• Journal of Korean Society of Water and Wastewater
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• v.34 no.4
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• pp.251-258
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• 2020

Sewer deterioration models are needed to forecast the remaining life expectancy of sewer networks by assessing their conditions. In this study, the serious defect (or condition state 3) occurrence probability, at which sewer rehabilitation program should be implemented, was evaluated using four probability distribution functions such as normal, lognormal, exponential, and Weibull distribution. A sample of 252 km of CCTV-inspected sewer pipe data in city Z was collected in the first place. Then the effective data (284 sewer sections of 8.15 km) with reliable information were extracted and classified into 3 groups considering the sub-catchment area, sewer material, and sewer pipe size. Anderson-Darling test was conducted to select the most fitted probability distribution of sewer defect occurrence as Weibull distribution. The shape parameters (β) and scale parameters (η) of Weibull distribution were estimated from the data set of 3 classified groups, including standard errors, 95% confidence intervals, and log-likelihood values. The plot of probability density function and cumulative distribution function were obtained using the estimated parameter values, which could be used to indicate the quantitative level of risk on occurrence of CS3. It was estimated that sewer data group 1, group 2, and group 3 has CS3 occurrence probability exceeding 50% at 13th-year, 11th-year, and 16th-year after the installation, respectively. For every data groups, the time exceeding the CS3 occurrence probability of 90% was also predicted to be 27th- to 30th-year after the installation.

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.4
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• pp.350-357
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• 2017

Near infrared spectroscopy (NIRS) is a rapid and accurate method for analyzing the quality of cereals, and dried animal forage. However, one limitation of this method is its inability to measure fermentation parameters in dried and ground samples because they are volatile, and therefore, respectively lost during the drying process. In order to overcome this limitation, in this study, fresh coarse haylage was used to test the potential of NIRS to accurately determine chemical composition and fermentation parameters. Fresh coarse Italian ryegrass haylage samples were scanned at 1 nm intervals over a wavelength range of 680 to 2500 nm, and optical data were recorded as log 1/reflectance. Spectral data, together with first- and second-order derivatives, were analyzed using partial least squares (PLS) multivariate regressions; scatter correction procedures (standard normal variate and detrend) were used in order to reduce the effect of extraneous noise. Optimum calibrations were selected based on their low standard error of cross validation (SECV) values. Further, ratio of performance deviation, obtained by dividing the standard deviation of reference values by SECV values, was used to evaluate the reliability of predictive models. Our results showed that the NIRS method can predict chemical constituents accurately (correlation coefficient of cross validation, $R_{cv}^2$, ranged from 0.76 to 0.97); the exception to this result was crude ash ($R_{cv}^2=0.49$ and RPD = 2.09). Comparison of mathematical treatments for raw spectra showed that second-order derivatives yielded better predictions than first-order derivatives. The best mathematical treatment for DM, ADF, and NDF, respectively was 2, 16, 16, whereas the best mathematical treatment for CP and crude ash, respectively was 2, 8, 8. The calibration models for fermentation parameters had low predictive accuracy for acetic, propionic, and butyric acids (RPD < 2.5). However, pH, and lactic and total acids were predicted with considerable accuracy ($R_{cv}^2$ 0.73 to 0.78; RPD values exceeded 2.5), and the best mathematical treatment for them was 1, 8, 8. Our findings show that, when fresh haylage is used, NIRS-based calibrations are reliable for the prediction of haylage characteristics, and therefore useful for the assessment of the forage quality.

• Journal of radiological science and technology
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• v.40 no.2
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• pp.205-211
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• 2017

There is a need for aggressive diagnosis and treatment in middle-aged and high-risk individuals who are more likely to progress from nonalcoholic fatty liver to hepatitis. In this study, nonalcoholic fatty liver was divided into severe, moderate, and severe, and classified by quantitative method using computer analysis of GLCM algorithm. The purpose of this study was to evaluate the characteristics of ultrasound images in the local fat avoidance region. Normal, mild, moderate, severe fatty liver, and focal fat sparing area, 80 cases, respectively. Among the parameters of the GLCM algorithm, the values of the Autocorrelation, Square of the deviation, Sum of averages and Sum of variances with high recognition rate of the liver ultrasound image were calculated. The average recognition rate of the GLCM algorithm was 97.5%. The result of local fat avoidance image analysis showed the most similar value to the normal parenchyma. Ultrasonography can be easily accessed by primary screening, but there may be differences in the accuracy of the test method or the correspondence of results depending on proficiency. GLCM algorithm was applied to quantitatively classify the degree of fatty liver. Local fat avoidance region was similar to normal parenchyma, so it could be predicted to be homogeneous liver parenchyma without fat deposition. We believe that GLCM computer image analysis will provide important information for differentiating not only fatty liver but also other lesions.

• Journal of the Korean Society of Radiology
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• v.14 no.1
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• pp.39-44
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• 2020

The purpose of this study was learning about chest X-ray image classification and accuracy research through Deep Learning using big data technology with Convolution Neural Network. Normal 1,583 and Pneumonia 4,289 were used in chest X-ray images. The data were classified as train (88.8%), validation (0.2%) and test (11%). Constructed as Convolution Layer, Max pooling layer size 2×2, Flatten layer, and Image Data Generator. The number of filters, filter size, drop out, epoch, batch size, and loss function values were set when the Convolution layer were 3 and 4 respectively. The test data verification results showed that the predicted accuracy was 94.67% when the number of filters was 64-128-128-128, filter size 3×3, drop out 0.25, epoch 5, batch size 15, and loss function RMSprop was 4. In this study, the classification of chest X-ray Normal and Pneumonia was predictable with high accuracy, and it is believed to be of great help not only to chest X-ray images but also to other medical images.

• Journal of Marine Life Science
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• v.5 no.2
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• pp.43-50
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• 2020

The aim of this study is toxicity assessment using two types of sea urchins (H. pulcherrimus, M. nudus) that can representative primary consumers in potential coastal environments pollutants, Zinc undecylenate (ZU), which is used for various purposes, such as pharmaceutical agents and anti-bacterial and anti-fungi. The Fertilization rate and normal embryogenesis rate of H. pulcherrimus and M. nudus were concentration-dependent decreased. Besides, EC₅₀ of fertilization rate with H. pulcherrimus and M. nudus were 11.27 mgl^-1 and 1.48 mgl^-1, and EC₅₀ of normal embryogenesis were 0.94 mgl^-1 and 3.78 mgl^-1. NOEC of normal embryogenesis were 0.20 and 0.78 mgl^-1, respectively. In addition, to find the safety criteria of the ZU on the marine environment. PNEC value was 0.0094 mgl^-1, calculated using the toxicity values of two species of sea urchin derived from this study and the acute toxicity results of the coastal area through literature research. The above results will be used as basic data for establishing environmental protection strategies for marine environmental pollutants.

• Korean Journal of Clinical Pharmacy
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• v.1 no.1
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• pp.31-36
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• 1991

Tobramycin is one of the most frequently selected agents for pharmacokinetic drug monitoring because of its narrow therapeutic index and essential role for the management of serious infections, especially gram-negative infections. Its pharmacokinetic parameters are dependent on race, sex, age, ideal body weight. disease states, and etc. Therefore, to schedule the dosing of tobramycin, the individual pharmacokinetic parameters such as half-life and volume of distribution are needed. However, these pharmacokinetic parameters have never been reported in Koreans. The purposes of this study were to evaluate the volume of distribution of tobramycin in cancer patients who had normal renal function, to compare the mean values of Vd reported in the literature, and to compare the measured half-life with the expected half-life based on ABW, LBW, and IBW, respectively. Venous blood samples were collected just before and thirty minutes after dosing during steady state. Serum tobramycin concentrations were determined by $TD_x$ (fluorescence immunoassay). IBW were measured by the method of Devine: and LBW were measured by the method of Hallynck. Creatinine clearances (CLcr) of the patients were estimated using the Cockcroft and Gault equation. Elimination rate constants (kel) were determined using the Welling and Craig equation. Infusion rate (ko), volume of distribution (Vd), and half-life $(t_{1/2})$ were determined using the Saw chuk and Zaske equation. The volume of distribution Was $27\%$ greater than the Schentag's study (0.26 vs 0.33 l/kg), but the half-life was similar to the Levy's study. The predicted half-lives based on IBW were the closest to actual half-lives (1.85 vs 2.01 hr).

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1242-1242
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• 2001

The use of fibre optic probes for NIR quality control in the industry is becoming very important, as it provides a powerful tool to reduce sample analysis time and it facilitates the implementation of on-line analyses. However, most of the applications of fibre optics and probes have been done on suspensions, clear liquids and films, chemical and pharmaceutical products and also on fruits and animal products. Traditional applications of near infrared spectroscopy in agriculture have been developed in reflectance mode and calibration transfer could be an interesting way to reduce efforts. Classical methods for calibration transfer between different instruments involve the use of sealed reference cups, but, as fibre optic analysis does not use cups, it is necessary to develop new methods for calibration transfer without standards (Blank et al., 1996). In this paper, we have studied how the most used mathematical pretreatments (three methods of Multiplicative Scatter Correction, Standard Normal Variate, Detrending and derivatives) and their combinations applied to calibration development can contribute to reduce spectral differences between instruments. Calibration equations were obtained for three sets of cereals (barley, wheat and maize) scanned in reflectance mode and then they were validated with samples analysed in reflectance and interactance-reflectance mode (fibre optic). Preliminary results show how some combination of pretreatments reduce the differences in the predicted values, measured as standard error of differences, facilitating the use of calibrations obtained in reflectance for samples analysed by interactance-reflectance. However, the application of pretreatments is not enough to satisfy the control limits for calibration transfer suggested by Shenk et al. (1992), and it should be necessary to combine them with a specific algorithm for instruments standardization.

• International Journal of Concrete Structures and Materials
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• v.10 no.sup3
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• pp.97-108
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• 2016

When the energy performance of concrete is substantially higher than that of normal type concrete, such concrete is regarded as energy efficient concrete (WBSCSD 2009). An experimental study was conducted to investigate mechanical properties of energy efficient concrete with binary, ternary and quaternary admixture at different curing ages. Slump test for workability and air content test were performed on fresh concretes. Compressive strength, splitting tensile strength were made on hardened concrete specimens. The mechanical properties of concrete were compared with predicted values by ACI 363R-84 Code, NZS 3101-95 Code, CSA A23.3-94 Code, CEB-FIP Model, EN 1991, EC 2-02, AIJ Code, JSCE Code, and KCI Code. The use of silica fume increased the compressive strengths, splitting tensile strengths, modulus of elasticities and Poisson's ratios. On the other hand, the compressive strength and splitting tensile strength decreased with increasing fly ash.

• Journal of the Korean Geotechnical Society
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• v.19 no.5
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• pp.145-154
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• 2003

In this study, the variation in excess pore pressure during dissipation is estimated by using successive cavity expansion theory and finite difference technique based on axisymmetric uncoupled linear consolidation theory with separate consideration of magnitude and initial distribution $\Delta{u}_{oct}$induced by changes of octahedral normal stress, and $\Delta{u}_{shear}$ induced by changes of octahedral shear stress. The coefficient of consolidation is also estimated by trial and error procedure until the predicted dissipation curve matches the measured curve at a typical degree of dissipation. The proposed method is applied to the results of miniature piezocone tests at Louisiana State University calibration chamber system. Based on the results of interpretation and the comparison with experimental measurements and those from other solutions, the prediction dissipation curves show a good match with those measured during dissipation tests and the values of coefficient of consolidation estimated by proposed method are more close to the range of laboratory measurements than those of other theories.

• Bulletin of the Korean Chemical Society
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• v.32 no.12
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• pp.4397-4402
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• 2011

The NF-${\kappa}B$ system of transcription factors plays a crucial role in inflammatory diseases, making it an important drug target. We combined quantitative structure activity relationships for predicting the activity of new compounds and quantitative dynamic models for the NF-${\kappa}B$ network with intracellular concentration models. GFA-MLR QSAR analysis was employed to determine the optimal QSAR equation. To validate the predictability of the $IKK{\beta}$ QSAR model for an external set of inhibitors, a set of ordinary differential equations and mass action kinetics were used for modeling the NF-${\kappa}B$ dynamic system. The reaction parameters were obtained from previously reported research. In the IKKb QSAR model, good cross-validated $q^2$ (0.782) and conventional $r^2$ (0.808) values demonstrated the correlation between the descriptors and each of their activities and reliably predicted the $IKK{\beta}$ activities. Using a developed simulation model of the NF-${\kappa}B$ signaling pathway, we demonstrated differences in $I{\kappa}B$ mRNA expression between normal and different inhibitory states. When the inhibition efficiency increased, inhibitor 1 (PS-1145) led to long-term oscillations. The combined computational modeling and NF-${\kappa}B$ dynamic simulations can be used to understand the inhibition mechanisms and thereby result in the design of mechanism-based inhibitors.