• Applied Microscopy
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• v.45 no.4
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• pp.195-198
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• 2015

Gas-assisted etching (GAE) with focused ion beam (FIB) was applied to prepare plan-view specimens of Cu thin-layer on a silicon substrate for transmission electron microscopy (TEM). GAE using $XeF_2$ gas selectively etched the silicon substrate without volume loss of the Cu thin-layer. The plan-view specimen of the Cu thin film prepared by FIB milling with GAE was observed by scanning electron microscopy and $C_S$-corrected high-resolution TEM to estimate the size and microstructure of the TEM specimen. The GAE with FIB technique overcame various artifacts of conventional FIB milling technique such as bending, shrinking and non-uniform thickness of the TEM specimens. The Cu thin film was uniform in thickness and relatively larger in size despite of the thickness of <200 nm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3146-3158
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• 2014

Efficient depth map coding is very crucial to the multi-view plus depth (MVD) format of 3-D video representation, as the quality of the synthesized virtual views highly depends on the accuracy of the depth map. Depth map contains smooth area within an object but distinct boundary, and these boundary areas affect the visual quality of synthesized views significantly. In this paper, we characterize the depth map by an auto-covariance analysis to show the locally anisotropic features of depth map. According to the characterization analysis, we propose an efficient depth map coding scheme, in which the directional discrete cosine transforms (DDCT) is adopted to substitute the conventional 2-D DCT to preserve the boundary information and thereby increase the quality of synthesized view. Experimental results show that the proposed scheme achieves better performance than that of conventional DCT with respect to the bitrate savings and rendering quality.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.623-626
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• 1996

Models from different perspectives including functinal view, behavioural view and information view are necessary to implement complex systems such as CIM. It is difficult to integrate those models into a unified framework since they describe different aspects of the system for different purposes. However, modeling from different perspectives is often the case, and many workers are involved in developing a system. Thus, the transformation or interconnection mechanism is required to cope with the consistency problem between them and to save the efforts during development. In this study, a methodology to thansform the IDEFO model into a process flow model is proposed.

• Journal of the Korean Society of Radiology
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• v.15 no.3
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• pp.321-327
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• 2021

Wrist PA-grip view is used to diagnose triangular fibrocartilage complex (TFCC) tear because it can easily diagnose damage to the surrounding wrist ligaments. However, despite advances in radiology equipment, distortion of images due to geometric elements still has many limitations. In this paper, we propose a method that can minimize the distortions of images by analyzing the distortions occurring in the wrist PA-grip view. A source of image distance (SID) were set at 130 cm and 150 cm for comparison with 110 cm. Depending on the SID, the phantom of wrist was moved at 0, 2, 4, 6, 8, and 10 cm in the X-axis and Y-axis directions, respectively. For quantitative evaluation, the difference of distance between the radius and ulna was measured in picture archiving and communication system (PACS) system. As a qualitative evaluation, survey was conducted among 20 radiologic technologists who examined the Wrist PA-grip view. The Kruskal Wallis test was performed to compare the distortion according to the phantom movement in the X-axis and Y-axis directions based on the SID, and the Tukey test was performed as a post-test. In the quantitative evaluation results, the measured values obtained in the X-axis was not significantly different in all groups (p>0.05). The measured values obtained in the Y-axis was significantly different in the most groups (p<0.05). Therefore, to reduce distortion while maintaining image quality, we recommend what examine the SID at 150 cm than 110 cm.

• Journal of the Korean Society of Radiology
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• v.16 no.3
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• pp.295-302
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• 2022

Sparse-view computed tomography (CT) imaging technique is able to reduce radiation dose, ensure the uniformity of image characteristics among projections and suppress noise. However, the reconstructed images obtained by the sparse-view CT imaging technique suffer from severe artifacts, resulting in the distortion of image quality and internal structures. In this study, we proposed a convolutional neural network (CNN) with wavelet transformation and residual learning for reducing artifacts in sparse-view CT image, and the performance of the trained model was quantitatively analyzed. The CNN consisted of wavelet transformation, convolutional and inverse wavelet transformation layers, and input and output images were configured as sparse-view CT images and residual images, respectively. For training the CNN, the loss function was calculated by using mean squared error (MSE), and the Adam function was used as an optimizer. Result images were obtained by subtracting the residual images, which were predicted by the trained model, from sparse-view CT images. The quantitative accuracy of the result images were measured in terms of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The results showed that the trained model is able to improve the spatial resolution of the result images as well as reduce artifacts in sparse-view CT images effectively. Also, the trained model increased the PSNR and SSIM by 8.18% and 19.71% in comparison to the imaging model trained without wavelet transformation and residual learning, respectively. Therefore, the imaging model proposed in this study can restore the image quality of sparse-view CT image by reducing artifacts, improving spatial resolution and quantitative accuracy.

• Journal of Korea Multimedia Society
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• v.21 no.10
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• pp.1131-1141
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• 2018

Motion Estimation which is used to reduce the redundant data plays an important role in video compressions. However, it requires huge computational complexity of the encoder part. And therefore many fast motion estimation methods has been developed to reduce complexity. Multi-view video is obtained by using many cameras at different positions and its complexity increases in proportion to the number of cameras. In this paper, we proposed a fast motion estimation method for multi-view video. The proposed method predicts a search start point by using correlated candidate vectors of the current block. According to the motion size of the start search point, a search start pattern of the current block is decided adaptively. The proposed method proves to be about 2 ~ 5 times faster than existing methods while maintaining similar image quality and bitrates.

• Journal of Korean Elementary Science Education
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• v.24 no.4
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• pp.417-425
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• 2005

Although there are some challenges to a view of science teaming as conceptual change, the view still occupies an important position in science teaming and teaching. Conceptual change theory implies that students' conceptions need to be exchanged for the new science conceptions. This was at the heart of conceptual change theory of Posner et al. (1982). According to this theory, cognitive conflict is known as an important factor in conceptual change even though there is still a controversial on effects on science teaming. This study is intended to interpret the cognitive conflict from cybernetics' perspective and explain difficulties of conceptual change which students have in teaming science and the conditions of conceptual change.

• Journal of Korean Society of Forest Science
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• v.35 no.1
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• pp.65-69
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• 1977

• Journal of Korean Society of Forest Science
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• v.63 no.1
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• pp.129-137
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• 1984

• Journal of Korean Society of Forest Science
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• v.35 no.1
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• pp.61-64
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• 1977