• Korean Journal of Plant Resources
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• 제35권4호
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• pp.417-427
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• 2022

In this study, we investigated in vitro immuno-stimulatory and anti-obesity activity of fruit (LIF), leaves (LIL) and stems (LIS) from Lonicera insularis Nakai in mouse macrophages RAW264.7 cells and mouse pre-adipocytes 3T3-L1 cells. LIF, LIL and LIS increased the production of immunostimulatory factors such as nitric oxide (NO), inducible nitric oxide synthase (iNOS), interleukin-1β (IL-1β), cyclooxygenase-2 (COX-2), tumor necrosis factor-α (TNF-α) and activated phagocytosis in RAW264.7 cells. Inhibition of toll-like receptor 2/4 (TLR2/4) partly blocked LIF, LIL and LIS mediated production of immunostimulatory factors. In addition, inhibition of mitogen-activated protein kinases (MAPK) signaling attenuated the production of immunostimulatory factors induced by LIF, LIL and LIS. Based on these results of this study, LIF, LIL and LIS is thought to activate macrophages the production of immunostimulatory factors and phagocytosis through toll-like receptor 2/4 (TLR2/4) and MAPKs signaling pathway. In anti-obesity study, LIF reduced the lipid accumulation in 3T3-L1 cells. LIF increased the protein phosphorylation expressions such as AMP-activated protein kinase (AMPK), hormone sensitive lipase (HSL), adipose triglyceride lipase (ATGL) related to the lipolysis of the adipocytes. In addition, LIF increased the expression of proteins involved in energy metabolism and brown adipose tissues differentiation such as peroxisome proliferator-activated receptor gamma coativator 1α (PGC-1α) and PR domain-containing16 (PRDM16). These results suggest that LIF is involved in lipid accumulation inhibition through expressing the proteins such as lipolysis and differentiation of white adipocytes to brown adipocytes.

• Communications of Mathematical Education
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• 제37권2호
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• pp.233-256
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• 2023

This study conducted foundational research to derive ways to use ChatGPT in mathematics education by analyzing ChatGPT's responses to questions from the National Assessment of Educational Achievement (NAEA) and the College Scholastic Ability Test (CSAT). ChatGPT, a generative artificial intelligence model, has gained attention in various fields, and there is a growing demand for its use in education as the number of users rapidly increases. To the best of our knowledge, there are very few reported cases of educational studies utilizing ChatGPT. In this study, we analyzed ChatGPT 3.5 responses to questions from the three-year National Assessment of Educational Achievement and the College Scholastic Ability Test, categorizing them based on the percentage of correct answers, the accuracy of the solution process, and types of errors. The correct answer rates for ChatGPT in the National Assessment of Educational Achievement and the College Scholastic Ability Test questions were 37.1% and 15.97%, respectively. The accuracy of ChatGPT's solution process was calculated as 3.44 for the National Assessment of Educational Achievement and 2.49 for the College Scholastic Ability Test. Errors in solving math problems with ChatGPT were classified into procedural and functional errors. Procedural errors referred to mistakes in connecting expressions to the next step or in calculations, while functional errors were related to how ChatGPT recognized, judged, and outputted text. This analysis suggests that relying solely on the percentage of correct answers should not be the criterion for assessing ChatGPT's mathematical performance, but rather a combination of the accuracy of the solution process and types of errors should be considered.

• The Journal of Bigdata
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• 제8권1호
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• pp.111-129
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• 2023

With the diffusion of digital innovation, the adoption of innovative medical technologies based on artificial intelligence is increasing in the medical field. This is driving the launch and adoption of AI-based SaMD(Software as a Medical Device), but there is a lack of research on the factors that influence the adoption of SaMD by medical institutions. The purpose of this study is to identify key factors that influence medical institutions' decisions to adopt AI-based SaMDs, and to analyze the weights and priorities of these factors. For this purpose, we conducted Delphi surveys based on the results of literature studies on technology acceptance models in healthcare industry, medical AI and SaMD, and developed a research model by combining HOTE(Human, Organization, Technology and Environment) framework and HABIO(Holistic Approach {Business, Information, Organizational}) framework. Based on the research model with 5 main criteria and 22 sub-criteria, we conducted an AHP(Analytical Hierarchy Process) analysis among the experts from domestic medical institutions and SaMD providers to empirically analyze SaMD adoption factors. The results of this study showed that the priority of the main criteria for determining the adoption of AI-based SaMD was in the order of technical factors, economic factors, human factors, organizational factors, and environmental factors. The priority of sub-criteria was in the order of reliability, cost reduction, medical staff's acceptance, safety, top management's support, security, and licensing & regulatory levels. Specifically, technical factors such as reliability, safety, and security were found to be the most important factors for SaMD adoption. In addition, the comparisons and analyses of the weights and priorities of each group showed that the weights and priorities of SaMD adoption factors varied by type of institution, type of medical institution, and type of job in the medical institution.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• 제18권1호
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• pp.159-172
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• 2023

The purpose of this study is to explore a collaborative start-up space(Co-Space) configuration plan in terms of university-regional linkage through demand analysis on the composition of university-regional linkage startup space. To this end, a survey was conducted for request analysis, and the collected data were analyzed through the t-test, The Lotus for Focus model. In addition, FGI was implemented for entrepreneurs, and the direction of the composition of the university-region Co-Space was derived from various aspects. The results of this study are as follows. First, as a result of the analysis of the necessity of university-community Co-Space, the necessity of opening up the start-up space recognized by local residents and the necessity of building the start-up space in the region were high. In addition, men recognized the need to build a space for start-ups in the community more highly than women did women. Second, as a result of analysis of demands for university-regional Co-Space, the difference between current importance and future necessity of university-regional Co-Space was statistically significant. Third, as a result of analysis on the composition of the startup space by cooperation between universities and regions, different demands were made for composition of the startup space considering openness and closeness, and for composition of the startup space size. The implications of the study are as follows. First, Co-Spaces need to be constructed in conjunction with universities in accordance with the demands of start-up companies in the region by stage of development. Second, it is necessary to organize a customized Co-Space that takes into account the size and operation of the start-up space. Third, it is necessary to establish an experience-based open space for local residents in the remaining space of the university. Fourth, it is necessary to establish a Co-Space that enables an organic network between local communities, start-up investment companies, start-up support institutions, and start-up companies. This study is significant in that it proposed the regional startup ecosystem and the cooperative start-up space structure for strengthening start-up sustainability through cooperation between universities and local communities. The results of this study are expected to be used as useful basic data for Co-Space construction to build a regional start-up ecosystem in a trend emphasizing the importance of start-up space, which is a major factor affecting start-up companies.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• 제14권4호
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• pp.195-204
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• 2009

In order to estimate sea surface current fields in the East Sea, we examined characteristics of mean dynamic topography (MDT) fields (or mean surface current field, MSC) generated from three different methods. This preliminary investigation evaluates the accuracy of surface currents estimated from satellite-derived sea level anomaly (SLA) data and three MDT fields in the East Sea. AVISO (Archiving, Validation and Interpretation of Satellite Oceanographic data) provides a MDT field derived from satellite observation and numerical models with $0.25^{\circ}$ horizontal resolution. Steric height field relative to 500 dbar from temperature and salinity profiles in the East Sea supplies another MDT field. Trajectory data of surface drifters (ARGOS) in the East Sea for 14 years provide another MSC field. Absolute dynamic topography (ADT) field is calculated by adding SLA to each MDT. Application of geostrophic equation to three different ADT fields yields three surface geostrophic current fields. Comparisons were made between the estimated surface currents from the three different methods and in-situ current measurements from a ship-mounted ADCP (Acoustic Doppler Current Profiler) in the southwestern East Sea in 2005. For offshore areas more than 50 km away from the land, the correlation coefficients (R) between the estimated versus the measured currents range from 0.58 to 0.73, with 17.1 to $21.7\;cm\;s^{-1}$ root mean square deviation (RMSD). For coastal ocean within 50 km from the land, however, R ranges from 0.06 to 0.46 and RMSD ranges from 15.5 to $28.0\;cm\;s^{-1}$. Results from this study reveal that a new approach in producing MDT and SLA is required to improve the accuracy of surface current estimations for the shallow costal zones of the East Sea.

• Journal of the Computational Structural Engineering Institute of Korea
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• 제37권1호
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• pp.67-76
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• 2024

In this paper, we present a DIP-MLS testing method that combines digital image processing with a rigid body-based MLS differencing approach to measure mechanical variables and analyze the impact of target location and image resolution. This method assesses the displacement of the target attached to the sample through digital image processing and allocates this displacement to the node displacement of the MLS differencing method, which solely employs nodes to calculate mechanical variables such as stress and strain of the studied object. We propose an effective method to measure the displacement of the target's center of gravity using digital image processing. The calculation of mechanical variables through the MLS differencing method, incorporating image-based target displacement, facilitates easy computation of mechanical variables at arbitrary positions without constraints from meshes or grids. This is achieved by acquiring the accurate displacement history of the test specimen and utilizing the displacement of tracking points with low rigidity. The developed testing method was validated by comparing the measurement results of the sensor with those of the DIP-MLS testing method in a three-point bending test of a rubber beam. Additionally, numerical analysis results simulated only by the MLS differencing method were compared, confirming that the developed method accurately reproduces the actual test and shows good agreement with numerical analysis results before significant deformation. Furthermore, we analyzed the effects of boundary points by applying 46 tracking points, including corner points, to the DIP-MLS testing method. This was compared with using only the internal points of the target, determining the optimal image resolution for this testing method. Through this, we demonstrated that the developed method efficiently addresses the limitations of direct experiments or existing mesh-based simulations. It also suggests that digitalization of the experimental-simulation process is achievable to a considerable extent.

• Journal of Korean Tunnelling and Underground Space Association
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• 제25권6호
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• pp.423-446
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• 2023

Shield TBM tunnel linings are segmented into segments and rings. This study investigates the response characteristics of the stress and displacement of the segment lining under seismic waves through modeling that considers the interface behavior between segments by applying a shell interface element to the contact surface between segments and rings. And there is no management criteria for ovaling deformation of segment linings in Korea. So, this study the ovality criteria and meaning of segment lining. The results of study showed that the distribution patterns of stress and displacement under seismic waves were similar between continuous linings and segment linings. However, the maximum values of stress and displacement showed differences from segment linings. The stress distribution of the continuous lining modeled as a shell type has a stress distribution that has continuity in the 3D cylindrical shape, but the segment lining is concentrated outside the segment, and the largest stress occurs at the location where the contact surface between the segment and the ring is concentrated. This intermittent and localized stress distribution shows an increasing as the ovality of the lining increases at seismic waves. The ovality at which the increase in stress distribution begins to show irregularity and localization is about 150‰. Ovality of 150‰ is an unrealistic value that cannot represent actual lining deformation. Therefore, the ovality of the segment lining increase with depth, but it does not have a significant impact on the stability caused by seismic load.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• 제9권1호
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• pp.15-23
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• 2014

A Case Study on Venture and Small-Business Executives' Use of Strategic Intuition in the Decision Making Process This paper is a case study on how Venture and Small-Business Executives managers can take advantage of their intuitions in situations where the business environment is increasingly uncertain, a novel situation occurs without any data to reflect on, when rational decision-making is not possible, and when the business environment changes. The case study is based on a literature review, in-depth interviews with 16 business managers, and an analysis of Klein, G's (1998) "Generic Mental Simulation Model." The "intuition" discussed in this analysis is classified into two types of intuition: the Expert Intuition which is based on one's own experiences, and Strategic Intuition which is based on the experience of others. Case study strategic management intuition and intuition, the experts were utilized differently. Features of professional intuition to work quickly without any effort by, while the strategic intuition, is time-consuming. Another feature that has already occurred, one expert intuition in decision-making about the widely used strategic intuition was used a lot in future decision-making. The case study results revealed that managers were using expert intuition and strategic intuition differentially. More specifically, Expert Intuition was activated effortlessly, while strategic intuition required more time. Also, expert intuition was used mainly for making judgments about events that have already happened, while strategic intuition was used more often for judgments regarding events in the future. The process of strategic intuition involved (1) Strategic concerns, (2) the discovery of medium, (3) Primary mental simulation, (4) The offsetting of key parameters, (5) secondary mental simulation, and (6) the decision making process. These steps were used to develop the "Strategic Intuition Decision-making Model" for Venture and Small-Business Executives. The case study results further showed that firstly, the success of decision-making was determined in the "secondary mental simulation' stage, and secondly, that more difficulty in management was encountered when expert intuition was used more than strategic intuition and lastly strategic intuition is possible to be educated.

• Journal of agricultural medicine and community health
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• 제38권3호
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• pp.163-173
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• 2013

Objectives: There has been an increase in the use of mind-body therapies to control cardiovascular risk factors recently. This trial was designed to determine whether the 'jeol'(Korean Buddhists' prostration) meditation program, as a new mind-body intervention, was effective in managing stress, depression and controlling cardiovascular risk factors in women working at a geriatric hospital. Methods: We conducted a randomized controlled trial to determine whether the 'jeol' meditation program could improve stress, anxiety, depression, and cardiovascular risk factors in women. We randomly assigned 57 participants to the intervention(29 participants) or control(28 participants) group. The subjects in the intervention group participated in a group Jeol meditation program once weekly, and practiced at home. The following variables were assessed: stress(Psychosocial Wellbeing Index), depression(Beck's Depression Inventory), body mass index(BMI), waist circumference, hemoglobin A1c(HbA1c), homeostasis model assessment(HOMA), low-density lipoprotein(LDL) cholesterol, high-density lipoprotein(HDL) cholesterol, and triglyceride were assessed. Results: After the 8-week program, 2 participants from the intervention group and 1 from the control group dropped out. The subjects in the intervention group exhibited decreased scores for stress(t=5.102, p<0.01), depression(t=5.259, p<0.01), BMI(t=2.942, p=0.007), and waist circumference(t=2.582, p=0.016); however these scores did not demonstrate a significant decrease in participants of the control group. The other variables showed no significant difference between the groups. Conclusion: The 'jeol' meditation program evidently reduced stress, anxiety, depression, body weight, and waist circumference in women, which suggests that this program could be employed as a mind-body therapies.

• Korean Journal of Environmental Biology
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• 제28권2호
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• pp.86-94
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• 2010

This study compares and contrasts the dynamics of plankton in 31 temperate lakes and reservoirs, and considers particularly the biomass ratio of zooplankton to phytoplankton and ecological model application. A total of 89 species of zooplankton were identified (70 rotifers, 14 cladocerans and 5 copepods) and a total of 554 species of phytoplankton were identified (176 Bacillariophyceae, 237 Chlorophyceae, 68 Cyanophyceae, and 73 other algal taxa). The total plankton abundance and species diversity were showed distinctive spatial and seasonal variation. Annual average phytoplankton density was $7,350{\pm}15,592$ cells $mL^{-1}$ (n=124), and the lowest was $855{\pm}448$ cells $mL^{-1}$ (n=4), while the highest was $72,048{\pm}13,4631$ cells $mL^{-1}$ (n=4). For zooplankton, small rotifer groups dominated the study sites, and approximately 3~10 species appeared in the study sites. Statistical analysis and an ecological model application revealed that the size of reservoirs affected the structure size of plankton community, i.e. relatively large number of species were found in smaller reservoirs. From this result, we can conclude that management strategy for the reservoir environment has to be focused more on small-size reservoirs, in terms of plankton community ecology.