• International Area Studies Review
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• v.20 no.2
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• pp.63-83
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• 2016

This paper examines the determinants of efficiency in a KOSDAQ-listed manufacturing firm. We use Data Envelopment Analysis (DEA) to estimate the efficiency of the export manufacturing firm. We employ two inputs (number of employees, equity) and one output (sales) in the DEA. The determinants of export manufacturing firm efficiency are estimated using the panel Tobit model. An analysis of 369 export manufacturing firms from 2013 to 2015 indicates the following results: First, the R&D intensity, the wage and salary intensity, total asset, and equity ratio each had a negative impact on both the CCR and BCC efficiency scores. However, export intensity had a negative impact on CCR efficiency scores in a KOSDAQ-listed total export manufacturing firm. Second, the R&D intensity had a positive impact on both the CCR and BCC efficiency scores, but export intensity, the wage and salary intensity, and equity ratio each had a negative impact on the CCR and BCC efficiency scores in a KOSDAQ-listed large export manufacturing firm. Third, the R&D intensity, the wage and salary intensity, total asset, and equity ratio each had a negative impact on both the CCR and BCC efficiency scores; respectively, in a KOSDAQ-listed small and medium export manufacturing firm.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.207-215
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• 2018

This study started from the point that the most important SMEs in the economic growth engine of Korea are prepared to grow through innovation. This study focuses on the fact that existing studies have focused on the open innovation of SMEs has been continued since the external knowledge search became an important concept, but mainly focused on the enterprise performance. The purpose of this study is to examine the moderating effect of innovation speed focusing on exports to Korean SMEs. The hypothesis suggests the depth and breadth of external knowledge search, which is the two methods of open innovation emphasized in the previous studies, and then shows the innovation speed on export performance as a moderating effect. Robust regression analysis was used for the analysis and the sample used for the analysis was valid 1,357 SMEs data. The hypothesis test for the moderation effect was performed by comparing the F-values between models. The proposed hypothesis was adopted and the moderation effect was verified.

• Atmosphere
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• v.28 no.4
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• pp.369-382
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• 2018

Planetary boundary layer height (PBLH), produced by the Local Data Assimilation and Prediction System (LDAPS), was verified using RawinSonde (RS) data obtained from observation at Daegwallyeong (DGW) and Sokcho (SCW) during the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic winter games (ICE-POP 2018). The PBLH was calculated using RS data by applying the bulk Richardson number and the parcel method. This calculated PBLH was then compared to the values produced by LDAPS. The PBLH simulations for DGW and SCW were generally underestimation. However, the PBLH was an overestimation from surface to 200 m and 450 m at DGW and SCW, respectively; this result of model's failure to correctly simulate the Surface Boundary Layer (SBL) and the Mixing Layer (ML) as the PBLH. When the accuracy of the PBLH simulation is low, large errors are seen in the mid- and low-level humidity. The highest frequencies of Planetary boundary layer (PBL) types, calculated by the LDAPS at DGW and SCW, were presented as types Ι and II, respectively. Analysis of meteorological factors according to the PBL types indicate that the PBLH of the existing stratocumulus were overestimated when the mid- and low-level humidity errors were large. If the instabilities of the surface and vertical mixing into clouds are considered important factors affecting the estimation of PBLH into model, then mid- and low-level humidity should also be considered important factors influencing PBLH simulation performance.

• Particle and aerosol research
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• v.14 no.4
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• pp.135-144
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• 2018

Based on a two-year measurement data, major sources for the ambient carbonaceous aerosols at the Anmyeon Global Atmosphere Watch (GAW) station were identified by using the Positive Matrix Factorization (PMF) model. The particulate matter less than or equal to $2.5{\mu}m$ in aerodynamic diameter (PM2.5) aerosols were sampled between June 2015 to May 2017 and carbonaceous species including ~80 organic compounds were analyzed. When the number of factors was 5 or 6, the performance evaluation parameters showed the best results, With 6 factor case, the characteristics of transported factors were clearer. The 6 factors were identified with various analyses including chemical characteristics and air parcel movement analysis. The 6 factors with their relative contributions were (1) anthropogenic Secondary Organic Aerosols (SOA) (10.3%), (2) biogenic sources (24.8%), (3) local biomass burning (26.4%), (4) transported biomass burning (7.3%), (5) combustion related sources (12.0%), and (6) transported sources (19.2%). The air parcel movement analysis result and seasonal variation of the contribution of these factors also supported the identification of these factors. Thus, the Anmyeon Island GAW station has been affected by both regional and local sources for the carbonaceous aerosols.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1383-1398
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• 2018

Sea surface wind is one of the most fundamental variables for understanding diverse marine phenomena. Although scatterometers have produced global wind field data since the early 1990's, the data has been used limitedly in oceanic applications due to it slow spatial resolution, especially at coastal regions. Synthetic Aperture Radar (SAR) is capable to produce high resolution wind field data. KOMPSAT-5 is the first Korean satellite equipped with X-band SAR instrument and is able to retrieve the sea surface wind. This study presents the validation results of sea surface wind derived from the KOMPSAT-5 backscattering coefficient data for the first time. We collected 18 KOMPSAT-5 ES mode data to produce a matchup database collocated with buoy stations. In order to calculate the accurate wind speed, we preprocessed the SAR data, including land masking, speckle noise reduction, and ship detection, and converted the in-situ wind to 10-m neutral wind as reference wind data using Liu-Katsaros-Businger (LKB) model. The sea surface winds based on XMOD2 show root-mean-square errors of about $2.41-2.74m\;s^{-1}$ depending on backscattering coefficient conversion equations. In-depth analyses on the wind speed errors derived from KOMPSAT-5 backscattering coefficient data reveal the existence of diverse potential error factors such as image quality related to range ambiguity, discrete and discontinuous distribution of incidence angle, change in marine atmospheric environment, impacts on atmospheric gravity waves, ocean wave spectrum, and internal wave.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.4
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• pp.468-475
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• 2019

An end-line flame arrester allows free venting in combination with flame protection for vertical vent applications. End-line flame arresters are employed in various fields, especially in shipping. In flame arresters, springs are essential parts because the spring load and the spring's elasticity determine the hood opening moment. In addition, the spring has to work under a high-temperature condition because of the burning gas flame. Therefore, it is necessary to analyze the mechanical load and elasticity of the spring when the flame starts to appear. Based on simulations of the working process of a specific end-line flame arrester, a thermal and structural analysis of the spring is performed. A three-dimensional model of a burned spring is built using computational fluid dynamics (CFD) simulation. Results of the CFD analysis are input into a finite element method simulation to analyze the spring structure. The research team focused on three cases of spring loads: 43, 93, and 56 kg, correspondingly, at 150 mm of spring deflection. Consequently, the spring load was reduced by 10 kg after 5 min under a $1,000^{\circ}C$ heat condition. The simulation results can be used to predict and estimate the spring's load and elasticity at the burning time variation. Moreover, the obtained outcome can provide the industry with references to optimize the design of the spring as well as that of the flame arrester.

• Atmosphere
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• v.29 no.3
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• pp.257-267
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• 2019

This study is to assess the applicability of the Extreme Forecast Index (EFI) algorithm of the ECMWF seasonal forecast system to the Global Seasonal Forecasting System version 5 (GloSea5), operational seasonal forecast system of the Korea Meteorological Administration (KMA). The EFI is based on the difference between Cumulative Distribution Function (CDF) curves of the model's climate data and the current ensemble forecast distribution, which is essential to diagnose the predictability in the extreme cases. To investigate its applicability, the experiment was conducted during the heat-wave cases (the year of 1994 and 2003) and compared GloSea5 hindcast data based EFI with anomaly data of ERA-Interim. The data also used to determine quantitative estimates of Probability Of Detection (POD), False Alarm Ratio (FAR), and spatial pattern correlation. The results showed that the area of ERA-Interim indicating above 4-degree temperature corresponded to the area of EFI 0.8 and above. POD showed high ratio (0.7 and 0.9, respectively), when ERA-Interim anomaly data were the highest (on Jul. 11, 1994 (> $5^{\circ}C$) and Aug. 8, 2003 (> $7^{\circ}C$), respectively). The spatial pattern showed a high correlation in the range of 0.5~0.9. However, the correlation decreased as the lead time increased. Furthermore, the case of Korea heat wave in 2018 was conducted using GloSea5 forecast data to validate EFI showed successful prediction for two to three weeks lead time. As a result, the EFI forecasts can be used to predict the probability that an extreme weather event of interest might occur. Overall, we expected these results to be available for extreme weather forecasting.

• Journal of Environmental Health Sciences
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• v.47 no.3
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• pp.267-278
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• 2021

Objectives: Using atmospheric dispersion representative models (AERMOD and CALPUFF), the emissions characteristics of each model were compared and analyzed in ready-mixed concrete manufacturing facilities that generate a large amount of particulate matter (PM-10, PM-2.5). Methods: The target facilities were the ready-mixed concrete manufacturing facilities (Siheung RMC, Goyang RMC, Ganggin RMC) and modeling for each facility was performed by dividing it into construction and operation times. The predicted points for each target facility were selected as 8-12ea (Siheung RMC 10, Goyang RMC 8, and Gangjin RMC 12ea) based on an area within a two-kilometer radius of each project district. The terrain input data was SRTM-3 (January-December 2019). The meteorological input data was divided into surface weather and upper layer weather data, and weather data near the same facility as the target facility was used. The predicted results were presented as a 24-hour average concentration and an annual average concentration. Results: First, overall, CALPUFF showed a tendency to predict higher concentrations than AERMOD. Second, there was almost no difference in the concentration between the two models in non-complex terrain such as in mountainous areas, but in complex terrain, CALPUFF predicted higher concentrations than AERMOD. This is believed to be because CALPUFF better reflected topographic characteristics. Third, both CALPUFF and AERMOD predicted lower concentrations during operation (85.2-99.7%) than during construction, and annual average concentrations (76.4-99.9%) lower than those at 24 hours. Fourth, in the ready-mixed concrete manufacturing facility, PM-10 concentration (about 40 ㎍/m³) was predicted to be higher than PM-2.5 (about 24 ㎍/m³). Conclusions: In complex terrain such as mountainous areas, CALPUFF predicted higher concentrations than AERMOD, which is thought to be because CALPUFF better reflected topographic characteristics. In the future, it is recommended that CALPUFF be used in complex terrain and AERMOD be used in other areas to save modeling time. In a ready-mixed concrete facility, PM-10, which has a relatively large particle size, is generated more than PM-2.5 due to the raw materials used and manufacturing characteristics.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1407-1419
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• 2020

Long time-series gridded data is crucial for the analyses of Earth environmental changes. Climate reanalysis and satellite images are now used as global-scale periodical and quantitative information for the atmosphere and land surface. This paper examines the feasibility of DCT-PLS (penalized least square regression based on discrete cosine transform) for the spatial gap filling of gridded data through the experiments for multiple variables. Because gap-free data is required for an objective comparison of original with gap-filled data, we used LDAPS (Local Data Assimilation and Prediction System) daily data and MODIS (Moderate Resolution Imaging Spectroradiometer) monthly products. In the experiments for relative humidity, wind speed, LST (land surface temperature), and NDVI (normalized difference vegetation index), we made sure that randomly generated gaps were retrieved very similar to the original data. The correlation coefficients were over 0.95 for the four variables. Because the DCT-PLS method does not require ancillary data and can refer to both spatial and temporal information with a fast computation, it can be applied to operative systems for satellite data processing.

• Journal of the Korean earth science society
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• v.43 no.2
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• pp.265-282
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• 2022

This study analyzes the impact of long-range transport of biomass burning emissions from northeastern China on the concentration of particulate matter of diameter less than 10 ㎛ (PM₁₀) in Korea using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Korea was impacted by anthropogenic emissions from eastern China, dust storms from northern China and Mongolia, and biomass burning emissions from northeast China between April 4-and 7, 2020. The contributions of long-range PM₁₀ transport were calculated by separating biomass burning emissions from mixed air pollutants with anthropogenic emissions and dust storms using the zeroing-out method. Further, the radiation energy budget over land and sea around the Korean Peninsula was analyzed according to the distribution of biomass burning emissions. Based on the WRF-Chem simulation during April 5-6, 2020, the contribution of long-range transport of biomass burning emissions was calculated as 60% of the daily PM₁₀ average in Korea. The net heat flux around the Korean Peninsula was in a negative phase due to the influence of the large-scale biomass burning emissions. However, the contribution of biomass burning emissions was analyzed to be <45% during April 7-8, 2020, when the anthropogenic emissions from eastern China were added to biomass burning emissions, and PM₁₀ concentration increased compared with the concentration recorded during April 5-6, 2020 in Korea. Furthermore, the net heat flux around the Korean Peninsula increased to a positive phase with the decreasing influence of biomass burning emissions.