• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.70-78
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• 2007

The performance of face recognition is greatly affected by the illumination effect because intra-person variation under different lighting conditions can be much bigger than the inter-person variation. In this paper, we propose an illumination robust face recognition by separating identity factor and illumination factor using the symmetric bilinear models. The translation procedure in the bilinear model requires a repetitive computation of matrix inverse operation to reach the identity and illumination factors. Sometimes, this computation may result in a nonconvergent case when the observation has an noisy information. To alleviate this situation, we suggest a ridge regressive bilinear model that combines the ridge regression into the bilinear model. This combination provides some advantages: it makes the bilinear model more stable by shrinking the range of identity and illumination factors appropriately, and it improves the recognition performance by reducing the insignificant factors effectively. Experiment results show that the ridge regressive bilinear model outperforms significantly other existing methods such as the eigenface, quotient image, and the bilinear model in terms of the recognition rate under a variety of illuminations.

• Journal of the Korean Society for Railway
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• v.14 no.2
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• pp.94-99
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• 2011

In this study, the stress reduction effect was evaluated for GFRP/Mg single lap bonded joints according to six different adherend shapes. Six different types of the single lap joint specimen were modeled and assessed using geometrically nonlinear finite element analysis. Moreover, three dimensional effect of stress distribution for the different adherend shapes was investigated. From the analysis, the dissimilar single lap bonded joint with the normal tapering and without the spew fillet (model 2) showed the highest stress values. In contrast, the peel stress values of both the square ended adherends with the spew fillet (model 3) and the reverse tapered adherends with the spew fillet (model 5) were 65.8% and 65.5% lower than the reference model.

• Journal of the Korean Society for Railway
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• v.13 no.6
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• pp.546-551
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• 2010

In this paper, the strain distribution of the bond layer has been compared with the experimental data and analyzed according to the different mesh refinements and element types. The mesh density was changed along the longitudinal direction of adherend, the longitudinal direction of overlapped region, the vertical direction of adherend, the vertical direction of adhesive and the width direction of the joint. In addition, the effect of the different types of element was evaluated using soild, shell and plane strain element. The geometric nonlinear analysis was performed to consider the large deformation of the joint. From the numerical result, at least 2 elements were needed to achieve a reliable result as the solid element used. In case of shell element, the peel strain at x/c=1 showed 22.8% error compared with the experiment but the shear strain showed a good agreement with the experiment within 1.67% error.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.3
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• pp.333-340
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• 2011

We evaluated the stress-reduction effect for different shapes of a composite adherend with or without a spew fillet. Six different single-lap joint specimens were modeled and assessed using nonlinear finite element analysis. Moreover, we investigated the effect of the stiffness ratio of the adherend and adhesive. The single-lap joint with normal tapering had the highest stress values, and the single-lap joint with reverse tapering and a spew fillet had the lowest stress values. The composite adherends with higher stiffness had lower stress values, and the adhesives with lower stiffness had lower stress values.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.5
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• pp.1543-1551
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• 1996

The static tensile load bearing capability of as adhesively-bonded tubular single lap jint that is calculated usign the linear mechanical properties of adhesive is usually far from the experimentally determined because the majority of the load transfer of the adhesively-bonded jointd is accomplished by the nonlinear behavior of the rubber-toughened eoxy adhesive. In this paper, both the nonlinear mechanical properties and the fabrication residual thermal stresses of adhesive were included in the calculation of the stresses of adhesively-bonded joints. The onlinear tensile properties of adhesive were approximated by an exponential form which was represented by the initial tensile modulus and ultimate tensile stength of adhesive. The stress distribution in the adhesive were calculated by applying the load obtained from the tensile tests. From the tensile tests and the stress analysis of adhesively-bonded hoints, the failure model for adhesively-bonded tubular single lap joints was proposed.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.3
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• pp.237-244
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• 2016

This paper presents a nonlinear Moving Least Squares(MLS) difference method for material nonlinearity problem. The MLS difference method, which employs strong formulation involving the fast derivative approximation, discretizes governing partial differential equation based on a node model. However, the conventional MLS difference method cannot explicitly handle constitutive equation since it solves solid mechanics problems by using the Navier's equation that unifies unknowns into one variable, displacement. In this study, a double derivative approximation is devised to treat the constitutive equation of inelastic material in the framework of strong formulation; in fact, it manipulates the first order derivative approximation two times. The equilibrium equation described by the divergence of stress tensor is directly discretized and is linearized by the Newton method; as a result, an iterative procedure is developed to find convergent solution. Stresses and internal variables are calculated and updated by the return mapping algorithm. Effectiveness and stability of the iterative procedure is improved by using algorithmic tangent modulus. The consistency of the double derivative approximation was shown by the reproducing property test. Also, accuracy and stability of the procedure were verified by analyzing inelastic beam under incremental tensile loading.

• Review of KIISC
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• v.29 no.3
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• pp.29-36
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• 2019

폭발적으로 성장하는 소셜 미디어 서비스로 인해 개인간의 연결이 강화된 환경에서는 URL로써 전파되는 피싱 공격의 위험성이 크게 강조된다. 최근 텍스트 분류 및 모델링 분야에서 그 성능을 입증받은 딥러닝 알고리즘은 피싱 URL의 구문적, 의미적 특징을 각각 모델링하기에 적절하지만, 기존에 사용하는 규칙 기반 앙상블 방법으로는 문자와 단어로부터 추출되는 특징간의 비선형적인 관계를 효과적으로 융합하는데 한계가 있다. 본 논문에서는 피싱 URL의 구문적, 의미적 특징을 체계적으로 융합하기 위한 컨볼루션 신경망 기반의 퓨전 신경망을 제안하고 기계학습 방법 중 최고의 분류정확도 (0.9804)를 달성하였다. 학습 및 테스트 데이터셋으로 45,000건의 정상 URL과 15,000건의 피싱 URL을 수집하였고, 정량적 검증으로 10겹 교차검증과 ROC커브, 정성적 검증으로 오분류 케이스와 딥러닝 내부 파라미터를 시각화하여 분석하였다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.733-744
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• 2012

Dynamic threshold public-key encryption provides dynamic setting of the group of all users, receivers and the threshold value. Over recent years, there are many studies on the construction of scheme, called ID-based dynamic threshold encryption, which combines the ID-based encryption with dynamic threshold encryption. In this paper, we analyze the ID-based dynamic threshold encryption proposed by Xing and Xu in 2011, and show that their scheme has a structural problem. We propose a conversion method from ID-based encryption which uses the bilinear map to ID-based dynamic threshold encryption. Additionally, we prove this converted scheme has CPA security under the full model.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.527-536
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• 2017

With the recent development of smart grid industry, the necessity for efficient EMS(Energy Management System) has been increased. In particular, in order to reduce electric load and energy cost, sophisticated electric load forecasting and efficient smart grid operation strategy are required. In this paper, for more accurate electric load forecasting, we extend the data collected at demand time into high time resolution and construct an artificial neural network-based forecasting model appropriate for the high time resolution data. Furthermore, to improve the accuracy of electric load forecasting, time series data of sequence form are transformed into continuous data of two-dimensional space to solve that problem that machine learning methods cannot reflect the periodicity of time series data. In addition, to consider external factors such as temperature and humidity in accordance with the time resolution, we estimate their value at the time resolution using linear interpolation method. Finally, we apply the PCA(Principal Component Analysis) algorithm to the feature vector composed of external factors to remove data which have little correlation with the power data. Finally, we perform the evaluation of our model through 5-fold cross-validation. The results show that forecasting based on higher time resolution improve the accuracy and the best error rate of 3.71% was achieved at the 3-min resolution.