{10}$ in Seoul was higher in the central area than the peripheral area. The annual average concentration of $PM_{10}$ and death from asthma displayed the tendency to gradually decrease. The correlation coefficient for all period was 0.92(p=0.000), and the correlation was 0.84(p=0.001) in case of remove Asian dust. The monthly average concentration of $PM_{10}$ has increased in the winter and decreased in the summer. The death from Asthma and correlation coefficient for all period was 0.588(p=0.044) and 0.640(p=0.025) in case of removing Asian dust. Although the causes of Asthma had a great diversity, the similar tendency by a factor of $PM_{10}$ meant that the correlation was high.

• Journal of Sensor Science and Technology
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• v.29 no.3
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• pp.211-214
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• 2020

Chlorine dioxide is very effective gas for sterilization or disinfection (in manufacturing), and does not produce harmful by-products after use. However, if its concentration exceeds 10 %, it become explosive and cannot be compressed or stored. Therefore, it is necessary to measure its concentration. In this study, the concentration of chlorine dioxide with a high oxidizing strength was measured using a metal oxide sensor. The sensor was a commercially available TGS series from Figaro. The sensitivity of the sensor was inversely proportional to a low concentration of chlorine dioxide gas below 6 ppm and returned to the initial resistance at about 6 ppm. When the gas concentration reached multiples of 10 ppm, resistance of the sensor increased to several megaohms.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.143-143
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• 2008

Nanowires are promising options for building nanoscale electronic structures coming from high conductivity of nanowires. In particular, Deoxyribonucleic acid (DNA), which is structurally nanowire, can obtain highly ordered electronic components for nanocircuitry and/or nanodevices because of its very flexible length controllability, nanometer-size diameter, about 2 nm, and self-assembling properties. In this work, we used the method to form DNA-Nanowires (NWs) by using chemical treatment on Silicon (Si) surface, and Aminopropyl-triethoxysilane (APTES) was used as inducer of DNA sequence to modify the characteristics of Si surface. Moreover, we performed tilting technique to align DNA by the direction of flow of DNA solution. We investigated the assembly process between DNA molecules and APTES - coated Si surface according to the APTES concentration, from $1.2{\mu}\ell$ to $120{\mu}\ell$. Atomic Force Microscopy (AFM) images showed the combination rate of DNA molecules by the change of APTES concentration. As APTES concentration becomes thicker, aggregation of DNA molecules occurs, and this makes a kind of DNA networks. In this respect, we confirmed that there's a positive relationship between the concentration of APTES and the formation rate of DNA nanowires. Since there have been lots of research preceded to utilize DNA nanowires as template, so by using this positive relationship with proper alignment technique, realization of nano electronic devices with DNA nanowires might be feasible.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.345-347
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• 2021

Various studies are being conducted to improve the accuracy of fine dust, but there is a problem that deep learning models are not well learned due to various characteristics according to the concentration of fine dust. This paper proposes an EEMD-based fine dust concentration prediction model to decompose the characteristics of fine dust concentration and reflect the characteristics. After decomposing the fine dust concentration through EEMD, the final fine dust concentration value is derived by ensemble of the prediction results according to the characteristics derived from each. As a result of the model's performance evaluation, 91.7% of the fine dust concentration prediction accuracy was confirmed.

• Journal of the Korean housing association
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• v.26 no.4
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• pp.55-62
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• 2015

The international concern on the inhalable fine dust is continuing to increase. In addition to the toxic properties of the fine dust itself, it can be more dangerous than other environmental factors since the dust pollution is hard to be detected by human sense. Although the information on outdoor air condition can be acquired easily, the indoor dust concentration is another problem because the indoor air condition is influenced by the architectural environment and human activity. It means occupants may be exposed to indoor dust pollution over a long period without being aware. Therefore the indoor dust concentration should be measured separately and visualized as an intuitive information. By visualizing, the indoor dust concentration in each space can be recognized practically in compare with the degree of pollution in adjacent spaces. Besides the visualization outcome can be used as base data for related research such as an analysis of the relation between indoor dust concentration and architectural environment. Meanwhile, with the development of network and micro sensing devices, it became possible to collect wide range of indoor environment data. In this regards, this paper suggests a system for visualization of indoor dust concentration and demonstrates it on an actual space.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.67-75
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• 2022

Recently, e-learning has been attracting significant attention due to COVID-19. However, while e-learning has many advantages, it has disadvantages as well. One of the main disadvantages of e-learning is that it is difficult for teachers to continuously and systematically monitor learners. Although services such as personalized e-learning are provided to compensate for the shortcoming, systematic monitoring of learners' concentration is insufficient. This study suggests a method to evaluate the learner's concentration by applying machine learning techniques. In this study, emotion and gaze data were extracted from 184 videos of 92 participants. First, the learners' concentration was labeled by experts. Then, statistical-based status indicators were preprocessed from the data. Random Forests (RF), Support Vector Machines (SVMs), Multilayer Perceptron (MLP), and an ensemble model have been used in the experiment. Long Short-Term Memory (LSTM) has also been used for comparison. As a result, it was possible to predict e-learners' concentration with an accuracy of 90.54%. This study is expected to improve learners' immersion by providing a customized educational curriculum according to the learner's concentration level.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.368-368
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• 2000

In this paper, we present forecasting ozone concentration with decision support system. Since the mechanism of ozone concentration is highly complex, nonlinear, and nonstationary, modeling of ozone prediction system has many problems and results of prediction are not good performance so far. Forecasting ozone concentration with decision support system is acquired to information from human knowledge and experiment data. Fuzzy clustering method uses the acquisition and dynamic polynomial neural network gives us a good performance for ozone prediction with ability of superior data approximation and self-organization.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.6
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• pp.585-592
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• 2015

In this study, by applying mobile based GIS and image analysis of particulate matter ($PM_{10}$) concentration in Seoul and Ulsan in Korea, to identify the user's location and also implemented the application to information exchange. It strengthened citizens' access to air quality information through the application and derived the expanded environment information sharing through real-time user participation. Through atmospheric concentrations image analysis, it showed a new environmental information construction possibility. It had the effect of expanding the information collecting through the local user participation on the limited information collected area which place is not yet constructed atmospheric monitoring network. Location-based particulate matter information service application provides a user location's $PM_{10}$ information from the 25 urban air monitoring network real-time database of the Ministry of Environment. Furthermore, if the user sent a picture of the atmosphere to the server, should match the image density values of the database and express on Seoul's maps through the IDW interpolation. And then a $PM_{10}$ concentration result is transmitted to user in real time.

• Journal of Environmental Science International
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• v.21 no.9
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• pp.1097-1113
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• 2012

Ozone is the secondary photochemical pollutant formed from ozone precursor such as nitrogen dioxide and non-methane volatile organic compounds(VOCs). The ambient concentration of ozone depends on several factors: sunshine intensity, atmospheric convection, the height of the thermal inversion layer, concentrations of nitrogen oxides and VOCs. Busan is located in the southeast coastal area of Korea so the ozone concentration of Busan is mainly affected from the meteorological variables related to the sea such as sea breeze. In this study the ozone concentrations of Busan in 2008~2010 were used to analyse the cause of the regional ozone difference in eastern area of Busan. The average ozone concentration of Youngsuri was highest in Busan however the average ozone concentration of Gijang was equal to the average ozone concentration of Busan in 2008~2010. The two sites are located in eastern area of Busan but the distance of two sites is only 9km. To find the reason for the difference of ozone concentration between Youngsuri and Gijang, the meteorological variables in two sites were analyzed. For the analysis of meteorological variables the atmospheric numerical model WRF(Weather Research and Forecasting) was used at the day of the maximum and minimum difference in the ozone concentration at the two sites. As a result of analysis, when the boundary layer height was lower and the sea breeze was weaker in Youngsuri, the ozone concentration of Youngsuri was high. Furthermore when the sea breeze blew from the south in the eastern area of Busan, the sea breeze at Youngsuri turned into the southeast and the intensity of sea breeze was weaker because of the mountain in the southern region of Youngsuri. In that case, the difference of ozone concentration between Youngsuri and Gijang was considerable.

• Proceedings of the KSRS Conference
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• v.1
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• pp.475-478
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• 2006

Total primary production resulting from the photosynthetic process can be defined as the amount of organic matter produced in a given period of time. It is proportional to the chlorophyll-a (chl-a) values in the surface layer of the ocean. The MODIS board on Aqua satellite measures visible and infrared radiation in 36 wavebands, providing simultaneous images of chl-a concentration and sea surface temperature (SST) in the upper layer of the sea. The seasonal distribution of chl-a concentration during one year from April 2005 to March 2006 was examined. Light has a role of starting the seasonal cycle. The Kuroshio Current in this area induces many oceanographical features affecting to the change of seasonal control. The chl-a concentration is also seasonal, which is low in summer and high in winter. In summer, the meandering of Kuroshio Current induces strong eddies and increases the chl-a concentration. In autumn, the delayed small autumn bloom occurred until last December due to the Kuroshio Current. When the Kuroshio axis moves far from the coast, the coastal water dominates and increases the concentration even in the winter. The spring bloom starts early at the beginning of March and decreases during the spring.