• Journal of the Korean Society for Precision Engineering
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• v.21 no.5
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• pp.83-83
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• 2004

The analysis of relative pose(position and rotation) between stereo cameras is very important to determine the solution that provides three-dimensional information for an arbitrary moving target with respect to robot-end. In the space of free camera-model, the rotational parameters act on non-linear factors acquiring a kinematical solution. In this paper the general solution of active stereo that gives a three-dimensional pose of moving object is presented. The focus is to achieve a derivation of linear equation between a robot′s end and active stereo cameras. The equation is consistently derived from the vector of quaternion space. The calibration of cameras is also derived in this space. Computer simulation and the results of error-sensitivity demonstrate the successful operation of the solution. The suggested solution can also be applied to the more complex real time tracking and quite general and are applicable in various stereo fields.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.5
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• pp.89-90
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• 2004

The analysis of relative pose(position and rotation) between stereo cameras is very important to determine the solution that provides three-dimensional information for an arbitrary moving target with respect to robot-end. In the space of free camera-model, the rotational parameters act on non-linear factors acquiring a kinematical solution. In this paper the general solution of active stereo that gives a three-dimensional pose of moving object is presented. The focus is to achieve a derivation of linear equation between a robot's end and active stereo cameras. The equation is consistently derived from the vector of quaternion space. The calibration of cameras is also derived in this space. Computer simulation and the results of error-sensitivity demonstrate the successful operation of the solution. The suggested solution can also be applied to the more complex real time tracking and quite general and are applicable in various stereo fields.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.1
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• pp.64-76
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• 2015

This paper suggests applying pseudospectral model predictive method for exo-atmospheric guidance. The method is a fusion of pseudospectral law and model predictive control, in which a two point boundary value problem is formulated using model predictive approach and solved by applying pseudospectral law. In this work, the method is applied to exo-atmospheric guidance with specific target requirement. The existing exo-atmospheric guidance methods suffice general requirements for guidance, but cannot ensure specific target constraints; whereas, the presented method is able to do so. The proposed guidance law is assessed through simulation of perturbed cases, and the tests suggest that the method is able to operate semi-autonomously under control and thrust vector perturbations.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.59.5-60
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• 2017

We present the relationship between vector magnetic field parameters and solar major flare occurrence rate. Based on this, we are developing a forecast model of major flare (M and X-class) occurrence rate within a day using hourly vector magnetic field data of Space-weather HMI Active Region Patch (SHARP) from May 2010 to April 2017. In order to reduce the projection effect, we use SHARP data whose longitudes are within ${\pm}60$ degrees. We consider six SHARP magnetic parameters (the total unsigned current helicity, the total photospheric magnetic free energy density, the total unsigned vertical current, the absolute value of the net current helicity, the sum of the net current emanating from each polarity, and the total unsigned magnetic flux) with high F-scores as useful predictors of flaring activity from Bobra and Couvidat (2015). We have considered two cases. In case 1, we have divided the data into two sets separated in chronological order. 75% of the data before a given day are used for setting up a flare model and 25% of the data after that day are used for test. In case 2, the data are divided into two sets every year in order to reduce the solar cycle (SC) phase effect. All magnetic parameters are divided into 100 groups to estimate the corresponding flare occurrence rates. The flare identification is determined by using LMSAL flare locations, giving more numbers of flares than the NGDC flare list. Major results are as follows. First, major flare occurrence rates are well correlated with six magnetic parameters. Second, the occurrence rate ranges from 0.001 to 1 for M and X-class flares. Third, the logarithmic values of flaring rates are well approximated by two linear equations with different slopes: steeper one at lower values and lower one at higher values. Fourth, the sum of the net current emanating from each polarity gives the minimum RMS error between observed flare rates and predicted ones. Fifth, the RMS error for case 2, which is taken to reduce SC phase effect, are smaller than those for case 1.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.67-76
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• 2008

Reliable face recognition under various illumination environments is essential for successful commercialization. Feature-based face recognition relies on a good choice of feature vectors. Gabor feature vectors are known to be more robust to variations of pose and illumination than any other feature vectors so that they are popularly adopted for face recognition. However, they are not completely independent of illuminations. In this paper, we propose an illumination-robust face recognition method based on the Gabor feature vector illumination PCA model. We first construct the Gabor feature vector illumination PCA model where Gator feature vector space is rendered to be decomposed into two orthogonal illumination subspace and face identity subspace. Since the Gabor feature vectors obtained by projection into the face identity subspace are separated from illumination, the face recognition utilizing them becomes more robust to illumination. Through experiments, it is shown that the proposed face recognition based on Gabor feature vector illumination PCA model performs more reliably under various illumination and Pose environments.

• Journal of Information Technology and Architecture
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• v.9 no.3
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• pp.333-344
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• 2012

This paper proposes a system which recommends movies using information from social network services containing personal interest and taste. Method for establishing data is as follows. The system gathers movies' information from web sites and user's information from social network services such as Facebook and twitter. The data from social network services is categorized into six steps of emotion level for more accurate processing following users' emotional states. Gathered data will be established into vector space model which is ideal for analyzing and deducing the information with the system which is suggested in this paper. The existing similarity measurement method for movie recommendation is presentation of vector information about emotion level and similarity measuring method on the coordinates using Cosine measure. The deducing method suggested in this paper is two-phase arithmetic operation as follows. First, using general cosine measurement, the system establishes movies list. Second, using similarity measurement, system decides recommendable movie list by vector operation from the coordinates. After Comparative Experimental Study on the previous recommendation systems and new one, it turned out the new system from this study is more helpful than existing systems.

• Journal of KIISE:Software and Applications
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• v.30 no.11
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• pp.1072-1079
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• 2003

This study is purported for suggesting a new clustering algorithm that enables incremental categorization of numerous documents. The suggested algorithm adopts the natures of the spherical k-means algorithm, which clusters a mass amount of high-dimensional documents, and the fuzzy ART(adaptive resonance theory) neural network, which performs clustering incrementally. In short, the suggested algorithm is a combination of the spherical k-means vector space model and concept vector and fuzzy ART vigilance parameter. The new algorithm not only supports incremental clustering and automatically sets the appropriate number of clusters, but also solves the current problems of overfitting caused by outlier and noise. Additionally, concerning the objective function value, which measures the cluster's coherence that is used to evaluate the quality of produced clusters, tests on the CLASSIC3 data set showed that the newly suggested algorithm works better than the spherical k-means by 8.04% in average.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.430-433
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• 2001

When the vector control, which does not need a speed signal from a mechanical speed sensor, it is possible to reduce the cost of the control equipment and to improve the control performance in many industrial application. This paper describes a rotor speed identification method of induction motor based on the theory of flux model reference adaptive system. The estimator execute the rotor speed identification so that the vector control of the induction motor may be achieved. The improved auxiliary variable of the two model are introduced In perform accurate rotor speed estimation. The control system is composed of the PI controller for speed control and current controller using space voltage vector PWM technique. High speed calculation and processing for vector control is carried out by TMS320C31 digital signal processor. Validity of the proposed control method is verified through simulation and experimental result.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.703-705
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• 1999

In this paper, we introduce the direction of arrival(DOA) estimation of distributed signal based on the improved ESPRIT algorithm. Most research on the estimation of DOA has been performed based on the assumption that the signal sources are point sources. However, we consider a two-dimensional distributed signal source model using improved ESPRIT algorithm. In the distributed signal source model, a source is represented by two parameters, the azimuth angle and elevation angle. We address the estimation of the elevation and azimuth angles of distributed sources based on the parametric source modeling in the three-dimensional space with two uniform linear arrays. The array output vector is obtained by integrating a steering vector over all direction of arrival with the weighting of a distributed source density function. We also develop an efficient estimation procedures that can reduce the computational complexity. Some examples are shown to demonstrate explicity the estimation procedures under the distributed signal source model.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.11
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• pp.93-101
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• 1993

The transfer function of vector-controlled induction motor is represented along with both unstructured and structured uncertainty such as the error of rotor time constant and current ripple. The low-pass-filter behavior of a magnetizing inductance gets rid of unstructured uncertainty in the transfer function. The robust controller to compensate variation of the transfer function is designed using simple P-I linear controllers. The coefficients of speed PI controller are determined from an overshoot and a rising time of system and the coefficients of model-following PI controller are obtained using the solution of Riccati equation of LQR control in the state space equation of the error system. Experimental results with the DSP-based model-following robust controller are shown a good robustness against the structured uncertainty of the motor.