• Journal of Environmental Health Sciences
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• v.47 no.1
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• pp.64-77
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• 2021

Objective: Biological monitoring of trace elements in human blood samples has become an important indicator of the health environment. The purpose of this study was to detect and evaluate multiple metal items in blood samples based on ICP-MS, to perform comparative evaluation with the existing analysis method, and to develop and verify a new method. Methods: 100 μL of whole blood from 80 healthy subjects was used to analyze ten metals (Sb, tAs, Cd, Pb, Mn, Hg, Mo, Ni, Se, Tl) using ICP-MS. Verification of the analysis method included calculation of linearity, accuracy, precision and detection limits. In addition, a comparative test with the conventional graphite furnace atomic absorption spectroscopy (GF-AAS) method was performed. In the case of Pb, Cd, and Hg in whole blood, cross-analysis between Pb, Cd, and Hg analysis methods was performed to confirm the difference between the existing method and the new method (ICP-MS). Results: The coefficient of determination (R2) was 0.999 or higher in seven items and 0.995 or higher in three items. The Pb result showed that Pearson's correlation coefficient was very high at 0.983, and the intraclass correlation coefficient was 0.966. The Cd result showed that Pearson's correlation coefficient was 0.917 between the existing method and the new analysis concentration value. Its intraclass correlation coefficient was 0.960, and there was no significant difference between the two groups. Hg had a low correlation at 0.687, and the intraclass correlation coefficient was 0.761, which was lower than that of Pb and Cd. The intra-day and inter-day accuracy of Pd and Cd were satisfactory, but Hg did not meet the criteria for both accuracy and precision when compared with the conventional analysis method. Conclusion: This study can be meaningful in that it proposes a more efficient and feasible analysis method by verifying a blood heavy metal concentration experiment using multiple simultaneous analyses. All samples were processed and analyzed using the new ICP-MS. It was confirmed that the agreement between the two methods was very high, with the agreement between the current and new methods being 0.769 to 0.998. This study proposes an efficient simultaneous methodology capable of analyzing multiple elements with small samples. In the future, studies of various applications and the reliability of ICP-MS analysis methods are required, and research on the verification of accurate, precise, and continuous analysis methods is required.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.43-50
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• 2021

For the implementation of innovative products or services companies use different innovation strategies, in particular, outsourcing is quite widespread, given the high level of specialization and professionalism of companies that provide such services. The aim of this article was to evaluate the link between outsourcing of innovative activities and indicators of companies' efficiency. The methodology of the research includes the methods of correlation analysis and regression analysis to reveal the correlation between the use of outsourcing of innovative products and services and the turnover of the EU enterprises. The results show a high level of innovative activity of EU enterprises (50.3% innovatively active). Innovative business processes are the most widespread form of innovation activity (41% of enterprises implement business processes, and the indicator is higher than 41% in the most developed EU countries). The turnover of enterprises with new or substantially improved products was found to grow by 10.92% for the period 2016-2018. The correlation analysis shows weak direct links between the indicator of turnover growth and the number of enterprises that have independently implemented innovations, or have implemented innovations jointly with third-party companies, or using outsourcing services. The highest level of direct connection was found between the growth of turnover of enterprises that launched a new product for the market and the growth of the number of enterprises that implemented innovations with the involvement of organizations (correlation 0.273). Based on the regression analysis it was found that with a 1% change in the growth rate of the number of innovation-active enterprises, the growth rate of turnover from new or improved products increased by 5.67%. At the same time, with a 1% change in the growth rate of the number of enterprises that implement innovation through outsourcing, the growth rate of turnover from new or improved products will increase by 7.15%.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1519-1522
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• 2002

In this paper, we propose a new adaptive dissolve detection method based on the analysis of a dissolve modeling error that is the difference between an ideally modeled dissolve curve without any correlation and an actual variance curve with a correlation. The dissolve modeling error is determined based on a correlation between two scenes and variances for each scene. First, Candidate regions are extracted by using the characteristics of a parabola that is downward convex, then the candidate region will be verified based on a dissolve modeling error. If a dissolve modeling error on a candidate region is less than a threshold that is defined by a dissolve modeling error with a target correlation, the candidate region should be a dissolve region with a correlation less than the target correlation. The threshold is adaptively determined based on the variances between the candidate regions and the target correlation. By considering the correlation between neighbor scenes, the proposed method is able to be a semantic scene-change detector. The proposed algorithm was tested on various types of data and its performance proved to be more accurate and reliable when compared with other commonly used methods

• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.472-476
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• 2014

The Joint Transform Correlator (JTC) has been the most suitable technique for real time optical pattern recognition and target tracking applications. This paper proposes a new application of the JTC system for an analysis of the blurring effect of the optical images caused by a defocused lens. We present the relation between the correlation peak, optical transfer function (OTF), and the amount of blurring caused by focusing error. Moreover, we show a possibility of calibrating the blurred image by simply measuring the correlation peak.

• Earthquakes and Structures
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• v.11 no.5
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• pp.779-807
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• 2016

Ground Motion Prediction Equations (GMPEs) are essential tools in seismic hazard analysis. With the introduction of probabilistic approaches for the estimation of seismic response of structures, also known as, performance based earthquake engineering framework; new tasks are defined for response spectrum such as the reference criterion for effective structure-specific selection of ground motions for nonlinear time history analysis. One of the recent efforts to introduce a high quality databank of ground motions besides the corresponding selection scheme based on the broadband spectral consistency is the development of SIMBAD (Selected Input Motions for displacement-Based Assessment and Design), which is designed to improve the reliability of spectral values at all natural periods by removing noise with modern proposed approaches. In this paper, a new global GMPE is proposed by using selected ground motions from SIMBAD to improve the reliability of computed spectral shape indicators. To determine regression coefficients, 204 pairs of horizontal components from 35 earthquakes with magnitude ranging from Mw 5 to Mw 7.1 and epicentral distances lower than 40 km selected from SIMBAD are used. The proposed equation is compared with similar models both qualitatively and quantitatively. After the verification of model by several goodness-of-fit measures, the epsilon values as the spectral shape indicator are computed and the validity of available prediction equations for correlation of the pairs of epsilon values is examined. General consistency between predictions by new model and others, especially, in short periods is confirmed, while, at longer periods, there are meaningful differences between normalized residuals and correlation coefficients between pairs of them estimated by new model and those are computed by other empirical equations. A simple collapse assessment example indicate possible improvement in the correlation between collapse capacity and spectral shape indicators (${\varepsilon}$) up to 20% by selection of a more applicable GMPE for calculation of ${\varepsilon}$.

• Korea Trade Review
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• v.47 no.1
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• pp.99-114
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• 2022

This paper analyzed the dynamic conditional correlation between the carbon emission trading prices of Korea, China, EU, New Zealand. This paper was analyzed using the daily data of carbon emission trading prices of each country from January 12, 2015 to January 13, 2021 using the DCC-GARCH model. Summarizing the research results, first, the dynamic conditional correlation between carbon emission trading prices in the EU, Korea, and China, excluding New Zealand, was strong, indicating that there was a co-movement phenomenon. Second, it was found that carbon emission trading prices in major countries have a stronger tendency to co-movement due to global shocks. Third, it appears that the dynamic conditional correlation between the carbon emission trading prices of Korea and China is gradually strengthening. This study confirmed that the co-movement between carbon emission trading prices in Korea and other countries gradually intensified as time passed. In particular, it is meaningful in suggesting the implication that the phenomenon of co-movement between carbon emission trading prices in Korea and China is gradually intensifying.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.4
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• pp.274-286
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• 2003

Numerical simulations are performed to investigate the turbulent convective heat transfer of the supercritical carbon dioxide flows in vertical and horizontal square ducts. The gas cooling process at the supercritical state experiences a sudden change in thermodynamic and transport properties. This results in the extraordinary variations of the heat transfer coefficients in the supercritical state, which are much different from those of single or two phase flows. Algebraic second moment closure which can include the effects of large thermophysical property variations of carbon dioxide and of buoyancy is employed to model the Reynolds stresses and turbulent heat fluxes in the governing equations. The previous correlations for the turbulent heat transfer coefficient for the supercritical carbon dioxide flows couldn't reflect the buoyancy effect. The present results are used to establish a new heat transfer coefficient correlation including the effects of large thermophysical property variation and buoyancy on in-duct cooling process of supercritical carbon dioxide.

• Journal of applied mathematics & informatics
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• v.30 no.5_6
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• pp.903-911
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• 2012

Let $\{u(t)\}$ and $\{u(dt)\}$ be two maximal length sequences of period $2^n-1$. The cross-correlation is defined by $C_d({\tau})=\sum{_{t=0}^{2^n-2}}(-1)^{u(t+{\tau})+v(t)$ for ${\tau}=0,1,{\cdots},2^n-2$. In this paper, we propose a new proof for finding the values and the number of occurrences of each value of $C_d({\tau})$ when $d=2^{k-2}(2^k+3)$, where $n=2k$, $k$ is a positive integer.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.5
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• pp.1388-1394
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• 2016

This paper presents a experimental study of two-phase flow boiling of FC-72 in multi channels. Flow boiling heat transfer coefficients are obtained with mass flux ranging from 152.9 to $353.9kg/m^2s$ and heat flux from 5.6 to $46.1kW/m^2$. The experimental results show that the heat transfer is governed by nucleate boiling mechanism in the low heat flux region. However, it is found that the effects of nucleate boiling and forced convection boiling are combined as the heat flux increases. A new correlation to predict the heat transfer coefficient is developed by using the dimensionless number such as Reynolds number, Weber number, boiling number. This correlation shows good predictive accuracy against the measured data.

• Journal of the Optical Society of Korea
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• v.14 no.2
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• pp.90-96
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• 2010

Joint transform correlator (JTC) has been the most suitable technique for real time pattern recognition. This paper proposes a new phase adjustment which adopts two steps of random phase adjustment in the spatial domain and additional phase adjustment in the Fourier domain. Simulated results are presented to show the optimum condition of the phase adjustment and the effect on the correlation peaks, the peak signal-to-noise ratio and the level of discrimination.