• Journal of Korea Water Resources Association
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• v.52 no.6
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• pp.381-395
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• 2019

The purpose of this study is to predict agricultural reservoir storage rate (RSR) in a month. This algorithm was developed by multiple linear regression model (MLRM) which included the past 3 months RSRs data and the future climate change scenarios. In order to improve use of predicted RSR, this study need the severe criteria in terms of drought. So, the predicted RSR was indexed as the 3 months reservoir drought index (RDI3) and then it was disaggregated into drought duration, severity, and intensity. For the future RSR estimation by climate change scenarios, the 6 RCP 8.5 scenarios of HadGEM2-ES, CESM1-BGC, MPI-ESM-MR, INM-CM4, FGOALS-s2, and HadGEM3-RA were used in three future evaluation periods (S1: 2011~2040, S2: 2041~2070, S3: 2071~2099). The future S3 period of HadGEM2-ES scenario which has the biggest increase in precipitation and temperature showed the largest decrease to 60.2% among the 6 scenarios compared to the historical RSR (1976~2005) 77.3%. In contrast, INM-CM4 scenario which has smallest changes in precipitation and temperature in S3 period showed the smallest decrease to 72.8%. For the CESM1-BGC and MPI-ESM-MR, FGOALS-s2, and HadGEM3-RA, the S3 period RSR showed 72.6%, 72.6%, 67.4%, and 64.5% decrease respectively. The future severe drought condition of RDI3 below -0.25 showed the increase trend for the number and severity up to -2.0 during S3 period.

• Management & Information Systems Review
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• v.38 no.1
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• pp.1-21
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• 2019

This study focuses on (1) the relationship between the network intensity of top managers and the R&D investment of Korean firms, and (2) the moderating effects of the type (related-division vs. unrelated-division) and system (physical division vs. spin-offs) of corporate division on this relationship. The sample of this study was all type and/or system of corporate division implemented by Korean firms during 18-years (1999-2016) study periods. The results of multiple regression analyses as follow. First, as was expected in hypothesis 1 the network intensity of top managers has a strong positive linear relation with the R&D investment of Korean firms. Second, regarding the moderating effect of division type the results show that related-divisions significantly intensify the positive relationship of the network intensity of top managers with the R&D of Korean firms although unrelated-divisions did not. Third, in the analysis of moderating effect of corporate division system the results present the stronger positive moderating effect of spin-offs rather than physical divisions. The findings of the study implies that strong network intensity of top managers can be beneficial to long-term decision such as R&D investment of Korean firms. They accords to network theory that emphasize the importance of strong network effect among top managers based on their trust. The findings also implies that researchers and practitioners should consider organizational-level factors such as organizational structure, culture, corporate governance, etc as well as individual-level factors such as the characteristics and relationships of organizational members when making the decision for firm.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.1-6
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• 2019

In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.

• Journal of The Korean Association For Science Education
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• v.39 no.2
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• pp.295-305
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• 2019

In previous study, visual representation competence taxonomy (VRC-T), which is composed of two dimensions, was developed for the purpose of promoting effective visual representation use and research in science education. In this study, elementary school students' visual representation competence for shadow phenomenon was investigated using VRC-T. In terms of visual representation competence, 'interpretation' was the highest score, followed by 'construction' and 'integration'. It also showed that students' visual representation competence was not high even after learning shadow-related units in the regular curriculum. On the other hand, text-based scientific knowledge was not correlated with all categories of visual representation competence. This indicates that there is a need to emphasize visual representation more in science class. Finally, hierarchical relationship among cognitive processes of VRC-T was explored according to ordering theory. If the tolerance level is somewhat loosened, a linear hierarchical relationship was found between the six cognitive processes. This suggests that VRC-T is an analytical framework that can be useful when designing assessment tools, tasks, and science class activities to enhance visual representation competence.

• Advances in nano research
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• v.10 no.2
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• pp.115-128
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• 2021

In this article, free vibration behavior of electro-magneto-thermo sandwich Timoshenko beam made of porous core and Graphene Platelet Reinforced Composite (GPLRC) in a thermal environment is investigated. The governing equations of motion are derived by using the modified strain gradient theory for micro structures and Hamilton's principle. The magneto electro are under linear function along the thickness that contains magnetic and electric constant potentials and a cosine function. The effects of material length scale parameters, temperature change, various distributions of porous, different distributions of graphene platelets and thickness ratio on the natural frequency of Timoshenko beam are analyzed. The results show that an increase in aspect ratio, the temperature change, and the thickness of GPL leads to reduce the natural frequency; while vice versa for porous coefficient, volume fractions and length of GPL. Moreover, the effect of different size-dependent theories such as CT, MCST and MSGT on the natural frequency is investigated. It reveals that MSGT and CT have most and lowest values of natural frequency, respectively, because MSGT leads to increase the stiffness of micro Timoshenko sandwich beam by considering three material length scale parameters. It is seen that by increasing porosity coefficient, the natural frequency increases because both stiffness and mass matrices decreases, but the effect of reduction of mass matrix is more than stiffness matrix. Considering the piezo magneto-electric layers lead to enhance the stiffness of a micro beam, thus the natural frequency increases. It can be seen that with increasing of the value of WGPL, the stiffness of microbeam increases. As a result, the value of natural frequency enhances. It is shown that in hc/h = 0.7, the natural frequency for WGPL = 0.05 is 8% and 14% less than its for WGPL = 0.06 and WGPL = 0.07, respectively. The results show that with an increment in the length and width of GPLs, the natural frequency increases because the stiffness of micro structures enhances and vice versa for thickness of GPLs. It can be seen that the natural frequency for aGPL = 25 ㎛ and hc/h = 0.6 is 0.3% and 1% more than the one for aGPL = 5 ㎛ and aGPL = 1 ㎛, respectively.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.59-69
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• 2021

Recently, large-scale offshore and coastal structures have been constructed owing to the increasing interest in eco-friendly energy development. To achieve this, precise simulations of waves are necessary to ensure the safe operations of marine structures. Several experiments are required in the field to understand the offshore wave; however, in terms of scale, it is difficult to control variables, and the cost is significant. In this study, numerical waves under various wave conditions are produced using a piston-type wavemaker, and the produced wave profiles are verified by comparing with the results from a numerical wave tank (NWT) modeled using the smoothed particle hydrodynamics (SPH) method and theoretical equations. To minimize the effect by the reflected wave, a mass-weighted damping zone is set at the right end of the NWT, and therefore, stable and uniform waves are simulated. The waves are generated using the linear and Stokes wave theories, and it is observed that the numerical wave profiles calculated by the Stokes wave theory yield high accuracy. When the relative depth is smaller than two, the results show good agreement irrespective of the wave steepness. However, when the relative depth and wave steepness are larger than 2 and 0.04, respectively, the errors are negligible if the measurement position is close to the excitation plate. However, the error is 10% or larger if the measurement position is away from the excitation location. Applicable target wave ranges are confirmed through various case studies.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.275-286
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• 2021

In this study, the analytical solution for diffraction near a vertical detached breakwater was suggested by superposing the solutions of diffraction near a semi-infinite breakwater suggested previously using linear wave theory. The solutions of wave forces acting on front, lee and composed wave forces on both side were also derived. Relative wave amplitude changed periodically in space owing to the interactions between diffracting waves and standing waves on front side and the interactions between diffracting waves from both tips of a detached breakwater on lee side. The wave forces on a vertical detached breakwater were investigated with monochromatic, uni-directional random and multi-directional random waves. The maximum composed wave force considering the forces on front and lee side reached maximum 1.6 times of wave forces which doesn't consider diffraction. This value is larger than the maximum composed wave force of semi-infinite breakwater considering diffraction, 1.34 times, which was suggested by Jung et al. (2021). The maximum composed wave forces were calculated in the order of monochromatic, uni-directional random and multi-directional random waves in terms of intensity. It was also found that the maximum wave force of obliquely incident waves was sometimes larger than that of normally incident waves. It can be known that the considerations of diffraction, the composed wave force on both front and lee side and incident wave angle are important from this study.

• Korean Journal of Cognitive Science
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• v.33 no.1
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• pp.1-22
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• 2022

Lavie's perceptual load theory (Lavie, 1995) proposes that the influence of distractors would be blocked as the load gets higher. Studies of perceptual load have usually adopted the flanker task, developed by Eriksen and Eriksen (1974), which measures reaction time on the target flanked by distractors. In the post-cueing forced task, participants should report the identity of the target cued later, and negative repetition effect (NRE) has often been observed. NRE means the effect that the accuracy of identification is worse when the target is flanked by the same nontargets than when flanked by different nontargets. This study has tried to check whether perceptual load has an effect on identification rate and NRE. Experiment 1 manipulated the similarity between targets and a distractor, and observed a tendency of NRE, but not the effect of perceptual load. Experiment 2 used 4, 2 (in two kinds of diagonal arrangement), or none distractors of the same identity to burden more perceptual load. NRE was significant and perceptual load showed significance but not a linear trend. Experiment 3 checked again whether NRE would be varied according to two levels of perceptual load strengthened by positional variability of load stimuli, but did not find the effect of perceptual load. It is concluded that perceptual load might have a limited effect on the early stage of perceptual processing due to divided attentional processing of the targets briefly exposed. Implications of this study were discussed.

• Geomechanics and Engineering
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• v.28 no.3
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• pp.299-311
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• 2022

Water-resisting key stratum (WKS) between coal seams is an important barrier that prevents water inrush from goaf in roof under multi-seam mining. The occurrence of water inrush can be evaluated effectively by analyzing the fracture of WKS in multi-seam mining. A "long beam" water inrush mechanical model was established using the multi-seam mining of No. 2+3 and No. 8 coal seams in Xiqu Mine as the research basis. The model comprehensively considers the pressure from goaf, the gravity of overburden rock, the gravity of accumulated water, and the constraint conditions. The stress distribution expression of the WKS was obtained under different mining distances in No. 8 coal seam. The criterion of breakage at any point of the WKS was obtained by introducing linear Mohr strength theory. By using the mechanical model, the fracture of the WKS in Xiqu Mine was examined and its breaking position was calculated. And the risk of water inrush was also evaluated. Moreover, breaking process of the WKS was reproduced with Flac3D numerical software, and was analyzed with on-site microseismic monitoring data. The results showed that when the coal face of No. 8 coal seam in Xiqu Mine advances to about 80 m ~ 100 m, the WKS is stretched and broken at the position of 60 m ~ 70 m away from the open-off cut, increasing the risk of water inrush from goaf in roof. This finding matched the result of microseismic analysis, confirming the reliability of the water inrush mechanical model. This study therefore provides a theoretical basis for the prevention of water inrush from goaf in roof in Xiqu Mine. It also provides a method for evaluating and monitoring water inrush from goaf in roof.

• Economic Analysis
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• v.27 no.1
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• pp.67-90
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• 2021

This study found an interesting fact that the nonlinear relationship structure between volatility and trading volume changed before and after the COVID-19 pandemic according to empirical analysis using Bitcoin (BTC) market data that sensitively reflects investors' trading behavior. That is, their relationship appeared positive (+) in a stable market state before COVID-19 pandemic, as in theory based on the information flow paradigm. In a state under severe market stress due to COVID-19 pandemic, however, their dependence structure changed and even negative (-). This can be seen as a consequence of increased market stress caused by COVID-19 pandemics from a behavioral economics perspective, resulting in structural changes in the asset market and a significant impact on the nonlinear dependence of volatility and trading volume (in particular, their dependence at extreme quantiles). Hence, it should be recognized that in addition to information flows, psychological phenomena such as behavioral biases or herd behavior, which are closely related to market stress, can be a key in changing their dependence structure. For empirical analysis, this study performs a test of Ross (2015) for detecting a structural change, and proposes a Copula Regression Quantiles (CRQ) approach that can identify their nonlinear relationship structure and the asymmetric dependence in their distribution tails without the assumption of i.i.d. random variable. In addition, it was confirmed that when the relationship between their extreme values was analyzed by linear models, incorrect results could be derived due to model specification errors.