• Nuclear Engineering and Technology
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• v.26 no.1
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• pp.108-118
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• 1994

A semi-empirical correlation has been developed for adiabatic interfacial friction factors in a long horizontal air-water countercurrent stratified flow conditions. Using a pipe and duct test sections, a series of experiments hate been conducted varying non-dimensional water depth and flow rates of air. On the basis of simultaneous measurement of the main flow parameters in a horizontal pipe and a duct, a semi-empirical correlation for the interfacial friction factor in a stratified flow regime has been developed employing a new concept of surface roughness in wavy flow. A total of 201 data point, including 15 concurrent pipe flow test data of others, have been used in the present analysis. A comparison between the data and the predictions of the present correlation shows that the agreement is within $\pm$30%.

• Nuclear Engineering and Technology
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• v.27 no.2
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• pp.189-202
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• 1995

An improved method is presented for the prediction of heat transfer coefficients in turbulent fall-ing liquid films with or without interfacial shear for both heating or condensation. A modified Mudawwar and El-Masri's semi-empirical turbulence model, particularly to extend its use for the turbulent falling film with high interfacial shear, is used to replace the eddy viscosity model incorporated in the unified approach unposed by Yih and Liu. The liquid film thickness and asymptotic heat transfer coefficients against the film Reynolds number for wide range of interfacial shear predicted by both present and existing methods are compared with experimental data. The results show that in general, predictions of the modified model agee more closely with experimental data than that of existing models.

• Nuclear Engineering and Technology
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• v.17 no.1
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• pp.45-52
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• 1985

A two inverted U-tubes condenser was constructed from transparent materials to study the heat removal capability of steam generators under filmwise reflux condensation mode. Essentially, two sets of experiments were performed: (1) the first dealt with the reflux condensation length, and (2) the second dealt with the flooding points with and without the presence of a noncondensible gas in the steam flow, and the effect of the flooding time. In addition, experimental results are compared with the predictions of analytical models.

• Journal of Integrative Natural Science
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• v.8 no.2
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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.

• International conference on construction engineering and project management
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• 2022.06a
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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.

• Proceedings of the Safety Management and Science Conference
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• 2010.11a
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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.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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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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• v.28 no.4
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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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• v.11 no.E
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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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• v.17 no.3
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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.