• Journal of the military operations research society of Korea
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• v.9 no.2
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• pp.61-68
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• 1983

The traditional theories of games are based on an assumption that the payoffs have a single dimension. In reality, any alternative is likely to imply more than one payoff. This paper deals with the game against nature with vector payoffs. The purpose of this paper is to develop methods for finding the practical optimal strategy in the game against nature with vector payoffs. Under the assumption that a prior probability over the stats of nature is given, this paper shows that a practical optimal strategy in this game can be obtained by applying a entropy method in order to assess the payoff weight and by employing the concept of compromise solutions in order to reduce the non-dominated solutions. When subjective payoff weights are unknown as well as known, these methods can be used. A numerical example is given.

• 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.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.116-126
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• 2019

In this paper, an improved one-against-one support vector machine algorithm is used to classify multiple power quality disturbances. To solve the problem of parameter selection, an improved particle swarm optimization algorithm is proposed to optimize the parameters of the support vector machine. By proposing a new inertia weight expression, the particle swarm optimization algorithm can effectively conduct a global search at the outset and effectively search locally later in a study, which improves the overall classification accuracy. The experimental results show that the improved particle swarm optimization method is more accurate than a grid search algorithm optimization and other improved particle swarm optimizations with regard to its classification of multiple power quality disturbances. Furthermore, the number of support vectors is reduced.

• Journal of Power Electronics
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• v.19 no.2
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• pp.443-453
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• 2019

As the core component of transmission systems, converters are very prone to failure. To improve the accuracy of fault diagnosis for wind power converters, a fault feature extraction method combined with a wavelet transform and compressed sensing theory is proposed. In addition, an improved AdaBoost-SVM is used to diagnose wind power converters. The three-phase output current signal is selected as the research object and is processed by the wavelet transform to reduce the signal noise. The wavelet approximation coefficients are dimensionality reduced to obtain measurement signals based on the theory of compressive sensing. A sparse vector is obtained by the orthogonal matching pursuit algorithm, and then the fault feature vector is extracted. The fault feature vectors are input to the improved AdaBoost-SVM classifier to realize fault diagnosis. Simulation results show that this method can effectively realize the fault diagnosis of the power transistors in converters and improve the precision of fault diagnosis.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.53-61
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• 2014

In this paper, we proposed covariance weight matrix using SPT matrix in order to accurate target estimation. We have estimated a target using modified covariance matrix and beam steering error method. We have minimized beam steering error in order to estimation desired a target. This method obtain optimum covariance weight using modified SPT matrix. This paper of proposal method is showed good performance than general method. We updated a weight of covariance matrix using modified SPT matrix. We obtain optimum covariance matrix weight to application beam steering error method in order to beam steering toward desired target. Through simulation, we showed that compare proposal method with general method. It have improved resolution of estimation target to good performance more proposed method than general method.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1129-1139
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• 2006

Pearson's correlation coefficient and vector similarity are generally applied to The users' similarity weight of user based recommender system. This study is needed to find that the correlation coefficient of similarity weight is effected by the number of pair response and significance probability. From the classified correlation coefficient by the significance probability test on the correlation coefficient and pair of response, the change of MAE is studied by comparing the predicted precision of the two. The results are experimentally related with the change of MAE from the significant correlation coefficient and the number of pair response.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.518-521
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• 1999

This paper describes high speed squirrel cage induction motor drives without speed sensors using neural network based on Kalman filter Learning. High speed motors are receiving inverasing attentions in various applications, because of advantages of high speed, small size and light weight with same power level. Larning rate by Kalman filtering is time varying, convergence time fast, effect of initial weight between neurons is small.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2157-2169
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• 2023

In order to handle the problem that puncture patterns will change the position distribution of original information bits and frozen bits in polar codes, which affects performance of puncture polar codes further, a minimum row weight and polar spectrum based puncture polar codes construction algorithm (called PA-MRWP) is proposed in this paper. The algorithm calculates row weight of generator matrix and sorts the row weight in ascending order first. Next, the positions with the minimum row weight are selected as initial puncture positions. If the rows with the same row weight cannot all be punctured, polar spectrum based auxiliary puncture scheme is used. In sub-channels with the same row weight, rows corresponding to the polarized sub-channels with higher reliability are selected as puncture positions to construct puncture vector, and the reliability is calculated based on polar spectrum. It is actually a two-step selection strategy, the proposed minimum row weight puncture (MRWP) algorithm is used for primary selection and polar spectrum based auxiliary puncture is used for adjustment. Simulation results show that, compared with worst quality puncture (WQP) algorithm, the proposed PA-MRWP algorithm and Gaussian approximation-aided minimum row weight puncture (GA-MRWP) algorithm provide gains of about 0.46 dB and 0.29 dB at bit error rate (BER) of 10^-4, respectively when code length N=400, code rate R=1/2. In addition, the proposed puncture algorithms improve the BER performance significantly with respect to quasi-uniform puncture (QUP) algorithm.

• The Korean Journal of Physiology
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• v.16 no.2
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• pp.129-136
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• 1982

We studied this experiment to compare the effects of exercise and other body conditions: i.e., Flack test, cold pressor test and bicycle ergometry on the electrocardiogram. We had sixty healthy college students who were thirty nine men and twenty one women. Their $mean{\pm}SD$ values of physical characteristics were as follows: age; $22.0{\pm}1.4$, weight; men $61.7{\pm}5.6\;kg$, women $46.2{\pm}7.47\;kg$. We observed the changes of P-Q and Q-T interval, R and T amplitude, mean QRS vector, S-T segment deviation, and P and T vector. The result obtained were summarized as follows: P vector was shifted rightward regardless of the type of stress. T vector was shifted var-in each stress but in the bicycle ergometry T vector was shifted leftward. Mean QRS vector was shifted rightward immediately after the bicycle ergometry. Percentage of the occurrence of the depression of S-T segment was 21.7% at the immediately after the submaximal bicycle ergometry in lead II. The elevation of S-T segment was often observed after the mild stresses. Increased amplitude of T wave in the cold pressor test and decreased amplitude of T wave in the bicycle ergometry were observed. In the bicycle ergometry and other stresses, the precise mechanism of S-T segment changes was unexplained but insufficient repolarization in base or apex of the left ventricle due to heart strain was indicated by so called S-T vector analysis.

• Journal of Computational Design and Engineering
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• v.2 no.2
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• pp.88-95
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• 2015

Recently, fiber composite materials have been attracting attention from industry because of their remarkable material characteristics, including light weight and high stiffness. However, the costs of products composed of fiber materials remain high because of the lack of effective manufacturing and designing technologies. To improve the relevant design technology, this paper proposes a novel simulation method for deforming fiber materials. Specifically, given a 3D model with constant thickness and known fiber orientation, the proposed method simulates the deformation of a model made of thick fiber-material. The method separates a 3D sheet model into two surfaces and then flattens these surfaces into two dimensional planes by a parameterization method with involves cross vector fields. The cross vector fields are generated by propagating the given fiber orientations specified at several important points on the 3D model. Integration of the cross vector fields gives parameterization with low-stretch and low-distortion.