• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.299-299
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• 2014

기존의 고출력 광원들이 환경문제 등으로 외국에서 규제대상으로 지정되고 있는 가운데고체 상태의 광원인 Light-emitting diode (LED)는 기존의 광원에 비해 에너지 절감효과 크기 때문에 인해 널리 사용되고 있는 추세이다. 대부분의 백색 LED의 경우 청색 LED에 황색 형광체를 사용하는 것이 일반적이다. 그러나 이의 경우 빛의 흡수와 재방출 과정에서 생기는 에너지 변환손실의 문제가 불가피하다. 또한, 두 종류의 색을 섞어서 나타나는 낮은 연색성의 문제가 있고 사용할 수 있는 형광체의 종류와 조합도 일본 등 해외에 출원된 특허권으로 연구개발에 어려움이 있다. 이를 해결하기 위해 본 연구에서는 형광체를 사용하지 않는 단일 백색 LED를 개발을 위하여 극성과 반극성을 조합한 구조를 연구하였다. Photo-lithography를 이용하여 다양한 크기와 구조의 홀 패턴을 얻을 수 있었으며, metal organic chemical vapor deposition을 이용하여 다양한 형태의 피라미드 구조를 성장할 수 있었다. 패턴의 홀 크기와 홀 사이의 간격을 조절하면서 성장을 진행 하였고, 그 결과 pyramid와 truncated pyramid 모양의 GaN 구조를 성장할 수 있었다. [그림 1] Pyramid 구조의 반극성 면과 truncated pyramid 구조의 극성 면사이의 성장속도 차이 때문에 양자우물의 두께가 달라짐을 확인하였다. 이로 인해 양자구속효과가 달라져 다른 파장의 발광을 기대할 수 있었다. 뿐만 아니라 In의 확산거리가 Ga보다 길어서 홀사이 간격을 달리하면 In조성비가 달라지는 효과가 있음을 확인하였고 다양한 홀 사이 간격으로부터 각기 다른 파장의 발광을 얻을 수 있었다. 파장을 조금 더 상세하게 분석하기 위하여 Photoluminescence과 Cathodoluminescence을 사용하였다. 이로써 여러 파장을 발광하는 패턴을 섞어 넓은 영역의 발광 스펙트럼을 만들었다. 특히 패턴을 섞는 방법도 홀과 에피 구조를 섞는 방법, 크기가 다른 홀 패턴을 배열하는 방법등 다양히 하며 가장 좋을 패턴을 연구하였다. 그리하여 최적의 패턴과 구조, 성장조건을 찾아 백색의 CIE 좌표값을 얻을 수 있었다.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.2
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• pp.24-29
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• 2014

Digital mammography is the most common technique for the early detection of breast cancer. To diagnose the breast cancer in early stages and treat efficiently, many image enhancement methods have been developed. This paper presents a multi-scale contrast enhancement method in the Laplacian pyramid for the digital mammogram. The proposed method decomposes the image into the contrast measures by the Gaussian and Laplacian pyramid, and the pyramid coefficients of decomposed multi-resolution image are defined as the frequency limited local contrast measures by the ratio of high frequency components and low frequency components. The decomposed pyramid coefficients are modified by the contrast measure for enhancing the contrast, and the final enhanced image is obtained by the composition process of the pyramid using the modified coefficients. The proposed method is compared with other existing methods, and demonstrated to have quantitatively good performance in the contrast measure algorithm.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.1-9
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• 2021

The hologram pyramid is an application of floating holograms, allowing the observer to see three-dimensional holograms from various angles without wearing wearable devices. Due to the low cost and ease of manufacturing, it has been used in a wide variety of fields as diverse as education, prototyping, showcase, and etc. But, when the observer looks at the hologram from the place where each side of the hologram pyramid is connected, the hologram looks cut and distorted. Also, the observer can see the only hologram of angles viewed head-on from each side. In this paper, we propose a method of generating a hologram image corresponding to the observer's gaze angle by tracking the observer's position and conducting reverse distortion. It provide a hologram of the angle viewed by the observer without cutting and distortion. In addition, the existing method and the proposed method were applied and compared in the hologram pyramid.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4439-4455
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• 2021

Compared with two-stage object detection algorithms, one-stage algorithms provide a better trade-off between real-time performance and accuracy. However, these methods treat the intermediate features equally, which lacks the flexibility to emphasize meaningful information for classification and location. Besides, they ignore the interaction of contextual information from different scales, which is important for medium and small objects detection. To tackle these problems, we propose an image pyramid network based on dual attention mechanism (DAIPNet), which builds an image pyramid to enrich the spatial information while emphasizing multi-scale informative features based on dual attention mechanisms for one-stage object detection. Our framework utilizes a pre-trained backbone as standard detection network, where the designed image pyramid network (IPN) is used as auxiliary network to provide complementary information. Here, the dual attention mechanism is composed of the adaptive feature fusion module (AFFM) and the progressive attention fusion module (PAFM). AFFM is designed to automatically pay attention to the feature maps with different importance from the backbone and auxiliary network, while PAFM is utilized to adaptively learn the channel attentive information in the context transfer process. Furthermore, in the IPN, we build an image pyramid to extract scale-wise features from downsampled images of different scales, where the features are further fused at different states to enrich scale-wise information and learn more comprehensive feature representations. Experimental results are shown on MS COCO dataset. Our proposed detector with a 300 × 300 input achieves superior performance of 32.6% mAP on the MS COCO test-dev compared with state-of-the-art methods.

• Journal of Preventive Medicine and Public Health
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• v.51 no.3
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• pp.163-168
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• 2018

Objectives: Due to their developmental characteristics, adolescents have a higher probability than other age groups of experiencing injuries caused by accidents, violence, and intentional self-harm. The severity and characteristics of injuries vary by the intentionality and mechanism of injury; therefore, there is a need for a national-level estimate of the scale and the severity of injuries in adolescents that takes these factors into account. Methods: By using data from the Emergency Department-based Injury In-depth Surveillance Data, National Emergency Department Information System, the Korean National Hospital Discharge In-depth Injury Survey, and cause of death statistics, we calculated the emergency department (ED) visit rate, hospitalization rate, and death rate of injuries per 100 000 adolescents for each injury mechanism. The calculated rates were used to generate the injury pyramid ratio (ratio of death rate to hospitalization rate to ED visit rate) to visualize the scale and the severity of the injury. Results: The mortality rate in adolescents due to injury was 10/100 000; the corresponding rates for hospitalization and ED visits were 1623 and 4923, respectively, resulting in an injury pyramid ratio with the general pyramid form, with a 1:162:492 ratio of deaths to hospitalizations to ED visits. The mortality rate due to suicide/intentional self-harm was 5/100 000, while 35 were hospitalized for this reason and 74 made ED visits. The pyramid ratio of 1:7:15 for intentional self-harm/suicide showed a steep pyramidal form, indicating considerable lethality. The mortality rate due to motor vehicle collisions (MVCs) was 3/100 000; 586 were hospitalized for this reason, while 1023 made ED visits. The pyramid ratio of 1:195:341 for MVCs showed a gradual pyramid form, indicating that the lethality was low and the scale of injury was high. Conclusions: The main categories of injuries in adolescents were visualized in pyramid form, contributing to an understanding of the scale of each injury by mechanism in terms of levels of death, hospitalization, and ED visits. These findings will be helpful for understanding how to prioritize injuries in adolescents.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1270-1281
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• 1999

피라미드 기법 1 은 d-차원의 공간을 2d개의 피라미드들로 분할하는 특별한 공간 분할 방식을 이용하여 고차원 데이타를 효율적으로 색인할 수 있는 새로운 색인 방법으로 제안되었다. 피라미드 기법은 고차원 사각형 형태의 영역 질의에는 효율적이나, 유사성 검색에 많이 사용되는 고차원 구형태의 영역 질의에는 비효율적인 면이 존재한다. 본 논문에서는 고차원 데이타를 많이 사용하는 유사성 검색에 효율적인 새로운 색인 기법으로 구형 피라미드 기법을 제안한다. 구형 피라미드 기법은 먼저 d-차원의 공간을 2d개의 구형 피라미드로 분할하고, 각 단일 구형 피라미드를 다시 구형태의 조각으로 분할하는 특별한 공간 분할 방법에 기반하고 있다. 이러한 공간 분할 방식은 피라미드 기법과 마찬가지로 d-차원 공간을 1-차원 공간으로 변환할 수 있다. 따라서, 변환된 1-차원 데이타를 다루기 위하여 B+-트리를 사용할 수 있다. 본 논문에서는 이렇게 분할된 공간에서 고차원 구형태의 영역 질의를 효율적으로 처리할 수 있는 알고리즘을 제안한다. 마지막으로, 인위적 데이타와 실제 데이타를 사용한 다양한 실험을 통하여 구형 피라미드 기법이 구형태의 영역 질의를 처리하는데 있어서 기존의 피라미드 기법보다 효율적임을 보인다.Abstract The Pyramid-Technique 1 was proposed as a new indexing method for high- dimensional data spaces using a special partitioning strategy that divides d-dimensional space into 2d pyramids. It is efficient for hypercube range query, but is not efficient for hypersphere range query which is frequently used in similarity search. In this paper, we propose the Spherical Pyramid-Technique, an efficient indexing method for similarity search in high-dimensional space. The Spherical Pyramid-Technique is based on a special partitioning strategy, which is to divide the d-dimensional data space first into 2d spherical pyramids, and then cut the single spherical pyramid into several spherical slices. This partition provides a transformation of d-dimensional space into 1-dimensional space as the Pyramid-Technique does. Thus, we are able to use a B+-tree to manage the transformed 1-dimensional data. We also propose the algorithm of processing hypersphere range query on the space partitioned by this partitioning strategy. Finally, we show that the Spherical Pyramid-Technique clearly outperforms the Pyramid-Technique in processing hypersphere range queries through various experiments using synthetic and real data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.321-322
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• 2008

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.582-591
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• 2009

The pyramid graph is an interconnection network topology based on regular square mesh and tree structures. In this paper, we adopt a strategy of classification into two disjoint groups of edges in regular square mesh as a base sub-graph constituting of each layer in the pyramid graph. Edge set in the mesh can be divided into two disjoint sub-sets called as NPC(represents candidate edge for neighbor-parent) and SPC(represents candidate edge for shared-parent) whether the parents vertices adjacent to two end vertices of the corresponding edge have a relation of neighbor or shared in the upper layer of pyramid graph. In addition, we also introduce a notion of shrink graph to focus only on the NPC-edges by hiding SPC-edges in the original graph within the shrunk super-vertex on the resulting graph. In this paper, we analyze that the lower and upper bound on the number of NPC-edges in a Hamiltonian cycle constructed on $2^n\times2^n$ mesh is $2^{2n-2}$ and $3*(2^{2n-2}-2^{n-1})$ respectively. By expanding this result into the pyramid graph, we also prove that the maximum number of NPC-edges containable in a Hamiltonian cycle is $4^{n-1}-3*2^{n-1}$-2n+7 in the n-dimensional pyramid.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.1
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• pp.33-46
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• 1996

Inthis paper, we investigate the compatible coding technique, which receives much interest ever since the introduction of HDTV. First, attempts have been made to analyze the theoretical transform coding gains for various hierarchical decomposition techniques, namely subband, pyramid and DCT-based decomposition techniques. It is shown that the spatical domain techniques proide higher transform coding gains than the DCT-based coding technique. Secondly, we compare the performance of these spatial domain techniques, in terms of the PSNR versus various rate allocations to each layer. Based on these analyses, it is believed that the pyramid decomposition is more appropriate for the compatible coding. Also in this paper, we propose a hybrid prediction pyramid coding technique, by combining the spatio-temporal prediction in MPEG-2[3] and the adaptive MC(Motion Compensation)[1]. In the proposed coding technigue, we also employ an adaptive DCT coefficient scanning technique to exploit the direction information of the 2nd-layer signal. Through computer simulations, the proposed hybrid prediction with adaptive scanning technuque shows the PSNR improvement, by about 0.46-1.78dB at low 1st-layer rate(about 0.1bpp) over the adaptive MC[1], and by about 0.33-0.63dB at high 1st-layer rate (about 0.32-0.43bpp) over the spatio-temporal prediction[3].

• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.199-204
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• 2007

In digital radiography, to improve the contrast of digital radiography image, the multi-scale nonlinear amplification algorithm based on unsharp masking is one of the major image enhancement algorithms. In this paper, we used the Laplacian pyramid to decompose a digital radiography(DR) image. In our simulation, the DR image was decomposed into seven layers and the coefficients of the each layer was amplified with nonlinear function. We also imported a noise containment algorithm to limit noise amplification. To enhance the contrast of image, we proposed a new adaptive non-linear gain amplification coefficients. As a result of having applied to some clinical data, a detail visibility was improved significantly without unacceptable noise boosting. Images that acquired with the proposed adaptive non-linear gain coefficients have shown superior quality to those that applied similar gain control method and expected to be accepted in the clinical applications.