• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.10
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• pp.1420-1425
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• 2012

Nowadays, Interior permanent magnet synchronous motor(IPMSM) which having high power density is much used for the vehicles. However, IPMSM causes a lot of losses because of high-speed driving and high current density, and temperature rising by iron loss and copper loss could reduce torque characteristics and durability of IPMSM. Therefore, analysis about thermal characteristics of IPMSM is required at design stage. In this paper, temperature characteristics according to current vector control method were analyzed through calculate thermal equivalent circuit. And calculated results were verified through comparing with the experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.3
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• pp.514-518
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• 2007

It is necessary to modify the state-of-the-art of speed control theory because of the phase asymmetry in the Linear Induction Motor (LIM)and for the constant speed control of mover using single vector control inverter system, it is important that primary stack is located in appropriated intervals in the 3D conveyer system using LIM. The dynamic characteristic analysis method of the vector controlled LIM using coupled FEM and control algorithm taking into account the movement is proposed. The focus of this paper is the analysis relative to selecting primary stack intervals in order to constant speed control in the 3D conveyer system using LIM.

• Korean Management Science Review
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• v.33 no.4
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• pp.51-64
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• 2016

The maximum weight of single stock in mutual fund is limited by regulations to enforce diversification. Under incomplete information with added constraints on portfolio weights, enhanced performance had been reported in previous researches. We analyze a weight vector to examine the effects of additional constraints on the portfolio's performance by computing the Euclidean distance from the in-sample tangency portfolio, as opposed to previous researches which analyzed ex-post return only. Empirical experiment was performed on Mean-variance and Minimum-variance model with Fama French's 30 industry portfolio and 10 industry portfolio for the last 1,000 months from August 1932 to November 2015. We find that diversification-constrained portfolios have 7% to 26% smaller Euclidean distances with the benchmark portfolio compared to those of unconstrained portfolios and 3% to 11% greater Sharpe Ratio.

• The Journal of the Acoustical Society of Korea
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• v.27 no.1E
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• pp.30-34
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• 2008

An improvement to the existing blind signal separation (BSS) method has been made in this paper. The proposed method models the inherent signal dependency observed in acoustic object to separate the real-world convolutive sound mixtures. The frequency domain approach requires solving the well known permutation problem, and the problem had been successfully solved by a vector representation of the sources whose multidimensional joint densities have a certain amount of dependency expressed by non-spherical distributions. Especially for speech signals, we observe strong dependencies across neighboring frequency bins and the decrease of those dependencies as the bins become far apart. The non-spherical joint density model proposed in this paper reflects this property of real-world speech signals. Experimental results show the improved performances over the spherical joint density representations.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.11-18
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• 2003

This paper proposes modified Lanczos vector superposition method for efficient dynamic analysis of structures. Proposed method is based on the modified Lanczos algorithm that generates stiffness-orthonormal Lanczos vectors. Proposed method has better computing efficiency than the conventional Lanczos vector superposition method in the analysis of multi-input-loaded structures. The efficiency of proposed method is verified through numerical examples. Comparison with other vector superposition methods is also presented through numerical examples.

• International Journal of Advanced Culture Technology
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• v.6 no.3
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• pp.142-150
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• 2018

This paper describes the algorithm that lowers the dimension, maintains the object recognition and significantly reduces the eigenspace configuration time by combining the edge orientation histogram and principle component analysis. By using the detected object region as a recognition input image, in this paper the object recognition method combined with principle component analysis and the multi-layer network which is one of the intelligent classification was suggested and its performance was evaluated. As a pre-processing algorithm of input object image, this method computes the eigenspace through principle component analysis and expresses the training images with it as a fundamental vector. Each image takes the set of weights for the fundamental vector as a feature vector and it reduces the dimension of image at the same time, and then the object recognition is performed by inputting the multi-layer neural network.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.913-914
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• 2017

Structural analyses of a engine system is required in development stage for increasing structural reliability and reducing weight. Attitude of a launch vehicle during flight is controlled by combustion chamber rotation varying with TVC (thrust vector control) actuator displacements. In this study nonlinear static analysis is performed for a 75 tonf-class liquid rocket engine using before and after the TVC actuation.

• Nonlinear Functional Analysis and Applications
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• v.26 no.2
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• pp.225-236
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• 2021

In this paper, we determine position vector of a line of curvature of a regular surface which is relatively normal-slant helix, with respect to Darboux frame. Then, a vector differential equation is established by means Darboux formulas, in the case of the geodesic torsion is vanishes. In terms of solution, we determine the parametric representation of a line of curvature which is relatively normal-slant helix, with respect to standard frame in Euclidean 3-space. Thereafter, we apply this result to find the position vector of a line of curvature which is isophote curve.

• Communications for Statistical Applications and Methods
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• v.31 no.4
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• pp.393-408
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• 2024

The sparse linear discriminant analysis can be incorporated into the penalized linear regression framework, but most studies have been limited to specific convex penalties, including the least absolute selection and shrinkage operator and its variants. Within this framework, concave penalties can serve as natural counterparts of the convex penalties. Implementing the concave penalized direction vector of discrimination appears to be straightforward, but developing its theoretical properties remains challenging. In this paper, we explore a class of concave penalties that covers the smoothly clipped absolute deviation and minimax concave penalties as examples. We prove that employing concave penalties guarantees an oracle property uniformly within this penalty class, even for high-dimensional samples. Here, the oracle property implies that an ideal direction vector of discrimination can be exactly recovered through concave penalized least squares estimation. Numerical studies confirm that the theoretical results hold with finite samples.

• The Pure and Applied Mathematics
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• v.24 no.4
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• pp.211-226
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• 2017

In this paper, machine learning models employed in various fields are discussed and applied to KOSPI200 stock index return forecasting. The results of hyperparameter analysis of the machine learning models are also reported and practical methods for each model are presented. As a result of the analysis, Support Vector Machine and Artificial Neural Network showed a better performance than k-Nearest Neighbor and Random Forest.