• Korean Journal of Materials Research
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• v.33 no.9
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• pp.367-371
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• 2023

In this study we examine variations in the structure of perovskite compounds of LaBa₂Cu₂O₉, LaBa2₂CaCu₃O₁₂ and LaBa₂Ca₂Cu₅O₁₅ synthesized using the solid state reaction method. The samples' compositions were assessed using X-ray fluorescence (XRF) analysis. The La: Ba: Ca: Cu ratios for samples LaBa₂Cu₂O₉, LaBa2₂CaCu₃O₁₂ and LaBa₂Ca₂Cu₅O₁₅ were found by XRF analysis to be around 1:2:0:2, 1:2:1:3, and 1:2:2:5, respectively. The samples' well-known structures were then analyzed using X-ray diffraction. The three samples largely consist of phases 1202, 1213, and 1225, with a trace quantity of an unknown secondary phase, based on the intensities and locations of the diffraction peaks. According to the measured parameters a, b, and c, every sample has a tetragonal symmetry structure. Each sample's mass density was observed to alter as the lead oxide content rose. Scanning electron microscope (SEM) images of the three phases revealed that different Ca-O and Cu-O layers can cause different grain sizes, characterized by elongated thin grains, without a preferred orientation.

• Computers and Concrete
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• v.33 no.1
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• pp.27-39
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• 2024

In this study, the authors investigate the free vibration behavior of three-phases functionally graded sandwich plates using a novel nth-order shear deformation theory. These plates are composed of a homogeneous core and two face-sheet layers made of different functionally graded materials. This is the novel type of the sandwich structures that can be applied in many fields of mechanical engineering and industrial. The proposed theory only requires four unknown displacement functions, and the transverse displacement does not need to be separated into bending and shear parts, simplifying the theory. One noteworthy feature of the proposed theory is its ability to capture the parabolic distribution of transverse shear strains and stresses throughout the plate's thickness while ensuring zero values on the two free surfaces. By eliminating the need for shear correction factors, the theory further enhances computational efficiency. Equations of motion are established using Hamilton's principle and solved via Navier's solution. The accuracy and efficiency of the proposed theory are verified by comparing results with available solutions. The authors then use the proposed theory to investigate the free vibration characteristics of three-phases functionally graded sandwich plates, considering the effects of parameters such as aspect ratio, side-to-thickness ratio, skin-core-skin thicknesses, and power-law indexes. Through careful analysis of the free vibration behavior of three-phases functionally graded sandwich plates, the work highlighted the significant roles played by individual material ingredients in influencing their frequencies.

• Journal of Dental Anesthesia and Pain Medicine
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• v.24 no.2
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• pp.119-128
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• 2024

Background: In pediatric dentistry, fear and anxiety are common among children. Local anesthetics (LA) are widely used to control pain and reduce discomfort in children during dental treatment. Topical anesthetics play a vital role in reducing pain and the unpleasant sensation of a needle puncture in children. Peppermint oil has been extensively used for various diseases. However, its anesthetic properties remain unknown. Peppermint oil, used in mouthwashes, toothpastes, and other topical preparations has analgesic, anesthetic, and antiseptic properties. This study aimed to compare and evaluate pain perception following the topical application of peppermint oil versus lignocaine spray before an intraoral injection in children, aged 8-13 years. Method: Fifty-two children, aged between 8-13 years, who required local anesthesia for dental treatment were divided into two groups of 26 each by simple random sampling (Group 1: 0.2% peppermint oil and Group 2: lignocaine spray). In both groups, physiological measurements (e.g., heart rate) were recorded using pulse oximetry before, during, and after the procedure. Objective pain measurement (Sound Eye Motor (SEM) scale) during administration and subjective measuremeant (Wong-Baker Faces Pain Rating Scale (WBFPRS)) after LA administration were recorded. This was followed by the required treatment of the child. Physiological parameters were compared between the two groups using an independent t-test for intergroup assessment and a paired t-test and repeated-measures ANOVA for intragroup comparisons. The Mann-Whitney U test was used to analyze the pain scores. Results: Intragroup mean heart rates, before, during, and after treatment were statistically significantly different (P < 0.05). However, the intergroup mean pulse rates did not differ significantly between the two groups. The mean WBFPS score in the lignocaine spray group was 4.133 ± 2.06 was statistically different from that of the peppermint oil group (0.933 ± 1.03; P < 0.001^*). The mean SEM score was significantly lower in the peppermint oil group than that in the lignocaine spray group (P = 0.006). No negative effects were observed in this study. Conclusion: 0.2% peppermint oil was effective in reducing pain perception.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1639-1645
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• 1991

Because of the important role LD converters play in the production of high quality steel, various dynamic models have been attempted in the past by many researchers not only to understand the complex chemical reactions that take place in the converter process but also to assist the converter operation itself using computers. And yet no single dynamic model was found to be completely satisfactory because of the complexity involved with the process. The process indeed involves dynamic energy and mass balances at high temperatures accompanied by complex chemical reactions and transport phenomena in the molten state. In the present study, a mathematical model describing the dynamic behavior of LD converter process has been developed. The dynamic model describes the time behavior of the temperature and the concentrations of chemical species in the hot metal bath and slag. The analysis was greatly facilitated by dividing the entire process into three zones according to the physical boundaries and reaction mechanisms. These three zones were hot metal (zone 1), slag (zone 2) and emulsion (zone 3) zones. The removal rate of Si, C, Mn and P and the rate of Fe oxidation in the hot metal bath, and the change of composition in the slag were obtained as functions of time, operating conditions and kinetic parameters. The temperature behavior in the metal bath and the slag was also obtained by considering the heat transfer between the mixing and the slag zones and the heat generated from chemical reactions involving oxygen blowing. To identify the unknown parameters in the equations and simulate the dynamic model, Hooke and Jeeves parttern search and Runge-Kutta integration algorithm were used. By testing and fitting the model with the data obtained from the operation of POSCO #2 steelmaking plant, the dynamic model was able to predict the characteristics of the main components in the LD converter. It was possible to predict the optimum CO gas recovery by computer simulation

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.571-576
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• 2002

There have been a lot of considerations dealing with improving the performance of neuro-fuzzy system. The studies on the neuro-fuzzy modeling have largely been devoted to two approaches. First is to improve performance index of system. The other is to reduce the structure size. In spite of its satisfactory result, it should be noted that these are difficult to extend to high dimensional input or to increase the membership functions. We propose a novel neuro-fuzzy system based on the efficient clustering method for initializing the parameters of the premise part. It is a very useful method that maintains a few number of rules and improves the performance. It combine the various algorithms to improve the performance. The Expectation-Maximization algorithm of Gaussian mixture model is an efficient estimation method for unknown parameter estimation of mirture model. The obtained parameters are used for fuzzy clustering method. The proposed method satisfies these two requirements using the Gaussian mixture model and neuro-fuzzy modeling. Experimental results indicate that the proposed method is capable of giving reliable performance.

• Tuberculosis and Respiratory Diseases
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• v.60 no.4
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• pp.437-450
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• 2006

Background : Acute respiratory distress syndrome (ARDS) is characterized by severe inflammatory pulmonary edema of unknown pathogenesis. To investigate the pathogenesis of ARDS associated with neutrophilic oxidative stress, the role of phospholipase $A_2$ ($PLA_2$) was evaluated by the inhibition of calcium channel. Methods : In Sprague-Dawley rats, acute lung injury (ALI) was induced by the instillation of E.coli endotoxin (ETX) into the trachea. At the same time, diltiazem was given 60 min prior to tracheal instillation of ETX. Parameters of ALI such as lung and neutrophil $PLA_2$, lung myeloperoxidase (MPO), BAL neutrophils, protein, surfactant were measured. Production of free radicals from neutrophils was measured also. Morphological studies with light microscope and electron microscope were carried out and electron microscopic cytochemistry for detection of free radicals was performed also. Results : Diltiazem had decreased the ALI parameters effectively in ETX given rats and decreased the production of free radicals from neutrophils and lung tissues. Morphological studies denoted the protective effects of diltiazem. Conclusion : Diltiazem, a calcium channel blocker, was effective in amelioration of ALI by the suppression of neutrophilic oxidative stress mediated by $PLA_2$ activation.

• Geotechnical Engineering
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• v.10 no.1
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• pp.47-62
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• 1994

It has been well known that the rainfall-triggered rise of groundwater levels is one of the most important factors resulting the instability of the hillside slopes. Thus, the prediction of porewater pressure is an essential step in the evaluation of landslide hazard. This study involves the development and verification of numerical groundwater flow model for the prediction of groundwater flow fluctuations accounting for both of unsatu나toed flow and saturated flow on steep hillside slopes. The first part of this study is to develop a nomerical groundwater flow model. The numerical technique chosen for this study is the finitro element method in combination with the finite difference method. The finite element method is used to transform the space derivatives and the finite difference method is used to discretize the time domain. The second part of this study is to estimate the unknown model parameters used in the proposed numerical model. There were three parameters to be estimated from input -output record $K_e$, $\psi_e$, b. The Maximum -A-Posteriori(MAP) optimization method is utilized for this purpose, . The developed model is applied to a site in Korea where two debris avalanches of large scale and many landslides of small scale were occurred. The results of example analysis show that the numerical groundwater flow model has a capacity of predicting the fluctuation of groundwater levels due to rainfall reasonably well.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.659-666
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• 2006

Servo-motors are used as key components of automated system by performing precise motion control as accurate positioning and accurate speed regulation in response to the commands from computers and sensors. Especially, the linear brushless servo-motors have numerous advantages over the rotary servo motors which have connection with the friction induced transfer mechanism such as ball screws, timing belts, rack/pinion. This paper proposes an estimation method of unknown motor system parameters using the informations from the sinusoidal driving type linear brushless DC motor dynamics and outputs. The estimated parameters can be used to tune the controller gain and a disturbance observer. In order to meet this purpose high performance Digital Signal Processor, TMS320F240, designed originally for implementation of a Field Oriented Control(FOC) technology is adopted as a controller of the liner BLDC servo motor. Having A/D converters, PWM generators, rich I/O port internally, this servo motor application specific DSP play an important role in servo motor controller. This linear BLDC servo motor system also contains IPM(Intelligent Power Module) driver and hail sensor type current sensor module, photocoupler module for isolation of gate signals and fault signals.

• Journal of Korea Water Resources Association
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• v.41 no.9
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• pp.943-958
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• 2008

This study employs Bayesian regression analysis for fitting discharge rating curves. The parameter estimates using the Bayesian regression analysis were compared to ordinary least square method using the t-distribution. In these comparisons, the mean values from the t-distribution and the Bayesian regression are not significantly different. However, the difference between upper and lower limits are remarkably reduced with the Bayesian regression. Therefore, from the point of view of uncertainty analysis, the Bayesian regression is more attractive than the conventional method based on a t-distribution because the data size at the site of interest is typically insufficient to estimate the parameters in rating curve. The merits and demerits of the two types of estimation methods are analyzed through the statistical simulation considering heteroscedasticity. The validation of the Bayesian regression is also performed using real stage-discharge data which were observed at 5 gauges on the Anyangcheon basin. Because the true parameters at 5 gauges are unknown, the quantitative accuracy of the Bayesian regression can not be assessed. However, it can be suggested that the uncertainty in rating curves at 5 gauges be reduced by Bayesian regression.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.33-41
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• 2023

As carbon-free has been getting interest, renewable energy sources have been increasing. However, renewable energy is intermittent and variable so it is difficult to predict the produced electrical energy from a renewable energy source. In this study, digital-twin concept is applied to solve difficulties in predicting electrical energy from a renewable energy source. Considering that rotation of wind turbine has high correlation with produced electrical energy, a model which simulates rotation in the drivetrain of a wind turbine is developed. The base of a drivetrain simulation model is set with well-known state equation in mechanical engineering, which simulates the rotating system. Simulation based machine learning is conducted to get unknown parameters which are not provided by manufacturer. The simulation is repeated and parameters in simulation model are corrected after each simulation by optimization algorithm. The trained simulation model is validated with 27 real wind turbine operation data set. The simulation model shows 4.41% error in average compared to real wind turbine operation data set. Finally, it is assessed that the drivetrain simulation model represents the real wind turbine drivetrain system well. It is expected that wind-energy-prediction accuracy would be improved as wind turbine digital twin including the developed drivetrain simulation model is applied.