• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2001년도 가을 학술발표회 논문집
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• pp.175-182
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• 2001

Effective length factor approach for framed column design has long played an important design-aid role. This approach, however, is effective only when the columns are in the form of prismatic or uniform cross sections. Structural engineers who have to design or analyse framed columns with variable cross sections need some means to do their job. By using the finite element method, the stability analysis of the isolated compression members with variable cross sections and that of the framed columns are performed. The parameters considered in the stability analysis are taper and sectional property parameters of the columns, the second moment of inertia ratio of beam to column, and beam span to column height ratio. On the basis of the stability analysis results, effective length factor formulas for the columns with variable sections are derived.

• Macromolecular Research
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• 제11권5호
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• pp.311-316
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• 2003

The kinetics of photoinitiated polymerization of dimethacrylate macromonomers have been studied to determine the diffusion-controlled reaction parameters using attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR). A predicted kinetic rate expression with a diffusion control factor was employed to estimate an effective rate constant and to define the reaction-controlled and diffusion-controlled regimes in the photopolymerization. An effective rate constant, k$_{e}$, can be obtained from the predicted kinetic rate expression. At the earlier stages of polymerization, the average values of kinetic rate constants do not vary during the reaction time. As the reaction conversion, $\alpha$, reaches the critical conversion, $\alpha$$_{c}$, in the predicted kinetic expression, the reaction becomes to be controlled by diffusion due to the restricted mobility of dimethacrylate macromonomers. A drop in value of effective rate constant causes a drastic decrease of reaction rate at the later stages of polymerization. By determining the effective rate constants, the reaction-controlled and diffusion-controlled regimes were properly defined even in the photopolymerization reaction system.m.m.

• 천문학회보
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• 제38권2호
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• pp.47.1-47.1
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• 2013

We present structural parameters of galaxies in the Extended Viro Cluster Catalog (EVCC), new catalog of galaxies in the Viro cluster using homogeneous Sloan Digital Sky Survey (SDSS) Date Release 7 (DR7) data. The EVCC covers more extended region of the Viro cluster than of the Virgo Cluster Catalog (VCC) and presents updated morphologies of galaxies using multi-band images and spectral features. We obtain the surface brightness profiles of galaxies using ellipse task in IRAF. Based on the analysis of surface brightness profile we construct a catalog of various structural parameters of galaxies, i.e. central surface brightness, effective radius, sersic index, effective surface brightness, and mean effective surface brightness. Taking advantage of these structural parameters in various parameter spaces, we refine criteria of dividing giant elliptical and dwarf elliptical galaxies. In addition, we found that bulge dominated galaxies have larger sersic index and brighter central surface brightness than disk dominated galaxies. At fixed magnitude, dwarf elliptical galaxies dwarf lenticular galaxies, and dwarf irregular low surface brightness (LSB) galaxies show larger effective radii than giant elliptical galaxies, giant lenticular galaxies, and irregular high surface brightness (HSB) galaxies, respectively. Dwarf elliptical galaxies and dwarf irregular LSB galaxies occupy the similar structural parameter spaces. We suggest that giant elliptical galaxies and dwarf elliptical galaxies may have different origin.

• The Korean Journal of Pain
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• 제33권3호
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• pp.258-266
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• 2020

Background: The genicular nerve block (GNB) is demonstrated from several reports to alleviate pain and improve knee functionality in patients with chronic knee osteoarthritis (OA). Ultrasound (US)-guided GNB has been the most used imaging method. This study aimed to compare the effectiveness of US-guided versus blind GNB in the treatment of knee OA. Methods: This prospective, randomized clinical trial included patients with knee OA based on American College of Rheumatology diagnostic criteria. The patients were evaluated for clinical and dynamometer parameters at the baseline, 4 weeks after treatment, and 12 weeks after treatment. The patients underwent blind injection or US-guided injection. Results: When compared with the baseline, both groups showed significant improvement in pain, physical function, and quality of life parameters. Significant differences were observed between the groups for clinical parameters (30-second chair stand test, 6-minute walk test) in favor of the US-guided group. On the other hand, blind injection was more significantly effective on some parameters of the Nottingham Health Profile. There wasn't any significant improvement in isokinetic muscle strength for either group. Conclusions: This study demonstrated that both US-guided and blind GNB, in the treatment of knee OA, were effective in reducing symptoms and improving physical function. GNB wasn't an effective treatment for isokinetic muscle function. US-guided injections may yield more effective clinical results than blind injections.

• 동력기계공학회지
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• 제19권5호
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• pp.25-31
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• 2015

This study deals with optimal conditions for design parameters of the multistage bollard with up and down installed on the street to protect pedestrians or stop cars. FE simulation and Taguchi method are used to achieve the optimization for the automatic multistage bollard to minimize effective stress caused by the external force. Thickness, height of stage 2, diameter and over-all height which affect its structural strength are chosen as design parameters. According to the experiments combined by orthogonal array, each of the effective stresses is evaluated. And the results are analyzed by using the signal to noise ratio concept of Taguchi method. From their results, the optimal combination of design parameters are proposed.

• Communications for Statistical Applications and Methods
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• 제27권3호
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• pp.301-311
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• 2020

Schwarz's Bayesian information criterion (BIC) is one of the most popular criteria for model selection, that was derived under the assumption of independent and identical distribution. For correlated data in longitudinal studies, Jones (Statistics in Medicine, 30, 3050-3056, 2011) modified the BIC to select the best linear mixed effects model based on the effective sample size where the number of parameters in covariance structure was not considered. In this paper, we propose an extended Jones' modified BIC by considering covariance parameters. We conducted simulation studies under a variety of parameter configurations for linear mixed effects models. Our simulation study indicates that our proposed BIC performs better in model selection than Schwarz's BIC and Jones' modified BIC do in most scenarios. We also illustrate an example of smoking data using a longitudinal cohort of cancer patients.

• 대한기계학회논문집B
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• 제24권5호
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• pp.709-717
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• 2000

Cyclic variability has long been recognized as limiting the range of operating conditions of spark ignition engines, in particular, under lean and highly diluted operation conditions. The cyclic combustion variations can be characterized by the pressure parameters, combustion parameters, and flame front parameters. The coefficient of variation in indicated mean effective pressure ($COV_{IMEP}$) defines the cyclic variability in indicated work per cycle, and it has been found that vehicle driveability problems usually result when $COV_{IMEP}$ exceeds about 10%. For analysis of the cyclic variability in SI engines at idling, the results show that cyclic variability by the $COV_{IMEP}$ or the coefficient of variation in maximum pressure can be explained and may be consequently reduced by the help of the optimum spark timings.

• Geomechanics and Engineering
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• 제25권4호
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• pp.341-345
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• 2021

1D sand compression response to ko-loading experiences volume contraction from low to high effective stress regimes. Previous study suggested compressibility model with physically correct asymptotic void ratios at low and high stress levels and examined only for both remolded clays and natural clays. This study extends the validity of Enhanced Terzaghi model for different sand types complied from 1D compression data. The model involved with four parameters can adequately fit 1D sand compression data for a wide stress range. The low stress obtained from fitting parameters helps to identify the initial fabric conditions. In addition, strong correlation between compressibility and the void ratio at low stress facilitates determination of self-consistent fitting parameters. The computed tangent constrained modulus can capture monotonic stiffening effect induced by an increase in effective stress. The magnitude of tangent stiffness during large strain test should not be associated with small strain stiffness values. The use of a single continuous function to capture 1D stress-strain sand response to ko-loading can improve numerical efficiency and systematically quantify the yield stress instead of ad hoc methods.

• 한국해양공학회지
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• 제36권3호
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• pp.194-210
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• 2022

Recently, an analysis method using machine learning for solving problems in coastal and ocean engineering has been highlighted. Machine learning models are effective modeling tools for predicting specific parameters by learning complex relationships based on a specified dataset. In coastal and ocean engineering, various studies have been conducted to predict dependent variables such as wave parameters, tides, storm surges, design parameters, and shoreline fluctuations. Herein, we introduce and describe the application trend of machine learning models in coastal and ocean engineering. Based on the results of various studies, machine learning models are an effective alternative to approaches involving data requirements, time-consuming fluid dynamics, and numerical models. In addition, machine learning can be successfully applied for solving various problems in coastal and ocean engineering. However, to achieve accurate predictions, model development should be conducted in addition to data preprocessing and cost calculation. Furthermore, applicability to various systems and quantifiable evaluations of uncertainty should be considered.

• International Journal of Internet, Broadcasting and Communication
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• 제15권2호
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• pp.240-247
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• 2023

In this paper, effective data management in industrial sites such as intelligent factories using time series data was studied. For effective management of time series data, variables considering the significance of the data were used, and hyper parameters calculated through LSTM AE were applied. We propose an optimized modeling considering the importance of each data section, and through this, outlier data of time series data can be efficiently processed. In the case of applying data significance and applying hyper parameters to which the research in this paper was applied, it was confirmed that the error rate was measured at 5.4%/4.8%/3.3%, and the significance of each data section and the significance of applying hyper parameters to optimize modeling were confirmed.