• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.253-258
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• 2017

The purpose of this study is to measure the difference of corporate social responsibility(hereinafter referred to as "CSR") effects on SME's depending on the level of business risk perception. For this aim, we divided the analysis target SEM's into two groups according to the level of business risk perception and examine whether there is any difference in CSR effects through t-test and the test of the structural model invariance across the groups. As a results, the difference of CSR activities between the two groups occurred in the communication and strategy. In terms of CSR effects, there was a gap in the financial performance.

• Water Engineering Research
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• v.3 no.3
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• pp.163-176
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• 2002

In this study, laboratory experiments have been performed to investigate characteristics of the velocity fields and turbulence for non-buoyant plane jet in the vicinity of the jet nozzle using PIV system. The experimental results show that, in the transition region, the lateral velocity profile is in good agreement with Gaussian distribution. However, the coefficient of Gaussian distribution, $\K_{u,}$, decreases with longitudinal distance in the transition region. The existing theoretical equation for the centerline velocity tends to overestimate the measured data in the transition region. A new equation for the centerline velocity derived by incorporating varying $k_{u}$ gives better agreement with the measured data than the previous equation. The results of the turbulence characteristics show peak values are concentrated on the shear layers. The Reynolds shear stress profile shows the positive peak in the upper layer and negative peak in the lower layer. The turbulent kinetic energy also provides double peaks at the shear layers. The peak of the Reynolds shear stress and the turbulent kinetic energy increases until x/B=8, and then it decreases afterwards.s.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.53-59
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• 2021

The purpose of this study is to identify anxiety and depression level for corona virus 19 among hospital nurses to the spread of COVID-19. Data were collected from 232 nurses in 5 hospitals from August to September in 2020 using questionnaire. Characteristics relative to variables were measured, and analyzed using SPSS 26.0 program for descriptive statistics, t-test, ANOVA, and pearson's correlation. The depression level differed according to gender. The anxiety about COVID-19 infection showed a significantly positive correlation to depression (r=.26, p<.001). Based on these results, several roles and coping strategies were suggested to help nurses recover and maintain their psychological stability and mental health.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4142-4149
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• 2021

In the radiation protection application, the metal-polymer composites have been developed for their radiation shielding properties. In this research, the elastomer composites doped by 10 ㎛ and 100nm size of lead, bismuth and tungsten particles as filler with 30 and 60 wt percentages were prepared. To survey the shielding properties of the polymer composites using gamma-ray emitted from 152Eu and 137Cs sources, the gamma flux was measured by using NaI(Tl) detector, then the linear attenuation coefficient was calculated. Also, the Monte Carlo simulation (MCs) method was used. The results showed a direct relationship between the linear attenuation coefficients of the absorbent and filler ratio. Also, the decrease in the particle size of the shielding material in each weight percentage improved the radiation shielding features. When the dimension of the particles was in the order of nano-size, more attenuation was achieved. At low energies used for medical diagnostic X-ray applications due to the predominance of the photoelectric effect, bismuth and lead were suitable selection as filler.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.860-866
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• 2019

The lead element or its salts are good radiation shielding materials. However, their toxic effects are high. Due to less toxicity of bismuth salts, the radiation shielding properties of the bismuth salts have been investigated and compared to that of lead salts to establish them as a better alternative to radiation shielding material to the lead element or its salts. The transmission geometry was utilized to measure the mass attenuation coefficient (${\mu}/{\rho}$) of different salts containing lead and bismuth using a high-resolution HPGe detector and different energies (between 81 and 1333 keV) emitted from point sources of $^{133}Ba$, $^{57}Co$, $^{22}Na$, $^{54}Mn$, $^{137}Cs$, and $^{60}Co$. The experimental ${\mu}/{\rho}$ results are compared with the theoretical values obtained through WinXCOM program. The theoretical calculations are in good agreement with their experimental ones. The radiation protection efficiencies, mean free paths, effective atomic numbers and electron densities for the present compounds were determined. The bismuth fluoride ($BiF_3$) is found to have maximum radiation protection efficiency among the selected salts. The results showed that present salts are more effective for reducing the intensity of gamma photons at low energy region.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.960-966
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• 2021

A technical approach to design and carry out an experiment to determine the uptake of selected radionuclides in site-specific conditions in Kuwait was developed and successfully executed for developing a radioecological decision support system. The radionuclides from soil-to-plant transfer factors have been obtained for leafy and non-leafy vegetables, and root crops cultivated in Kuwait. Two types of vegetated soils were selected and spiked with high concentrations of three relatively short-lived selected radionuclides (⁸⁵Sr, ¹³⁴Cs, and ¹³³Ba). The highest strontium and barium transfer factors were found in the order: leafy vegetables > root crops > non-leafy vegetables. The approximate range of radiocesium transfer factor was found to be low in all plant groups and was comparable to those reported elsewhere in different soil types of temperate and tropical environments. A strong negative correlation between the obtained transfer factors and the distribution coefficient of the radionuclide in soil was found. It is recommended to adopt the newly derived parameters for the sensitive areas in Kuwait and other Gulf countries instead of using the generic parameters, whenever dose calculation codes are used. This will help to more accurately assess and predict the end results of the committed effective dose equivalent through ingestion pathway.

• Nuclear Engineering and Technology
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• v.53 no.5
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• pp.1652-1657
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• 2021

Nuclear materials can be utilized not only for peaceful uses, but also for military purposes; hence, the international community has devoted itself to the control, management and safeguarding of nuclear materials. Nuclear materials are of varying degrees of usability for development of nuclear weapons. Thus, several methods for assessing the attractiveness of nuclear materials for nuclear weapons purposes have been proposed. When these methods are applied to unirradiated depleted, natural, and low-enriched uranium (DU, NU, and LEU), they are certainly classified as non-attractive nuclear materials. However, when nuclear material attractiveness is to be evaluated for potential radiological dispersal device (RDD) uses, it is required to develop a different method for the different aspects and factors. In the present study, we derived a novel method for evaluating nuclear material attractiveness for use in RDD development. To this end, the specific activity and dose coefficient were identified as the two sub-factors, and, in consideration of those, the mass causing detrimental health effects was determined to be the main factor impacting on nuclear materials attractiveness. Based on this factor, the attractiveness of unirradiated DU, NU, and LEU for RDD use was qualitatively compared with that of ¹³⁷Cs.

• International Journal of Advanced Culture Technology
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• v.11 no.3
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• pp.310-314
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• 2023

The purpose of this study is to predict the remaining capacity of lithium-ion batteries and evaluate their performance using five artificial intelligence models, including linear regression analysis, decision tree, random forest, neural network, and ensemble model. We is in the study, measured Excel data from the CS2 lithium-ion battery was used, and the prediction accuracy of the model was measured using evaluation indicators such as mean square error, mean absolute error, coefficient of determination, and root mean square error. As a result of this study, the Root Mean Square Error(RMSE) of the linear regression model was 0.045, the decision tree model was 0.038, the random forest model was 0.034, the neural network model was 0.032, and the ensemble model was 0.030. The ensemble model had the best prediction performance, with the neural network model taking second place. The decision tree model and random forest model also performed quite well, and the linear regression model showed poor prediction performance compared to other models. Therefore, through this study, ensemble models and neural network models are most suitable for predicting the remaining capacity of lithium-ion batteries, and decision tree and random forest models also showed good performance. Linear regression models showed relatively poor predictive performance. Therefore, it was concluded that it is appropriate to prioritize ensemble models and neural network models in order to improve the efficiency of battery management and energy systems.

• Journal of Convergence for Information Technology
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• v.10 no.5
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• pp.92-100
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• 2020

The purpose of this study is to analyze the relationship between export weight, import weight, export amount, import amount, and trade balance of ICT industry. The data used were gathered from the Korea Customs Service trade statistics. The analysis period used annual data for 19 years from 2000 to 2018. The change rate analysis was shown in order of trade balance, export amount, import amount, import weight and export weight. The increase rate analysis showed that the trade balance was the highest at 919%.. In the correlation analysis, the trade balance and export amount were 0.95, showing the highest correlation coefficient. As a result of the regression analysis, the export amount for the trade balance, the dependent variable, was Coefficient 2.37, which was positive(+). Each variable is changing independently of one another. Since 2000, the trade balance of the Korean ICT industry has led 84% of Korea's total trade balance. In the future, Korea's ICT industry should be further developed for Korea's economic development, and exports should be further increased to increase the trade balance. In the next paper, we will try to find a field that can be specifically developed by subdividing the ICT industry.

• 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.