• International Area Studies Review
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• v.22 no.3
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• pp.175-200
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• 2018

Since the 1990s rising intangible asset has become one of the main driving forces of investment stagnation and jobless growth in advanced income countries. We investigate how does the impact of firms' profitability on employment growth depends on the intangibility and whether the relationship between profitability and tangibility has complementarity. With data on Korean firms over the period 1988~2017 we investigate the effects of intangibility and profitability on employment growth based on the econometric approach of system GMM. The empirical results are as follows. (1) the profit rate has gradually led to lower employment growth, while it had positive effect on employment before the period of financial crisis. The estimated values and signs of profit rate coefficients varies from traditional industries to high/medium tech. industries. (2) the effect of increasing asset intangibility ratio on employment growth is negative and statistically significant. (3) the coefficients of interaction term of (profit rate ${\times}$ intangibility ratio) have significant negative values. It means employment effect of profit rate are becoming higher(lower) as intangibility ratio is at the lower(higher) level; profits rate and intangibility are not complement with each other. The results imply that to boost employment industrial policy which has the capacity to coordinate business intangibility is preferred to expansionary demand policy.

• (The)Korea Educational Review
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• v.22 no.3
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• pp.353-383
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• 2016

The purpose of this study is to examine the outcomes and implementation process from various stakeholders' perspectives related to the CAMPUS Asia (Collective Action for Mobility Program of University Student in Asia) pilot project, and thereby provide practical suggestions for it. The pilot projet of the CAMPUS Asia lasted four years from 2012 to 2015. A hybrid approach was used to analyze its implementation process, and diverse sources of data such as documents, surveys, and interviews were employed for analysis. Findings showed the accomplishments of the CAMPUS Asia pilot project for promoting participants' development and building the foundation for international cooperation at the governmental and institutional levels, while various limitations were also identified. In addition, analysis was conducted to identify the contextual factors that influenced the outcomes and limitations of the CAMPUS Asia pilot project at the governmental, institutional, and student levels. Based on these findings, multiple suggestions to maximize the effect of the CAMPUS Asia pilot project were provided, for example, to set up the ultimate goals of the project clearly, for governments to coordinate different academic systems by country and address the issue of credit transfer, to establish the uniqueness of the project, to strengthen the curriculum of each consortium, to co-manage the extra-curricular activities, and to develop the specialized career paths.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.768-776
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• 2021

Current protection-coordination methods use the reverse time characteristics of the T-C curve, which is not effective for a LVDC distribution system because the protective operation time of converters and DC circuit breakers is much faster than AC protection devices. Therefore, an algorithm is proposed for fault-section isolation using the fault current slope to minimize the blackout region and coordinate between converters and protection devices in a rapid and accurate manner. The method deals with the slope characteristics of a fault current, which may depend on the fault location in an LVDC distribution system. Thus, an LVDC distribution system can be operated in a stable manner by isolating the fault section selectively before the shutdown of the main converter using slope characteristics, which change in proportion to the line impedance and fault location. A 1.5-kV LVDC distribution system was modeled to verify the effectiveness of the proposed algorithm using PSCAD/EMTDC. The system is composed of a distribution substation, LVDC converter, and distribution lines. The simulation results confirm that the proposed algorithm is a useful tool for minimizing the fault section in an LVDC distribution system.

• Korean Journal of Environmental Agriculture
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• v.40 no.1
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• pp.49-59
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• 2021

BACKGROUND: Soil salinity causes reduction of crop productivity. Rhizosphere microbes have metabolic capabilities and ability to adaptation of plants to biotic and abiotic stresses. Plant growth-promoting bacteria (PGPB) could play a role as elicitors for inducing tolerance to stresses in plants by affecting resident microorganism in soil. This study was conducted to demonstrate the effect of selected strains on rhizosphere microbial community under salinity stress. METHODS AND RESULTS: The experiments were conducted in tomato plants in pots containing field soil. Bacterial suspension was inoculated into three-week-old tomato plants, one week after inoculation, and -1,000 kPa-balanced salinity stress was imposed. The physiological and biochemical attributes of plant under salt stress were monitored by evaluating pigment, malondialdehyde (MDA), proline, soil pH, electrical conductivity (EC) and ion concentrations. To demonstrate the effect of selected Bacillus strains on rhizosphere microbial community, soil microbial diversity and abundance were evaluated with Illumina MiSeq sequencing, and primer sets of 341F/805R and ITS3/ITS4 were used for bacterial and fungal communities, respectively. As a result, when the bacterial strains were inoculated and then salinity stress was imposed, the inoculation decreases the stress susceptibility including reduction in lipid peroxidation, enhanced pigmentation and proline accumulation which subsequently resulted in better plant growth. However, bacterial inoculations did not affect diversity (observed OTUs, ACE, Chao1 and Shannon) and structure (principle coordinate analysis) of microbial communities under salinity stress. Furthermore, relative abundance in microbial communities had no significant difference between bacterial treated- and untreated-soils under salinity stress. CONCLUSION: Inoculation of Bacillus strains could affect plant responses and soil pH of tomato plants under salinity stress, whereas microbial diversity and abundance had no significant difference by the bacterial treatments. These findings demonstrated that Bacillus strains could alleviate plant's salinity damages by regulating pigments, proline, and MDA contents without significant changes of microbial community in tomato plants, and can be used as effective biostimulators against salinity stress for sustainable agriculture.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.115-123
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• 2021

Pine nuts are Korea's representative nut forest products and profitable crops. However, pine nuts are harvested by climbing the trees themselves, thus the risk is high. In order to solve this problem, it is necessary to harvest pine nuts using a robot or an unmanned aerial vehicle(UAV). In this paper, we propose a deep learning based detection method for harvesting pine nut in UAV aerial images. For this, a video was recorded in a real pine forest using UAV, and a data augmentation technique was used to supplement a small number of data. As the data for 3D detection, Unity3D was used to model the virtual pine nut and the virtual environment, and the labeling was acquired using the 3D transformation method of the coordinate system. Deep learning algorithms for detection of pine nuts distribution area and 2D and 3D detection of pine nuts objects were used DeepLabV3+, YOLOv4, and CenterNet, respectively. As a result of the experiment, the detection rate of pine nuts distribution area was 82.15%, the 2D detection rate was 86.93%, and the 3D detection rate was 59.45%.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1349-1365
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• 2020

In recent years, in the fields of smart cities and digital twins, research on model generation is increasing due to the advantage of acquiring actual 3D coordinates by using point clouds. In addition, there is an increasing demand for a solid model that can easily modify the shape and texture of the building. In this paper, we propose a method to create a clustered solid building model based on point cloud data. The proposed method consists of five steps. Accordingly, in this paper, we propose a method to create a clustered solid building model based on point cloud data. The proposed method consists of five steps. In the first step, the ground points were removed through the planarity analysis of the point cloud. In the second step, building area was extracted from the ground removed point cloud. In the third step, detailed structural area of the buildings was extracted. In the fourth step, the shape of 3D building models with 3D coordinate information added to the extracted area was created. In the last step, a 3D building solid model was created by giving texture to the building model shape. In order to verify the proposed method, we experimented using point clouds extracted from unmanned aerial vehicle images using commercial software. As a result, 3D building shapes with a position error of about 1m compared to the point cloud was created for all buildings with a certain height or higher. In addition, it was confirmed that 3D models on which texturing was performed having a resolution of less than twice the resolution of the original image was generated.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.285-294
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• 2021

Motivated by the mixed results in the previous studies on the relationship between speech production and perception, the current study aims to investigate the relationship between production and perception in depth through a case study on how Korean EFL university students produce and perceive American English vowels. To this end, 19 Korean students at a university located in the Seoul-metropolitan area participated in the production and perception tests on American English vowels to elucidate the precedence relationship and the correlation between production and perception. Results showed that precedence of neither perception nor production was found in the overall result. However, either precedence of perception or production was found for the vowels [ɛ], [α], [ɔ], [u], which implies that the precedence relationship between production and perception varies depending on individual vowels. As for the correlation between production and perception, no correlation was attested between production and perception, suggesting that production and perception skills are not closely linked for these participants. Given that mastering language requires to coordinate two distinct production and perception skills and that L2 learners' preception and production skills become more closely connected as the learners' L2 experience and proficiency increases, no correlation between production and perception attested by the current EFL students implies that the correlation between production and perception varies during the course of foreign language/L2 acquisition in such a way that production and perception skills become increasingly related. Implications of the findings were further discussed and pedagogical suggestions were provided.

• The Journal of Information Systems
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• v.30 no.1
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• pp.151-177
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• 2021

Purpose This paper aims to improve management performance by effectively responding to production needs and reducing inventory through synchronizing production planning and procurement in the aviation industry. In this study, the differences in production planning and execution were first analyzed in terms of demand, supply, inventory, and process using the big data collected from a domestic aircraft manufacturers. This paper analyzed the problems in procurement and inventory management using legacy big data from ERP system in the company. Based on the analysis, we performed a simulation to derive an efficient procurement and inventory management plan. Through analysis and simulation of operational data, we were able to discover procurement and inventory policies to effectively respond to production needs. Design/methodology/approach This is an empirical study to analyze the cause of decrease in inventory turnover and increase in inventory cost due to dis-synchronize between production requirements and procurement. The actual operation data, a total of 21,306,611 transaction data which are 18 months data from January 2019 to June 2020, were extracted from the ERP system. All them are such as basic information on materials, material consumption and movement history, inventory/receipt/shipment status, and production orders. To perform data analysis, it went through three steps. At first, we identified the current states and problems of production process to grasp the situation of what happened, and secondly, analyzed the data to identify expected problems through cross-link analysis between transactions, and finally, defined what to do. Many analysis techniques such as correlation analysis, moving average analysis, and linear regression analysis were applied to predict the status of inventory. A simulation was performed to analyze the appropriate inventory level according to the control of fluctuations in the production planing. In the simulation, we tested four alternatives how to coordinate the synchronization between the procurement plan and the production plan. All the alternatives give us more plausible results than actual operation in the past. Findings Based on the big data extracted from the ERP system, the relationship between the level of delivery and the distribution of fluctuations was analyzed in terms of demand, supply, inventory, and process. As a result of analyzing the inventory turnover rate, the root cause of the inventory increase were identified. In addition, based on the data on delivery and receipt performance, it was possible to accurately analyze how much gap occurs between supply and demand, and to figure out how much this affects the inventory level. Moreover, we were able to obtain the more predictable and insightful results through simulation that organizational performance such as inventory cost and lead time can be improved by synchronizing the production planning and purchase procurement with supply and demand information. The results of big data analysis and simulation gave us more insights in production planning, procurement, and inventory management for smart manufacturing and performance improvement.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.553-566
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• 2021

River confluence is often characterized by shear layer and the associated strong mixing. In natural rivers, the main channel and its tributary can be separated by the shear layer using contrasting colors. The shear layer can be easily observed using aerial images from satellite or unmanned aerial vehicles. This study proposes a low-cost identification method extracting geographic features of the shear layer using RGB aerial image. The method consists of three stages. At first, in order to identify the shear layer, it performs image segmentation using a Gaussian mixture model and extracts the water bodies of the main channel and tributary. Next, the self-organizing map simplifies the flow line of the water bodies into the 1-dimensional curve grid. After that, the curvilinear coordinate transformation is performed using the water body pixels and the curve grid. As a result, the shear layer identification method was successfully applied to the confluence between Nakdong River and Nam River to extract geometric shear layer features (confluence angle, upstream- and downstream- channel widths, shear layer length, maximum shear layer thickness).

• Korean Journal of Food Science and Technology
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• v.54 no.3
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• pp.362-368
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• 2022

The sensory characteristics of nine rice-based distilled soju were determined using check-all-that-apply (CATA) profiling. A total of 53 consumers evaluated the soju for two appearance attributes, nine aroma attributes, nine flavor/taste attributes, four mouth-feel related sensory attributes, and overall desirability. The total sum of CATA terms indicated that 14 characteristics showed frequency differences of over 10 and that there were significant differences among nine samples for eleven sensory attributes as determined using Cochran's q test (p<0.05). Based on correspondence analysis of CATA data, the samples were primarily separated by the first dimension, which accounted for 89% of the total variance among samples. The "brown color," "fruit taste," and "grain aroma" characteristics had higher frequencies than those for the "white color," "acetone aroma," and 'alcohol taste" characteristics. Overall, there was a higher preference for oak-aged samples than for samples aged in other containers. "sweet aroma', 'fruit aroma," and "sweet taste" seemed to positively affect consumer preferences, while "bitter taste," "alcohol taste," and "acetone aroma" appeared to negatively affect consumer preferences as determined by principal coordinate analysis.