• Journal of the Korean Society of Visualization
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• v.21 no.1
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• pp.47-56
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• 2023

Bubble condensation, which involves the interaction of bubbles within the subcooled liquid flow, plays an important role in the effective control of thermal devices. In this study, numerical simulations are performed using a VOF (Volume of Fluid) model to investigate the effect of tube diameter on bubble condensation. As the tube diameter decreases, condensation bubbles persist for a long time and disappear at a higher position. It is observed that for small tube diameters, the heat transfer coefficients of condensation bubbles, which is a quantitative parameter of condensation rate, are smaller than those for large tube diameters. When the tube diameter is small, the subcooled liquid around the condensing bubble is locally participated in the condensation of the bubble to fill the reduced volume of the bubble due to the generation of a backflow in the narrow space between the bubble and the wall, so that the heat transfer coefficient decreases.

• ETRI Journal
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• v.45 no.3
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• pp.379-393
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• 2023

Underwater communication (UWC) is widely used in coastal surveillance and early warning systems. Precise channel estimation is vital for efficient and reliable UWC. The sparse direct-adaptive filtering algorithms have become popular in UWC. Herein, we present an improved adaptive convex-combination method for the identification of sparse structures using a reweighted normalized leastmean-square (RNLMS) algorithm. Moreover, to make RNLMS algorithm independent of the reweighted l₁-norm parameter, a modified sparsity-aware adaptive zero-attracting RNLMS (AZA-RNLMS) algorithm is introduced to ensure accurate modeling. In addition, we present a quantitative analysis of this algorithm to evaluate the convergence speed and accuracy. Furthermore, we derive an excess mean-square-error expression that proves that the AZA-RNLMS algorithm performs better for the harsh underwater channel. The measured data from the experimental channel of SPACE08 is used for simulation, and results are presented to verify the performance of the proposed algorithm. The simulation results confirm that the proposed algorithm for underwater channel estimation performs better than the earlier schemes.

• Journal of Korean Tunnelling and Underground Space Association
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• v.14 no.1
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• pp.23-35
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• 2012

Due to the convenience, RMR has been widely applied in civil engineering works such as tunnel, slope, and so on. Many researchers have studied to suggest more simple and trustable RMR by modifying its parameters. However, those researches have just focused on looking for easy modified-RMRs by reducing number of parameters using various statistical analyses. Therefore, this research studied questions of modified-RMRs and gaps between RMR and its parameters. Approximately 2,000 parameters of 400 RMRs from various tunnel sites were normalized respectively and compared with one another to study their relations and divergences. The comparison results showed that there were common patterns among RMR and parameters. Data of uniaxial compressive strength and RQD, qualitative parameters, were located in upper side of RMR line. Discontinuity condition and ground water, quantitative oriented parameters, were opposite to them. It means if both qualitative and quantitative parameters can be properly combined then it can be easy to make simple and easy modified-RMRs without using difficult statistics. This results also show that the majority of field engineers used to estimate RMR conservatively when they did quantitative oriented parameters.

• Journal of Veterinary Clinics
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• v.28 no.1
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• pp.101-107
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• 2011

This study aimed to determine dose-response (DR) curve of avian influenza (AI) virus to predict the probability of illness or adverse health effects that may result from exposure to a pathogenic microorganism in a quantitative microbial risk assessment. To determine the parametric DR relationship of several strains of AI virus, 7 feeding trial data sets challenging humans (5 sets) and chickens (2 sets) for strains of H3N2 (4 sets), H5N1 (2 sets) and H1N1 (1 set) from the published literatures. Except for one data set (study with intra-tracheal inoculation for data set no. 6), all were obtained from the studies with intranasal inoculation. The data were analyzed using three types of DR model as the basis of heterogeneity in infectivity of AI strains in humans and chickens: exponential, beta-binomial and beta-Poisson. We fitted to the data using maximum likelihood estimation to get the parameter estimates of each model. The alpha and beta values of the beta-Poisson DR model ranged 0.06-0.19 and 1.7-48.8, respectively for H3N2 strain. Corresponding values for H5N1 ranged 0.464-0.563 and 97.3-99.4, respectively. For H1N1 the parameter values were 0.103 and 12.7, respectively. Using the exponential model, r (infectivity parameter) ranged from $1.6{\times}10^{-8}$ to $1.2{\times}10^{-5}$ for H3N2 and from $7.5{\times}10^{-3}$ to $4.0{\times}10^{-2}$ for H5N1, while the value was $1.6{\times}10^{-8}$ for H1N1. The beta-Poisson DR model provided the best fit to five of 7 data sets tested, and the estimated parameter values in betabinomial model were very close to those of beta-Poisson. Our study indicated that beta-binomial or beta-Poisson model could be the choice for DR modeling of AI, even though DR relationship varied depending on the virus strains studied, as indicated in prior studies. Further DR modeling should be conducted to quantify the differences among AI virus strains.

• Geophysics and Geophysical Exploration
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• v.10 no.1
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• pp.60-68
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• 2007

Conventional analysis of spectral induced polarization (SIP) data consists of measuring impedances over a range of frequencies, followed by spectral analysis to estimate spectral parameters. For the quantitative and accurate estimation of subsurface SIP parameter distribution, however, a sophisticated and stable inversion technique is required. In this study, we have developed a two-step inversion approach to obtain the two-dimensional distribution of SIP parameters. In the first inversion step, all the SIP data measured over a range of frequencies are simultaneously inverted, adopting cross regularisation of model complex resistivities at each frequency. The cross regularisation makes it possible to enhance the noise characteristics of the inversion by imposing a strong assumption, that complex resistivities should show similar characteristics over a range of frequencies. In numerical experiments, we could verify that our inversion approach successfully reduced inversion artefacts. As a second step, we have also developed an inversion algorithm to obtain SIP parameters based on the Cole-Cole model, in which frequency-dependent complex resistivities from the first step are inverted to obtain a two-dimensional distribution of SIP parameters. In numerical tests, the SIP parameter images showed a fairly good match with the exact model, which suggests that SIP imaging can provide a very useful subsurface image to complement resistivity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.490-492
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• 2016

Pancreatic ultrasound imaging is used to diagnose pancreatic hyperplasia, pancreatic steatosis, pancreatic cancer and the like. If the diagnosis of pancreatic steatosis is pancreatic parenchyma echo shades splashes spleen than in the pancreas ultrasound it determines that the fat is deposited. And research on ultrasound imaging of pancreatic cancer but is actively conducted research studies on pancreatic steatosis is insufficient In addition, pancreatic steatosis is often an error in accordance with the diagnostic criteria are vague and subjective diagnosis of the artisan. This study was a quantitative analysis using the feature value extracting a feature of an image extracted by applying a parameter to the algorithm GLCM image of the normal and pancreatic fat. Setting a region of interest ($5{\times}5pixel$) in the mild 89 case, moderate 89 case, severe 89 case, total image 267 case using GLCM algorithm, and using the Autocorrelation, Sum average, Sum of squares, Sum varience 4 kinds parameter in each image It was analyzed.

• Journal of the Korean Geotechnical Society
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• v.23 no.1
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• pp.39-49
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• 2007

In this study, quantitative sensitivity analysis on rockfill material influencing the dam crest settlement of CFRD (Concrete-Faced Rockfill Dam) subjected to earthquake loading was carried out. The purpose of this study is to indicate the most important input parameter from the results of sensitivity analysis, to show the quantitative variation of settlement at the crest of CFR type dam during earthquake with this input parameter, and to recommend the approximate estimation method of the settlement on the crest of CFRD subjected to earthquake loading. The statistic characteristics of rockfill parameters which were obtained from large triaxial tests were evaluated. The total 108 dynamic numerical analyses (2 input earthquake, 2 magnitudes for each earthquake, 27 rockfill material property combinations) on CFRD were conducted. The global sensitivity analysis was carried out using the results of numerical analysis. From the sensitivity analysis, It was found that the crest settlement of the CFRD subjected to earthquake was absolutely affected by the shear modulus of rockfill material irrespective of the input earthquakes and the magnitude of input acceleration. On the contrary, it was found that the effect of cohesion and friction angle of rockfill was negligible. From the results of sensitivity analysis and numerical analysis, the approximate estimation method of the settlement on the crest of CFRD subjected to earthquake loading was recommended on condition that the rockfill shear modulus and simple dam information was known.

• Journal of the Korean Society of Safety
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• v.35 no.3
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• pp.105-115
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• 2020

This study compares the difference of fit factors (FF) and visual acuity according to masks and eyeglasses preferences for 54 participants. We the precautions and behaviors of discomfort when wearing masks of eyewear wearers. Contact lens discomfort and priority action of complaints was investigated Glasses fitting factors is Optical Center Height(OH), Vertex Distance(VD) and Pantoscopic Angle(PA). We measured those factors and expressed by the ratio of standard point and change point. Quantitative fit factor was measured by Portacount Pro+ 8038. Also, we selected to 6 exercises among 8 exercises OSHA QNFT (Quantitative Fit testing) protocol to measure the fit factors. The pass/ fail criterion of FF was set at 100. Visual acuity(VA) test chart is developed by Chunsuk Han was used, Descriptive statistics was performed. Descriptive statistics(SAS ver 9.2), it is used geometric means, Wilcoxon analysis(P=0.05) When wearing the mask preferentially, fit factor(FF) was high according to the step of glasses fitting parameter. on the other hand, when the glasses first choice, the visual acuity(VA) was high. there was no significant difference. In the case of fit factor (FF), mask first choice/ glasses first choice is OH (p=0.671/ p=0.332), VD (p=0.602/ p=0.571) and PA (p=0.549/ p=0.607). Visual acuity (VA), mask first choice/ glasses first choice is OH (p=0.753/ p=0.386), VD (p=0.815/ p=0.557) and PA (p=0.856/ p=0.562). The workers of workplace and office chose glasses but occupational health workers and students chose mask. In case of discomforts, it was suggested to remove the mask and tolerate discomforts. The main discomforts and usual action of lens were dryness, hyperemia, foreign body sensation, ophthalmodynia, decreased vision and glasses wearing. Therefore, it is necessary to develop a mask wearing method education program considering glasses fitting and develop a hybrid model that minimizes inconvenience when wearing glasses and a mask at the same time.

• Bulletin of the Korean Chemical Society
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• v.26 no.12
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• pp.2007-2016
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• 2005

An artificial neural network (ANN) is successfully presented for prediction acidity constant (pKa) of various benzoic acids and phenols with diverse chemical structures using a nonlinear quantitative structure-property relationship. A three-layered feed forward ANN with back-propagation of error was generated using six molecular descriptors appearing in the multi-parameter linear regression (MLR) model. The polarizability term $(\pi_1)$, most positive charge of acidic hydrogen atom $(q^+)$, molecular weight (MW), most negative charge of the acidic oxygen atom $(q^-)$, the hydrogen-bond accepting ability $(\epsilon_B)$ and partial charge weighted topological electronic (PCWTE) descriptors are inputs and its output is pKa. It was found that properly selected and trained neural network with 205 compounds could fairly represent dependence of the acidity constant on molecular descriptors. For evaluation of the predictive power of the generated ANN, an optimized network was applied for prediction pKa values of 37 compounds in the prediction set, which were not used in the optimization procedure. Squared correlation coefficient $(R^2)$ and root mean square error (RMSE) of 0.9147 and 0.9388 for prediction set by the MLR model should be compared with the values of 0.9939 and 0.2575 by the ANN model. These improvements are due to the fact that acidity constant of benzoic acids and phenols in water shows nonlinear correlations with the molecular descriptors.

• Tunnel and Underground Space
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• v.18 no.6
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• pp.465-479
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• 2008

For the quantitative identification of rock behavior in shallow tunnels, we recommend using the rock behavior index (RBI) by the analytic hierarchy process (AHP) and the Rock Engineering Systems (RES). AHP and RES can aid engineers in effectively determining complex and un-structured rock behavior utilizing a structured pair-wise comparison matrix and an interaction matrix, respectively. Rock behavior types are categorized as rock fall, cave-in, and plastic deformation. Seven parameters influencing rock behavior for shallow depth rock tunnel are determined: uniaxial compressive strength, rock quality designation (RQD), joint surface condition, stress, pound water, earthquake, and tunnel span. They are classified into rock mass intrinsic, rock mass extrinsic, and design parameters. An advantage of this procedure is its ability to obtain each parameter's weight. We applied the proposed method to the basic design of Seoul Metro Line O and quantified the rock behavior into RBI on rock fall, cave-in, and plastic deformation. The study results demonstrate that AHP and RES can give engineers quantitative information on rock behavior.