• Journal of the Korean Geotechnical Society
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• v.22 no.8
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• pp.107-118
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• 2006

Among a variety of influencing components, time-variant seepage and long-term underground motion are important to understand the abnormal behavior of tunnels. Excessiveness of these two components could be the direct cause of severe damage on tunnels, however, it is not easy to quantify the effect of these on the behavior of tunnels. These parameters can be estimated by using inverse methods once the appropriate relationship between inputs and results is clarified. Various inverse methods or parameter estimation techniques such as artificial neural network and least square method can be used depending on the characteristics of given problems. Numerical analyses, experiments, or monitoring results are frequently used to prepare a set of inputs and results to establish the back analysis models. In this study, a back analysis method has been developed to estimate geotechnically hard-to-known parameters such as permeability of tunnel filter, underground water table, long-term rock mass load, size of damaged zone associated with seepage and long-term underground motion. The artificial neural network technique is adopted and the numerical models developed in the first part are used to prepare a set of data for learning process. Tunnel behavior, especially the displacements of the lining, has been exclusively investigated for the back analysis.

• Journal of the Korean earth science society
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• v.45 no.2
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• pp.157-171
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• 2024

The purposes of this study were: (1) to revalidate the revised Systems Thinking Measuring Instrument (Re_STMI) reported by Lee et al. (2024) among Vietnamese high school students and (2) to investigate the differences in systems thinking abilities between Korean and Vietnamese high school students. To achieve this, data from 234 Vietnamese high school students who responded to translated Re_STMI consisting of 20 items and an Scale consisting of 20 items were used. Validity analysis was conducted through item response analysis (Item Reliability, Item Map, Infit and Outfit MNSQ, DIF between male and female) and exploratory factor analysis (principal axis factor analysis using Promax). Furthermore, structural equation modeling was employed with data from 475 Korean high school students to verify the latent mean analysis. The results were as follows: First, in the item response analysis of the 20 translated Re_STMI items in Vietnamese, the Item Reliability was .97, and the Infit MNSQ ranged from .67 to 1.38. The results from the Item Map and DIF analysis align with previous findings. In the exploratory factor analysis, all items were loaded onto intended sub-factors, with sub-factor reliabilities ranging from .662 to .833 and total reliability at .876. Confirmatory factor analysis for latent mean analysis between Korean and Vietnamese students yielded acceptable model fit indices (χ²/df: 2.830, CFI: .931, TLI: .918, SRMR: .043, RMSEA: .051). Lastly, the latent mean analysis between Korean and Vietnamese students revealed a small effect size in systems analysis, mental models, team learning, and shared vision factors, whereas a medium effect size was observed in personal mastery factors, with Vietnamese high school students showing significantly higher results in systems thinking. This study confirmed the reliability and validity of the Re_STMI items. Furthermore, international comparative studies on systems thinking using Re_STMI translated into Vietnamese, English, and other languages are warranted in the context of students' systems thinking analysis.

• The Journal of Korean Institute for Practical Engineering Education
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• v.2 no.2
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• pp.120-136
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• 2010

As there has recently been a rapid increase in importance of lifelong study, the number of learners participating in lifelong educational programs is increasing geometrically and lifelong educational institutions turned out to be the best one where everyone wants to study. Hereupon, aimed at team leaders managing the whole nation lifelong institutions and teachers interacting briskly with learners, we tried to research and analyze main cause affecting performances of lifelong educational institutions of university in this study based on Resource Based View and Dynamic Capability Theory for continuous development of lifelong educational institutions and securement of the competition. The contents and results of this study run as follows First, We tried to investigate the relation between resources and performances of lifelong educational institutions of university as contents and results of this study. The results were analyzed that material resources like an easy accessibility, superiority of facilities and teachers' excellence of lifelong educational institutions have an beneficial influence. Second, We tried to understand a leading cause affecting Dynamic Capabilities of lifelong educational institutions. The analyzed results were that material and human resources like easy accessibility, superiority of facilities, superiorities of teachers and director's empowering readership as a superior and organizational culture(autonomy, interaction) affect Dynamic Capabilities. These results could be understood that lifelong educational institution characteristics of university are well reflected. Third, We tried to find that even though elements of Resource Based view are surely important, Dynamic Capabilities of the organization are more important for continuous development and growth of lifelong educational institutions. Upon investigation, we found that there were mediating effectiveness in relations between Absorptive Capability and Innovative Capability which are Dynamic Capabilities and performances. Like preceding, there wes also mediating effectiveness in relations between empowering and organizational culture(autonomy, interaction) of a superior. And to conclude, superiority of resources could contribute to developing lifelong educational institutions to some degree but considering features of lifelong educational markets rapidly changed, Dynamic Capabilities of organization are more important for continuous growth and expensive preferability.