• Journal of Korean Society for Atmospheric Environment
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• v.33 no.6
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• pp.544-553
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• 2017

There is an overall guideline of the installation of air quality monitoring stations in Korea, but specified steps for the selection of monitoring sites for hazardous air pollutants(HAPs) are not provided. In this study, we proposed a systematic method for the selection of monitoring sites for HAPs using geographic information system (GIS). As a case study, the Seoul metropolitan area (Seoul, Incheon, and Gyeonggi Province) was chosen, and 15 factors including population, vehicle registration, and emission data were compiled for each grid cell ($7km{\times}7km$). The number of factors above the top 30% of individual data for each grid cell was used to select priority monitoring sites for HAPs. In addition, several background sites were added for data comparison and source identification. Three scenarios were suggested: Scenario 1 with 7 sites, Scenario 2 with 17 sites, and Scenario 3 with 30 sites. This proposal is not the final result for an intensive monitoring program, but it is an example of method development for selecting appropriate sampling sites. These results can be applied not only to HAPs monitoring in megacities but also to the national HAPs monitoring network.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.3
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• pp.311-318
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• 2014

Electromagnetic compatibility(EMC) performance of the first Korea space launch vehicle(KSLV-I) should be ensured and verified in order to guarantee the normal operation among the spacecraft, ground facilities which are installed in the space center, and other wireless communication networks. For the purpose of the EMC performance verification, pertinent EMC test specifications, methods, and procedures for both the subsystems and the system should be established in consideration of operational properties and electromagnetic environmental effects. And it is required to maintain and control the EMC properties consistently in accordance with the determined specifications up to the program closing phase. In this paper, sequential management work conducted during the overall development process of the KSLV-I is explained, and not only the phased EMC test plan for each model of the KSLV-I and its subsystem but also test method, specification, and results of the verification tests are presented. And also, multipaction analysis results are presented.

• Journal of Environmental Science International
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• v.26 no.9
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• pp.1013-1021
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• 2017

Exposure to Diesel Particulate Matter (DPM) potentially causes adverse health effects (e.g. respiratory symptoms, lung cancer). Due to a lack of data on Elemental Carbon (EC) exposure levels in underground copper ore mining (unlike other underground mining industries such as non-metallic and coal mining), this case study aims to provide individual miners' EC exposure levels, and information on their work practices including use of personal protective equipment. EC measurement was carried out during different work activities (i.e. drilling, driving a loader, plant fitting, plant operation, driving a Specialized Mining Vehicle (SMV)) as per NIOSH Method 5040. The copper miners were working 10 h/day and 5 days/week. This study found that the most significant exposures to EC were reported from driving a loader (range $0.02-0.42mg/m^3$). Even though there were control systems (i.e. water tanks and DPM filters) on the diesel vehicles, around 49.5% of the results were over the adjusted recommendable exposure limit ($0.078mg/m^3$). This was probably due to: (1) driver's frequently getting in and out of the diesel vehicles and opening the windows of the diesel vehicles, and (2) inappropriate maintenance of the diesel vehicles and the DPM control systems. The use of the P2 type respirator provided was less than 19.2%. However, there was no significant difference between the day shift results and the night shift results. In order to prevent or minimize exposure to EC in the copper ore mine, it is recommended that the miners are educated in the need to wear the appropriate respirator provided during their work shifts, and to maintain the diesel engine and emission control systems on a regular basis. Consideration should be given to a specific examination of the diesel vehicles' air-conditioning filters and the air ventilation system to control excessive airborne contaminants in the underground copper mine.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.194-202
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• 2003

In this paper, we introduce a category of Multi-FNN (Fuzzy-Neural Networks) models, analyze the underlying architectures and propose a comprehensive identification framework. The proposed Multi-FNNs dwell on a concept of fuzzy rule-based FNNs based on HCM clustering and evolutionary fuzzy granulation, and exploit linear inference being treated as a generic inference mechanism. By this nature, this FNN model is geared toward capturing relationships between information granules known as fuzzy sets. The form of the information granules themselves (in particular their distribution and a type of membership function) becomes an important design feature of the FNN model contributing to its structural as well as parametric optimization. The identification environment uses clustering techniques (Hard C - Means, HCM) and exploits genetic optimization as a vehicle of global optimization. The global optimization is augmented by more refined gradient-based learning mechanisms such as standard back-propagation. The HCM algorithm, whose role is to carry out preprocessing of the process data for system modeling, is utilized to determine the structure of Multi-FNNs. The detailed parameters of the Multi-FNN (such as apexes of membership functions, learning rates and momentum coefficients) are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the proposed model, two numeric data sets are experimented with. One is the numerical data coming from a description of a certain nonlinear function and the other is NOx emission process data from a gas turbine power plant.

• Spatial Information Research
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• v.23 no.4
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• pp.79-89
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• 2015

This study aims to design and implement a traffic model that can simulate the traffic behavior on the microscopic level by using the GIS. In the design of the model, the vehicle in the simulation environment recognizes the GIS road centerline data as road network data reflecting number of lanes, speed limit and so on. In addition, the behavior model was designed by dividing functions into the environmental perception model, time headway distribution model, car following model, and lane changing model. The implemented model was applied to Jahamun-road of Jongno-gu district to verify the accuracy of the model. As a result, the simulation results on the Jahamun-road had no great error compared with the actual observation data. In the aspect of usability of model, it is judged that this model will be able to effectively contribute to analysis of amount of carbon emission by traffic, evaluation of traffic flow, plans for location of urban infrastructure and so on.

• Proceedings of the KSME Conference
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• 2000.11b
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• pp.150-155
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• 2000

Exhaust emissions from vehicles are the main source of air pollution. Many researchers are trying to find the way of reducing vehicle emissions, especially in the cold transient period of the FTP-75 test. In this study, UEGI (Unburned Exhaust Gas Ignition) technology, warming up the close-coupled catalytic converter (CCC) by igniting the unburned exhaust mixture using two glow plugs installed in the upstream of the catalyst, was developed. It was applied to an exhaust system with a hydrocarbon adsorber to ensure an effective reduction of HC emission during the cold start period. Results showed that the CCC reaches the light-off temperature (LOT) in a shorter time compared with the baseline exhaust system, and HC and CO emissions are reduced significantly during the cold start.

• Journal of Power System Engineering
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• v.20 no.6
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• pp.93-98
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• 2016

Environmental problems are issued throughout all over the world and which are needed the strength management. In case of the diesel cars are also being developing and studying continuously about various after-treatments device such as EGR, LNT, SCR, DPF and DOC etc. which are used for decreasing $NO_X$ and PM. The air temperature goes up to $39^{\circ}C$ in summer and goes down to $-20^{\circ}C$ in winter because of the location. These changing of the temperature can effect to the engine and harmful exhaust gas discharged and it seems to make the increase - decrease different. The result of the evaluate while changing between the test-mode and the air temperature, which expresses that WLTC-mode is 2.2 times and FTP_75 mode is 4.1~6 times increase to the comparison NEDC-mode of the current regulation. The exhaust characteristic of $NO_X$ by the changing temperature increases in the low temperature and 4.3 times in $14^{\circ}C$ and 21.3 times in $-7^{\circ}C$ with maximum when it compares to $23^{\circ}C$. The fuel efficiency of the different weight car and engine with same data is about 5.7 % in maximum.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.8
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• pp.852-858
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• 2005

Modeling techniques for air quality are useful tools in air quality management. Especially, the air quality in urban area is significantly influenced by local surroundings such as buildings and traffic. When considering the air quality in a street canyon, which is usually filmed by a series of consecutive buildings and a street, currently available air dispersion model have a number of limitations to predict the air quality properly. In this study, it is aimed to propose an empirical model for the air quality in urban street canyons. A series of wind tunnel tests, followed by statistical analysis, were conducted. In conclusion, it is found that a wide street canyon and a perpendicular external wind to the street canyon are beneficial to achieve an enhanced air quality in street canyon environment. The model prediction using the proposed model also shows reliable correlations to the wind tunnel test results.

• Journal of Korean Society for Atmospheric Environment
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• v.16 no.1
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• pp.11-22
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• 2000

Polycyclic aromatic hydrocarbons(PAHs) have known as potentially hazardous air pollutants(HAPs0 to human health because of its carcinogenic and mutagenic behaviors. The purpose of this study was to determine the level of 6 PAHs(Fluoranthene, Pyrene, Benzo[a]anthracene, Chrysene, Benzo[b]fluoranthene, and Benzo[a]pyrene) as well as 10 inorganic elements(Cr, Na, K, Zn, Pb, Fe, Cu, Ti, Al and Cd) in the ambient PM-10. The total of 115 samples had been collected from February, 1996 to June, 1996 on quartz fiber by a PM-10 high volume air sampler near the Yong-Tong Apartment complexes. A statistical analysis was performed for the PAHs and inorganic elements data set using a principal component analysis in order to identify qualitatively the potential sources of PM-10. A total of 6 principal components were separated by intensive data pretrement and transformation processes, such as soil, refuse incineration, oil burning, coal burning, field burning, vehicle emission sources. The results showed that PAHs were associated with various burning activities like refuse and field burning, coal burning, and oil burning emissions in the study area. These derived sources were well matched with the previously known source profiles in terms of compositonal order and level of measured species. The combination data set consisted of both organic and inorganic species might provide more powerful source signature and might increase the number of potentially derived sources than PAHs or inorganic data alone.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.1
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• pp.30-42
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• 2008

In this study, the chemical compositions of $PM_{2.5}$ samples collected at the Redwood National Park IMPROVE site in California from March 1988 to May 2004 were analyzed to provide source identification and apportionment. A total of 1,640 samples were collected and 33 chemical species were analyzed by particle induced X-ray emission, proton elastic scattering analysis, photon induced X-ray fluorescence, ion chromatography, and thermal optical reflectance methods. Positive matrix factorization (PMF) was used to develop source profiles and to estimate their mass contributions. The PMF modeling identified five sources and the average mass was apportioned to motor vehicle (35.8%, $1.58\;{\mu}g/m^3$), aged sea salt (23.2%, $1.02\;{\mu}g/m^3$), fresh sea salt (21.4%, $0.94\;{\mu}g/m^3$), wood/field burning (16.1%, $0.71\;{\mu}g/m^3$), and airborne soil (3.5%, $0.15\;{\mu}g/m^3$), respectively. To analyze local source impacts from various wind directions, the CPF and NPR analyses were performed using source contribution results with the wind direction values measured at the site. These results suggested that sources of $PM_{2.5}$ are also sources of visibility degradation and then source apportionment studies derived for $PM_{2.5}$ are also used for understanding visibility problem.