• International Journal of Aeronautical and Space Sciences
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• v.8 no.2
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• pp.76-81
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• 2007

The fiber reinforced laminated composite structures are very susceptible to be damaged when they are impacted by foreign objects. To increase the impact resistance of the laminated composite structures, shape memory alloy(SMA) thin film is embedded in the structure. For the numerical impact analysis of SMA hybrid composite structures, SMA modeling tool is developed to consider pseudoelastic effect of SMAs. Moreover, the damage analysis is considered using failure criteria and a simple damage model for reasonable impact analysis. The numerical results are verified with the experimental ones. Impact analyses for composite plate with pre-strained SMAs are numerically performed and the damage areas are investigated.

• Research in Mathematical Education
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• v.17 no.3
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• pp.199-220
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• 2013

The main objective of this study is to explore the relationship between psychological factors (i.e. math anxiety, attention, attitude, Working Memory Capacity (WMC), and Field dependency) and students' mathematics problem solving based on Revised Bloom Taxonomy. A sample of 169 K11 school girls were tested on (1) The Witkin's cognitive style (Group Embedded Figure Test). (2) Digit Span Backwards Test. (3) Mathematics Anxiety Rating Scale (MARS). (4) Modified Fennema-Sherman Attitude Scales. (5) Mathematics Attention Test (MAT), and (6) Mathematics questions based on Revised Bloom Taxonomy (RBT). Results obtained indicate that the effect of these items on students mathematical problem solving is different in each cognitive process and level of knowledge dimension.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.346-348
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• 2006

실시간 운영체제를 탑재한 임베디드 시스템(Embedded System)은 특성상 다른 시스템에 비해 상대적으로 저 용량의 메모리를 지닌다. 따라서 제한된 메모리를 효율적으로 사용할 수 있는 기법이 적용될 필요가 있다. 외부 단편화(External Fragmentation)로 생긴 메모리 공간을 재조정하는 기법도 효율적인 메모리 사용을 위한 방안이며, 본 논문에서는 실시간 운영체제에서 가용한 메모리를 효율적으로 활용할 수 있는 메모리 압축(Memory Compaction) 기법에 대해서 설계 및 구현하였다.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.08a
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• pp.260-260
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• 2010

현대 사회가 고도의 정보화 사회로 변화하는 가운데 능동행렬 액정 표시 소자(AMLCD : Active Matrix Liquid Crystal Display)는 정보 디스플레이 분야에서 없어서는 안될 중요한 위치를 차지하게 됐다. AMOLED는 자체발광형이므로 LCD에 비해 시야각, contrast, 시인성이 우수하며, 화소를 낮은 전류 밀도로 구동시킨다는 장점이 있다. OLED 소자는 각 화소를 구동할 수 있는 박막 트랜지스타가 필요하며, OLED 소자와 결합된 TFT의 연구도 진행되고 있다. 더욱이 모바일 소자에서 낮은 구동 전압과 비용의 절감을 위해 System On Panels (SOP)에 대한 연구가 또한 진행되고 있다. LCD 패널위에 콘트롤러와 메모리와 같은 소자를 직접화시킴으로써 액정 표시 장치를 소형화시킬 수 있으며 신뢰성을 향상시킬 수가 있다. 본 연구에서는 SOP를 위한 ELA 방법을 통하여 결정화한 poly-Si TFT memory를 제작하여 전기적 특성을 조사하였다.

• Journal of the Optical Society of Korea
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• v.20 no.3
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• pp.368-380
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• 2016

There is no doubt that adaptive optics (AO) is the most promising method to compensate wavefront disturbance in free space optics communication (FSO). In order to improve the performance of the AO system described by discrete-time linear system model with time-delay and implicit phase turbulent model, new controllers based on a Kalman filter and its extensions are proposed. Based on the standard Kalman filter, we propose a fading memory filter to deal with the ruleless strong interference; sequential and U-D filters are applied to reduce implementation complexity for the embedded controllers. Theoretical analysis and the numerical simulations show that the proposed fading memory filter can upgrade the performance for AO systems in consideration of the unforeseen strong pulse interference, and the sequential and U-D filters perform well compared with a Kalman filter.

• Journal of information and communication convergence engineering
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• v.13 no.1
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• pp.27-35
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• 2015

Multiprecision multiplication is the most expensive operation in public key-based cryptography. Therefore, many multiplication methods have been studied intensively for several decades. In Workshop on Cryptographic Hardware and Embedded Systems 2011 (CHES2011), a novel multiplication method called 'operand caching' was proposed. This method reduces the number of required load instructions by caching the operands. However, it does not provide full operand caching when changing the row of partial products. To overcome this problem, a novel method, that is, 'consecutive operand caching' was proposed in Workshop on Information Security Applications 2012 (WISA2012). It divides a multiplication structure into partial products and reconstructs them to share common operands between previous and next partial products. However, there is still room for improvement; therefore, we propose a finely designed operand-caching mode to minimize useless memory accesses when the first row is changed. Finally, we reduce the number of memory access instructions and boost the speed of the overall multiprecision multiplication for public key cryptography.

• Journal of the Semiconductor & Display Technology
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• v.15 no.3
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• pp.40-45
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• 2016

In this paper, the fire engine pump is controlled and monitored by the AJAX (Asynchronous Javascript and Xml) in the web server. The embedded system with built-in system having a processor and a memory of high performance occurs many problems in transmitting the large amount of data in real time through the web server. The AJAX is different from HTML (Hyper Text Makeup Language) with java script technology and can make RIA (Rich Internet Application). It process the necessary data by using asynchronous and it take advantage of usefulness, accessibility, a fast response time. Using AJAX can build up web server with real time and monitoring that fire engine pump status, check processing pump memory in the event of fire, also remotely monitors can do. The web server system can control the fire engine pump as like the black box. The experimental results show the effectiveness and commercialize possibility.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.232-234
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• 2003

자바가상기계는 힙 영역과 자바 스택 영역에 객체와 스택 프레임을 할당할 공간이 없을 때 가비지 콜렉션과 함께 이미 해제된 힙과 자바 스택 영역을 재사용 가능하도록 메모리 공간을 재구성하게 된다. 한편 메모리 단편화로 인해 객체 또는 스택 프레임을 더 이상 할당하지 못하는 경우 자바가상기계는 컴펙션을 수행하여 메모리 단편화를 제거하면서 메모리를 재구성한다. 하지만 자바가상기계에서 메모리 재구성은 가비지 콜렉션및 컴펙션과 함께 길고 예측할 수 없는 지연시간에 의해 내장형 자바가상기계의 성능을 저하시키는 단점을 가진다. 본 논문은 소규모 내장형 자바가상기계의 성능을 개선하기 위한 방안으로, 가변 크기를 가지는 객체와 스택 프레임을 고정 크기로 변환하여 메모리를 할당하는 고정 크기 메모리 할당에 대해 기술하고 있다. 고정 크기 메모리 할당은 메모리 전체 사용율은 떨어지지만 외부 단편화가 발생하지 않기 때문에 회수된 메모리 공간을 재구성하지 않고도 힙 영역과 자바 스택 영역에 객체와 스택 프레임을 할당 가능하다. 본 논문에서 기술한 고정 크기 메모리 할당 방식으로 객체와 스택 프레임을 할당하게 되면 가변 크기 메모리 할당 보다 약 10% ~ 30% 효율향상을 보였다.

• Journal of the Optical Society of Korea
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• v.9 no.3
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• pp.92-94
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• 2005

We present a novel method for three-dimensional optical memory and microchannel embedded in fused silica glass. Three-dimensional dot patterning with a femtosecond laser pulse and observation with optical microscope are performed. Dot patterns are created by use of a 0.42 N.A. objective to focus 100 fs laser pulses inside the material. We demonstrate data storage with $2{\mu}m$ dot pitch and $7{\mu}m$layer spacing $(36 Gbit/cm^3)$. A three-dimensional microchannel acting as microfluidic and microoptical components is directly fabricated inside a silica glass. The optical micrographs of the microchannel are obtained by a digital camera of a microscope.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.12-25
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• 2022

In recent years, deep convolutional neural networks have made significant progress in the research of single image super-resolution. However, it is difficult to be applied in practical computing terminals or embedded devices due to a large number of parameters and computational effort. To balance these problems, we propose CSRNet, a lightweight neural network based on channel split residual learning structure, to reconstruct highresolution images from low-resolution images. Lightweight refers to designing a neural network with fewer parameters and a simplified structure for lower memory consumption and faster inference speed. At the same time, it is ensured that the performance of recovering high-resolution images is not degraded. In CSRNet, we reduce the parameters and computation by channel split residual learning. Simultaneously, we propose a double-upsampling network structure to improve the performance of the lightweight super-resolution network and make it easy to train. Finally, we propose a new evaluation metric for the lightweight approaches named 100_FPS. Experiments show that our proposed CSRNet not only speeds up the inference of the neural network and reduces memory consumption, but also performs well on single image super-resolution.