• Korean Journal of Remote Sensing
• /
• v.26 no.6
• /
• pp.605-615
• /
• 2010

This study demonstrates the feasibility of small satellite, namely PROBA platform with the compact high resolution imaging spectrometer (CHRIS), for aerosol retrieval in Hong Kong. The rationale of our technique is to estimate the aerosol reflectances by decomposing the Top of Atmosphere (TOA) reflectances from surface reflectance and Rayleigh path reflectances. For the determination of surface reflectances, the modified Minimum Reflectance Technique (MRT) is used on three winter ortho-rectified CHRIS images: Dec-18-2005, Feb-07-2006, Nov-09-2006. For validation purpose, MRT image was compared with ground based multispectral radiometer measurements and atmospherically corrected Landsat image. Results show good agreements between CHRIS-derived surface reflectance and both by ground measurement data as well as by Landsat image (r>0.84). The Root-Mean-Square Errors (RMSE) at 485, 551 and 660nm are 0.99%, 1.19%, and 1.53%, respectively. For aerosol retrieval, Look Up Tables (LUT) which are aerosol reflectances as a function of various AOT values were calculated by SBDART code with AERONET inversion products. The CHRIS derived Aerosol Optical Thickness (AOT) images were then validated with AERONET sunphotometer measurements and the differences are 0.05~0.11 (error=10~18%) at 440nm wavelength. The errors are relatively small compared to those from the operational moderate resolution imaging spectroradiometer (MODIS) Deep Blue algorithm (within 30%) and MODIS ocean algorithm (within 20%).

• Bulletin of the Korean Chemical Society
• /
• v.13 no.6
• /
• pp.620-624
• /
• 1992

The analytical performance of glow discharge mass spectrometer (GD-MS), using a flat type ion source is discussed. The efficiency of ion extraction was maximized at the distance between anode and cathode of 6 mm. At the operation condition of 4 mA, -1000 volt, and 1 mbar for the source, the optimum voltages for sampler and skimmer were40 volt and -280 volt, respectively. The intensities of Cu, Zn, and Mn were increased as a function of square root of current approximately. Korea standard reference materials (KSRM) were tested for an application study. The detection limits of most elements were obtained in the range of several ppm at the optimized operating condition. The peaks of aluminum and chromium were interfered by those of residual gases. The depth profile of nickel coated copper specimens (3, 5, 10 ${\mu}m$ thickness) were obtained by plotting time versus intensities of Ni and Cr after checking the thickness of nickel coated using a scanning electron microscope (SEM). At this moment, the sputtering rate of 0.2 ${\mu}m/min$ at the optimum operating condition was determined from the slope of the plot of time to the coating thickness. The roughness spectra of specimen's crater after 16 min, discharge were obtained using a Talysuf5m-120 roughness tester as well.

• Journal of Korean Medicine Rehabilitation
• /
• v.31 no.2
• /
• pp.81-97
• /
• 2021

Objectives This study was designed to identify the changes of autonomic nervous system (ANS) which was induced by acupuncture at the field of the auricular branch of the vagus nerve. Methods 30 healthy adults were selected and classified into two groups; experimental group, control group. After providing mental stress, acupuncture was applied at external ear in experimental group and no treatment executed in control group. The evaluation of ANS function was measured by heart rate variability (HRV). We statically analyzed the difference of HRV parameters which include mean heart rate (MHRT), standard deviation of all N-N intervals (SDNN), square root of the mean of the sum of the squares of differences between adjacent N-N intervals (RMSSD), total power (TP), low frequency power (LF), high frequency power (HF), LF/HF ratio. Results All subjects showed significant increase in SDNN, LF after stress stimulation (p<0.05). Immediately after intervention, MHRT was significantly decreased (p<0.001) and RMSSD, HF were significantly increased in experimental group (p<0.05). After the end of intervention, SDNN, HF, RMSSD, TP, LF were significantly increased in experimental group (p<0.01, p<0.05). And when comparing baseline HRV, SDNN, LF were significantly increased in control group (p<0.01) and SDNN, RMSSD, TP, LF were significantly increased in experimental group (p<0.05). In the subgroup analysis, normal balance of ANS group showed significant increase in TP, LF, SDNN, HF (p<0.01, p<0.05). Conclusions We suggested that acupuncture at external ear, region of the vagus nerve distribution could increase parasympathetic activity and cause changes and reregulation of the ANS.

• Kosin Medical Journal
• /
• v.33 no.3
• /
• pp.369-379
• /
• 2018

Objectives: Analysis of heart rate variability (HRV) has been used as a measure of cardiac autonomic function. According to the pNN50 statistic, the percentage of differences between successive normal RR intervals (RRI) that exceed 50 ms, has been known to reflect cardiac vagal modulation. Relatively little is known about the validity of pNN50 during general anesthesia (GA). Therefore, we evaluated the correlation of pNN50 with other variables such as HF, RMSSD, SD1 of HRV reflecting the vagal tone, and examined the validity of pNN50 in anesthetized patients. Methods: We assessed changes in RRI, pNN50, root mean square of successive differences of RRI (RMSSD), high frequency (HF) and standard deviation 1 (SD1) of $Poincar{\acute{e}}$ plots after GA using sevoflurane anesthesia. We also calculated the probability distributions for the family of pNNx statistics (x: 2-50 ms). Results: All HRV variables were significantly decreased during GA. HF power was not correlated with pNN50 during GA (r = 0.096, P = 0.392). Less than pNN47 was shown to have a correlation with other variables. Conclusions: These data suggest that pNN50 can not reflect the level of vagal tone during GA.

• Journal of Korean Society on Water Environment
• /
• v.35 no.5
• /
• pp.425-431
• /
• 2019

Recently, people have been attracting attention to the good quality of water resources as well as water welfare. to improve the quality of life. This study is a papers on the prediction of benthic macroinvertebrate index (BMI), which is a aquatic ecological health, using the machine learning based CFS (Correlation-based Feature Selection) method and the random forest model to compare the measured and predicted values of the BMI. The data collected from the Han River's branch for 10 years are extracted and utilized in 1312 data. Through the utilized data, Pearson correlation analysis showed a lack of correlation between single factor and BMI. The CFS method for multiple regression analysis was introduced. This study calculated 10 factors(water temperature, DO, electrical conductivity, turbidity, BOD, $NH_3-N$, T-N, $PO_4-P$, T-P, Average flow rate) that are considered to be related to the BMI. The random forest model was used based on the ten factors. In order to prove the validity of the model, $R^2$, %Difference, NSE (Nash-Sutcliffe Efficiency) and RMSE (Root Mean Square Error) were used. Each factor was 0.9438, -0.997, and 0,992, and accuracy rate was 71.6% level. As a result, These results can suggest the future direction of water resource management and Pre-review function for water ecological prediction.

• Korean Journal of Optics and Photonics
• /
• v.33 no.6
• /
• pp.324-330
• /
• 2022

We measured the Dill and Mack model parameters that determine the exposure and development characteristics of photoresists, respectively. First, photoresist samples were prepared while altering the exposure dose, and changes in transmittance were measured. Analyzing these results, the Dill model parameters A, B, and C were determined. In particular, the exact solution of the Dill model equation was used to determine the C parameter. In addition, changes in thickness were measured as a function of development time for different exposure doses, and the Mack model parameters R_min, R_max, a, and n were determined using the results. We also determined parameter values for the reduced Mack model that uses only three parameters, R_min, R_max, and n. The root mean square error between the model predictions and the measured values for the photoresist thickness was found to increase slightly compared to the case using the original Mack model with four parameters.

• Korean Journal of Remote Sensing
• /
• v.37 no.1
• /
• pp.161-167
• /
• 2021

This paper presents the method to quantitatively evaluate the uncertainty of the semi-empirical Bidirectional Reflectance Distribution Function (BRDF) model for Himawari-8/AHI. The uncertainty of BRDF modeling was affected by various issues such as assumption of model and number of observations, thus, it is difficult that evaluating the performance of BRDF modeling using simple uncertainty equations. Therefore, in this paper, Monte-Carlo method, which is most dependable method to analyze dynamic complex systems through iterative simulation, was used. The 1,000 input datasets for analyzing the uncertainty of BRDF modeling were generated using the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) Radiative Transfer Model (RTM) simulation with MODerate Resolution Imaging Spectroradiometer (MODIS) BRDF product. Then, we randomly selected data according to the number of observations from 4 to 35 in the input dataset and performed BRDF modeling using them. Finally, the uncertainty was calculated by comparing reproduced surface reflectance through the BRDF model and simulated surface reflectance using 6S RTM and expressed as bias and root-mean-square-error (RMSE). The bias was negative for all observations and channels, but was very small within 0.01. RMSE showed a tendency to decrease as the number of observations increased, and showed a stable value within 0.05 in all channels. In addition, our results show that when the viewing zenith angle is 40° or more, the RMSE tends to increase slightly. This information can be utilized in the uncertainty analysis of subsequently retrieved geophysical variables.

• Journal of Ocean Engineering and Technology
• /
• v.36 no.2
• /
• pp.101-107
• /
• 2022

Dean (1965) proposed the use of the root mean square error (RMSE) in the dynamic free surface boundary condition (DFSBC) and kinematic free-surface boundary condition (KFSBC) as an error evaluation criterion for wave theories. There are well known wave theories with RMSE more than 1%, such as Airy theory, Stokes theory, Dean's stream function theory, Fenton's theory, and trochodial theory for deep-water waves. However, none of them can be applied for deep-water breaking waves. The purpose of this study is to provide a closed-form solution for deep-water waves with RMSE less than 1% even for breaking waves. This study is based on a previous study (Shin, 2016), and all flow fields were simplified for deep-water waves. For a closed-form solution, all Fourier series coefficients and all related parameters are presented with Newton's polynomials, which were determined by curve fitting data (Shin, 2016). For verification, a wave in Miche's limit was calculated, and, the profiles, velocities, and the accelerations were compared with those of 5^th-order Stokes theory. The results give greater velocities and acceleration than 5^th-order Stokes theory, and the wavelength depends on the wave height. The results satisfy the Laplace equation, bottom boundary condition (BBC), and KFSBC, while Stokes theory satisfies only the Laplace equation and BBC. RMSE in DFSBC less than 7.25×10^-2% was obtained. The series order of the proposed method is three, but the series order of 5^th-order Stokes theory is five. Nevertheless, this study provides less RMSE than 5^th-order Stokes theory. As a result, the method is suitable for offshore structural design.

• Nuclear Engineering and Technology
• /
• v.54 no.6
• /
• pp.2107-2119
• /
• 2022

Accurate remaining useful life (RUL) prediction for critical components of nuclear power equipment is an important way to realize aging management of nuclear power equipment. The electric gate valve is one of the most safety-critical and widely distributed mechanical equipment in nuclear power installations. However, the electric gate valve's extended service in nuclear installations causes aging and degradation induced by crack propagation and leakages. Hence, it is necessary to develop a robust RUL prediction method to evaluate its operating state. Although the particle filter(PF) algorithm and its variants can deal with this nonlinear problem effectively, they suffer from severe particle degeneracy and depletion, which leads to its sub-optimal performance. In this study, we combined the whale algorithm with regularized particle filtering(RPF) to rationalize the particle distribution before resampling, so as to solve the problem of particle degradation, and for valve RUL prediction. The valve's crack propagation is studied using the RPF approach, which takes the Paris Law as a condition function. The crack growth is observed and updated using the root-mean-square (RMS) signal collected from the acoustic emission sensor. At the same time, the proposed method is compared with other optimization algorithms, such as particle swarm optimization algorithm, and verified by the realistic valve aging experimental data. The conclusion shows that the proposed method can effectively predict and analyze the typical valve degradation patterns.

• Geomechanics and Engineering
• /
• v.34 no.3
• /
• pp.267-284
• /
• 2023

Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.