• Nuclear Engineering and Technology
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• 제26권1호
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• pp.108-118
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• 1994

긴 수평관에서 공기와 물의 역성층류시 적용할 수 있는 단열계면 마찰계수에 대한 준 실험식을 개발하였다. 둥근관과 사각관으로 된 단열 역성층류 실험장치를 사용하여 물의 수위 및 공기의 속도를 변화시키면서 일련의 실험을 수행하였다. 수평으로 된 원형 및 사각형 실험관속으로 흐르는 유체의 주요 유동 변수들을 동시에 측정한 실험치들과 계면이 물결파에 의해 거칠어진다는 새로운 개념을 도입하여 성층류영역의 계면마찰 계수에 대한 준 실험식을 개발하였다. 이 해석에는 다른 연구자들의 병류실험치 15개를 포함하여 총 201개의 실험치들을 사용하였다. 이 실험치들과 여기서 제안한 준 실험식의 예측치와 비교하면 오차 범위는 $\pm$30% 정도이다.

• Nuclear Engineering and Technology
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• 제27권2호
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• pp.189-202
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• 1995

계면 전단응력이 있을 때와 없을 때 가열 또는 응축되면서 하강하는 난류액막의 열전달 계수를 예측하기 위한 개선된 방법을 제시하였다. 특히 큰 계면 전단응력이 있을 때 하강하는 난류액막에 적용할 수 있도록 Mudawwar와 El-Masri의 준 실험적 난류모델을 수정하여 Yih와 Liu가 제안한 통합적 접근방법에 사용한 와류점성모델대신에 사용하였다. 광범위한 크기의 계면전단응력에 대해 액막 레이놀즈 수 대액체막 두께 및 접근적 열전달 계수를 개선된 방법과 다른 여러 기존 방법으로 예측하여 실험값들과 비교하였다. 그 결과 일반적으로 수정한 모델과 예측한 값이 다른 기존 모델로 예측한 값보다 실험 치와 더밀접하게 일치하는 것을 보여주었다.

• Nuclear Engineering and Technology
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• 제17권1호
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• pp.45-52
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• 1985

가압 경수로의 소형 냉각재 사고시 증기 발생기 U-자관 내에서의 억류 응축 현상(reflux condensation phenomena)은 주요한 열제거 수단이 된다. 열제거 Mechanism이 순수히 역류 응축 현상에 의 할 때, 증기 발생기의 열제거 능력을 평가하기 위하여 원자로 증기 발생기의 U-자관을 모사하는 두개의 U-자 관을 가진 증기응축 장치를 제작하여 다음 두 가지의 실험을 수행하였다. 첫째로, U-자관속에서 역류 응축 현상이 일어날 때 증기의 유입량을 증가시켜 가면서 역류 응축이 일어나는 액체 막 길이 (filmwise reflux condensation length)를 측정하였다. 둘째로는 길이가 다른 두 개의 U-자관에 증기만을 유입시킬 때와 증기와 공기를 동시에 유입시킬 때에 대한 Flooding Point를 측정하여 U-자관의 길이와 비응축성 가스가 Flooding Point에 미치는 영향을 조사하였다. 그리고 수학적 모델을 이용한 이론적 측정값과 실험 Data를 비교하였다.

• 통합자연과학논문집
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• 제8권2호
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• pp.81-88
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• 2015

c-Jun N-terminal kinase-3 (JNK3) is a member of the mitogen-activated protein kinase family (MAPK), and plays an important role in neurological disorders. Therefore, identification of selective JNK3 inhibitor may contribute towards neuroprotection therapies. In this work, we performed hologram quantitative structure-activity relationship (HQSAR) on a series of thiophene trisubstituted derivatives. The best predictions were obtained for HQSAR model with $q^2=0.628$ and $r^2=0.986$. Statistical parameters from the generated QSAR models indicated the data is well fitted and have high predictive ability. HQSAR result showed that atom, bond and chirality descriptors play an important role in JNK3 activity and also shows that electronegative groups is highly favourble to enhance the biological activity. Our results could be useful to design novel and selective JNK3 inhibitors.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.814-822
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• 2022

The deployment of sensors for Structural Health Monitoring requires a complicated network arrangement, ground truthing, and calibration for validating sensor performance periodically. Any conventional sensor on a structural element is also subjected to static and dynamic vertical loadings in conjunction with other environmental factors, such as brightness, noise, temperature, and humidity. A structural model with strain gauges was built and tested to get realistic sensory information. This paper investigates different deep learning architectures and algorithms, including unsupervised, autoencoder, and supervised methods, to benchmark blind drift calibration methods using deep learning. It involves a fully connected neural network (FCNN), a long short-term memory (LSTM), and a gated recurrent unit (GRU) to address the blind drift calibration problem (i.e., performing calibrations of installed sensors when ground truth is not available). The results show that the supervised methods perform much better than unsupervised methods, such as an autoencoder, when ground truths are available. Furthermore, taking advantage of time-series information, the GRU model generates the most precise predictions to remove the drift overall.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2010년도 추계학술대회
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• pp.233-243
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• 2010

Mahalanobis Taguchi System (MTS) is a pattern information technology, which has been used in different diagnostic applications to make quantitative decisions by constructing a multivariative measurement scale using data analytic methods. In MTS approach, Mahalanobis distance (MD) is used to measure the degree of abnormality of patterns and principles of Taguchi methods are used to evaluate accuracy of predictions based on the scale constructed. The advantage of MD is that it takes into consideration the correlations between the variables and this consideration is very important in pattern analysis. The purpose of this study is constructing admission diagnosis system and define the effect of admission requirements for student's academic accomplishment.

• 천문학회보
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• 제42권2호
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• pp.81.2-81.2
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• 2017

Polarized mid-infrared emission from polycyclic aromatic hydrocarbons (PAHs) can provide a crucial test of basic physics of alignment of nanoparticles and opens a potential new window into studying magnetic fields. In this talk, I will present a new model of polarized PAH emission that takes into account the effect of PAH alignment with the magnetic field due to resonance paramagnetic relaxation. I will then present our predictions for the polarization level of the strong PAH emission features from the interstellar medium. I will present the first detection of polarization of PAH emission at 11.3micron which is consistent with our theoretical prediction. Finally, I will discuss important implications of this work for tracing magnetic fields via mid-IR PAH features and for constraining the polarization of anomalous microwave emission that is useful for the quest of CMB B-modes.

• Geomechanics and Engineering
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• 제28권4호
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• pp.359-374
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• 2022

Geology conditions are crucial in decision-making during the planning and design phase of a tunnel project. Estimation of the geology conditions of road tunnels is subject to significant uncertainties. In this work, the effectiveness of a novel regression method in estimating geological or geotechnical parameters of road tunnel projects was explored. This method, called Gaussian process regression (GPR), formulates the learning of the regressor within a Bayesian framework. The GPR model was trained with data of old tunnel projects. To verify its feasibility, the GPR technique was applied to a road tunnel to predict the state of three geological/geomechanical parameters of Rock Mass Rating (RMR), Rock Structure Rating (RSR) and Q-value. Finally, in order to validate the GPR approach, the forecasted results were compared to the field-observed results. From this comparison, it was concluded that, the GPR is presented very good predictions. The R-squared values between the predicted results of the GPR vs. field-observed results for the RMR, RSR and Q-value were obtained equal to 0.8581, 0.8148 and 0.8788, respectively.

• Journal of Korean Society for Atmospheric Environment
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• 제11권E호
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• pp.45-54
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• 1995

Indoor air quality models are useful to predict indoor air pollutant concentrations as a function of several indoor factors. Indoor air quality model was developed to evaluate the pollutant removal efficiency of variable-air-volume/bypass filtration system (VAV/BPFS) compared with the conventional variable-air-volume (VAV) system. This model provides relative pollutant removal effectiveness of VAV/BPFS by concentration ratio between the conventional VAV system and VAV/BPFS. The predictions agree closely, from 5 to 10 percent, with the measured values for each energy load. As a results, we recommend the VAV/BPFS is a promising alternative to conventional VAV system because it is capable of reducing indoor air pollutant concentration and maintaining good indoor air quality.

• Food Science and Biotechnology
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• 제17권3호
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• pp.642-650
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• 2008

A mathematical model was developed for predicting the growth rate of Enterobacter sakazakii in tryptic soy broth medium as a function of the combined effects of temperature (5, 10, 20, 30, and $40^{\circ}C$), pH (4, 5, 6, 7, 8, 9, and 10), and the NaCl concentration (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10%). With all experimental variables, the primary models showed a good fit ($R^2=0.8965$ to 0.9994) to a modified Gompertz equation to obtain growth rates. The secondary model was 'In specific growth $rate=-0.38116+(0.01281^*Temp)+(0.07993^*pH)+(0.00618^*NaCl)+(-0.00018^*Temp^2)+(-0.00551^*pH^2)+(-0.00093^*NaCl^2)+(0.00013^*Temp*pH)+(-0.00038^*Temp*NaCl)+(-0.00023^*pH^*NaCl)$'. This model is thought to be appropriate for predicting growth rates on the basis of a correlation coefficient (r) 0.9579, a coefficient of determination ($R^2$) 0.91, a mean square error 0.026, a bias factor 1.03, and an accuracy factor 1.13. Our secondary model provided reliable predictions of growth rates for E. sakazakii in broth with the combined effects of temperature, NaCl concentration, and pH.