• Journal of Korea Water Resources Association
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• v.40 no.6 s.179
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• pp.459-468
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• 2007

To estimate the groundwater recharge, the fully distributed parameter based model, MIKE SHE was applied to the Gyeongan-cheon watershed which is one of the tributaries of Han River Basin, and covers approximately $260km^2$ with about 49 km main stream length. To set up the model, spatial data such as topography, land use, soil, and meteorological data were compiled, and grid size of 200m was applied considering computer ability and reliability of the results. The model was calibrated and validated using a split sample procedure against 4-year daily stream flows at the outlet of the watershed. Statistical criteria for the calibration and validation results indicated a good agreement between the simulated and observed stream flows. The annual recharges calculated from the model were compared with the values from the conventional groundwater recession curve method, and the simulated groundwater levels were compared with the observed values. As a result, it was concluded that the model could reasonably simulate the groundwater level and recharge, and could be a useful tool for estimating spatially/temporally the groundwater recharges, and enhancing the analysis of the watershed water cycle.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.4
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• pp.255-267
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• 2020

Under SLD conditions, due to the large size of droplets, physical phenomena such as wall-droplet interaction and deformation have a significant effect on the icing process. Accordingly, many studies have been conducted in order to computationally simulate SLD effects. As one of the efforts, post-processing method have been proposed to describe wall-droplet interaction effect, which modified collection efficiency using Wright model. However, since the model doesn't properly consider the wall condition, it still overestimated collection efficiency and impingement limit. To solve this problem, impingement areas were divided into 3 different regions, and the post-processing method was introduced with the new wall-droplet interaction model developed based on Bai and Gosman rebound model. In order to consider the effect of deformation, the most suitable model was selected by comparing the deformation models used in the various icing codes. As a result, the modified post-processing method showed improved accuracy in predicting the impingement limits and collection efficiency by further estimating mass flux loss due to rebound, and it was observed that the result was the closest to the experimental data when the deformation effect was included by using Wiegand model.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.122-131
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• 2010

This paper introduces the concept of a virtual ecosystem and reports the following three mathematical approaches that could be widely used to construct such an ecosystem, along with examples: (1) a molecular dynamics simulation approach for animal flocking behavior, (2) a stochastic lattice model approach for termite colony behavior, and (3) a rule-based cellular automata approach for biofilm growth. The ecosystem considered in this study consists of artificial organisms and their environment. Each organism in the ecosystem is an agent that interacts autonomously with the dynamic environment, including the other organisms within it. The three types of model were successful to account for each corresponding ecosystem. In order to accurately mimic a natural ecosystem, a virtual ecosystem needs to take many ecological variables into account. However, doing so is likely to introduce excess complexity and nonlinearity in the analysis of the virtual ecosystem's dynamics. Nonetheless, the development of a virtual ecosystem is important, because it can provide possible explanations for various phenomena such as environmental disturbances and disasters, and can also give insights into ecological functions from an individual to a community level from a synthetic viewpoint. As an example of how lower and higher levels in an ecosystem can be connected, this paper also briefly discusses the application of the second model to the simulation of a termite ecosystem and the influence of climate change on the termite ecosystem.

• Journal of Korean Home Economics Education Association
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• v.31 no.3
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• pp.41-55
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• 2019

The present study examined the direct effects of parental support and monitoring on multicultural adolescents' school adjustment and the mediating role of ego-resilience in the relationships, under the condition of controlling foreign mothers' Korean language abilities. We used data from 1,325 1^st grade middle school students from multicultural families, who participated in the Multicultural Adolescent Panel Survey(MAPS) administered by the National Youth Policy Institute(NYPI). Structural equation modeling analysis revealed the following: parental support and monitoring directly and positively related with multicultural adolescents' school adjustment, and the direct effect of parental support on the school adjustment of multicultural adolescents was greater than that of parental monitoring. In addition, the adolescents' ego-resilience partially mediated the relationships between parental support and monitoring, and their school adjustment. Finally, we recommended the roles of parent education and home economics education in supporting school adjustment and elevating ego-resilience in multicultural adolescents.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.5
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• pp.443-448
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• 2015

Obstructive sleep apnea (OSA) is a syndrome characterized by the repetitive episodic collapse of the upper airway. Maxillomandibular advancement surgery is one of the most effective surgical treatment methods in treating obstructive sleep apnea. The advancement of both maxill and mandible can enlarge the cross-sectional areas and volumes of the postero-superior airway. The purpose of this study is to analyze flow patterns in the upper airway before and after maxillomandibular advancement surgery. Here, we analyzed flow phenomena of inspiration and expiration to prevent obstructive sleep apnea patient from happening side effect. Modeling of the upper airway carried out from clinical CT scanned images. We used time-dependent values for boundary condition. CFD analyses were performed and evaluated section of minimum area (SMA), compared with patient inside upper airway before and after maxillomandibular advancement surgery in SMA, and negative pressure effects. The study showed the greatest enlargment of the section of minimum cross-sectional area. Moreover, the velocity and the negative airway pressure were decreased. According to the result of this study, the maxillomandibular advancement surgery stabilizes the airflow in the postero-superior airway of OSA patients.

• Geophysics and Geophysical Exploration
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• v.5 no.4
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• pp.236-249
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• 2002

We have extended the three-dimensional (3-D) resistivity imaging algorithm to cover the 3-D resistivity tomography problem, where resistivity data are acquired using electrodes installed in several boreholes as well as at the earth surface. The imaging algorithm consists of the 3-D finite element forward modeling and least-squares inversion scheme, where the ACB (Active Constraint Balancing) is adopted to enhance the resolving power of the inversion. Sensitivity analysis with numerical verifications shows that 3-D resistivity tomography is a very appealing method and can be used to get 3-D attitude of subsurface structures with very high-resolution. Moreover, we could accurately handle the topography effect, which could cause artifacts in the resistivity tomography. In the application of 3-D resistivity tomography to the real field data set acquired at the quarry mine, we could derive a very reasonable and accurate image of the subsurface.

• Journal of Veterinary Clinics
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• v.33 no.2
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• pp.107-112
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• 2016

The objective of this study was to determine potential contributing factors associated with biosecurity level of farrow-to-finish pig farms and to develop a classification tree model to explore how these factors related to each other based on prediction model. To this end, the author analyzed data (n = 193) extracted from a cross-sectional study of 344 farrow-to-finish farms which was conducted between March and September 2014 aimed to explore swine disease status at farm level. Standardized questionnaires with information about basic demographical data and management practices were collected in each farm by on-site visit of trained veterinarians. For the classification of the data sets regarding biosecurity level as a dependent variable and predictor variables, Chi-squared Automatic Interaction Detection (CHAID) algorithm was applied for modeling classification tree. The statistics of misclassification risk was used to evaluate the fitness of the model in terms of prediction results. Categorical multivariate input data (40 variables) was used to construct a classification tree, and the target variable was biosecurity level dichotomized into low versus high. In general, the level of biosecurity was lower in the majority of farms studied, mainly due to the limited implementation of on-farm basic biosecurity measures aimed at controlling the potential introduction and transmission of swine diseases. The CHAID model illustrated the relative importance of significant predictors in explaining the level of biosecurity; maintenance of medical records of treatment and vaccination, use of dedicated clothing to enter the farm, installing fence surrounding the farm perimeter, and periodic monitoring of the herd using written biosecurity plan in place. The misclassification risk estimate of the prediction model was 0.145 with the standard error of 0.025, indicating that 85.5% of the cases could be classified correctly by using the decision rule based on the current tree. Although CHAID approach could provide detailed information and insight about interactions among factors associated with biosecurity level, further evaluation of potential bias intervened in the course of data collection should be included in future studies. In addition, there is still need to validate findings through the external dataset with larger sample size to improve the external validity of the current model.

• 재활복지
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• v.21 no.1
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• pp.253-277
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• 2017

The purpose of this study was to develop the Constraints in Physical Activity Scale for people with physical Disabilities(CPASD) which measures the constraints in physical activity of people with physical disabilities. For this study, the 5 step analytic framework of unified validity developed by Messick (1995), the framework for conducting a strong program of construct validation by Benson (1998) method were applied. Furthermore, the validity of CPASD was systematically presented by applying common factor model and measurement model to 264 persons with physical disabilities. The conclusion based on the results and discussions of this study is as follows. First, CPASD presented evidence of job validity. Four factors (17 items) were developed, consisting of leader constraints, economic constraints, prejudice, and exercise environment constraints through the analysis of the factor structure and the fit of factor coefficients. Second, the factor structure of the developed CPASD (leader constraint, economic constraint, prejudice, exercise environment constraint) was statistically distinguished and stably reflected the existing exercise participation constraints theory. Third, the developed CPASD presented evidence of the validity of the criteria. Leader constraints and prejudice were negatively correlated with positive motor emotions, leader constraints, prejudice, and exercise environment constraints were positively correlated with negative motor emotions. Therefore, in future research, it is necessary to reevaluate the current system and actual condition related to leader constraints, economic constraints, prejudices, and exercise environment constraints derived as factors of CPASD. To do this, it is necessary to judge the degree of reality based on the causal relationship verification and IRT theory using CPASD.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.1-20
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• 2021

As the Great Reset is discussed at the World Economic Forum due to the COVID-19 pandemic, artificial intelligence, the driving force of the 4th industrial revolution, is also in the spotlight. However, corporate research in the field of artificial intelligence is still scarce. Since 2000, related research has focused on how to create value by applying artificial intelligence to existing companies, and research on how startups seize opportunities and enter among existing businesses to create new value can hardly be found. Therefore, this study analyzed the cases of startups using the comprehensive framework of the multi-level perspective with the research question of how artificial intelligence based startups, a sub-industry of software, have different innovation patterns from the existing software industry. The target firms are gazelle firms that have been certified as venture firms in South Korea, as start-ups within 7 years of age, specializing in machine learning modeling purposively sampled in the medical, finance, marketing/advertising, e-commerce, and manufacturing fields. As a result of the analysis, existing software companies have achieved process innovation from an enterprise-wide integration perspective, in contrast machine learning technology based startups identified unit processes that were difficult to automate or create value by dismantling existing processes, and automate and optimize those processes based on data. The contribution of this study is to analyse the birth of artificial intelligence-based startups and their innovation patterns while validating the framework of an integrated multi-level perspective. In addition, since innovation is driven based on data, the ability to respond to data-related regulations is emphasized even for start-ups, and the government needs to eliminate the uncertainty in related systems to create a predictable and flexible business environment.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.11-20
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• 2021

This study extracts topics related to university education through newspaper articles and analyzes the characteristics of each topic and the reporting patterns of each newspaper. The 9 topics were discovered using LDA. Topic 1 and Topic 3 are related to university support projects for education, but Topic 3 is focused on local universities. Topic 2 is about university education after COVID-19, Topic 4 teaching-learning methods, Topic 5 government policies, Topic 6 the high school education contribution university support projects, Topic 7 the university education vision, Topic 8 internationalization, and Topic 9 the entrance exam. The Chosun Ilbo, Kyunghyang, and Hankyoreh reported a lot of articles associated to lectures after COVID-19, government policies, and comments on university education. Relevant articles since 2016 have been analyzed by newspaper type and before/after COVID-19 through which differences in the topics were studied and discussed. These findings would suggest a basic policy guideline for university education and imply that the positive and negative effects of the media need to be considered.