• Analytical Science and Technology
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• v.29 no.4
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• pp.170-178
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• 2016

Accuracy and precision of ID methods for different spike isotopes of ⁷⁶Se, ⁷⁷Se, and ⁷⁸Se were compared for the analysis of Selenium using quadrupole ICP/MS equipped with Octopole reaction cell. From the analysis of Se inorganic standard solution, all of three spikes showed less than 1 % error and 1 % RSD for both short-term (a day) and long-term (several months) periods. They showed similar results with each other and ⁷⁸Se showed was a bit better than ⁷⁶Se and ⁷⁷Se. However, different spikes showed different results when NIST SRM 1568a and SRM 2967 were analyzed because of the several interferences on the m/z measured and calculated. Interferences due to the generation of SeH from ORC was considered as well as As and Br in matrix. The results showed similar accuracy and precisions against SRM 1568a, which has a simple background matrix, for all three spikes and the recovery rate was about 80% with steadiness. The %RSD was a bit higher than inorganic standard (1.8 %, 8.6 %, and 6.3 % for ⁷⁸Se, ⁷⁶Se and ⁷⁷Se, respectively) but low enough to conclude that this experiment is reliable. However, mussel tissue has a complex matrix showed inaccurate results in case of ⁷⁸Se isotope spike (over 100 % RSD). ⁷⁶Se and ⁷⁷Se showd relatively good results of around 98.6 % and 104.2 % recovery rate. The errors were less than 5 % but the precision was a bit higher value of 15 % RSD. This clearly shows that Br interferences are so large that a simple mathematical calibration is not enough for a complex-matrixed sample. In conclusion, all three spikes show similar results when matrix is simple. However, ⁷⁸Se should be avoided when large amount of Br exists in matrix. Either ⁷⁶Se or ⁷⁷Se would provide accurate results.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.89-101
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• 2015

This paper proposes a statistical model of 3-D positions when tracking moving targets using the uncooled infrared (IR) stereo camera system. The proposed model is derived from two errors. One is the position error which is caused by the sampling pixels in the digital image. The other is the timing jitter which results from the irregular capture-timing in the infrared cameras. The capture-timing in the IR camera is measured using the jitter meter designed in this paper, and the observed jitters are statistically modeled as Gaussian distribution. This paper derives an integrated probability distribution by combining jitter error with pixel position error. The combined error is modeled as the convolution of two error distributions. To verify the proposed statistical position error model, this paper has some experiments in tracking moving objects with IR stereo camera. The 3-D positions of object are accurately measured by the trajectory scanner, and 3-D positions are also estimated by stereo matching from IR stereo camera system. According to the experiments, the positions of moving object are estimated within the statistically reliable range which is derived by convolution of two probability models of pixel position error and timing jitter respectively. It is expected that the proposed statistical model can be applied to estimate the uncertain 3-D positions of moving objects in the diverse fields.

• Journal of KSNVE
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• v.8 no.5
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• pp.964-973
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• 1998

In this paper we propose a levitation and imbalance compensation controller design methodology of magnetic bearing system. In order to achieve levitation and elimination of unbalance vibartion in some operation speed we use the discrete-time Q-parameterization control. When rotor speed p = 0 there are no rotor unbalance, with frequency equals to the rotational speed. So in order to make levitatiom we choose the Q-parameterization controller free parameter Q such that the controller has poles on the unit circle at z = 1. However, when rotor speed p $\neq$ 0 there exist sinusoidal disturbance forces, with frequency equals to the rotational speed. So in order to achieve asymptotic rejection of these disturbance forces, the Q-parameterization controller free parameter Q is chosen such that the controller has poles on the unit circle at z = $exp^{ipTs}$ for a certain speed of rotation p ( $T_s$ is the sampling period). First, we introduce the experimental setup employed in this research. Second, we give a mathematical model for the magnetic bearing in difference equation form. Third, we explain the proposed discrete-time Q-parameterization controller design methodology. The controller free parameter Q is assumed to be a proper stable transfer function. Fourth, we show that the controller free parameter which satisfies the design objectives can be obtained by simply solving a set of linear equations rather than solving a complicated optimization problem. Finally, several simulation and experimental results are obtained to evaluate the proposed controller. The results obtained show the effectiveness of the proposed controller in eliminating the unbalance vibrations at the design speed of rotation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.638-643
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• 2004

소형화된 기계가공시스템은 사용재료의 다양화와 에너지 및 공간의 감소와 같은 장점을 가지고 작고 정밀한 부품을 가공할 수 있는 시스템으로 주목받고 있다. 이러한 시스템이 비록 그 크기가 일반적인 가공시스템에 비해 작지만 정렬 및 조립공정, 기계요소의 불완정성에 의한 기하학적 오차는 여전히 존재한다. 기하학적 오차 평가는 기계시스템의 정밀도를 효과적으로 적은 비용으로 향상시킬 수 있는 오차보정기술을 적용할 수 있는 토대가 된다. 일반적으로, 3 축의 직선축으로 이루어진 공작기계는 21 개의 오차요소를 가진다. 레이져간섭계는 이러한 오차요소를 평가하는데 널리 사용되고 있지만 광학계를 정렬하고 설치하는 데 많은 어려움이 있으며 한번의 설치로 한 개의 오차요소만이 측정 가능하다. 또한, 소형공작기계의 경우, 그 크기로 인해 기존의 레이져 간섭계를 직접적으로 적용할 수 없다. 따라서, 본 연구에서는 소형공작기계를 포함한 소형가공시스템의 기하학적 오차 평가를 위한 새로운 다자유도 측정시스템을 제안하였다. 5 개의 정전용량변위센서를 사용하는 이 시스템을 통해 한 축의 움직임에 따른 5 개의 오차요소를 동시에 측정 가능하다. 균질 변환행렬을 이용한 측정알고리듬을 구성하고 이를 모의시험을 통해 평가하였다. 수학적 모델링을 통해 각 센서의 출력값을 유도하고 이를 이용하여 각 오차요소를 계산하기 위한 식을 유도하였다. 여기서, 단순화된 식을 적용한 경우, 임의의 오차에 대한 측정 알고리듬의 정확도를 평가하였다. 또한, 측정 시스템의 설치시 발생하는 셋업오차에 대한 측정 알고리듬의 민감도 분석을 행하였다. 제안하는 측정 시스템은 구조가 간단하고 고가의 부가장비가 필요치 않다. 또한, 적은 비용으로 구성할 수 있으며 높은 측정 정밀도를 가지고 소형가공시스템에 필요한 오차 평가를 행할 수 있다.가 함유된 계란을 생산하고 섭취하였을 때 특정항체들의 결합을 통해 병원성 미생물의 성장이나 군체를 형성하는 것을 무력화시켜 결과적으로 병원균을 감소시키거나 억제시킨다는 점이다. 오늘날 약물에 내성을 지닌 박테리아의 출현으로 질병감염을 막는데 항생제의 사용효과가 점차 감소하고 있기 때문에 이러한 항생제를 대체할 수 있는 방안으로 계란항체를 이용할 수 있다.한 중공 플랜지 형상의 단조 방법 중 보다 적절한 단조방법인 압조 단조에 있어서 일반적으로 사용되고 있는 SM10C에 대한 유한요소 해석을 수행하였으며, 제품의 형상비에 따라 폴딩 결함의 발생 유무를 검토하고, 폴딩 결함 없이 단조하기 위한 중공 플랜지의 형상한계 비를 제시하였다.도 경미하게 나타났으나, 경련이 나타난 쥐에서는 KA만을 투여한 흰쥐와 구별되지 않았다. 이상의 APT의 항산화 효과는 KA로 인한 뇌세포 변성 개선에 중요한 인자로 작용할 것으로 사료되나, 보다 명확한 APT의 기전을 검색하고 직접 임상에 응응하기 위하여는 보다 다양한 실험 조건이 보완되어야 찰 것으로 생각된다. 항우울약들의 항혈소판작용은 PKC-기질인 41-43 kD와 20 kD의 인산화를 억제함에 기인되는 것으로 사료된다.다. 것으로 사료된다.다.바와 같이 MCl에서 작은 Dv 값을 갖는데, 이것은 CdCl$_{4}$$^{2-}$ 착이온을 형성하거나 ZnCl$_{4}$$^{2-}$ , ZnCl$_{3}$$^{-}$같은 이온과 MgCl$^{+}$, MgCl$_{2}$같은 이온종을 형성하기 때문인것 같다. 한편 어떠한 용리액에서던지 NH$_{4}$$^{+}$의 경

• Journal of the Korean Society of Marine Environment & Safety
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• v.18 no.6
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• pp.545-550
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• 2012

Wind resource assessment is necessary when designing wind farm. To get the assessment, we must use a long term(20 years) observed wind data but it is so hard. so that we usually measured more than a year on the planned site. From the wind data, we can calculate wind energy related with the wind farm site. However, it calculate wind energy to collect the long term data from Met-mast(Meteorology Mast) station on the site since the Met-mast is unstable from strong wind such as Typhoon or storm surge which is Non-periodic. To solve the lack of the long term data of the site, we usually derive new data from the long term observed data of AWS(Automatic Weather Station) around the wind farm area using mathematical interpolation method. The interpolation method is called MCP(Measure-Correlative-Predict). In this study, based on the MCP Regression Model proposed by us, we estimated the wind energy at Handong site using AEP(Annual Energy Production) from Gujwa AWS data in Jeju. The calculated wind energy at Handong was shown a good agreement between the predicted and the measured results based on the linear regression MCP. Short term AEP was about 7,475MW/year. Long term AEP was about 7,205MW/year. it showed an 3.6% of annual prediction different. It represents difference of 271MW in annual energy production. In comparison with 20years, it shows difference of 5,420MW, and this is about 9 months of energy production. From the results, we found that the proposed linear regression MCP method was very reasonable to estimate the wind resource of wind farm.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.253-260
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• 2019

Radiation dose enhancement is a method of increasing the cross section of interaction, thus increasing the deposited dose. This can contribute to linear energy transfer, LET and relative biological effectiveness, RBE. Previous studies on dose enhancement have been mainly focused on X, ${\gamma}-rays$, but in this study, the dose enhancement was analyzed for proton using Monte Carlo simulation using MCNP6. Based on the mathematical modeling method, energy spectrum and relative intensity of spread out Bragg-peak were calculated, and evaluated dose enhancement factor and dose distribution of dose enhancement material, such as aurum and gadolinium. Dose enhancement factor of 1.085-1.120 folds in aurum, 1.047-1.091 folds in gadolinium was shown. In addition, it showed a decrease of 95% modulation range and practical range. This may lead to an uncertain dose in the tumor tissue as well as dose enhancement. Therefore, it is necessary to make appropriate corrections for spread out Bragg-peak and practical range from mass stopping power. It is expected that Monte Carlo simulation for dose enhancement will be used as basic data for in-vivo and in-vitro experiments.

• Journal of Environmental Impact Assessment
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• v.29 no.6
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• pp.403-413
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• 2020

A mathematical model comprised with eight simultaneous quasi-linear partial differential equations was suggested to provide optimal chlorination strategy. Upstream weighted finite element method was employed to construct multidimensional numerical code. The code was verified against measured concentrations in three type of reactors. Boundary conditions and reaction rate were calibrated for the sixteen cases of experimental results to regenerate the measured values. Eight reaction rate coefficients were estimated from the modeling result. The reaction rate coefficients were expressed in terms of pH and temperature. Automatic optimal algorithm was invented to estimate the reaction rate coefficients by minimizing the sum of squares of the numerical errors and combined with the model. In order to minimize the concentration of chlorine and pollutants at the final usage sites, a real-time predictive control system is imperative which can predict the water quality variables from the chlorine disinfection process at the water purification plant to the customer by means of a model and operate the disinfection process according to the influent water quality. This model can be used to build such a system in water treatment plants.

• Journal of the Korea Society for Simulation
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• v.31 no.1
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• pp.29-41
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• 2022

As one of the alternatives to solve the problem of unstable food supply and demand imbalance caused by abnormal climate change, the need for plant factories is increasing. Airflow in plant factory is recognized as one of important factor of plant which influence transpiration and heat transfer. On the other hand, Digital Twin (DT) is getting attention as a means of providing various services that are impossible only with the real system by replicating the real system in the virtual world. This study aimed to develop a digital twin model for airflow prediction that can predict airflow in various situations by applying the concept of digital twin to a plant factory in operation. To this end, first, the mathematical formalism of the digital twin model for airflow analysis in plant factories is presented, and based on this, the information necessary for airflow prediction modeling of a plant factory in operation is specified. Then, the shape of the plant factory is implemented in CAD and the DT model is developed by combining the computational fluid dynamics (CFD) components for airflow behavior analysis. Finally, the DT model for high-accuracy airflow prediction is completed through the validation of the model and the machine learning-based calibration process by comparing the simulation analysis result of the DT model with the actual airflow value collected from the plant factory.