• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.74-76
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• 2007

A hybrid optimization method is proposed for cogging torque reducing in BLDC motor. The proposed hybrid optimization method comprises a response surface method (RSM) and a gradient search method (GSM). The RSM is effective and global method in optimization problem but having large approximation error. The GSM is accurate and fast search method for optimal solution but having local behavior. To reduce approximation error and computation time a hybrid method (RSM+GSM) is proposed method. To illustrate the effectiveness of the proposed method, a comparison between conventional RSM and the proposed hybrid method is made. A simulation results verify that the hybrid method can achieve favorable design performance.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.253-257
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• 2009

As the value of B2B integration gets more importance and the business process becomes more complex, BPEL4WS standard has been focused for the solution of the problems which is based on web service technology. Many vendors implement the standard in their systems to integrate B2B and web service based inner-Enterprise Application(EA)s. But there is no way to use the standard to integrate non-web service based EAs, because the standard is designed only for Service Oriented Architecture (SOA) over web services. This paper proposes Hybrid Service Orchestration Framework to participate web services and also non-web service based EAs in the business process as a partner using BPEL4WS standard. The framework introduces Hybrid Service Architecture to represent non-web service based EAs as a service, so BPEL4WS could be used to integrate web services and non-web service based EAs. And the framework also introduces Hybrid Service Toolkit to support software level facilities. The paper also introduces Hybrid Orchestration System that is based on Hybrid Service Orchestration Framework.

• Journal of Magnetics
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• v.16 no.3
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• pp.240-245
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• 2011

A new hybrid ON/OFF method is presented for the fast solution of electromagnetic inverse problems in high frequency domains. The proposed method utilizes both topological sensitivity (TS) and material sensitivity (MS) to update material properties in unit design cells. MS provides smooth design space and stable convergence, while TS enables sudden changes of material distribution when MS slows down. This combination of two sensitivities enables a reduction in total computation time. The TS and MS analyses are based on a variational approach and an adjoint variable method (AVM), which permits direct calculation of both sensitivity values from field solutions of the primary and adjoint systems. Investigation of the formulations of TS and MS reveals that they have similar forms, and implementation of the hybrid ON/OFF method that uses both sensitivities can be achieved by one optimization module. The proposed method is applied to dielectric material reconstruction problems, and the results show the feasibility and effectiveness of the method.

• Journal of the Korea Safety Management & Science
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• v.13 no.3
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• pp.107-114
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• 2011

Traveling salesman problem is to minimize the total cost for a traveling salesman who wants to make a tour given finite number of cities along with the cost of travel between each pair them, visiting each cities exactly once before returning home. Traveling salesman problem is known to be NP-hard, and it needs a lot of computing time to get the optimal solution, so that heuristics are more frequently developed than optimal algorithms. This study suggests a hybrid parallel genetic algorithm(HPGA) for traveling salesman problem The suggested algorithm combines parallel genetic algorithm, nearest neighbor search, and 2-opt. The suggested algorithm has been tested on 7 problems in TSPLIB and compared the results of existing methods(heuristics, meta-heuristics, hybrid, and parallel). Experimental results shows that HPGA could obtain good solution in total travel distance minimization.

• Structural Engineering and Mechanics
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• v.40 no.6
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• pp.813-827
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• 2011

This paper provides a numerical solution for a finite internally cracked plate using hybrid crack element method (HCE). In the formulation, an inclined crack is placed in any place of a rectangular element and the complex variable method is used. The complex potentials are expressed in a series form, and several undetermined coefficients are involved. The complex potentials for the cracked rectangle are first suggested in this paper. Based on a variational principle, the element stiffness matrix can be evaluated. The next steps are same as in the usual finite element method. Several numerical examples with computed stress intensity factor and T-stress are presented.

• Korean Journal of Hydrosciences
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• v.5
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• pp.85-97
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• 1994

A hybrid finite difference method for the longitudinal dispersion equation, which is based on combining the Holly-Preissmann scheme with fifth-degree Hermite interpolating polynomial and the generalized Crank-Nicholson scheme, is described and comparatively evaluated with other characteristics-based numerical methods. Longitudinal dispersion of an instantaneously-loaded pollutant source is simulated, and computational results are compared with the exact solution. The present method is free from wiggles regardless of the Courant number, and exactly reproduces the location of the peak concentration. Overall accuracy of the computation increases for smaller value of the weighting factor, $\theta$of the model. Larger values of $\theta$ overestimates the peak concentration. Smaller Courant number yields better accuracy, in general, but the sensitivity is very low, especially when the value of $\theta$ is small. From comparisons with the hybrid method using cubic interpolating polynomial and with splitoperator methods, the present method shows the best performance in reproducing the exact solution as the advection becomes more dominant.

• Fibers and Polymers
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• v.3 no.1
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• pp.1-7
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• 2002

Cellulose carbonate was prepared by the reaction of cellulose pulp and $CO_2$ with treatment reagents, such as aqueous $Zncl_2$ (20-40 wt%) solution, acetone or ethyl acetate, at -5-$0^{\circ}C$ and 30-40 bar ($CO_2$) for 2 hr. Among the treatment reagents, ethyl acetate was the most effective. Cellulose carbonate was dissolved in 10% sodium hydroxide solution containing zinc oxide up to 3 wt% at -5-$0^{\circ}C$. Intrinsic viscosities of raw cellulose and cellulose carbonate were measured with an Ubbelohde viscometer using 0.5 M cupriethylenediamine hydroxide (cuen) as a solvent at $20^{\circ}C$ according to ASTM D1795 method. The molecular weight of cellulose was rarely changed by carbonation. Solubility of cellulose carbonate was tested by optical microscopic observation, UV absorbance and viscosity measurement. Phase diagram of cellulose carbonate was obtained by combining the results of solubility evaluation. Maximum concentration of cellulose carbonate for soluble zone was increased with increasing zinc oxide content. Cellulose carbonate solution in good soluble zone was transparent and showed the lowest absorbance and the highest viscosity. The cellulose carbonate and its solution were stable in refrigerator (-$5^{\circ}C$ and atmospheric pressure).

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.125-140
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• 2013

We call a data set in which the number of records belonging to a certain class far outnumbers the number of records belonging to the other class, 'imbalanced data set'. Most of the classification techniques perform poorly on imbalanced data sets. When we evaluate the performance of a certain classification technique, we need to measure not only 'accuracy' but also 'sensitivity' and 'specificity'. In a customer churn prediction problem, 'retention' records account for the majority class, and 'churn' records account for the minority class. Sensitivity measures the proportion of actual retentions which are correctly identified as such. Specificity measures the proportion of churns which are correctly identified as such. The poor performance of the classification techniques on imbalanced data sets is due to the low value of specificity. Many previous researches on imbalanced data sets employed 'oversampling' technique where members of the minority class are sampled more than those of the majority class in order to make a relatively balanced data set. When a classification model is constructed using this oversampled balanced data set, specificity can be improved but sensitivity will be decreased. In this research, we developed a hybrid model of support vector machine (SVM), artificial neural network (ANN) and decision tree, that improves specificity while maintaining sensitivity. We named this hybrid model 'hybrid SVM model.' The process of construction and prediction of our hybrid SVM model is as follows. By oversampling from the original imbalanced data set, a balanced data set is prepared. SVM_I model and ANN_I model are constructed using the imbalanced data set, and SVM_B model is constructed using the balanced data set. SVM_I model is superior in sensitivity and SVM_B model is superior in specificity. For a record on which both SVM_I model and SVM_B model make the same prediction, that prediction becomes the final solution. If they make different prediction, the final solution is determined by the discrimination rules obtained by ANN and decision tree. For a record on which SVM_I model and SVM_B model make different predictions, a decision tree model is constructed using ANN_I output value as input and actual retention or churn as target. We obtained the following two discrimination rules: 'IF ANN_I output value <0.285, THEN Final Solution = Retention' and 'IF ANN_I output value ${\geq}0.285$, THEN Final Solution = Churn.' The threshold 0.285 is the value optimized for the data used in this research. The result we present in this research is the structure or framework of our hybrid SVM model, not a specific threshold value such as 0.285. Therefore, the threshold value in the above discrimination rules can be changed to any value depending on the data. In order to evaluate the performance of our hybrid SVM model, we used the 'churn data set' in UCI Machine Learning Repository, that consists of 85% retention customers and 15% churn customers. Accuracy of the hybrid SVM model is 91.08% that is better than that of SVM_I model or SVM_B model. The points worth noticing here are its sensitivity, 95.02%, and specificity, 69.24%. The sensitivity of SVM_I model is 94.65%, and the specificity of SVM_B model is 67.00%. Therefore the hybrid SVM model developed in this research improves the specificity of SVM_B model while maintaining the sensitivity of SVM_I model.

• Journal of Powder Materials
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• v.15 no.5
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• pp.359-364
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• 2008

To satisfy the demand of higher cutting performance, mechanical properties with tungsten carbide (WC-Co) tool materials were investigated. Hardness and transverse rupture strength with WC grain size, Co content and density were measured. Compared to H, K, and S manufacture maker as tungsten carbide (WC-Co) tool materials were used for high-speed machining of end-milling operation. The three tungsten carbide (WC-Co) tool materials were evaluated by cutting of STD 11 cold-worked die steel (HRC25) under high-speed cutting condition. Also, tool life was obtained from measuring flank wear by CCD wear measuring system. Tool dynamometer was used to measure cutting force. The cutting force and tool wear are discussed along with tool material characteristics. Consequently, the end-mill of K, H manufacture maker showed higher wear-resistance due to its higher hardness, while the S maker endmill tool showed better performance for high metal removal.

• Korean Journal of Materials Research
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• v.18 no.12
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• pp.635-639
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• 2008

In this paper, experimental studies of the regrinding of tungsten carbide (WC-Co) tools for high-speed machining were conducted. Regrinding and a subsequent evaluation test were carried out for a flat endmill tool with diameters of 10 mm and 3 mm using a CNC five-axis tool grinder and a CNC three-axis machining center. Tool wear on the two types of endmill tools increased as the cutting length increased, and the tool wear was not influenced by the regrinding state. In case of the micro endmill with a tool diameter of 3 mm, the effective regrinding time was determined for a flank wear threshold of 0.3 mm considering the tool life according to cutting length. The tool lives of the 10 mm and 3 mm endmill tools were increased by 80% and 72%, respectively. This conclusion proves the Feasibility of the recycling of tungsten carbide materials in the high-speed machining of high-hardened materials for industrial applications.