• 대한기계학회논문집B
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• 제22권4호
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• pp.440-451
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• 1998

An experimental study has been conducted to investigate solidification of NH$_{4}$CI-H$_{2}$0 mixtures inside a vertical rectangular enclosure. Solidification process is visualized by the shadowgraph method. Emphasis is placed on the effect of solidification parameters such as the aspect ratio, cooling wall temperature and initial composition. The aspect ratio shows a dominant effect on the number and developing time of the double diffusive layers which reveals the relative strength of solutal convection to thermal convection. Similar flow pattern is observed when the concentration difference between interdendritic liquid and the pure liquid which drives solutal convection is the same regardless of the different cooling wall temperature and initial concentration.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2002년도 춘계학술대회논문집
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• pp.273-277
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• 2002

This paper describes an optimal synthesis method of binary neural network(BNN) for an approximation problem of a circular region and synthetic image having four class using a newly proposed learning algorithm. Our object is to minimize the number of connections and neurons in hidden layer by using a Newly Expanded and Truncated Learning Algorithm(NETLA) based on the multilayer BNN. The synthesis method in the NETLA is based on the extension principle of Expanded and Truncated Learning (ETL) learning algorithm using the multilayer perceptron and is based on Expanded Sum of Product (ESP) as one of the boolean expression techniques. The number of the required neurons in hidden layer can be reduced and fasted for learning pattern recognition.. The superiority of this NETLA to other algorithms was proved by simulation.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2001년도 춘계학술대회논문집:21세기 신지식정보의 창출
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• pp.64-76
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• 2001

In this paper, A simple image hologram encryption and decryption technique based on the principle of interference are proposed. The technique using the photorefractive material for getting a stable interference pattern is also proposed. And combine these two techniques, I would like to implement a stable optical information security system. In the encrypting process, I would generate binary phase hologram which can reconstruct original image perfectly, and regard this hologram as original image to be encrypted image. And then the hologram is encrypted as randomly generated binary phase image. Reference image is also generated from the encrypted image by applying interference rule. In the decrypting process, I can get a interference intensity by interfering the reference image and the encrypted image in the interferometer. and transform inferference intensity information into phase information. I recover original image by inverse Fourier transforming the phase information. In this process, the intensity information generated by interference of two images is very sensitive to external vibrations. So, I would like to get a stable interference using the characteristic of SPPCM(self pumped phase conjugate mirror) in photorefractive materials, especially BaTiO₃.

• 한국통신학회논문지
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• 제28권5C호
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• pp.468-475
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• 2003

본 논문에서는 패턴생성을 위한 최적의 이진 위상 컴퓨터형성 홀로그램을 설계하기 위해 합성된 SA알고리듬 및 유전 알고리듬을 이용하였다. 제안된 방법의 탐색과정에서 sGA를 사용하여 BPCGH를 생성하고. 결과 홀로그램 패턴을 SA 알고리듬의 초기 랜덤 투과함수로 이용하여 최적의 BPCGH를 설계하였다. 컴퓨터 시뮬레이션에서 독립적으로 사용된 SA 알고리듬과 유전 알고리듬을 비교한 결과 제안한 알고리듬이 회절 효율이 향상된 것을 확인할 수 있었다.

• 한국멀티미디어학회논문지
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• 제24권11호
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• pp.1461-1471
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• 2021

This paper presents a light exposure correction algorithm for less pleasant images, acquired with a light metering failure. Since conventional tone mapping and gamma correction methods adopt a function mapping with the same range of input and output, the results are pleasurable for almost symmetric distributions to their intensity average. However, their corrections gave insufficient outputs for asymmetric cases at either bright or dark regions. Also, histogram modification approaches show good results on varied pattern images, but these generate unintentional noises at flat regions because of the compulsive shift of the intensity distribution. Therefore, in order to sufficient corrections for both bright and dark areas, the proposed algorithm calculates the gamma coefficients using primary parameters extracted from the global distribution. And the fusion weights are adaptively determined with complementary parameters, considering the classification information of a binary segmentation. As the result, the proposed algorithm can obtain a good output about both the symmetric and the asymmetric distribution images even with severe exposure values.

• 대한한의학회지
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• 제40권4호
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• pp.49-60
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• 2019

Objectives: To develop a standardized diagnostic pattern identification equation for stroke patients, our group conducted a study to derive the predictive logistic equations. However, the sample size was relatively small. In the current study, we aimed to derive new predictive logistic equations for each diagnostic pattern using an expanded number of subjects. Methods: This study was a hospital-based multi-center trial recruited stroke patients within 30 days of symptom onset. Patients' general information, and the variables related to diagnostic pattern identification were measured. The diagnostic pattern of each patient was identified independently by two Korean Medicine Doctors. To derive a predictive model for pattern identification, binary logistic regression analysis was applied. Results: Among the 1,251 patients, 385 patients (30.8%) had the Fire Heat Pattern, 460 patients (36.8%) the Phlegm Dampness Pattern, 212 patients (16.9%) the Qi Deficiency Pattern, and 194 patients (15.5%) the Yin Deficiency Pattern. After the regression analysis, the predictive logistic equations for each pattern were determined. Conclusion: The predictive equations for Fire Heat, Phlegm Dampness, Qi Deficiency, and Yin Deficiency would be useful to determine individual stroke patients' pattern identification in the clinical setting. However, further studies using objective measurements are necessary to validate these data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권9호
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• pp.4549-4566
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• 2017

This work presents a novel facial descriptor, which is named as multiscale adaptive local directional texture pattern (MALDTP) and employed for expression recognition. We apply an adaptive threshold value to encode facial image in different scales, and concatenate a series of histograms based on the MALDTP to generate facial descriptor in term of Gabor filters. In addition, some dedicated experiments were conducted to evaluate the performance of the MALDTP method in a person-independent way. The experimental results demonstrate that our proposed method achieves higher recognition rate than local directional texture pattern (LDTP). Moreover, the MALDTP method has lower computational complexity, fewer storage space and higher classification accuracy than local Gabor binary pattern histogram sequence (LGBPHS) method. In a nutshell, the proposed MALDTP method can not only avoid choosing the threshold by experience but also contain much more structural and contrast information of facial image than LDTP.

• 융합보안논문지
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• 제14권5호
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• pp.49-56
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• 2014

본 논문에서는 기존의 제안된 LDP(Local Directional Pattern)에 기반하여 지역적인 얼굴특징을 표현하는 방법을 제안한다. 제안된 방법은 눈과 입과 같은 얼굴의 영구적인 특징과 표정이 변하면서 발생하는 일시적인 특징을 효과적으로 표현할 수 있도록 얼굴특징별로 크기와 형태를 달리하는 중첩 가능한 블록을 설정하고 이를 바탕으로 얼굴 특징벡터를 구성한다. 제안된 중첩 블록설정 및 특징 표현 방법은 기하학적 특징을 기반으로 하는 접근 방법의 장점을 수용할 뿐만 아니라 각 얼굴특징의 움직임 특성을 이용하여 얼굴검출에 대한 오류를 수용할 수 있고, 블록사이즈의 가변성으로 인한 공간정보를 유지할 수 있어 표본오차를 줄일 수 있는 장점이 있다. 실험결과, 제안된 방법은 기존 방법에 비해 인식률이 향상됨을 확인하였고, 기존 얼굴 특징 벡터보다 길이가 짧기 때문에 연산량 또한 감소하는 것을 확인하였다.

• 한국멀티미디어학회논문지
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• 제4권3호
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• pp.247-256
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• 2001

디지털 워터마킹은 데이터 내부에 지각적으로 인식되지 않는 신호를 삽입하여 저작권을 보호하기 위한 방법으로 압축, 기하학적 변환, 크기변환 등의 공격도 영상 데이터가 견고한 특성을 나타낼 수 있는 방법을 중심으로 연구되어 왔으나 프린트 영상에 대하여 저작권을 보호하는 연구는 그다지 활발하지 않았다. 본 논문에서는 이진 프린트 영상에 워터마크를 삽입하는 새로운 방법을 제안한다. 제안방법은 영상을 디더링 한 후 $16\times{16}$ 크기의 블록에서 1(백화소)의 개수를 카운팅하고 카운팅 배열을 $2\times{2}$ 블록씩 나누어 워터마크 값에 따라 다르게 정의된 기준 블록 패턴과 비교함으로 워터마크를 삽입한다. 워터마크 정보는 '1' 과 '0'의 두 가지를 사용하여 동일한 워터마크 비트로 더 많은 정보를 표현할 수 있다. 워터마크 검출은 워터마크가 삽입된 영상과 기준 블록 패턴을 이용해 워터마크 정보를 재구성하고, 재구성된 워터마크와 디더 영상에 삽입된 원본의 워터마크 정보와 비교함으로 가능하다. 성능평가는 워터마크 삽입영상을 프린트 한 후 스캔하여 기존의 방법과 검출 성능을 비교하였다.

• 제어로봇시스템학회논문지
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• 제19권6호
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• pp.527-533
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• 2013

BCI (Brain-Computer Interface) is a system that transforms a subject's brain signal related to their intention into a control signal by classifying EEG (electroencephalograph) signals obtained during the imagination of movement of a subject's limbs. The BCI system allows us to control machines such as robot arms or wheelchairs only by imaging limbs. With the exact same experiment environment, activated brain regions of each subjects are totally different. In that case, a simple approach is to use as many channels as possible when measuring brain signals. However the problem is that using many channels also causes other problems. When applying a CSP (Common Spatial Pattern), which is an EEG extraction method, many channels cause an overfitting problem, and in addition there is difficulty using this technique for medical analysis. To overcome these problems, we suggest an optimal channel selection method using a BPSO (Binary Particle Swarm Optimization), BPSO with channel impact factor, and GA. This paper examined optimal selected channels among all channels using three optimization methods and compared the classification accuracy and the number of selected channels between BPSO, BPSO with channel impact factor, and GA by SVM (Support Vector Machine). The result showed that BPSO with channel impact factor selected 2 fewer channels and even improved accuracy by 10.17~11.34% compared with BPSO and GA.