• Journal of Technologic Dentistry
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• v.35 no.4
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• pp.281-286
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• 2013

Purpose: Surface modification is important techniques in modern dental and orthopedic implants. This study was performed to try embedding of bioactive materials in porous Ti implants. Methods: Porous Ti implant samples were fabricated by sintering of spherical Ti powders in a high vacuum furnace. It's diameter and height were 4mm and 20mm. Embedding process was used to suction and vacuum chamber. Loading properties of porous Ti implants were evaluated by scanning electron microscope(SEM), confocal laser scanning microscope(CLSM), and UV-Vis-NIR spectrophotometer. Results: Internal pore structure was formed fully open pore. Average pore size and porosity were $10.253{\mu}m$ and 17.506%. Conclusion: Porous Ti implant was fabricated successfully by sintering method. Particles are necking strongly each other and others portions were vacancy. This porous structure can be embedded to bioactive materials. Therefore bioactive materials will be able to embedding to porous Ti implants. Bioactive materials embedding in the porous Ti implant will induced new bone faster.

• Journal of KIISE
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• v.43 no.6
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• pp.678-685
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• 2016

Named Entity Recognition and Classification (NERC) is a task for recognition and classification of named entities such as a person's name, location, and organization. There have been various studies carried out on Korean NERC, but they have some problems, for example lacking some features as compared with English NERC. In this paper, we propose a method that uses word embedding as features for Korean NERC. We generate a word vector using a Continuous-Bag-of-Word (CBOW) model from POS-tagged corpus, and a word cluster symbol using a K-means algorithm from a word vector. We use the word vector and word cluster symbol as word embedding features in Conditional Random Fields (CRFs). From the result of the experiment, performance improved 1.17%, 0.61% and 1.19% respectively for TV domain, Sports domain and IT domain over the baseline system. Showing better performance than other NERC systems, we demonstrate the effectiveness and efficiency of the proposed method.

• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.870-875
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• 2003

We Present digital watermarking using a quadratic equation embedding method in wavelet transform domain in order to improve the invisibility. Generally, embedding watermark used a simple equation form, but we extended a quadratic equation form in this paper. We performed a computer simulation in order to compare proposed method to other methods using LENA, GOLDHILL, BARBARA, and MAN images By computer experiments, invisibility of the proposed method better than the conventional methods at 100 % normalized similarity.

• Journal of the Korean Mathematical Society
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• v.35 no.1
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• pp.225-234
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• 1998

We compute genus distributions for bouquets of dipoles by using the method concerning the cycle structure of permutations in the symmetric group. From this, we can deduce that every bouquet of dipoles is upper embeddable. We find a foumula for computing the embedding polynomials for bouquets of dipoles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2101-2123
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• 2023

Recent studies have shown that the neural network-based binary code similarity detection technology performs well in vulnerability mining, plagiarism detection, and malicious code analysis. However, existing cross-architecture methods still suffer from insufficient feature characterization and low discrimination accuracy. To address these issues, this paper proposes a cross-architecture binary function similarity detection method based on composite feature model (SDCFM). Firstly, the binary function is converted into vector representation according to the proposed composite feature model, which is composed of instruction statistical features, control flow graph structural features, and application program interface calling behavioral features. Then, the composite features are embedded by the proposed hierarchical embedding network based on a graph neural network. In which, the block-level features and the function-level features are processed separately and finally fused into the embedding. In addition, to make the trained model more accurate and stable, our method utilizes the embeddings of predecessor nodes to modify the node embedding in the iterative updating process of the graph neural network. To assess the effectiveness of composite feature model, we contrast SDCFM with the state of art method on benchmark datasets. The experimental results show that SDCFM has good performance both on the area under the curve in the binary function similarity detection task and the vulnerable candidate function ranking in vulnerability search task.

• Journal of Technologic Dentistry
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• v.36 no.3
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• pp.179-184
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• 2014

Purpose: This study was performed to investigate the release behavior of bioactive materials as a BMP-2 embedding on the porous titanium implant. Methods: Porous Ti implant samples were fabricated by sintering of spherical Ti powders in a high vacuum furnace. Specimens diameter and height were 4mm and 10mm. Embedding materials were used to stamp ink. Sectional images, porosity and release behavior of porous Ti implants were evaluated by scanning electron microscope(SEM), mercury porosimeter and UV-Vis-NIR spectrophotometer. Results: Internal pore structure was formed fully open pore. Average pore size and porosity were $8.993{\mu}m$ and 8.918%. Embedding materials were released continually and slowly. Conclusion: Porous Ti implant was fabricated successfully by sintering method. Particles are necking strongly each other and others portions were vacancy. Therefore bioactive materials will be able to embedding to porous Ti implants. If the development of the fusion implant of the bioactive material will be able to have the chance to several patients.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1369-1373
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• 2015

Curve subdivision interpolation reconstructs edge well with low complexity, however it lacks of ability to recover texture components, instead. While, neighbor embedding is superior in texture reconstruction. Therefore, in this paper, a novel Super Resolution technique which combines curve subdivision interpolation and neighbor embedding is proposed. First, edge region and non-edge regions are classified. Then, for edge region, the curve subdivision algorithm is used to make two polynomials derived from discrete pixels and adaptive weights are adapted for gradients of 4 different sides to make smooth edge. For non edge region, neighbor-embedding method is used to conserve texture property in original image. Consequently results show that the proposed technique conserves sharp edges and details in texture better, simultaneously.

• ETRI Journal
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• v.32 no.6
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• pp.969-971
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• 2010

Based on a de-embedding technique, a new method is proposed which is capable of evaluating chip impedance behavior over absorbed power in flip-chip bonded UHF radio frequency identification transponder ICs. For the de-embedding, four compact co-planar test fixtures, an equivalent circuit for the fixtures, and a parameter extraction procedure for the circuit are developed. The fixtures are designed such that the chip can absorb as much power as possible from a power source without radiating appreciable power. Experimental results show that the proposed modeling method is accurate and produces reliable chip impedance values related with absorbed power.

• ETRI Journal
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• v.35 no.3
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• pp.512-522
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• 2013

In this paper, the radius weight mean (RWM) and the feature-embedding technique are used to present a novel watermarking scheme for color images. Simulations validate that the stego-images generated by the proposed scheme are robust against most common image-processing operations, such as compression, color quantization, bit truncation, noise addition, cropping, blurring, mosaicking, zigzagging, inversion, (edge) sharpening, and so on. The proposed method possesses outstanding performance in resisting high compression ratio attacks: JPEG2000 and JPEG. Further, to provide extra hiding storage, a steganographic method using the RWM with the least significant bit substitution technique is suggested. Experiment results indicate that the resulting perceived quality is desirable, whereas the peak signal-to-noise ratio is high. The payload generated using the proposed method is also superior to that generated by existing approaches.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.631-635
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• 2004

The rapid development of digital media and communication network urgently brings about the need of data certification technology to protect IPR (Intellectual property right). This paper proposed a new watermarking method for embedding contents owner's audio signal in order to protect color image IPR. Since this method evolves the existing static model and embeds audio signal of big data, it has the advantage of restoring signal transformed due to attacks. Three basic stages of watermarking include: 1) Encode analogue ID owner's audio signal using PCM and create new 3D audio watermark; 2) Interleave 3D audio watermark by linear bit expansion and 3) Transform Y signal of color image into wavelet and embed interleaved audio watermark in the low frequency band on the transform domain. The results demonstrated that the audio signal embedding in color image proposed in this paper enhanced robustness against lossy JPEG compression, standard image compression and image cropping and rotation which remove a part of image.