• Journal of Integrative Natural Science
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• v.17 no.1
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• pp.1-12
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• 2024

Many abnormal climate events are occurring around the world. The cause of abnormal climate is related to temperature. Factors that affect temperature include excessive emissions of carbon and greenhouse gases from a global perspective, and air circulation from a local perspective. Due to the air circulation, many abnormal climate phenomena such as abnormally high temperature and abnormally low temperature are occurring in certain areas, which can cause very serious human damage. Therefore, the problem of abnormal temperature should not be approached only as a case of climate change, but should be studied as a new category of climate crisis. In this study, we proposed a model for the classification of abnormal temperature using random forests based on various meteorological data such as longitudinal observations, yellow dust, ultraviolet radiation from 2018 to 2022 for each region in Korea. Here, the meteorological data had an imbalance problem, so the imbalance problem was solved by oversampling. As a result, we found that the variables affecting abnormal temperature are different in different regions. In particular, the central and southern regions are influenced by high pressure (Mainland China, Siberian high pressure, and North Pacific high pressure) due to their regional characteristics, so pressure-related variables had a significant impact on the classification of abnormal temperature. This suggests that a regional approach can be taken to predict abnormal temperatures from the surrounding meteorological environment. In addition, in the event of an abnormal temperature, it seems that it is possible to take preventive measures in advance according to regional characteristics.

• Journal of Auto-vehicle Safety Association
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• v.10 no.2
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• pp.13-19
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• 2018

The purpose of this study was to evaluate the effect of air bag deployment in passenger car head-on collisions on injuries to the driver. The drivers in head-on collisions who were brought to the emergency rooms of two hospitals from January 2011 and October 2014 were evaluated, as were the vehicles involved. The driver injury level were assessed by utilizing Collision Deformation Classification (CDC) codes, and the Abbreviated Injury Scale (AIS) and Injury Severity Score (ISS), respectively. In this study, it was shown that the chest ISS and AIS were significantly high when an air bag only is deployed. A statistically significant difference was found in the crush extent when the driver who fastened the seatbelt was found to be affected more than the ISS 9. Even when an air bag is deployed in a head-on car collision, injury severity can vary according to accident circumstances and crash severity. Accordingly, first aid can be rapidly given, and the injured person can be quickly referred to a hospital, only if the assessment of persons involved in a vehicle accident is accurately carried out.

• Atmosphere
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• v.17 no.1
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• pp.45-53
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• 2007

In order to investigate the impacts of heat wave on human health, cluster analysis of meteorological elements (e.g., temperature, dewpoint, sea level pressure, visibility, cloud amount, and wind components) for identifying offensive synoptic air masses is employed. Meteorological data at Seoul during the past 30 years are used. The daily death data at Seoul are also employed. Occurrence frequency of heat waves which is defined by daily maximum temperature greater than the threshold temperature (i.e., $31.2^{\circ}C$) was analyzed. The result shows that the frequency and duration of heat waves at Seoul are increasing during the past 30 years. In addition, the increasing trend of the frequency and duration clearly appears in late spring and early autumn as well as summer. Factor analysis shows that 65.1% of the total variance can be explained by 4 components which are linearly independent. Eight clusters (or synoptic air masses) were classified and found to be optimal for representing the summertime air masses at Seoul, Korea. The results exhibit that cluster-mean values of meteorological variables of an offensive air mass (or cluster) are closely correlated with the observed and standardized deaths.

• Journal of Korean Society for Atmospheric Environment
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• v.17 no.4
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• pp.331-345
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• 2001

The increase of carbon monoxide in the ambient air due to the emissions from point sources without control was estimated using three -dimensional numerical models. The target area was Ulsan where one of the largest industrial complexes was located. As a typical example using numerical models for air quality impact analysis of criteria pollutants that will determine whether the air quality standards would be exceeded or not, the following approaches were suggested. They include: (1) investigation of pre-existing atmospheric conditions, (2) identification of major factors causing high concentrations, (3) selection of episode days. (4) preparation of three-dimensional meteorological data, (5) confirmation of agreement between measured and predicted concentrations in the emission conditions of episode days, and (6) estimation of the impact due to changes of the emission conditions. In the present work, daily meteorological conditions for the specific period were classified into four clusters of distinctive features, and the episode days were selected individually from each cluster. Emphasis was placed on the selection of episodes representing meteorological conditions conducive to high concentrations especially for point sources that were sensitive to the wind direction variations.

• Asian Journal of Atmospheric Environment
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• v.5 no.4
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• pp.278-291
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• 2011

Korea has experienced dramatic development and has become highly industrialized and urbanized during the past 40 years, which has resulted in rapid economic growth. Due to the industrialization and urbanization, however, air pollutant emission sources have increased substantially. Rapid increases in emission sources have caused Korea to suffer from serious air pollution. An air pollutant emissions inventory is one set of essential data to help policymakers understand the current status of air pollution levels, to establish air pollution control policies and to analyze the impacts of implementation of policies, as well as for air quality studies. To accurately and realistically estimate administrative district level air pollutant emissions of Korea, we developed a Korean Emissions Inventory System named the Clean Air Policy Support System (CAPSS). In CAPSS, emissions sources are classified into four levels. Emission factors for each classification category are collected from various domestic and international research reports, and the CAPSS utilizes various national, regional and local level statistical data, compiled by approximately 150 Korean organizations. In this paper, we introduced for the first time, a Korean national emissions inventory system and release Korea's official 2007 air pollutant emissions for five regulated air pollutants.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.41 no.3
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• pp.211-219
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• 2017

In this study, we performed numerical simulations on a circulating air classifier using a commercial computational fluid dynamics program. The variations in the grade efficiency, the cut-size and the cut-sharpness were calculated and discussed. By controlling the rotating speed of the main fan, the cut-size could be rapidly increased. However the linearity of the cut-size variation with respect to the main fan speed was not sufficient for application to contaminated soil classification processes. On the other hand, by varying the rotating speed of the classifying fan, the cut-size gradually decreased and could be precisely adjusted. Using both the main fan and the classifying fan, we could achieve larger cut-sharpness values and better classifying performances.

• Korean Journal of Materials Research
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• v.23 no.9
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• pp.510-516
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• 2013

Fly ash is one of the aluminosilicate sources used for the synthesis of geopolymers. The particle size distribution of fly ash and the content of unburned carbon residue are known to affect the compressive strength of geopolymers. In this study, the effects of particle size and unburned carbon content of fly ash on the compressive strength of geopolymers have been studied over a compositional range in geopolymer gels. Unburned carbon was effectively separated in the $-46{\mu}m$ fraction using an air classifier and the fixed carbon content declined from 3.04 wt% to 0.06 wt%. The mean particle size ($d_{50}$) decreased from $22.17{\mu}m$ to $10.79{\mu}m$. Size separation of fly ash by air classification resulted in reduced particle size and carbon residue content with a collateral increase in reactivity with alkali activators. Geopolymers produced from carbon-free ash, which was separated by air classification, developed up to 50 % higher compressive strength compared to geopolymers synthesized from raw ash. It was presumed that porous carbon particles hinder geopolymerization by trapping vitreous spheres in the pores of carbon particles and allowing them to remain intact in spite of alkaline attack. The microstructure of the geopolymers did not vary considerably with compressive strength, but the highest connectivity of the geopolymer gel network was achieved when the Si/Al ratio of the geopolymer gel was 5.0.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.6
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• pp.357-365
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• 2022

Refrigerant mischarging is one of the most frequently occurring failure modes in air conditioners, and both undercharging and overcharging degrade cooling performance. Therefore, it is important to accurately determine the amount of charged refrigerant. In this study, a support vector machine (SVM) model was developed to multi-classify the refrigerant mischarge through steady-state identification via fuzzy clustering techniques. For steady-state identification, a fuzzy clustering algorithm was applied to the air conditioner operation data using the difference between moving averages. The identification results using the proposed method were compared with those using existing steady-state determination techniques studied through the inversed Fisher's discriminant ratio (IFDR). Subsequently, the main features were selected using minimum redundancy maximum relevance (mRMR) considering the correlation among candidate features, and an SVM multi-classification model was devised using the derived features. The proposed method achieves satisfactory accuracy and robustness from test data collected in the new domain.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.6
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• pp.656-665
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• 2012

Recently, yearly production of SRF (Solid Recovered Fuel) as an alternative fuel has been rapidly increasing because of the limited waste disposal, rise in oil prices and reduction of greenhouse gas emission. However, SRF using facilities are excluded from the National Air Pollutant Emission Estimation because SRF using facilities are not yet included among the SCC (Source Classification Code). The purpose of this research was to estimate the emission and emission factor of SRF using facilities' PM and $NO_x$, in order to investigate whether or not they are included in the National Air Pollutant Emission Estimation. The emission factors of SRF using facilities' PM and $NO_x$ are calculated as 0.216 kg/ton, and 3.970 kg/ton, and the emission was estimated based on the yearly total SRF usage of 2011. The results above was 18.7% for PM and 12.8% for $NO_x$ emissions from combustion facility (SCC2) in manufacturing industry combustion (SCC1) of CAPSS. If CAPSS estimate the emission by adding SCC on unlisted SRF in case of Boiler (SCC3) fuel, both PM and $NO_x$'s emissions would increase by 15.8% and 11.3% compare to the emissions for the existing combustion facility. As a result, emissions caused by SRF should be considered when calculating the National Air Pollutant Emission Estimation. In addition, further researches to develop emission factor and improve subdivided SCC should be done in the future, for the accurate and reliable estimation of National Emission.

• Korean Journal of Food Science and Technology
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• v.28 no.3
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• pp.506-513
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• 1996

Soybean hull was microparticulated at cut-off wheel speed of 9,000 rpm and air-classified into fine and coarse fraction at air classifying wheel speeds (ACWS) of 10.000, 15,000 and 20,000 rpm. respectively. Proximate analysis of the coarse and fine fractions of the microparticulated/air-classified soybean hull showed that ash, protein and lipid were enriched in the coarse fractions and carbohydrates in the fine fraction. Dietary fiber were enriched in coarse fractions and dietary fiber and dietary fiber content increased with decreasing ACWS. Mean particle size of fine fractions ranged from $3.1{\mu}m\;to\;5.5{\mu}m$ that of coarse fractions ranged from $9.9{\mu}m\;to\;20.0{\mu}m$ and both increased with decreasing ACWS. The particles were mostly oval-shaped regardless of the fractions. Generally the fraction of low ACWS showed higher viscosity. In water holding capacity, oil absorption and emulsion capacity, there was significant difference between coarse and fine fractions while there was no significant difference as a function of different ACWS. Oil absorption of flying batter was decreased significantly in the fraction of ACWS 15,000. when cakes and cooking were prepared partially substituted with soybean hull fraction, there was no significant changes on their physical and sensory properties up to 10% substitution.