• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.167-170
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• 2006

This study proposes a new wavelet watermark technique based on the Linear Bit Expansion. To ensure the security of the watermark, it is Amold Transformed before embedding. Then the wavelet transformation of watermark and original images is processed. Since the size of the watermark image is a quarter of the original site, it uses linear bit-expansion to enlarge the watermark image. Lastly, watermark is inserted in a given intensity to the corresponding low frequency subbands of the wavelet-transformed images proposed in this paper. When detecting the presence of watermark, the similarity between extracted watermark and the original watermark is compared applying the F norm function.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.3
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• pp.28-34
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• 2002

This paper describes embedding non-linearly watermark data in the components of pixel intensities in the spatial domain of an image. The principle of the proposed method is that when an image is segmented regularly to the blocks, the pixels of the block have the non-linear properties without any similarity. That is, for the block with strong non-linear property human can't feel the visual different to the modified pixel values, on the other hand for the block with weak non-linear property human can feel the visual different to the a little modified pixel values. Thus we could embed the watermark data according to the non-linear property of the blocks. As the result of the simulation, against some general image processing attacks our algorithm could keep robust and be responsible for the copyright certainly. 

• Structural Engineering and Mechanics
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• v.16 no.4
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• pp.391-404
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• 2003

Local reinforcement in dowel type timber joints is essential to improve ductility, to increase load carrying capacity and to reduce the risk of brittle failure, especially in the case of using solid dowel. In many types of reinforcing materials available today, DVW (densified veneer wood) has been demonstrated to be the most advantages in terms of compatibility, embedding performance and ductility. Preliminary studies show that using appropriately sized DVW discs bonded into the timber interfaces may be an effective way to reinforce the connection. In this paper, non-linear 3-dimensional finite element models, incorporating orthotropic and non-linear material behaviour, have been developed to simulate structural performance of the timber joints locally reinforced by DVW discs. Different contact algorithms were applied to simulate contact conditions in the joints. The models were validated by the corresponding structural tests. Correlation between the experimental results and the finite element simulations is reasonably good. Using validated finite element models, parametric studies were undertaken to investigate effects of the DVW disc sizes and the end distances on shear stresses and normal stresses in a possible failure plane in the joint.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.21-31
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• 2023

In this paper, we focused on the problem of evaluating multi-class classification accuracy and simulation of multiple classifier performance metrics. Multi-class classifiers for sentiment analysis involved many challenges, whereas previous research narrowed to the binary classification model since it provides higher accuracy when dealing with text data. Thus, we take inspiration from the non-linear Support Vector Machine to modify the algorithm by embedding dynamic hyperplanes representing multiple class labels. Then we analyzed the performance of multi-class classifiers using macro-accuracy, micro-accuracy and several other metrics to justify the significance of our algorithm enhancement. Furthermore, we hybridized Enhanced Convolution Neural Network (ECNN) with Dynamic Support Vector Machine (DSVM) to demonstrate the effectiveness and efficiency of the classifier towards multi-class text data. We performed experiments on three hybrid classifiers, which are ECNN with Binary SVM (ECNN-BSVM), and ECNN with linear Multi-Class SVM (ECNN-MCSVM) and our proposed algorithm (ECNNDSVM). Comparative experiments of hybrid algorithms yielded 85.12 % for single metric accuracy; 86.95 % for multiple metrics on average. As for our modified algorithm of the ECNN-DSVM classifier, we reached 98.29 % micro-accuracy results with an f-score value of 98 % at most. For the future direction of this research, we are aiming for hyperplane optimization analysis.

• Journal of the Korean Mathematical Society
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• v.47 no.3
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• pp.547-572
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• 2010

We study existence of positive solutions of the classical nonlinear Schr$\ddot{o}$dinger equation $-{\Delta}u\;+\;V(x)u\;-\;f(x,\;u)\;-\;H(x)u^{2*-1}\;=\;0$, u > 0 in $\mathbb{R}^n$ $u\;{\rightarrow}\;0\;as\;|x|\;{\rightarrow}\;{\infty}$. In fact, we consider the following more general quasi-linear Schr$\ddot{o}$odinger equation $-div(|{\nabla}u|^{m-2}{\nabla}u)\;+\;V(x)u^{m-1}$ $-f(x,\;u)\;-\;H(x)u^{m^*-1}\;=\;0$, u > 0 in $\mathbb{R}^n$ $u\;{\rightarrow}\;0\;as\;|x|\;{\rightarrow}\;{\infty}$, where m $\in$ (1, n) is a positive number and $m^*\;:=\;\frac{mn}{n-m}\;>\;0$, is the corresponding critical Sobolev embedding number in $\mathbb{R}^n$. Under appropriate conditions on the functions V(x), f(x, u) and H(x), existence and non-existence results of positive solutions have been established.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.953-960
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• 2014

In Shamir's (t,n)-threshold based secret image sharing schemes, there exists a problem that the secret image can be reconstructed when an arbitrary attacker becomes aware of t secret image pieces, or t participants are malicious collusion. It is because that utilizes linear combination polynomial arithmetic operation. In order to overcome the problem, we propose a secret image sharing scheme using matrix decomposition and adversary structure. In the proposed scheme, there is no reconstruction of the secret image even when an arbitrary attacker become aware of t secret image pieces. Also, we utilize a simple matrix decomposition operation in order to improve the security of the secret image. In experiments, we show that performances of embedding capacity and image distortion ratio of the proposed scheme are superior to previous schemes.

• Journal of Acupuncture Research
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• v.29 no.2
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• pp.29-36
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• 2012

The purpose of this article is to review all the wrinkle treatments reported so far, and to introduce a method of dermal subcision, especially localized fine wrinkles. In order to remove wrinkles, laser, ulthera and drug therapy are commonly used in western medicine while Miso facial rejuvenation acupuncture, $Jung-An$ acupuncture and needle-embedding therapy are used in oriental medicine. However, as researches on fine wrinkles have been insufficiently conducted until now. Dermal subcision stated in this study is considered to be a safe and effective way to ameliorate fine linear-shaped wrinkles around or below eyes and mouth by increasing the circulation of qi and blood. also, reproducing dermal layer. More and further related cases and researches are expected in the future.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.832-835
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• 2004

In this paper, we proposed a blind watermarking algorithm to use characteristics of a scalar quantizer which is similar with the recommended in the JPEG2000 and JPEG. This algorithm shifts a quantization index according to the value of each watermark bit to prevent losing the watermark information during the compression by quantization. Therefore, the watermark is embedded during the process of quantization, not an additional process for watermarking, and adaptively applied as an assigned quantizer according to application area. In the embedding process, a LFSR(Linear feedback shift register) is used to hide the watermarking positions. Therefore the embedded watermark can be extracted by only the owner who knows the initial value of LFSR without the original image. The experimental results showed that the proposed algorithm satisfies the robustness and imperceptibility corresponding to the major requirement of watermarking.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.605-607
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• 2018

본 논문에서는 음절 임베딩과 양방향 LSTM-CRF 모델을 이용한 한국어 문장 자동 띄어쓰기 시스템을 제안한다. 문장에 대한 자질 벡터 표현을 위해 문장을 구성하는 음절을 Unigram 및 Bigram으로 나누어 각 음절을 연속적인 벡터 공간에 표현하고, 양방향 LSTM을 이용하여 현재 자질에 양방향 자질들과 의존성을 부여한 새로운 자질 벡터를 생성한다. 이 새로운 자질 벡터는 전방향 신경망과 선형체인(Linear-Chain) CRF를 이용하여 최적의 띄어쓰기 태그 열을 예측하고, 생성된 띄어쓰기 태그를 기반으로 문장 자동 띄어쓰기를 수행하였다. 문장 13,500개와 277,718개 어절로 이루어진 학습 데이터 집합과 문장 1,500개와 31,107개 어절로 이루어진 테스트 집합의 학습 및 평가 결과는 97.337%의 음절 띄어쓰기 태그 분류 정확도를 보였다.

• Journal of the Korean Vacuum Society
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• v.8 no.4B
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• pp.536-540
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• 1999

We have developed a refractory WNx self-aligned gate GaAs metal-semiconductor field-effect transistor(MESFET) using $SiO_2$ side-wall process. The MESFET hasa fully ion-implanted, planar, symmetric self-alignment structure, and it is quite suitable for integration. The uniform trans-conductance of 354nS/mm up to Vgs=+0.6V and the saturation current of 171mA/mm were obtained. As high as 43GHz of cut-off frequency hs been realized without any de-embedding of parasitic effects. The refractory WNx self-aligned gate GaAs MESFET technology is one of the most promising candidates for realizing linear power amplifier ICs and multifunction monolithic ICs for use in the digital mobile communication systems such as hand-held phone(HHP), personal communication system (PCS) and wireless local loop(WLL).