• International Journal of Quality Innovation
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• v.6 no.1
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• pp.109-118
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• 2005

The parameter design is the most emphasized measure by researchers for a new products development. It is critical for makers to achieve simultaneously in both the time-to-market production and the quality enhancement. However, there are difficulties in practical application, such as (1) complexity and nonlinear relationships co-existed among the system's inputs, outputs and control parameters, (2) interactions occurred among parameters, (3) where the adjustment factors of Taguchi's two-phase optimization procedure cannot be sure to exist in practice, and (4) for some reasons, the data became lost or were never available. For these incomplete data, the Taguchi methods cannot treat them well. Neural networks have a learning capability of fault tolerance and model free characteristics. These characteristics support the neural networks as a competitive tool in processing multivariable input-output implementation. The successful fields include diagnostics, robotics, scheduling, decision-making, prediction, etc. This research is a case study of spherical annealing model. In the beginning, an original model is used to pre-fix a model of parameter design. Then neural networks are introduced to achieve another model. Study results showed both of them could perform the highest spherical level of quality.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.3
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• pp.330-335
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• 1999

The goal of the study is to determine the most sensitive parameter to represent the degree of muscle force and fatigue. Various numerical parameters such as the first coefficient of Autoregressive (AR) Model, Root Mean Square (RMS), Zero Crossing Rate (ZCR), Mean Power Frequency (MPF), Median Frequency (MF) were tested in this study. Ten healthy male subjects participated in the experiment. They were asked to extend their trunk by using the right and left erector spinae muscles during a sustained isometric contraction for twenty seconds. The force levels were 15%, 30%, 45%, 60%, and 75% of Maximal Voluntary Contraction (MVC), and the order of trials was randomized. The results showed that RMS was the best parameter to measure the force level of the muscle, and that the first coefficient of AR model was relatively sensitive parameter for the fatigue measurement at less than 60% MVC condition. At the 75% MVC, however, both MPF and the first coefficient of AR Model showed the best performance in quantification of muscle fatigue. Therefore, the sensitivity of measurement can be improved by properly selecting the parameter based upon the level of force during a sustained isometric condition.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.10a
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• pp.429-436
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• 2005

In this study, we have compared with the differences between the extent of sampling disturbance and consolidation characteristics by experiments, which are consolidation test and have been performed with Kwang-Yang clay samples. The effects on sampling disturbance to consolidation characteristics of soft clay have been inverstigated by using soil samples obtained from large block sampling and piston sampling methods. Through a few experiments, we've got important results which are that the consoilidation parameter of large block sample(Pc, Cc, Cv) is much larger than the value of parameter of piston sample. We've also found the fact that the large block sample using the large size sampler is much better than piston sample in the quality of goods to lessen the effects on disturbance of sampling. When compared to the parameter of consolidation along with the methods of experiment, we found that the result performed by large size consolidation test is the greatest one and CRS is much better than standard consolidation test to seek for proper parameter.

• Journal of the Korean Society of Physical Medicine
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• v.7 no.1
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• pp.21-28
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• 2012

Purpose : The purpose of this study was to examine the gait parameter and plantar foot pressure of adults with Down syndrome(DS) during walking in order to provide data for developing evidence-based deficit or common rehabilitation strategies. Method : 15 participants with DS(12 men, 3 women; age $26.06{\pm}4.47$) and 15 healthy subjects(12 men, 3 women; age $25.33{\pm}3.43$) were matched age. They walked at self selected speeds on a GAITRite system and RS-scan system, and had the following measurements done: cadence, stride length, step width, foot angle, percent stance, percent double support, and plantar foot pressure in 10 areas of the foot. Results : In comparison of gait parameter(cadence, stride length, step width, foot angle, percent stance, and percent double support) between adults with DS and healthy subjects, there was significant differences(p<.05). Regarding plantar foot pressure during gait with or without DS, there were statisically significant differences in the area of Toes 1-5, Metatasal 1-4, Midfoot, and Heel(Medial and lateral)(p<.05). Conclusion : Our data show that DS walk with a less physiolosical gait pattern and plantar foot pressure than healthy subjects. Based on our results, DS patients need targeted rehabilitation and exercise strategies.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.47-53
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• 2001

In this paper, we compare the classification performances of both ensemble and clustering algorithms (Data Bagging, Variable Selection Bagging, Parameter Combining, Clustering) to logistic regression in consideration of various characteristics of input data. Four factors used to simulate the logistic model are (1) correlation among input variables (2) variance of observation (3) training data size and (4) input-output function. In view of the unknown relationship between input and output function, we use a Taguchi design to improve the practicality of our study results by letting it as a noise factor. Experimental study results indicate the following: When the level of the variance is medium, Bagging & Parameter Combining performs worse than Logistic Regression, Variable Selection Bagging and Clustering. However, classification performances of Logistic Regression, Variable Selection Bagging, Bagging and Clustering are not significantly different when the variance of input data is either small or large. When there is strong correlation in input variables, Variable Selection Bagging outperforms both Logistic Regression and Parameter combining. In general, Parameter Combining algorithm appears to be the worst at our disappointment.

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.3
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• pp.305-318
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• 2016

This study is to evaluate the uncertainty of the soil parameters associated with the Gap parameter during shield TBM tunnel excavation of ${\bigcirc}{\bigcirc}$ International Airport Terminal 2 connecting railway construction basic design. And This study is to evaluate the adequacy of the shield TBM design by performing a reliability analysis of the Surface settlement. In addition, By analyzing the reliability indices of the design constants and Sensitivity probability of failure to be used in designing an integer parameter Gap, and By evaluating the design constants of a great influence on the surface subsidence, it was to provide a basis for carrying out an optimum design.

• Journal of Navigation and Port Research
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• v.29 no.8 s.104
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• pp.667-671
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• 2005

This study was carried out to examine the prediction of ship's manoeuvrability in initial design stage. New parameter representing basic hull form and stem shape were proposed. Captive model test were carried out to investigate the correlation coefficient between hydrodynamic coefficient and hull parameter. The results showed which parameter are positive correlation with hydrodynamic coefficient. Moreover correlation was examined between stem hull shape and ship's manoeuvrability. New empirical formulas for hydrodynamic coefficients were proposed These results can be used to predict a ship's manoeuvrability in initial design stage.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.876-881
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• 2004

Finite element model updating is an inverse problem to identify and correct uncertain modeling parameters that leads to better predictions of the dynamic behavior of a target structure. Unlike other inverse problems, the restrictions on selecting parameters all: very high since the updated model should maintains its physical meaning. That is, only the regions with modeling errors should be parameterized. And the variations of the parameters should be kept small while the updated results give acceptable correlations with experimental data. To avoid an ill-conditioned numerical problem, the number of parameters should be kept as small as possible. Thus it is very difficult to select an adequate set of updating parameters which meet all these requirements. In this paper, the importance of updating parameter selection is illustrated through a case study, and an automated procedure to guide the parameter selection is suggested based on simple observations. The effectiveness of the suggested procedure is tested with two example problems, ones is a simulated case study and the other is a real engineering structure.

• Tunnel and Underground Space
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• v.21 no.6
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• pp.494-507
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• 2011

Rock joint surface roughness is one of the most important parameters in shear behavior analysis of rock joint surface. Until now, estimation of joint surface roughness has been conducted by various statistical methods with two-dimensional analysis. In this study, standard roughness profile suggested by Barton and Choubey (1977) was expanded into a 3D surface and its surface roughness was analyzed by surface angularity parameter. And the validity of quantification based on surface angularity was secured through comparison with $Z_2$ and Ai parameter. Also the surface angularity parameter was compared with shear strength by joint shear test using the replicated specimen.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.15 no.2
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• pp.64-70
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• 2019

In recent years, attention has been paid to the integrity of steam generator (SG) tubes due to severe accident and beyond design basis accident conditions. In these transient conditions, steam generator tubes may be damaged by high temperature and pressure, which might result in a risk of fission products being released to the environment due to the failure. Alloy 690 which has increased the Cr content has been replaced for the SG tube due to its high corrosion resistance against stress corrosion cracking (SCC). However, there is lack of research on the high temperature creep rupture and life prediction model of Alloy 690. In this study, creep test was performed to estimate the high temperature creep rupture life of Alloy 690 using tube specimens. Based on manufacturer's creep data and creep test results performed in this study, creep life prediction was carried out using the Larson-Miller (LM) Parameter, Orr-Sherby-Dorn (OSD) parameter, Manson-Haford (MH) parameter, and Wilshire's approach. And a hyperbolic sine (sinh) function to determine master curves in LM, OSD and MH parameter methods was used for improving the creep life estimation of Alloy 690 material.