• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.92-99
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• 2021

Light-scattering fine particulate matter monitors can measure particulate matter (PM) concentrations in every second and can be designed in a portable size. They can measure the concentrations of various PM sizes (PM_1.0, PM_2.5, PM_4.0 and PM₁₀) with a single sensor. They measure the number and size of particulate matters and convert them to weight per volume (concentration). These devices show a large error for asian dust. This paper proposes a scheme that compensates the PM_2.5 concenstration error for asian dust by multiple linear regression machine learning in light-scattering PM monitors. This scheme can be effective with only two or three types of PM sizes. The experimental results compare a beta-ray PM monitor of national institute of environmental research and a light-scattering PM monitor during a month. The correlation coefficient (R²) of theses two devices was 0.927 without asian dust, but it was 0.763 due to asian dust during the entire experimental period and improved to 0.944 by the proposed machine learning.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.3
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• pp.196-201
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• 2011

Emission from meat cooking may contribute to the concentration of the Particulate Matters(PM) in the city. This study is to investigate the particle size and the emission characteristics of particulate matters from pork and beef cooking. The chamber was installed for sampling of PM generated from pork belly and beef sirloin cooking including seasoned ones. Cascade Impactor and Portable Aerosol Monitor (PAM) were used to analyse the particle size distribution. At the result of the Cascade Impactor sampling, particulate matters from the pork cooking was higher than that of beef. The gravimetric concentration of PM according to the size was highest at the range of $1.95{\sim}3.2{\mu}m$ and the gravimetric concentration of PM from the non-seasoned meat was higher than that of the seasoned one. The emission factors from pork, pork seasoned, beef and beef seasoned were 1.36 g/kg, 1.03 g/kg, 1.23 g/kg, 0.92 g/kg respectively. To see the result of PAM sampling, the ranges of $1.6{\sim}2.5{\mu}m$ and $2.5{\sim}3.5{\mu}m$ were reveled as highest. The ration of $PM_{2.5}/PM_{10}$ from pork and beef was 0.56~0.58. The emission factors from pork, pork seasoned, beef and beef seasoned measured by PAM were revealed as 3.37 g/kg, 2.76 g/kg, 2.93 g/kg, 2.77 g/kg respectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.573-581
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• 2020

Using CCTV images and weather parameters, a method for estimating PM (Particulate Matter) index was proposed, and an experiment was conducted. For CCTV images, we proposed a method of estimating the PM index by applying a deep learning technique based on a CNN (Convolutional Neural Network) with ROI(Region Of Interest) image including a specific spot and an full area image. In addition, after combining the predicted result values by deep learning with the two weather parameters of humidity and wind speed, a post-processing experiment was also conducted to calculate the modified PM index using the learned regression model. As a result of the experiment, the estimated value of the PM index from the CCTV image was R2(R-Squared) 0.58~0.89, and the result of learning the ROI image and the full area image with the measuring device was the best. The result of post-processing using weather parameters did not always show improvement in accuracy in all cases in the experimental area.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2009.10a
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• pp.270-271
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• 2009

• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.374-385
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• 2022

Purpose: Even if a damage is applied to the dust of the construction site containing the first-class carcinogen, it is dismissed or 5~30% of the amount of noise damage compensation is paid., Because of such loopholes, some construction companies are neglecting the dust management of the construction site, and the damage of the workers and the residents in the construction site continues. Method: The purpose of this study is to examine the problems of the calculation criteria of damage compensation amount of construction site dust, the measurement of dust concentration, the analysis of measurement data (the data of electric signboard measuring device by the mining scattering method), the prediction and evaluation methods such as modeling, and to suggest improvement measures. Result: It is found that it is impossible to calculate the amount of damages from dust damage in the construction site by calculating the current dust damage compensation amount and dust concentration modeling and measurement. Conclusion: It will receive an application for compensation for damage within the site where damage is expected (about 100m in the straight line and the boundary line of the site), and present a method of calculating the amount of compensation that differentially evaluates dust damage to the degree of dust management and compliance with dust-related legal standards.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.294-301
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• 2013

The particle matter concentrations in the subway stations should be monitored and controlled for the health of commuters on the subway system. Seoul Metro and Seoul Metropolitan Rapid Transit Corporation are measuring several air pollutants regularly. In this paper, the reliability of the cheap instruments using light scattering method is improved with the help of a linear regression analysis technique to measure the $PM_{10}$ concentrations continuously in the subway stations. In addition, a monitoring system is implemented to display and record the data of $PM_{10}$, $CO_2$, humidity, and temperature. To transmit and receive these measured sensor data, CDMA M2M wireless communication method is applied.

• Journal of the Korean Society for Railway
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• v.20 no.1
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• pp.11-19
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• 2017

Since operation of railway trains is a major source of particle pollution in tunnel air, a particle removal device can be an effective measure to remove wear particles. To obtain design conditions of the particle removal device that will be installed underneath the railway trains, the wind speed and particle concentration underneath the trains were investigated using a three-dimensional ultrasonic anemometer and a DustTrak aerosol monitor, respectively. The measurements were made for the trains running on Seoul Metropolitan Subway Line 5 on February 10, 2015. The data were analyzed according to the track geometry (straight, curved) and train speed pattern (acceleration, cruising, and deceleration) between stations. Train speed was also analyzed. The average wind speed and $PM_{10}$ concentration underneath the trains were ~30% of the train speed and ${\sim}200{\mu}g/m^3$ for both straight and curved sections. Average $PM_{10}$ concentration for deceleration sections was higher than that for acceleration sections.

• Particle and aerosol research
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• v.18 no.3
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• pp.61-68
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• 2022

In this study, a fluidized bed particle generator was developed to generate an aerosol without supply of compressed air and to increase portability. It was assumed that the mixing ratio of the test particles and beads, the input amount, and the air flow rate supplied to the generator would have effect on the aerosol generation characteristics. The product of these three parameters was set as a characteristic parameter and particle generation characteristics according to the change of the characteristic parameter were observed. As a result, it was confirmed that the input amount of test particles and beads was not suitable as a characteristic parameter and a characteristic parameter expressed as a product of the mass mixing ratio and the air flowrate was newly defined. When the new characteristic parameter is applied, it can be confirmed that the total amount of particles generated from the particle generator is a function of the characteristic parameter. As a result of measuring the amount of particle generation by adjusting the characteristic parameter, it was confirmed that the performance required for the test particle generator for the field inspection equipment of PM-2.5 sensors could be satisfied.

• Journal of the Korea Society of Computer and Information
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• v.18 no.1
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• pp.149-156
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• 2013

In this paper, Commercial program, STAR-CCM+, was used for computer simulation. And also Multi Inner Stage(MIS) cyclone which especially designed for the real experiments of particle removal efficiency. Under negative pressure condition of outlet, computer simulation was performed to predict the removal efficiency for $5{\mu}m$ and $10{\mu}m$ particles by using a turbulence model and lagrangian method. The simulation results are 55.7% and 64.1% for $5{\mu}m$ and $10{\mu}m$ particles, respectively. To compare the simulation results with the actual test of MIS cyclone, we generated the $SiO_2$ particles by heat reactor. Although removal efficiency of actual tests is 63~76% at different flow rate, the size of $SiO_2$ particles which confirmed by SEM(scanning electron microscope) and WAPS(wide range aerosol particle spectrometer) is too small(15~30nm) to compare each results. And so the alternative experiments were performed by using commercial alumina particles ($5{\mu}m$, $10{\mu}m$ and $20{\mu}m$). It was shown that the actual removal efficiency, 76~95%, from MIS cyclone is higher than simulated one.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.3
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• pp.60-66
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• 2011

The$PM_{10}$ concentrations in the underground should be monitored for the health of commuters on the subway system. Seoul Metro and Seoul Metropolitan Rapid Transit Corporation are measuring several air pollutants regularly. In this paper, the reliability of the instruments using light scattering method is improved with the help of a linear regression analysis technique to measure the $PM_{10}$ concentrations continuously in the subway stations. In addition, an USN monitoring system is implemented to display and record the data of $PM_{10}$, CO/$CO_2$, humidity, and temperature. To transmit and receive these measured sensor data, 2.4GHz Zigbee, 424MHz wireless communication, and CDMA M2M method are applied and evaluated.