• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.244-246
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• 2003

우리의 일상생활에서 차지하고 있는 소프트웨어의 비중은 점점 더 커져가고 있으며, 그만큼 소프트웨어의 오류가 우리에게 미치는 영향도 커지고 있다. 또한, 현대의 소프트웨어는 더 복잡해지고 높은 안정성이 필요하게 되므로 기존 소프트웨어와는 다른 새로운 패러다임의 소프트웨어가 필요하다. 적응형 소프트웨어는 소프트웨어 스스로가 자신의 기능을 추론하고 오류가 발생하면 이에 적절하게 대처할 수 있는 새로운 소프트웨어 패러다임이다. 적응형 소프트웨어를 개발하려면 소프트웨어가 적응해야 하는 상황을 모델링 하는 기술이 필요하다. 본 논문에서는 프로덕트 라인 개발 방법에서 사용하는 휘쳐 모델을 사용해 적응형 소프트웨어의 상황을 모델링 하는 기법을 제안한다.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2950-2952
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• 1999

This paper presents the method of 3D reconstruction of the depth information from the endoscopic stereo scopic images. After camera modeling to find camera parameters, we performed feature-point based stereo matching to find depth information. Acquired some depth information is finally 3D reconstructed using the NURBS(Non Uniform Rational B-Spline) method and OpenGL. The final result image is helpful for the understanding of depth information visually.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2818-2820
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• 2001

This paper presents the method of 3D reconstruction of the depth information from the endoscopic stereo scopic images. After camera modeling to find camera parameters, we performed feature-point based stereo matching to find depth information. Acquired some depth information is finally 3D reconstructed using the NURBS(Non Uniform Rational B-Spline) algorithm. The final result image is helpful for the understanding of depth information visually.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.294-296
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• 1995

In this paper, a vector control method for a AC-Excited BLSM(Brushless Synchronous Motor) is proposed. The BLSM has a feature that separate exciter is not needed for excitation. The proposed method is described in two parts as follow, one is the design of drive and the other is a modeling for its implementation. Rotor flux is estimated using indirect sensing method based on voltage equation in the synchronously rotation reference frame. And rotor position is calculated from rotor angular velocity and stator current. Through computer simulation results of this proposed system, it is shown that the BLSM drive has a ability of precision torque control from the static and dynamic performance.

• Asia pacific journal of information systems
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• v.1 no.1
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• pp.63-86
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• 1991

In this paper, our concern is the artificial neural network-based patten classification, when can resolve the difficulties in the Autoregressive Moving Average(ARMA) model identification problem To effectively classify a time series into an approriate ARMA model, we adopt the Multi-layered Backpropagation Network (MLBPN) as a pattern classifier, and Extended Sample Autocorrelation Function (ESACF) as a feature extractor. To improve the classification power of MLBPN's we suggest an integrated neural network system which consists of an AR Network and many small-sized MA Networks. The output of AR Network which will gives the MA order. A step-by-step training strategy is also suggested so that the learned MLBPN's can effectively ESACF patterns contaminated by the high level of noises. The experiment with the artificially generated test data and real world data showed the promising results. Our approach, combined with a statistical parameter estimation method, will provide a way to the automation of ARMA modeling.

• Proceedings of the KAIS Fall Conference
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• 2001.11a
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• pp.144-146
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• 2001

The synthesis of injection-molded parts has been done empirically, since it requires profound knowledge about injection molding which is not available to designers through current CAD systems. Appropriate U3 programs for mold design analysis to an existing geometric modeler is used to provide designers, at the initial stage, with comprehensive process knowledge for synthesis, performance analysis and feature-based geometric modeling.

• Smart Structures and Systems
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• v.23 no.4
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• pp.393-403
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• 2019

Applying more features gives us better accuracy in modeling; however, increasing the inputs causes the curse of dimensions. In this paper, a new structure has been proposed for fault detecting and identifying (FDI) of high-dimensional systems. This structure consist of two structure. The first part includes Auto-Encoders (AE) as Deep Neural Networks (DNNs) to produce feature engineering process and summarize the features. The second part consists of the Local Model Networks (LMNs) with LOcally LInear MOdel Tree (LOLIMOT) algorithm to model outputs (multiple models). The fault detection is based on these multiple models. Hence the residuals generated by comparing the system output and multiple models have been used to alarm the faults. To show the effectiveness of the proposed structure, it is tested on single-shaft industrial gas turbine prototype model. Finally, a brief comparison between the simulated results and several related works is presented and the well performance of the proposed structure has been illustrated.

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.183-188
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• 2010

A factorization-based 3D reconstruction system is realized to recover 3D scene from an image sequence. The image sequence is captured from uncalibrated perspective camera from several views. Many matched feature points over all images are obtained by feature tracking method. Then, these data are supplied to the 3D reconstruction module to obtain the projective reconstruction. Projective reconstruction is converted to Euclidean reconstruction by enforcing several metric constraints. After many triangular meshes are obtained, realistic reconstruction of 3D models are finished by texture mapping. The developed system is implemented in C++, and Qt library is used to implement the system user interface. OpenGL graphics library is used to realize the texture mapping routine and the model visualization program. Experimental results using synthetic and real image data are included to demonstrate the effectiveness of the developed system.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.49-56
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• 2023

This study proposed a damage location estimation method for automated image-based port infrastructure inspection. Memory efficiency was improved by calculating the homography matrix using feature detection technology and outlier removal technology, without going through the 3D modeling process and storing only damage information. To develop an algorithm specialized for port infrastructure, the algorithm was optimized through ground-truth coordinate pairs created using images of port infrastructure. The location errors obtained by applying this to the sample and concrete wall were (X: 6.5cm, Y: 1.3cm) and (X: 12.7cm, Y: 6.4cm), respectively. In addition, by applying the algorithm to the concrete wall and displaying it in the form of an exterior damage map, the possibility of field application was demonstrated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4502-4518
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• 2015

Fisher linear discriminant analysis (LDA) is one of the most popular projection techniques for feature extraction and has been widely applied in face recognition. However, it cannot be used when encountering the single sample per person problem (SSPP) because the intra-class variations cannot be evaluated. In this paper, we propose a novel method called local similarity based linear discriminant analysis (LS_LDA) to solve this problem. Motivated by the "divide-conquer" strategy, we first divide the face into local blocks, and classify each local block, and then integrate all the classification results to make final decision. To make LDA feasible for SSPP problem, we further divide each block into overlapped patches and assume that these patches are from the same class. To improve the robustness of LS_LDA to outliers, we further propose local similarity based median discriminant analysis (LS_MDA), which uses class median vector to estimate the class population mean in LDA modeling. Experimental results on three popular databases show that our methods not only generalize well SSPP problem but also have strong robustness to expression, illumination, occlusion and time variation.