• The Transactions of the Korean Institute of Electrical Engineers C
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• v.48 no.7
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• pp.542-549
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• 1999

Corona discharges form at the surface of a transmission line conductor when the electric-field intensity on the conductor surface exceeds the breakdown strength of air. In order to decrease the electric-field intensity on the conductor surface, a new 6 conductor bundle has been studied. This bundle, hybrid conductor bundle, consists of using a larger subconductor at the bottom two conductor positions in the 6-conductor bundles of each phase of the line. The electric field on these two larger subconductors is reduced which in turn reduces the corona noise. It is shown that this is a better solution for decreasing the electric-field intensity than ether the conventional bundle or the asymmetric bundle proposed by EPRI.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1281-1285
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• 2004

There are numerous emotions in the human world. Human expresses and recognizes their emotion using various channels. The example is an eye, nose and mouse. Particularly, in the emotion recognition from facial expression they can perform the very flexible and robust emotion recognition because of utilization of various channels. Hybrid-feature extraction algorithm is based on this human process. It uses the geometrical feature extraction and the color distributed histogram. And then, through the independently parallel learning of the neural-network, input emotion is classified. Also, for the natural classification of the emotion, advancing two-dimensional emotion space is introduced and used in this paper. Advancing twodimensional emotion space performs a flexible and smooth classification of emotion.

• Smart Structures and Systems
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• v.14 no.6
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• pp.1197-1220
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• 2014

Accurate actuator tracking is critical to achieve reliable real-time hybrid simulation results for earthquake engineering research. The frequency-domain evaluation approach provides an innovative way for more quantitative post-simulation evaluation of actuator tracking errors compared with existing time domain based techniques. Utilizing the Fast Fourier Transform the approach analyzes the actuator error in terms of amplitude and phrase errors. Existing application of the approach requires using the complete length of the experimental data. To improve the computational efficiency, two techniques including data decimation and frequency decimation are analyzed to reduce the amount of data involved in the frequency-domain evaluation. The presented study aims to enhance the computational efficiency of the approach in order to utilize it for future on-line actuator tracking evaluation. Both computational simulation and laboratory experimental results are analyzed and recommendations on the two decimation factors are provided based on the findings from this study.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.269-278
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• 2006

This paper presents the new hybrid data mining technique using error pattern, modeling of improving classification accuracy. The proposed method improves classification accuracy by combining two different supervised learning methods. The main algorithm generates error pattern modeling between the two supervised learning methods(ex: Neural Networks, Decision Tree, Logistic Regression and so on.) The Proposed modeling method has been applied to the simulation of 10,000 data sets generated by Normal and exponential random distribution. The simulation results show that the performance of proposed method is superior to the existing methods like Logistic regression and Discriminant analysis.

• 한국신재생에너지학회:학술대회논문집
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• 2005.11a
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• pp.537-540
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• 2005

A battery is the primary energy source device presently used in hybrid electric vehicle. It can store much energy, but cannot provide enough current without inefficient units. However, an ultracapcitor can provide much current, but cannot store much energy. It will have better fuel economy by combining the two energy sources in parallel. The purpose of this paper is making the simulator of the two HEV systems. The one has only battery, the other have battery and ultarcapacitor in parallel. To compare the fuel economy, dynamic programing was used for optimization and prius was used for HEV model.

• Journal of ILASS-Korea
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• v.12 no.2
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• pp.101-107
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• 2007

The purpose of this study is to analyze spray and evaporation characteristics of DME fuel at the high pressure and temperature. For the numerical analysis of dimethyl ether(DME) fuel spray characteristics, hybrid breakup model was applied to the DME spray and its breakup process. In order to obtain experimental results for comparison with the predicted ones, the visualization of the spray evolution process was executed by using a Nd:YAG laser. Also, the numerical investigation was conducted by the two hybrid models for primary and secondary breakup of the DME spray. The primary breakup model was used the Kelvin-Helmholtz(KH) breakup model. In the secondary breakup process, Rayleigh-Taylor(RT) and Drop Deformation Breakup(DDB) model was applied. The results of this study provide the macroscopic characteristics of the spray such as spray tip penetration and cone angle, and prediction accuracy of the two hybrid model.

• Journal of Information Technology Applications and Management
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• v.15 no.1
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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.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.659-668
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• 2017

The inverse Weibull distribution (IWD) can be readily applied to a wide range of situations including applications in medicines, reliability and ecology. It is generally known that the lifetimes of test items may not be recorded exactly. In this paper, therefore, we consider the maximum likelihood estimation (MLE) and Bayes estimation of the entropy of a IWD under generalized progressive hybrid censoring (GPHC) scheme. It is observed that the MLE of the entropy cannot be obtained in closed form, so we have to solve two non-linear equations simultaneously. Further, the Bayes estimators for the entropy of IWD based on squared error loss function (SELF), precautionary loss function (PLF), and linex loss function (LLF) are derived. Since the Bayes estimators cannot be obtained in closed form, we derive the Bayes estimates by revoking the Tierney and Kadane approximate method. We carried out Monte Carlo simulations to compare the classical and Bayes estimators. In addition, two real data sets based on GPHC scheme have been also analysed for illustrative purposes.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1133-1138
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• 2006

This paper considers a hybrid flow shop scheduling problem for the objective of minimizing the number of tardy jobs. The hybrid flow shop consists of two stages in series, each of which has multiple identical parallel machines, and the problem is to determine the allocation and sequence of jobs at each stage. A branch and bound algorithm that gives the optimal solutions is suggested that incorporates the methods to obtain the lower and upper bounds. Dominance properties are also derived to reduce the search space. To show the performance of the algorithm, computational experiments are done on randomly generated problems, and the results are reported.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.5
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• pp.673-678
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• 2011

For the wind-diesel hybrid electric power generation system equiped with two diesel generators, the diesel power sharing is studied analytically and a power sharing technique of less fuel consumption is developed. Based on the technique, as example, a diesel power sharing algorithm is suggested for two diesel generators of capacity 500Kw(200Kw+300Kw).