• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.49-52
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• 2006

최근 대규모 지역 혹은 전 지구에 걸친 분석 및 모니터링을 위한 위성영상의 사용이 늘어나면서 이를 처리하기 위한 효율적인 '영상좌표 상호등록'법이 요구되고 있다. 이에 본 연구에서는 일반적으로 오랜 시간이 소요되는 '영상좌표 상호등록'의 효율성을 높이기 위해 '사전검수영역기반정합법'(Pre-qualified area based matching)을 사용하였다. 이를 통해 '영상좌표 상호등록'시 연산시간을 현저히 단축시켰고 추출된 정합점에 과대오차제거법을 적용함으로서 단순히 영역기반정합법을 적용한 경우에 비해서 정확도가 향상됨을 확인할 수 있었다. 제안한 알고리즘을 이용하여 테스트 프로그램을 작성, 한반도 Landsat ETM+ 영상 3장을 이용하여 테스트하였다. 정합점 간의 평균제곱오차는 0.436 영상소, 정합점은 평균 38,475개로 나타났다. 연산시 간은 평균 약 8분으로 나타났다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.12
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• pp.1112-1115
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• 2016

Global Positioning System(GPS) is a useful system used in both civilian and military applications. However, the signal of GPS is susceptible to jamming attacks due to low receive sensitivity, since the signals come from the satellite located at over 20,000 km above the earth. In this paper, we have conducted a preceding research on a non-Foster matching circuit that efficiently matches an electrically ultra-small GPS antenna. Electrically Small Antennas(ESAs) are inefficient radiators and are difficult to match in wideband due to extremely high quality factor. In order to match small GPS antenna in wideband, a non-Foster matching circuit for a small GPS antenna was designed. A negative impedance converter circuit consisting of Linvill's cross-coupled pair transistors was fabricated and its stability was verified by the time-domain stability analysis. In addition, anechoic chamber measurements show that the non-Foster matching circuit for small GPS antenna can lead bore-sight gain improvement by more than 17 dB.

• The Journal of the Acoustical Society of Korea
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• v.20 no.8
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• pp.67-73
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• 2001

The shallow-water environment presents additional challenges arising from the complex interaction patterns of the sound with the sea bed. In order to overcome the difficulties generated by shallow-water propagation, broad-band matched field processing has been employed in an effort to increase robustness by utilizing multiple frequency information. In this paper, a coherent broad-band matched field processor is introduced that incorporates the spatial coherence of the acoustic field not only over one frequency but across frequencies. The incoherent and coherent processors are applied to the experimental data where it is shown that both processors give a high probability of correct localization. Also it is found that a coherent processor has better performance in the sidelobe pattern of ambiguity surfaces.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10B
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• pp.1210-1215
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• 2011

In this paper, a supervised adaptive equalization algorithm based on probability density function (PDF) matching method is introduced and its decision-feedback version is proposed for underwater communication channels with strong impulsive noise and severe multipath characteristics. The conventional least mean square (LMS) algorithm based on mean squared error (MSE) criterion has shown to be incapable of coping with impulsive noise and multipath effects commonly shown in underwater communications. The linear PDF matching algorithm, which shows immunity to impulsive noise, however, has revealed to yield unsatisfying performance under severe multipath environments with impulsive noise. On the other hand, the proposed nonlinear PDF matching algorithm with decision feedback proves in the simulation to possess superior robustness against impulsive noise and multipath characteristics of underwater communication channels.

• Journal of Biomedical Engineering Research
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• v.21 no.2
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• pp.157-163
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• 2000

최근 MR영상을 허혈성 뇌졸중의 초급성기에 뇌조직의 관류 이상을 조기에 진단하려는 연구들이 진행되고 있으나 아직 일반적인 진단용 소프트웨어만 있을 뿐 영상 자료를 후처리하여 뇌조직의 구조 및 기능적인 정보를 제공하는 mapping 영상을 특수 소프트웨어는 실용화되어 있지 않다. 본 논문에서는 Gamma-variate 곡선 정합을 이용한 뇌관류 파라미터 영상 mapping의 알고리즘 구현에 관해 연구하였다. 관류 MR영상의 각 화소마다 측정된 시간에 따른 신호강도의 변화 곡선은 비선형적이어서 뇌관류에 관한 여러 가지 혈역학적 변수들을 보다 정확하게 계산할 수 없었다. 그래서 수렴속도가 빠르고 안정성이 높은 비선형 최적화 알고리즘인 Levenberg-Marquardt 알고리즘(LMA)을 활용하였다. 즉 시간에 따른 신호강도의 변화 곡선을 Gamma-variate 함수를 이용하여 곡선 정합한 후, CBV, MTT, CBF, TTP, BAT, MS의 여러 가지 혈역학적 변수를 LMA에 의해 계산하였다. 그 결과로 관류 MR영상으로부터 얻은 mapping 영상은 초급성 허혈성 뇌졸중에서 관류에 관한 혈역학적 변화를 평가함으로써 나중에 생길 뇌경색의 범위를 예견하는 데에 유용하였다.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.253-261
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• 2013

In this paper, we study the problem of controlling composite asynchronous sequential machines. The considered asynchronous machine consists of two input/state machines in cascade connection, where the output of the front machine is delivered to the input channel of the rear machine. The objective is to design a corrective controller realizing model matching such that the stable state behavior of the closed-loop system matches that of a reference model. Since the controller receives the state feedback of the rear machine only, there exists uncertainty about the present state of the front machine. We specify the existence condition for a corrective controller given the uncertainty. The design procedure for the proposed controller is described in a case study.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.64-74
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• 2019

Although a non-rigid registration has high demands in clinical practice, it has a high computational complexity and it is very difficult for ensuring the accuracy and robustness of registration. This study proposes a method of applying a non-rigid registration to 3D magnetic resonance images of brain in an unsupervised learning environment by using a deep-learning network. A feature vector between two images is produced through the network by receiving both images from two different patients as inputs and it transforms the target image to match the source image by creating a displacement vector field. The network is designed based on a U-Net shape so that feature vectors that consider all global and local differences between two images can be constructed when performing the registration. As a regularization term is added to a loss function, a transformation result similar to that of a real brain movement can be obtained after the application of trilinear interpolation. This method enables a non-rigid registration with a single-pass deformation by only receiving two arbitrary images as inputs through an unsupervised learning. Therefore, it can perform faster than other non-learning-based registration methods that require iterative optimization processes. Our experiment was performed with 3D magnetic resonance images of 50 human brains, and the measurement result of the dice similarity coefficient confirmed an approximately 16% similarity improvement by using our method after the registration. It also showed a similar performance compared with the non-learning-based method, with about 10,000 times speed increase. The proposed method can be used for non-rigid registration of various kinds of medical image data.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.93-106
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• 2019

Persona is an actor's external ego constructed by playing various roles, and his/her another self-portrait in the eyes of the audience. This study was conducted to analyze persona identity containing core persona(CP) and to gain implications for the growth strategy of the actress Son Ye-jin called "melo queen" by verifying consistency between the CP and audience responses to her starring works of the past. According to the related theories and models, the persona was firstly set as image, visuality, personality and consistency, and it was used to extract and sort descriptive texts about Son related news articles in the last 5 years of the six major Korean newspapers using the content analysis method. After that, we analyzed the number of viewers of her movies and the audience share of her dramas by genre. As a result, Son's persona components were found to have a proportion for 54.2% images (34.0% for melo and romance images, 20.2% for non-melo and romance images), 25.6% for visibility, 13.8% for consistency, and 6.4% for personality. Her CP was derived from a melo and romance image. Comparing this with the audience reaction, the melo romance genre dominated and showed consistency in the drama, but in the case of the film, the non-melo romance was dominant and did not match each other. The results were attributed to a wide gap between dramas and movies in terms of key viewers, box office factors, degree of genre hybridity and experimentality. Therefore, Son should actively use her CP in the drama and challenge the various roles in order to expand her persona spectrum in the film.

• Journal of the Korea Computer Graphics Society
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• v.7 no.1
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• pp.37-49
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• 2001

We propose an optimization of mutual information for multiresolution image registration to represent useful information as integrated form obtaining from complementary information of multi modality images. The method applies mutual information as cost function to measure the statistical dependency or information redundancy between the image intensities of corresponding pixels in both images, which is assumed to be maximal if the images are geometrically aligned. As experimental results we validate visual inspection for accuracy, changning initial condition and addictive noise for robustness. Since our method uses the native image rather than prior feature extraction, few user interaction is required to perform the registration. In addition it leads to robust density estimation and convergence as applying non-parametric density estimation and stochastic multiresolution optimization.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.6
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• pp.445-449
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• 2009

In this paper, we propose a computationally efficient multi GPU accelerated image registration technique to correct the motion difference between the pre-contrast CT image and post-contrast CTA image. Our method consists of two steps: multi GPU based image registration and a cerebrovascular visualization. At first, it computes a similarity measure considering the parallelism between both GPUs as well as the parallelism inside GPU for performing the voxel-based registration. Then, it subtracts a CT image transformed by optimal transformation matrix from CTA image, and visualizes the subtracted volume using GPU based volume rendering technique. In this paper, we compare our proposed method with existing methods using 5 pairs of pre-contrast brain CT image and post-contrast brain CTA image in order to prove the superiority of our method in regard to visual quality and computational time. Experimental results show that our method well visualizes a brain vessel, so it well diagnose a vessel disease. Our multi GPU based approach is 11.6 times faster than CPU based approach and 1.4 times faster than single GPU based approach for total processing.