• Journal of Distribution Science
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• v.20 no.7
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• pp.97-105
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• 2022

Purpose: This study aims to analyze and prove the effect of logistic capability and Total Quality Management practices on Micro, Small and Medium Enterprises (SME) performance directly or mediated by non-financial performance. Research design, data and methodology: This study tested the hypothesis using Hierarchical multiple regression analysis, the method of data collection in this study was using questionnaire, the sampling technique was purposive sampling technique, with SME that has been established for more than 5 years and manufacturing. The data analyzed were 180 respondents using SPSS 25. Results: The findings showed that logistic capability has direct and indirect effects on SME financial performance and has a positive effect on SME financial performance mediated by non-financial performance. While the total quality management practices have a positive effect on SME financial performance mediated by non-financial performance. Thus, companies can achieve maximum financial performance if they invest in developing employee knowledge and concerning on non-financial actions, such as employee satisfaction, innovation and proactively seeking market opportunities. Conclusions: In conclusion, one of the main factors that companies need to consider to improve financial performance is non-financial performance in mediating the effect of logistic capability and TQM practices on the financial performance of SMEs.

• Geomechanics and Engineering
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• v.28 no.1
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• pp.89-105
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• 2022

The behavior of the soil subgrade is complex and irregular against loads. When modeling, the soil is often replaced by a more straightforward system called a subgrade model. The Winkler method of linear elastic springs is a popular method of soil modeling in which the spring constant shows the modulus of subgrade reaction. In this research, the factors affecting the distribution of the modulus of subgrade reaction of elastoplastic subgrades are examined. For this purpose, critical theories about the modulus of subgrade reaction were examined. A square raft foundation on a sandy soil subgrade with was analyzed at different internal friction angles and Young's modulus values using ABAQUS software. To accurately model the actual soil behavior, the elastic, perfectly plastic constitutive model was applied to investigate a foundation on discrete springs. In order to increase the accuracy of soil modeling, equations have been proposed for the distribution of the subgrade reaction modulus. The constitutive model of the springs is elastic, perfectly plastic. It was observed that the modulus of subgrade reaction under an elastic load decreased when moving from the corner to the center of the foundation. For the ultimate load, the modulus of subgrade reaction increased as it moved from the corner to the center of the foundation.

• Structural Engineering and Mechanics
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• v.86 no.3
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• pp.349-359
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• 2023

This paper presents a technique for determining the optimal number of elements in stochastic finite element analysis based on reliability analysis. Using the change-of-variable perturbation stochastic finite element approach, the probability density function of the dynamic responses of stochastic structures is explicitly determined. This method combines the perturbation stochastic finite element method with the change-of-variable technique into a united model. To further examine the relationships between the random fields, discretization of the random field parameters, such as the variance function and the scale of fluctuation, is also performed. Accordingly, the reliability index is calculated based on the explicit probability density function of responses with Gaussian or non-Gaussian random fields in any number of elements corresponding to the random field discretization. The numerical examples illustrate the effectiveness of the proposed method for a one-dimensional cantilever reinforced concrete column and a two-dimensional steel plate shear wall. The benefit of this method is that the probability density function of responses can be obtained explicitly without the use simulation techniques. Any type of random variable with any statistical distribution can be incorporated into the calculations, regardless of the restrictions imposed by the type of statistical distribution of random variables. Consequently, this method can be utilized as a suitable guideline for the efficient implementation of stochastic finite element analysis of structures, regardless of the statistical distribution of random variables.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2590-2608
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• 2023

The high-altitude and mobility characteristics of unmanned aerial vehicles (UAVs) have made them a key element of new radio systems, particularly because they can exceed the limits of terrestrial networks. However, at high altitudes, UAVs can be significantly affected by intercell interference at a high line-of-sight probability. To mitigate this drawback, we propose an algorithm that selects the optimal beam to reduce interference and maximize transmission efficiency. The proposed algorithm comprises two steps: constructing a user-location-based fingerprint database according to the user types presented herein and cooperative beam selection. Simulations were conducted using cellular cooperative downlink systems for analyzing the performance of the proposed method, and the signal-to-interference-plus-noise cumulative distribution function and spectral efficiency cumulative distribution function were used as performance analysis indicators. Simulation results showed that the proposed algorithm could reduce the effect of interference and increase the performance of the desired signal. Moreover, the algorithm could efficiently reduce overheads and system cost by reducing the amount of resources required for information exchange.

• Journal of the Korean Society of Safety
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• v.35 no.3
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• pp.79-85
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• 2020

Ahn-heung Proving Ground(APG) of Agency for Defense Development(ADD) is the only weapon test site which has been performing firing tests for many kinds of missile, artillery and ammunition. APG has been performing the firing tests of so many times every year. The tests related to missiles, artillery and ammunitions cover 80% among the quantity of annual test events. The target area of many kinds of missile, artillery and ammunition is on the sea. Therefore, APG has its marine firing ranges which were approved by the ministry of Defense. Both weapons and ships can run into each other on the sea. APG has to monitor and detect the positions of the ships in the specific dangerous zone on the sea. The positions of the ships are detected by Scanter 2001 radar and GPS100 detection radar. Evading the time period when the ships appear very often on the sea may be a good solution to keep the maritime safety. And evading the place where the ships appear very often on the sea may be a good solution as well. This paper is to analyze the ships' distribution characteristics of marine firing range, which are to raise the efficiency of many kinds firing tests which have been performed in APG of ADD. Ship distribution data from February 2014 to December 2016 were used in this paper. Ship distribution was analyzed with monthly data, seasonal data and etc. The number of the ships in approved sea area is higher in the morning than in the afternoon, and in fall than other seasons, and from August to November, and below 0.5 m in the hight of wave. Using the these conditions, we can raise the test efficiency of many kinds firing tests and guarantee maritime safety. The number of the ships in approved sea area is entirely unrelated to visibility of the sea. The time period when the number of the ships are high on the sea is morning. The season when the number of the ships are comparatively high on the sea is fall. APG of ADD could raise the efficiency of the firing tests and improve the maritime safety, using the analysis results of the characteristics on the ship distribution.

• Progress in Medical Physics
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• v.23 no.3
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• pp.162-168
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• 2012

In proton therapy, in vivo dose verification is one of the most important parts to fully utilize characteristics of proton dose distribution concentrating high dose with steep gradient and guarantee the patient safety. Currently, in order to image the proton dose distribution, a prompt gamma distribution detection system, which consists of an array of multiple CsI(Tl) scintillation detectors in the vertical direction, a collimator, and a multi-channel DAQ system is under development. In the present study, the optimal design of prompt gamma distribution detection system was studied by Monte Carlo simulations using the MCNPX code. For effective measurement of high-energy prompt gammas with enough imaging resolution, the dimensions of the CsI(Tl) scintillator was determined to be $6{\times}6{\times}50mm^3$. In order to maximize the detection efficiency for prompt gammas while minimizing the contribution of background gammas generated by neutron captures, the hole size and the length of the collimator were optimized as $6{\times}6mm^2$ and 150 mm, respectively. Finally, the performance of the detection system optimized in the present study was predicted by Monte Carlo simulations for a 150 MeV proton beam. Our result shows that the detection system in the optimal dimensions can effectively measure the 2D prompt gamma distribution and determine the beam range within 1 mm errors for 150 MeV proton beam.

• The Korean Journal of Applied Statistics
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• v.32 no.5
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• pp.693-702
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• 2019

Deep learning has gained popularity for the classification and prediction task. Neural network layers become deeper as more data becomes available. Saturation is the phenomenon that the gradient of an activation function gets closer to 0 and can happen when the value of weight is too big. Increased importance has been placed on the issue of saturation which limits the ability of weight to learn. To resolve this problem, Glorot and Bengio (Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 249-256, 2010) claimed that efficient neural network training is possible when data flows variously between layers. They argued that variance over the output of each layer and variance over input of each layer are equal. They proposed a method of initialization that the variance of the output of each layer and the variance of the input should be the same. In this paper, we propose a new method of establishing initialization by adopting truncated normal distribution and truncated cauchy distribution. We decide where to truncate the distribution while adapting the initialization method by Glorot and Bengio (2010). Variances are made over output and input equal that are then accomplished by setting variances equal to the variance of truncated distribution. It manipulates the distribution so that the initial values of weights would not grow so large and with values that simultaneously get close to zero. To compare the performance of our proposed method with existing methods, we conducted experiments on MNIST and CIFAR-10 data using DNN and CNN. Our proposed method outperformed existing methods in terms of accuracy.

• The Bulletin of The Korean Astronomical Society
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• v.12
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• pp.4.2-4.2
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• 1987

• The Bulletin of The Korean Astronomical Society
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• v.15
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• pp.11.3-12
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• 1990

• The Bulletin of The Korean Astronomical Society
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• v.25 no.2
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• pp.38-38
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• 2000