• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.51-56
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• 2021

In this paper, performance degradation in the cross-eye jamming due to amplitude mismatch of two jamming antennas is considered. The mismatch of the amplitude ratio is modeled as a random variable with a normal distribution of the difference between the actual amplitude ratio and the nominal amplitude ratio due to mechanical defects. In the proposed analytic performance analysis, the first-order Taylor series expansion and the second-order Taylor series expansion is adopted. Performance measure of the cross-eye jamming is the mean square difference (MSD). The analytically derived MSD is validated by comparing the analytically derived MSD with the first-order Taylor series-based simulation-based MSD and the second-order Taylor series-based simulation-based MSD. It shows that the analysis-based MSD is superior to the Monte-Carlo-based MSD, which has a high calculation cost.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1187-1198
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• 2021

Sea wind isrecently drawing attraction as one of the sources of renewable energy. Thisstudy describes a new method to produce a 10 m resolution sea wind field using Sentinel-1 images and low-resolution NWP (Numerical Weather Prediction) data with artificial intelligence technique. The experiment for the South East coast in Korea, 2015-2020,showed a 40% decreased MAE (Mean Absolute Error) than the generic CMOD (C-band Model) function, and the CC (correlation coefficient) of our method was 0.901 and 0.826, respectively, for the U and V wind components. We created 10m resolution sea wind maps for the study area, which showed a typical trend of wind distribution and a spatially detailed wind pattern as well. The proposed method can be applied to surveying for wind power and information service for coastal disaster prevention and leisure activities.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.127-134
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• 2021

This study aims to determine the role of innovative capabilities as a mediator in analyzing entrepreneurial marketing's effect on sustainable competitive advantage in food and beverage micro-, small-, and medium- enterprises (MSMEs). Data was obtained from a food and beverage store manager in Tangerang City, comprising 119 samples. Furthermore, the G⁎Power, a tool used to calculate statistical power analysis for various t-tests, F tests, χ2 tests, z tests, and several exact tests, was used to determine the number of research samples, the α error probability of 5%, and 3 variables. The data collection method used questionnaires with Likert Scale 1-5 to indicate strongly disagree to strongly agree. To analyze data, we used Path Analysis supported by SmartPLS statistics software. Path analysis is a form of multiple regression statistical analysis that is used to evaluate causal models by examining the relationships between a dependent variable and two or more independent variables. It aims to provide estimates of the magnitude and significance of hypothesized causal connections between sets of variables. The data processing process took place in two stages, namely the estimation model testing with validity and reliability, and the structural model testing to decide the impact or correlation between variables utilizing the t-test. The result showed a positive and significant effect of entrepreneurial marketing to innovative capability and competitive advantage through the innovative capability of MSMEs.

• International Area Studies Review
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• v.16 no.1
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• pp.275-301
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• 2012

This study analyzes the regional disparity in India between 24 states over the period 1980 to 2009. The traditional regressive and spatial autoregressive models are used that includes measures of spatial effects. The results provide no evidence that convergence is valid in India. However, the results indicate that spatial interaction is an important element of state growth in India. The result of spatial analysis excluded two outliner states reveals more strong relationship between the weighted spatial income level and the state growth rates. Moreover, the results find that the coefficients of spatial lag of initial per capital and error terms are significantly negative. The coefficient of variation measures that the distribution of state income level has diverged over time. Therefore, this study concludes that the growth of regional state income does not have a tendency to converge rater than diverge. The results is rational because as the Indian economy is growing rapidly, some states grow faster than the others while initial poor states become the poorest ones, which increases regional disparity in India.

• Journal of the Korea Society for Simulation
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• v.27 no.4
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• pp.69-77
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• 2018

Launching system is designed to store the payload, withstand the rigors, and prevent it from rusting and damaging. The behavior during initial deployment of the missile is determined by production, assembly and insertion condition of a launching tube and a missile. The purpose of this research is to confirm the safety of a launching tube by statistically analyzing behavior of the missile, during initial deployment stage. Error parameters which effect initial behavior of the missile are selected and analyzed through Monte-Carlo Simulation. Based on the result of simulation, tip-off and stress distribution between rail and shoe is predicted by using the commercial analysis program called Recurdyn. Lastly, the safety factor is calculated based on yield strength of the material and maximum stress of the rail during the process of launching. The safety of the launching system is verified from the result of the safety factors.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.6
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• pp.331-337
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• 2018

This paper presents dynamic algorithm of the MLS(moving least squares) difference method using first order differential Approximation. The governing equations are only discretized by the first order MLS derivative approximation. The system equation consists of an assembly of the approximate function, so the shape of system equation is similar to FEM(finite element method). The CDM(central difference method) is used for time integration of dynamic equilibrium equation. The natural frequency analyses of the MLS difference method and FEM are performed, and two analysis results are compared. Also, the accuracy of the proposed numerical method is verified by displaying the dynamic analysis results together with the results by the existing second order differential approximation. In the process of assembling the first order MLS derivative approximation, the oscillation error was suppressed and the stress distribution was interpreted as relatively uniform.

• Ocean Systems Engineering
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• v.9 no.3
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• pp.287-328
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• 2019

Comprehensive understanding of the flood risk assessments via frequency analysis often demands multivariate designs under the different notations of return periods. Flood is a tri-variate random consequence, which often pointing the unreliability of univariate return period and demands for the joint dependency construction by accounting its multiple intercorrelated flood vectors i.e., flood peak, volume & durations. Selecting the most parsimonious probability functions for demonstrating univariate flood marginals distributions is often a mandatory pre-processing desire before the establishment of joint dependency. Especially under copulas methodology, which often allows the practitioner to model univariate marginals separately from their joint constructions. Parametric density approximations often hypothesized that the random samples must follow some specific or predefine probability density functions, which usually defines different estimates especially in the tail of distributions. Concentrations of the upper tail often seem interesting during flood modelling also, no evidence exhibited in favours of any fixed distributions, which often characterized through the trial and error procedure based on goodness-of-fit measures. On another side, model performance evaluations and selections of best-fitted distributions often demand precise investigations via comparing the relative sample reproducing capabilities otherwise, inconsistencies might reveal uncertainty. Also, the strength & weakness of different fitness statistics usually vary and having different extent during demonstrating gaps and dispensary among fitted distributions. In this literature, selections efforts of marginal distributions of flood variables are incorporated by employing an interactive set of parametric functions for event-based (or Block annual maxima) samples over the 50-years continuously-distributed streamflow characteristics for the Kelantan River basin at Gulliemard Bridge, Malaysia. Model fitness criteria are examined based on the degree of agreements between cumulative empirical and theoretical probabilities. Both the analytical as well as graphically visual inspections are undertaken to strengthen much decisive evidence in favour of best-fitted probability density.

• Atmosphere
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• v.29 no.2
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• pp.115-129
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• 2019

Surface winds over the ocean influence not only the climate change through air-sea interactions but the coastal erosion through the changes in wave height and direction. Thus, demands on a reliable projection of future changes in surface winds have been increasing in various fields. For the future projections, climate models have been widely used and, as a priori, their simulations of surface wind are required to be evaluated. In this study, we evaluate the climatological mean surface winds over the Korean Waters simulated by five regional climate models participating in Coordinated Regional Climate Downscaling Experiment (CORDEX) for East Asia (EA), an international regional climate model inter-comparison project. Compared with the ERA-interim reanalysis data, the CORDEX-EA models, except for HadGEM3-RA, produce stronger wind both in summer and winter. The HadGEM3-RA underestimates the wind speed and inadequately simulate the spatial distribution especially in summer. This summer wind error appears to be coincident with mean sea-level pressure in the North Pacific. For wind direction, all of the CORDEX-EA models simulate the well-known seasonal reversal of surface wind similar to the ERA-interim. Our results suggest that especially in summer, large-scale atmospheric circulation, downscaled by regional models with spectral nudging, significantly affect the regional surface wind on its pattern and strength.

• Geomechanics and Engineering
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• v.17 no.4
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• pp.367-374
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• 2019

This study concluded the results of a research on the features of cement based permeation grout, based on some important grout parameters, such as the rheological properties (yield stress and viscosity), coefficient of permeability to grout ($k_G$) and the inject ability of cement grout (N and $N_c$ assessment), which govern the performance of cement based permeation grouting in porous media. Due to the limited knowledge of these important grout parameters and other influencing factors (filtration pressure, rate and time of injection and the grout volume) used in the field work, the application of cement based permeation grouting is still largely a trial and error process in the current practice, especially in the local construction industry. It is seen possible to use simple formulas in order to select the injection parameters and to evaluate their inter-relationship, as well as to optimize injection spacing and times with respect to injection source dimensions and in-situ permeability. The validity of spherical and cylindrical flow model was not verified by any past research works covered in the literature review. Therefore, a theoretical investigation including grout flow models and significant grout parameters for the design of permeation grouting was conducted in this study. This two grout flow models were applied for three grout mixes prepared for w/c=0.75, w/c=1.00 and w/c=1.25 in this study. The relations between injection times, radius, pump pressure and flow rate for both flow models were investigated and the results were presented. Furthermore, in order to investigate these two flow model, some rheological properties of the grout mixes, particle size distribution of the cement used in this study and some geotechnical properties of the sand used in this work were defined and presented.

• Atmosphere
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• v.28 no.4
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• pp.479-490
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• 2018

This study assesses the prediction skill of regional scale model for the mean temperature anomaly over South Korea produced by Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF) chain. The initial and boundary conditions of WRF are derived from PNU CGCM. The hindcast period is 11 years from 2007 to 2017. The model's prediction skill of mean temperature anomaly is evaluated in terms of the temporal correlation coefficient (TCC), root mean square error (RMSE) and skill scores which are Heidke skill score (HSS), hit rate (HR), false alarm rate (FAR). The predictions of WRF and PNU CGCM are overall similar to observation (OBS). However, TCC of WRF with OBS is higher than that of PNU CGCM and the variation of mean temperature is more comparable to OBS than that of PNU CGCM. The prediction skill of WRF is higher in March and April but lower in October to December. HSS is as high as above 0.25 and HR (FAR) is as high (low) as above (below) 0.35 in 2-month lead time. According to the spatial distribution of HSS, predictability is not concentrated in a specific region but homogeneously spread throughout the whole region of South Korea.