• Journal of Pharmaceutical Investigation
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• v.38 no.2
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• pp.135-142
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• 2008

The present study describes the evaluation of the bioequivalence of two atorvastatin tablets, Lipitor $Tablet^{(R)}$ (Pfizer, reference drug) and Atorva $Tablet^{(R)}$ (Yuhan, test drug), according to the guidelines of Korea Food and Drug Administration (KFDA). Forty-nine healthy male Korean volunteers received each medicine at the atorvastatin dose of 40 mg in a $2{\times}2$ crossover study with a two weeks washout interval. After drug administration, serial blood samples were collected at a specific time interval from 0-48 hours. The plasma atorvastatin concentrations were monitored by an high performance liquid chromatography -tandem mass spectrometer (LC-MS/MS) employing electrospray ionization technique and operating in multiple reaction monitoring (MRM) and positive ion mode. The total chromatographic run time was 4.5 min and calibration curves were linear over the concentration range of 0.1-100 ng/mL for atorvastatin. The method was validated for selectivity, sensitivity, linearity, accuracy and precision. $AUC_t$ (the area under the plasma concentration-time curve from time zero to 48hr) was calculated by the linear log trapezoidal rule method. $C_{max}$ (maximum plasma drug concentration) and $T_{max}$ (time to reach $C_{max}$) were complied trom the plasma concentration-time data. Analysis of variance was carried out using logarithmically transformed $AUC_t$ and $C_{max}$. No significant sequence effect was found for all of the bioavailability parameters indicating that the crossover design was properly performed. The 90% confidence intervals of the $AUC_t$ ratio and the $C_{max}$ ratio for Atorva $Tablet^{(R)}$ / Lipitor $Tablet^{(R)}$ were ${\log}\;0.9413{\sim}{\log}\;1.0179$ and ${\log}\;0.831{\sim}{\log}\;1.0569$, respectively. These values were within the acceptable bioequivalence intervals of ${\log}\;0.8{\sim}{\log}\;1.25$. Based on these statistical considerations, it was concluded that the test drug, Atorva $Tablet^{(R)}$ was bioequivalent to the reference drug, Lipitor $Tablet^{(R)}$.

• Journal of Korea Water Resources Association
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• v.46 no.5
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• pp.519-530
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• 2013

To provide a reliable tool for runoff simulations of ungauged watersheds upstream of reservoirs, a daily runoff simulation model, Tank model, is restructured, the parameter regionalization of the model is conducted, and the model's applicability is evaluated. Taking into account the characteristics of runoffs from the watersheds, a three-tank model is employed. The percolation process of the model's third tank is eliminated, considering the water budgets of the watersheds, and its evapotranspiration component is improved, reflecting the conditions of meteorological observation in South Korea. The sensitivity analysis of the model shows that the model's behaviors, varying with a sensitive parameter, ${\alpha}$, are reasonable. The regional parameter estimation equations are determined, using the characteristics and land uses of the watersheds as variables. The model is applied for the runoff simulations of three watersheds and the water stage simulation of one reservoir, and the simulation results are then compared with the observed values, which prove to be in close agreement with the observations. In addition, the results from simulating inflows of twenty-four reservoirs using the model show that the averages of evapotranspiration rate and runoff rate are 42.8% and 56.6%, respectively, which are resonable. Consequently, it is concluded that the model is practically applicable to simulating runoffs from watersheds upstream of reservoirs, and simulated inflow data are useful for watershed management and reservoir planning, design, and operation.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.683-690
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• 2021

The ventilation system of the engine room of a ship is generally installed to supply the combustion air necessary for the internal combustion engine and to remove the heat source generated in the engine room, and it must satisfy the international standard (ISO 8861) for the design conditions and calculation standards for the ventilation of the ship engine room. The response delay of the ventilation system including the fire detector is affected by the airflow formed inside the area and the location of the fire detector. In this study, to improve the initial fire detection response speed of a fire detector installed on a fishing vessel and to maintain the sensitivity of the installed detector, the smoke behavior was simulated using the air flow field inside the engine room, the amount of combustion air in the internal combustion engine, and the internal pressure of the engine room as variables. Analysis of the simulation results showed that reducing the flow rate in the air flow field and increasing the vortex by reducing the internal pressure of the engine room and installing a smoke curtain would accelerate the rise of the ceiling of the smoke component and improve the smoke detector response speed and ventilation system.

• Journal of the Korea Society for Simulation
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• v.28 no.2
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• pp.1-14
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• 2019

A full scale hydrodynamic simulation that requires an accurate reproduction of shock-induced detonation was conducted for design of an energetic component system. A detailed hydrodynamic analysis SW was developed to validate the reactive flow model for predicting the shock propagation in a train configuration and to quantify the shock sensitivity of the energetic materials. The pyrotechnic device is composed of four main components, namely a donor unit (HNS+HMX), a bulkhead (STS), an acceptor explosive (RDX), and a propellant (BPN) for gas generation. The pressurized gases generated from the burning propellant were purged into a 10 cc release chamber for study of the inherent oscillatory flow induced by the interferences between shock and rarefaction waves. The pressure fluctuations measured from experiment and calculation were investigated to further validate the peculiar peak at specific characteristic frequency (${\omega}_c=8.3kHz$). In this paper, a step-by-step numerical description of detonation of high explosive components, deflagration of propellant component, and deformation of metal component is given in order to facilitate the proper implementation of the outlined formulation into a shock physics code for a full scale hydrodynamic simulation of the energetic component system.

• Membrane Journal
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• v.32 no.4
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• pp.253-263
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• 2022

This study suggests a guideline for designing unit process of wastewater reuse in terms of a maintenance of the process based on critical parameters to draw a high quality performance of RO unit. Defining the parameters was done by applying membrane integrity test (MIT) in pretreatment process utilizing lab-scale MF. SDI is utilized for judging whether permeate is suitable to RO unit. However, result said TOC concentration matching with particle count analysis is better for judging the permeate condition. When membrane test pressure (P_test) was measured to derive log removal value in PDT, virgin state of membrane fiber was used to measure dynamic contact angle utilizing surface tension of the membrane fiber. Actually, foulant affects to the state of membrane surface, and it decreases the P_test value along with time elapsed. Consequently, LRV_DIT is also affected by P_test value. Thus, sensitivity of direct integrity test descends with result of P_test value change, so P_test value should be considered not the virgin state of the membrane but its current state. Overall, this study focuses on defining design parameters suitable to MF pretreatment for RO process in wastewater reuse by assessing its impact. Therefore, utilities can acknowledge that the membrane surface condition must be considered when users conduct the direct integrity test so that P_test and other relative parameter used to calculate LRV_DIT are adequately measured.

• Imaging Science in Dentistry
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• v.53 no.3
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• pp.193-198
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• 2023

Purpose: Artificial intelligence (AI) is poised to play a major role in medical diagnostics. Periodontal disease is one of the most common oral diseases. The early diagnosis of periodontal disease is essential for effective treatment and a favorable prognosis. This study aimed to assess the effectiveness of AI in diagnosing periodontal bone loss through radiographic analysis. Materials and Methods: A literature search involving 5 databases (PubMed, ScienceDirect, Scopus, Health and Medical Collection, Dentistry and Oral Sciences) was carried out. A specific combination of keywords was used to obtain the articles. The PRISMA guidelines were used to filter eligible articles. The study design, sample size, type of AI software, and the results of each eligible study were analyzed. The CASP diagnostic study checklist was used to evaluate the evidence strength score. Results: Seven articles were eligible for review according to the PRISMA guidelines. Out of the 7 eligible studies, 4 had strong CASP evidence strength scores (7-8/9). The remaining studies had intermediate CASP evidence strength scores (3.5-6.5/9). The highest area under the curve among the reported studies was 94%, the highest F1 score was 91%, and the highest specificity and sensitivity were 98.1% and 94%, respectively. Conclusion: AI-based detection of periodontal bone loss using radiographs is an efficient method. However, more clinical studies need to be conducted before this method is introduced into routine dental practice.

• Journal of the Korean Geotechnical Society
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• v.22 no.6
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• pp.15-26
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• 2006

Although numerous investigations have been performed over the years to predict the behavior and bearing capacity of piles, the mechanisms are not yet entirely understood. The prediction of bearing capacity is a difficult task, because large numbers of factors affect the capacity and also have complex relationship one another. Therefore, it is extremely difficult to search the essential factors among many factors, which are related with ground condition, pile type, driving condition and others, and then appropriately consider complicated relationship among the searched factors. The present paper describes the application of Artificial Neural Network (ANN) in predicting the capacity including its components at the tip and along the shaft from dynamic load test of the driven piles. Firstly, the effect of each factor on the value of bearing capacity is investigated on the basis of sensitivity analysis using ANN modeling. Secondly, the authors use the design methodology composed of ANN and genetic algorithm (GA) to find optimal neural network model to predict the bearing capacity. The authors allow this methodology to find the appropriate combination of input parameters, the number of hidden units and the transfer structure among the input, the hidden and the out layers. The results of this study indicate that the neural network model serves as a reliable and simple predictive tool for the bearing capacity of driven piles.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.457-468
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• 2020

Problems arising during pile design works for plant construction, civil and architecture work are mostly come from uncertainty of geotechnical characteristics. In particular, obtaining the N-value measured through the Standard Penetration Test (SPT) is the most important data. However, it is difficult to obtain N-value by drilling investigation throughout the all target area. There are many constraints such as licensing, time, cost, equipment access and residential complaints etc. it is impossible to obtain geotechnical characteristics through drilling investigation within a short bidding period in overseas. The geotechnical characteristics at non-drilling investigation points are usually determined by the engineer's empirical judgment, which can leads to errors in pile design and quantity calculation causing construction delay and cost increase. It would be possible to overcome this problem if N-value could be predicted at the non-drilling investigation points using limited minimum drilling investigation data. This study was conducted to predicted the N-value using an Artificial Neural Network (ANN) which one of the Artificial intelligence (AI) method. An Artificial Neural Network treats a limited amount of geotechnical characteristics as a biological logic process, providing more reliable results for input variables. The purpose of this study is to predict N-value at the non-drilling investigation points through patterns which is studied by multi-layer perceptron and error back-propagation algorithms using the minimum geotechnical data. It has been reviewed the reliability of the values that predicted by AI method compared to the measured values, and we were able to confirm the high reliability as a result. To solving geotechnical uncertainty, we will perform sensitivity analysis of input variables to increase learning effect in next steps and it may need some technical update of program. We hope that our study will be helpful to design works in the future.

• Journal of The Korean Association For Science Education
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• v.44 no.1
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• pp.11-27
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• 2024

This study aimed to investigate the role of scientific empathy in influencing students' productive disciplinary engagement in scientific activities and analyze the key factors of scientific empathy that manifest during this process. Twelve fifth-grade students were divided into three subgroups based on their general empathic abilities. Lessons promoting productive disciplinary engagement, integrating design thinking processes, were conducted. Subgroup discourse analysis during idea generation and prototype stages, two of five problem-solving steps, enabled observation of scientific empathy and practice aspects. The results showed that applying scientific empathy effectively through design thinking facilitated students' productive disciplinary engagement in science. In the idea generation stage, we observed an initial increase followed by a decrease in scientific empathy and practice utterances, while during the prototyping stage, utterance frequency increased, particularly in the later part. However, subgroups with lower empathic abilities displayed decreased discourse frequency in scientific empathy and practice during the prototype stage due to a lack of collaborative communication. Across all empathic ability levels, the students articulated all five key factors of scientific empathy through their utterances in situations involving productive science engagement. In the high empathic ability subgroup, empathic understanding and concern were emphasized, whereas in the low empathic ability subgroup, sensitivity, scientific imagination, and situational interest, factors of empathizing with the research object, were prominent. These results indicate that experiences of scientific empathy with research objects, beyond general empathetic abilities, serve as a distinct and crucial factor in stimulating diverse participation and sustaining students' productive engagement in scientific activities during science classes. By suggesting the potential multidimensional impact of scientific empathy on productive disciplinary engagement, this study contributes to discussions on the theoretical structure and stability of scientific empathy in science education.

• The Korean Journal of Pesticide Science
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• v.14 no.4
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• pp.319-325
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• 2010

To understand the influences of the substituents ($R_1{\sim}R_4$) on insecticidal activity of N'-phenyl-N-methylformamidine analogues (1~22) against two spotted spider mite (Tetranychus urticae), comparative molecular field analysis (CoMFA) model and comparative molecular similarity indices analysis (CoMSIA) model as three dimensional quantitative structure-activity relationships (3D-QSARs) model were derived and discussed quantitatively. From the results, the correlativity and predictability ($r^2{_{cv.}}=0.575$ and $r^2{_{ncv.}}=0.945$) of the CoMFA 1 model were higher than those of the rest models. The the CoMFA 1 and CoMSIA 1 model with the sensitivity of the perturbation and the prediction produced ($d_q{^{2'}}/dr^2{_{yy}}=1.071{\sim}1.146$ & $q^2=0.545{\sim}0.626$) by a progressive scrambling analysis were not dependent on chance correlation. The insecticidal activities from the optimized CoMFA 1 model were depend upon the steric field (62.5%), electrostatic field (28.9%), and hydrophobic field (8.6%) of N'-phenyl-N-methylformamidine analogues. Therefore, the inhibitory activities with optimized CoMFA 1 model were dependent upon steric factor. From the contour maps of the optimized models, it is predicted that the structural distinctions that contribute to the insecticidal activity will be able to applied new potent insecticides design.