• 한국전산구조공학회논문집
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• 제23권5호
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• pp.475-482
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• 2010

본 논문에서는 대규모 자유도 시스템의 병렬처리를 위하여 2단계로 이루어진 영역분할법(Domain Decomposition Method) 기반의 병렬 알고리즘을 제안하였다. 분할된 영역의 내부 및 외부 경계를 상위영역문제로 정의하고 국부영역문제는 변위 경계조건이 모두 주어지는 분할영역에서의 Dirichlet 문제로 구성한다. 상위영역에서는 전체 상위영역에 대한 강성 행렬의 어셈블이 필요없는 반복법을 통하여 변위를 구하고, 이를 바탕으로 국부영역에서 Multi-Frontal Sparse Solver (MFSS)를 이용하여 변위를 계산한다. 상위영역문제의 연산에서 프로세서 간의 데이터 교환을 최소화하여 계산효율을 유지하며, 동시에 해석 가능한 자유도를 증대시키는 병렬 PCG(Preconditioned Conjugate Gradient)법 기반의 알고리즘을 개발하였다. 제안된 알고리즘을 적용하여 수치해석을 수행한 결과, 프로세서 수가 증가할수록 계산성능의 손실없이 해석 가능한 자유도가 비례하여 증가하는 선형 확장성을 관찰할 수 있었으며, 대규모 자유도 문제에 효과적으로 사용 가능함을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.113-115
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• 2005

This thesis presents a method for 3D modeling of facial expression from frontal and mirror-reflected multi-image. Since the proposed system uses only one camera, two mirrors, and simple mirror's property, it is robust, accurate and inexpensive. In addition, we can avoid the problem of synchronization between data among different cameras. Mirrors located near one's cheeks can reflect the side views of markers on one's face. To optimize our system, we must select feature points of face intimately associated with human's emotions. Therefore we refer to the FDP (Facial Definition Parameters) and FAP (Facial Animation Parameters) defined by MPEG-4 SNHC (Synlhetic/Natural Hybrid Coding). We put colorful dot markers on selected feature points of face to detect movement of facial deformation when subject makes variety expressions. Before computing the 3D coordinates of extracted facial feature points, we properly grouped these points according to relative part. This makes our matching process automatically. We experiment on about twenty koreans the subject of our experiment in their late twenties and early thirties. Finally, we verify the performance of the proposed method tv simulating an animation of 3D facial expression.

• 인지과학
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• 제18권4호
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• pp.445-455
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• 2007

본 논문은 주성분분석기법을 이용한 치아의 다면특징을 기반으로 한 새로운 생체 식별시스템을 제안한다. 치아의 다면 특징들은 정면치아와 좌측, 우측 치아들로 이루어진다. 우리는 실생활 환경에서 보안 접속을 위하여 치아를 이용한 생체식별을 목표로 한다. 다면 치아 영상들은 특별히 고안된 실험환경에서 획득되었으며, 개인 식별을 위한 특징으로 42개의 주성분이 개발되었다. 개인 식별은 학습된 다면치아와 회전된 다면치아 사이의 최소근접기법에 의해 계산되었다. 2도 회전 후의 다면치아 인식성능은 평균값으로 좌측면 치아 95.2%, 우측면 치아 91.3%을 보였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 추계학술대회논문집
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• pp.561-562
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• 2008

The numerical analysis of sound radiation by vibrating structure is a well known and mature technology used in many industries. Accurate methods based on the boundary or finite element method have been successfully developed over the last two decades and are now available in standard CAE tools. These methods are however known to require significant computational resources which, furthermore, very quickly increase with the frequency of interest. The low speed of most current methods is a main obstacle for a systematic use of acoustic CAE in industrial design processes. In this paper we are going to present a set of innovative techniques that significantly speed-up the calculation of acoustic radiation indicators (acoustic pressure, velocity, intensity and power; contribution vectors). The modeling is based on the well known combination of finite elements and infinite elements but also combines the following ingredients to obtain a very high performance: o a multi-frontal massively parallel sparse direct solver; o a multi-frequency solver based on the Krylov method; o the use of pellicular acoustic modes as a vector basis for representing acoustic excitations; o the numerical evaluation of Green functions related to the specific geometry of the problem under investigation. All these ingredients are embedded in the ACTRAN/AR CAE tool which provides unprecedented performance for acoustic radiation analysis. The method will be demonstrated on several applications taken from various industries.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권10호
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• pp.4903-4929
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• 2018

In this study, a fully automatic pose and expression invariant 3D face alignment algorithm is proposed to handle frontal and profile face images which is based on a two pass course to fine alignment strategy. The first pass of the algorithm coarsely aligns the face images to an intrinsic coordinate system (ICS) through a single 3D rotation and the second pass aligns them at fine level using a minimum nose tip-scanner distance (MNSD) approach. For facial recognition, multi-view faces are synthesized to exploit real 3D information and test the efficacy of the proposed system. Due to optimal separating hyper plane (OSH), Support Vector Machine (SVM) is employed in multi-view face verification (FV) task. In addition, a multi stage unified classifier based face identification (FI) algorithm is employed which combines results from seven base classifiers, two parallel face recognition algorithms and an exponential rank combiner, all in a hierarchical manner. The performance figures of the proposed methodology are corroborated by extensive experiments performed on four benchmark datasets: GavabDB, Bosphorus, UMB-DB and FRGC v2.0. Results show mark improvement in alignment accuracy and recognition rates. Moreover, a computational complexity analysis has been carried out for the proposed algorithm which reveals its superiority in terms of computational efficiency as well.

• Archives of Plastic Surgery
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• 제40권5호
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• pp.564-569
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• 2013

Background Scalp defects may be caused by various etiological factors, and they represent a significant surgical and aesthetic concern. Various surgical techniques can be applied for reconstructive work such as primary closure, skin grafting, pedicled or free flaps. In this article, the authors share their clinical experience with scalp operations using the technique of local flaps and discuss the application of this method from the perspective of not only the size of the defect, but also in relation to the anatomical area, quality of surrounding tissue, and patient's condition. Methods During the period from December 2007 to December 2012, 13 patients with various scalp defects, aged 11 to 86 years, underwent reconstruction with local pedicle flaps. The indications were based on the patients' condition (age, sex, quality of surrounding tissue, and comorbidities) and wound parameters. Depending on the size of the defects, they were classified into three groups as follows: large, 20 to 50 $cm^2$; very large, 50 to 100 $cm^2$; extremely large, 100 $cm^2$. The location was defined as peripheral (frontal, temporal, occipital), central, or combined (more than one area). We performed reconstruction with 11 single transposition flaps and 1 bipedicle with a skin graft on the donor area, and 2 advancement flaps in 1 patient. Results In all of the patients, complete tissue coverage was achieved. The recovery was relatively quick, without hematoma, seroma, or infections. The flaps survived entirely. Conclusions Local flaps are widely used in scalp reconstruction since they provide healthy, stable, hair-bearing tissue and require a short healing time for the patients.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2000년도 추계 학술대회논문집
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• pp.1-8
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• 2000

In this work, Internet Supercomputing methodology is introduced and the concept is materialized for large-scale finite element analysis. The primary resources of Internet Supercomputing are numerous idling PCs connected by Internet with no regards to their locations. Therefore, it becomes one of the most affordable ways to achieve supercomputing power unlimitedly if the appropriate parallel algorithm and the operating program are developed for this slow network environment. Under the above concept, virtual supercomputing system InterSup I is constructed and tested. To establish the InterSup I system, 64 CPU nodes, which are located in several places and connected by Internet, are conscripted, and parallel finite element software is developed for linear static analysis of structures based on the parallel multi-frontal algorithm. By the established InterSup I system, analysis of finite element structural model having around five million DOFs are solved to check the affordability and effectiveness of Internet Supercomputing.

• 한국멀티미디어학회:학술대회논문집
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• 한국멀티미디어학회 2004년도 춘계학술발표대회논문집
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• pp.859-862
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• 2004

전두엽에서 뇌파를 측정했을 때 안전도에 의해 뇌파는 크게 왜곡되게 되는데, 제안한 뇌파 적응필터를 이용하여 측정된 뇌파에서 안전도를 제거하게 된다. 제안한 필터는 전두엽에서 다채널 뇌파를 처리할 수 있는 구조이며 적응필터 기반의 FIR 필터구조로 이루어져 기존의 다채널 적응필터 구조보다 계산량을 크게 줄였고, 짧은 연산 시간으로 실시간 DSP 보드 수행시 더 많은 채널을 수행할 수 있게 되었다. 또한 일반적인 적응필터와는 달리 기준신호 없이 신호처리가 가능한 적응 신호선 보정기 구조이므로 한 채널에 대해서 하나의 입력 신호로 원하는 신호를 얻을 수 있다. 실험을 통하여 제안한 FIR 필터가 뇌파 측정시 안전도를 효과적으로 제거함을 확인하였다.

• Korean Journal of Acupuncture
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• 제30권3호
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• pp.161-170
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• 2013

목적 : 침치료는 침자극을 가한 뒤, 발침한 뒤에 효과를 나타낸다. 그러므로 침연구에 있어서 침자극을 가하고 발침한 뒤에 나타나는 침의 반응을 관찰하여야 할 필요가 있다. 이에 본 연구에서는 안정성 네트워크를 이용하여 침자극 후의 반응을 관찰하여 발침 후에 뇌에 미치는 침의 반응을 관찰하였다. 방법 : 침자극에 의하여 나타나는 안정성 네트워크의 변화를 관찰하기 위하여 기능성 자기공명 영상장치를 사용하여 12명의 건강인을 대상으로 우측 양릉천 혈자리에 자침한 후, 침자극 전후의 뇌를 촬영하였다. 그리고 regional homogeneity(ReHo)와 amplitude of low frequency fluctuation(ALFF)를 이용하여 데이터를 분석하였다. 결과 : ReHo와 ALFF에서 공통적으로 안정성 네트워크가 증가된 영역은 좌우측 중전두이랑, 좌측 내측전두이랑, 좌측 상전두이랑, 그리고 우측 뒤쪽 띠이랑의 뇌부위였다. 특히 ReHo분석 결과 섬엽, 앞쪽 띠이랑과 선조체에서 안정성 네트워크가 증가된 것이 관찰되었는데, 이들 영역은 침의 진통작용과 관련된 영역들이다. 하지만 ALFF 분석결과에서는 이들 영역들이 나타나지 않았다. 결론 : ReHo와 ALFF 모두에서 침자극에 의한 안정성 네트워크의 변화를 관찰할 수 있었다. 또한 ReHo분석을 통하여 침자극에 의한 진통관련 영역들의 반응을 관찰할 수 있었다.

• 제어로봇시스템학회논문지
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• 제21권1호
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• pp.59-64
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• 2015

In this paper, we found the usefulness of the deep belief network (DBN) in the fields of brain-computer interface (BCI), especially in relation to imagined speech. In recent years, the growth of interest in the BCI field has led to the development of a number of useful applications, such as robot control, game interfaces, exoskeleton limbs, and so on. However, while imagined speech, which could be used for communication or military purpose devices, is one of the most exciting BCI applications, there are some problems in implementing the system. In the previous paper, we already handled some of the issues of imagined speech when using the International Phonetic Alphabet (IPA), although it required complementation for multi class classification problems. In view of this point, this paper could provide a suitable solution for vowel classification for imagined speech. We used the DBN algorithm, which is known as a deep learning algorithm for multi-class vowel classification, and selected four vowel pronunciations:, /a/, /i/, /o/, /u/ from IPA. For the experiment, we obtained the required 32 channel raw electroencephalogram (EEG) data from three male subjects, and electrodes were placed on the scalp of the frontal lobe and both temporal lobes which are related to thinking and verbal function. Eigenvalues of the covariance matrix of the EEG data were used as the feature vector of each vowel. In the analysis, we provided the classification results of the back propagation artificial neural network (BP-ANN) for making a comparison with DBN. As a result, the classification results from the BP-ANN were 52.04%, and the DBN was 87.96%. This means the DBN showed 35.92% better classification results in multi class imagined speech classification. In addition, the DBN spent much less time in whole computation time. In conclusion, the DBN algorithm is efficient in BCI system implementation.