• 소성∙가공
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• 제10권4호
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• pp.319-328
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• 2001

Quantitative evaluation of the tribological conditions at the tool-workpiece interface in metal forming is usually accomplished by the ring compression test. This paper describes an experimental investigation into friction factor under warm forming conditions according to the lubricants and the lubricating methods using the ring compression test. Four different lubricants, two water based graphite and two oil based graphite lubricants, and three different lubricating methods were applied in the experiments. Calibration curves with the friction shear factor were obtained using FEM analysis and verified by the experimental results. The influence of lubricant and lubricating methods on friction are discussed. In the ring compression test, the lower friction factor got to spray the oil based lubricant on die and billet in warm forging temperature.

• 한국경영과학회지
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• 제30권4호
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• pp.27-43
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• 2005

This paper presents a new hybrid data mining technique using error pattern modeling to improve classification accuracy when the data type of a target variable is binary. The proposed method increases prediction accuracy by combining two different supervised learning methods. That is, the algorithm extracts a subset of training cases that are predicted inconsistently by both methods, and models error patterns from the cases. Based on the error pattern model, the Predictions of two different methods are merged to generate final prediction. The proposed method has been tested using practical 10 data sets. The analysis results show that the performance of proposed method is superior to the existing methods such as artificial neural networks and decision tree induction.

• Journal of Information Technology Applications and Management
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• 제15권1호
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• pp.225-242
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• 2008

PM (Inconsistency Pattern Modeling) is a hybrid supervised learning technique using the inconsistence pattern of input variables in mining data sets. The IPM tries to improve prediction accuracy by combining more than two different supervised learning methods. The previous related studies have shown that the IPM was superior to the single usage of an existing supervised learning methods such as neural networks, decision tree induction, logistic regression and so on, and it was also superior to the existing combined model methods such as Bagging, Boosting, and Stacking. The objectives of this paper is explore the characteristics of the IPM. To understand characteristics of the IPM, three experiments were performed. In these experiments, there are high performance improvements when the prediction inconsistency ratio between two different supervised learning techniques is high and the distance among supervised learning methods on MDS (Multi-Dimensional Scaling) map is long.

• 한국식품영양과학회지
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• 제30권1호
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• pp.138-142
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• 2001

Solid contents, free sugars, phenlic compounds and glycyrrhizin of extracts obtained from by-products of Glycyrrhizia uralensis by three different methods, i.e., shaking, heating, and static methods, were determined. Solid contents of extracts obtained by shaking, heating and static method were 15.6%, 15.0% and 5.3%, respectively. Phenolic compound contents of them were 11.33 mg/100 mL, 11.21 mg/100mL and 10.15 mg/100 mL. Main free sugars in the extracts from the by-products of G. uralensis were fructose, glucose, sucrose, and maltose. Glycyrrhizin content of the extracts from the by-products of G. uralensis were 2.79%, 3.54% and 0.63%, respectively. Extract obtained by the shaking methods had an ability of donating electron to DPPH. The relative antioxidant effects of th extract obtained from the shaking method showed 70% inhibitory effect of peroxidation on egg yolk lecithin.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2006년도 춘계 학술발표회 논문집
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• pp.199-207
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• 2006

Before getting to the actual study of the load distribution factor in various excavating methods, this research is preliminarily focused on the comparison of two different excavation methods, CD cut method and Ringcut method. Especially, the purpose of this research is to study the behavioral mechanism of two tunnels which share the same construction environment but different excavating method. Two numerical analysis models with the same tunnel section and material properties are compared in this study, and they are analyzed by 3D Finite Element Analysis. In each model, face stability, crown displacement, ground settlement, and shotcrete-lining stress are computed. Thus, the general behavior of CD cut method and Ringcut method are studied, and it certified what should be considered for the calculation of the load distribution factor.

• 한국식품영양학회지
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• 제13권1호
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• pp.66-70
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• 2000

The volatile components of Korea ginger were compared by using different isolation methods, head-space sampling procedure(HSSP), simultaneous distillation extrction(SDE) and soild pahse micro-extractions(SPME). Sixty-one components were identified by GC-MSD in the extracts obtained from each extraction methods. However, the components identified showed a difference in their composition wit the extraction methods. In the extract by HSSP, fifty-five components including a high volatile compound such as acetaldehyde, ethylacetate, 2,3-butandione were detected, and thirty-one components were identified in the extract by SPME. While, the low volatile components such as elemol, zingiberenol and ${\beta}$-eudesmol were detected only in the extract by SDE method. The results suggest that SDE method is the best for the analysis of low volatile components, whereas HSSP is a proper method for the analysis of high volatile components from natural resources.

• Structural Engineering and Mechanics
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• 제65권1호
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• pp.91-98
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• 2018

Three structure-dependent integration methods with no numerical dissipation have been successfully developed for time integration. Although these three integration methods generally have the same numerical properties, such as unconditional stability, second-order accuracy, explicit formulation, no overshoot and no numerical damping, there still exist some different numerical properties. It is found that TLM can only have unconditional stability for linear elastic and stiffness softening systems for zero viscous damping while for nonzero viscous damping it only has unconditional stability for linear elastic systems. Whereas, both CEM and CRM can have unconditional stability for linear elastic and stiffness softening systems for both zero and nonzero viscous damping. However, the most significantly different property among the three integration methods is a weak instability. In fact, both CRM and TLM have a weak instability, which will lead to an adverse overshoot or even a numerical instability in the high frequency responses to nonzero initial conditions. Whereas, CEM possesses no such an adverse weak instability. As a result, the performance of CEM is much better than for CRM and TLM. Notice that a weak instability property of CRM and TLM might severely limit its practical applications.

• International journal of advanced smart convergence
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• 제9권2호
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• pp.173-178
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• 2020

A common problem with neural network learning is that it is too suitable for the specificity of learning. In this paper, various methods were compared to avoid overfitting: regularization, drop-out, different numbers of data and different types of neural networks. Comparative studies of the above-mentioned methods have been provided to evaluate the test accuracy. I found that the more data using method is better than the regularization and dropout methods. Moreover, we know that deep convolutional neural networks outperform multi-layer neural networks and simple convolution neural networks.

• Structural Engineering and Mechanics
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• 제28권4호
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• pp.443-460
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• 2008

The aim of this paper is to propose a design procedure for predicting the buckling strength of built-up, cold-formed steel columns based on the two well known methods; the effective width method and the Direct Strength Method. Several design approaches, based on different elastic buckling solutions, were considered in this investigation. Traditional hand methods, without interaction effects between the different modes, and a new numerical spline finite strip method were used to predict the buckling stresses. All of the proposed methods were compared with experimental data on plain and lipped, built-up columns. Results have shown that the effective width approaches are more accurate than the Direct Strength Method. However, both methods can be investigated using more experimental data to assess a practical design method for built-up columns.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2007년도 학술발표회 논문집
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• pp.909-910
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• 2007

The volatile organic compounds exposure is governed by the source distance and dispersion of the pollutant into air and groundwater. The purpose of this study was to validate suggested models for the prediction of concentration distributions. The study design was organized into different methods to simulate industry site. The distribution models generally showed a fair agreement with measured data. For graphical representation of concentration of volatile hydrocarbon, it has to obtain a continuous representation of the contamination of the site. Therefore, the used interpolative methods examined for this project are the IDW(inverse Distance Weighting) and kriging method. In the results, in summary, all two different methods can be used to quantify exposures at a particular source area, and thus provide, a solid foundation for making risk-based decisions. All the calculations can be performed using Excel's built-in functions, and the capabilities of geospatial analysis allow the results to be displayed visually. However, anyone who uses these methods should understand all of the assumptions and limitation.