• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.10a
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• pp.190-195
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• 1997

Recently it is increased by degrees to construct complex or large lattice type structures such as bridges, towers, cranes, and structures that can be used for space technology. In general, in order to analyze, these structures we have used the finite element method(FEM). In this method, however, it is necessary to use a large amount of computer memory and computation time because the FEM requires many degrees of freedom for solving dynamic problems for these structures. For overcoming this problem, the authors have developed the transfer dynamic stiffness coefficient method(TDSCM). This method is based on the concepts of the transfer and the synthesis of the dynamic stiffness coefficient which is related to force and displacement vector at each node. In this paper, the authors formulate vibration analysis algorithm for a complex and large lattice type structure using the transfer of the dynamic stiffness coefficient. And the validity of TDSCM demonstrated through numerical computational and experimental results.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.446-449
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• 2003

The conventional GSC is inappropriate in real situation when the target signal is present. The steering vector error cancels the target signal and the target signal misadjusts the weight of the adaptive filter. To prevent the target signal cancellation, the robust GSC using the constrained adaptive filters was already proposed. However, the adaptive weight misadjustment is not settled in robust GSC. This Paper proposes a revised robust sidelobe canceller with adaptive compensator. To compensate the influence of target signal, the adaptive compensator is used in cascade. In computer simulation, we show the performance improvement by comparing the robust GSC with the proposed GSC.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1749-1757
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• 2008

This research proposes a modified version of single pass algorithm specialized for text clustering. Encoding documents into numerical vectors for using the traditional version of single pass algorithm causes the two main problems: huge dimensionality and sparse distribution. Therefore, in order to address the two problems, this research modifies the single pass algorithm into its version where documents are encoded into not numerical vectors but other forms. In the proposed version, documents are mapped into tables and the operation on two tables is defined for using the single pass algorithm. The goal of this research is to improve the performance of single pass algorithm for text clustering by modifying it into the specialized version.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1203-1212
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• 2017

Intrusion detection systems (IDSs) are crucial in this overwhelming increase of attacks on the computing infrastructure. It intelligently detects malicious and predicts future attack patterns based on the classification analysis using machine learning and data mining techniques. This paper is devoted to thoroughly evaluate classifier ensembles for IDSs in IEEE 802.11 wireless network. Two ensemble techniques, i.e. voting and stacking are employed to combine the three base classifiers, i.e. decision tree (DT), random forest (RF), and support vector machine (SVM). We use area under ROC curve (AUC) value as a performance metric. Finally, we conduct two statistical significance tests to evaluate the performance differences among classifiers.

• Proceedings of the KIPE Conference
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• 2010.11a
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• pp.248-249
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• 2010

This paper describes development of hardware simulator for the PMSG(Permanent Magnet Synchronous Generator) wind power system, which was designed using real wind data. The simulator consists of a realistic wind turbine model using anemometer, vector drive, induction motor. The turbine simulator generates torque and speed signals for a specific wind turbine with respect to given wind speed. This torque and speed signals are scaled down to fit the input of 3kW PMSG. The PMSG-side converter operates to track the maximum power point and the grid-side inverter controls the active and reactive power supplied to the grid. The operational feasibility was first verified by computer simulations with PSCAD/EMTDC. The feasibility of real system implementation was confirmed through experimental works with a hardware set-up.

• Journal of Information Processing Systems
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• v.4 no.1
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• pp.17-26
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• 2008

This research proposes a new strategy where documents are encoded into string vectors and modified version of KNN to be adaptable to string vectors for text categorization. Traditionally, when KNN are used for pattern classification, raw data should be encoded into numerical vectors. This encoding may be difficult, depending on a given application area of pattern classification. For example, in text categorization, encoding full texts given as raw data into numerical vectors leads to two main problems: huge dimensionality and sparse distribution. In this research, we encode full texts into string vectors, and modify the supervised learning algorithms adaptable to string vectors for text categorization.

• Annual Conference of KIPS
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• 2012.11a
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• pp.461-463
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• 2012

본 연구는 실시간 영상에서 정면 얼굴을 가지고 있는 이미지를 탐지하는 방법에 대한 것이다. 모든 프레임마다 얼굴 인식 등의 연산을 수행한다면 계산량과 시간이 문제이다. 우리가 제안하는 방법은 동일인이 등장하는 영상 중 동일한 얼굴을 추적하여 움직임의 차이를 이용하여 정면 이미지를 판단하는 것이다. Gaussian Mixture Model 과 Motion template 을 이용하였으며, 실험을 통해 도출된 결과는 제안 알고리즘의 유용성을 어느 정도 증명할 수 있었다.

• Annual Conference of KIPS
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• 2012.11a
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• pp.468-471
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• 2012

음성을 통한 자동화된 감정 인식은 편리하고 다양한 서비스를 제공할 수 있어 중요한 연구분야라고 할 수 있다. 기계학습의 다양한 알고리즘을 사용하여 감정을 인식하는 연구가 진행되어 왔지만 그 성능은 아직 초보적 단계를 벋어나지 못하고 있는 실정이다. 앞선 연구에서 우리는 비감독 학습 방법으로 감성을 그룹화 하고 이것을 이용하여 다시 감독 학습을 하는 시스템을 소개 하였다. 본 연구에서 우리는 감독 학습 방법에서 사용했던 오류 역전파 알고리즘을 support vector machine(SVM) 으로 변경하고 몇 가지 구조를 변경하여 기능을 개선하였다. 실험을 통하여 성능을 측정하였으며 어느 정도 개선된 결과를 얻을 수 있었다.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1326-1335
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• 2021

As part of the cell division method, we proposed a method for segmenting images generated by topography microscopes through deep learning-based feature generation and graph segmentation. Hybrid vector shapes preserve the overall shape and boundary information of cells, so most cell shapes can be captured without any post-processing burden. NIH-3T3 and Hela-S3 cells have satisfactory results in cell description preservation. Compared to other deep learning methods, the proposed cell image segmentation method does not require postprocessing. It is also effective in preserving the overall morphology of cells and has shown better results in terms of cell boundary preservation.