• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권5호
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• pp.546-550
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• 2010

본 논문에서는 모바일 폰에서 오프라인 필기체 과분할 인식의 후처리 방법에 관하여 논하였다. 제안된 방법은 조합 행렬 생성, 문자 조합 필터링, 문자 유사도 측정으로 구성된다. 조합 행렬 생성 과정은 각각의 조각의 인식 결과로부터 생성가능한 모든 조합 행렬을 계산하는 부분이며 조합 행렬을 그래프로 구성하게 된다. 문자 조합 필터링 과정은 그래프의 노드들과 단어 사전을 비교하여 불필요한 노드를 삭제하는 과정이며 문자 유사도 측정과정은 단어 사전의 각각의 단어들과 Levenshtein 거리(distance)를 계산하여 최적의 후처리 결과를 추출하게 된다. 제안된 방법의 인식률은 85.8%의 정확도를 보였다.

• 한국멀티미디어학회논문지
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• 제22권6호
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• pp.655-664
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• 2019

In this paper, we propose a novel way of combining multiple deep convolutional neural network (DCNN) architectures which work well for accurate video face identification by adopting a serial combination of 3D and 2D DCNNs. The proposed method first divides an input video sequence (to be recognized) into a number of sub-video sequences. The resulting sub-video sequences are used as input to the 3D DCNN so as to obtain the class-confidence scores for a given input video sequence by considering both temporal and spatial face feature characteristics of input video sequence. The class-confidence scores obtained from corresponding sub-video sequences is combined by forming our proposed class-confidence matrix. The resulting class-confidence matrix is then used as an input for learning 2D DCNN learning which is serially linked to 3D DCNN. Finally, fine-tuned, serially combined DCNN framework is applied for recognizing the identity present in a given test video sequence. To verify the effectiveness of our proposed method, extensive and comparative experiments have been conducted to evaluate our method on COX face databases with their standard face identification protocols. Experimental results showed that our method can achieve better or comparable identification rate compared to other state-of-the-art video FR methods.

• 한국정보전자통신기술학회논문지
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• 제14권3호
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• pp.208-214
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• 2021

최근 많은 지능형 보안 시나리오 및 범죄수사에서는 사진이 아닌 얼굴 영상과 다수의 정면 사진과의 매칭을 요구한다. 기존의 얼굴 인식 시스템은 이러한 요구를 충분히 충족시킬 수 없다. 본 논문에서는 동일 인물의 스케치와 사진 간의 양식 차이를 줄임으로써, 이질적 얼굴 인식 시스템의 성능을 향상시키는 알고리즘을 제안한다. 제안하는 알고리즘은 텍스처 기술자들(그레이 레벨 동시 발생 행렬, 멀티스케일 지역 이진 패턴)을 통하여 영상의 텍스처 특징들을 각각 추출하고, 이를 바탕으로 고유특징 정규화 및 추출기법을 통해 변환 행렬을 생성하게 된다. 이렇게 생성된 벡터들 간 계산된 스코어 값은 스코어 정규화 방식들을 통하여 최종적으로 스케치 영상의 신원을 인식하게 된다.

• The Plant Pathology Journal
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• 제30권1호
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• pp.10-24
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• 2014

Genetic diversity and differentiation of 50 Colletotrichum spp. isolates from legume crops studied through multigene loci, RAPD and ISSR analysis. DNA sequence comparisons by six genes (ITS, ACT, Tub2, CHS-1, GAPDH, and HIS3) verified species identity of C. truncatum, C. dematium and C. gloeosporiodes and identity C. capsici as a synonym of C. truncatum. Based on the matrix distance analysis of multigene sequences, the Colletotrichum species showed diverse degrees of intera and interspecific divergence (0.0 to 1.4%) and (15.5-19.9), respectively. A multilocus molecular phylogenetic analysis clustered Colletotrichum spp. isolates into 3 well-defined clades, representing three distinct species; C. truncatum, C. dematium and C. gloeosporioides. The ISSR and RAPD and cluster analysis exhibited a high degree of variability among different isolates and permitted the grouping of isolates of Colletotrichum spp. into three distinct clusters. Distinct populations of Colletotrichum spp. isolates were genetically in accordance with host specificity and inconsistent with geographical origins. The large population of C. truncatum showed greater amounts of genetic diversity than smaller populations of C. dematium and C. gloeosporioides species. Results of ISSR and RAPD markers were congruent, but the effective maker ratio and the number of private alleles were greater in ISSR markers.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2004년도 The 3rd Annual Conference for The Korean Society for Bioinformatics Association of Asian Societies for Bioinformatics 2004 Symposium
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• pp.265-271
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• 2004

The interaction network of protein -protein plays an important role to understand the various biological functions of cells. Currently, the high -throughput experimental techniques (two -dimensional gel electrophoresis, mass spectroscopy, yeast two -hybrid assay) provide us with the vast amount of data for protein-protein interaction at the proteome scale. In order to recognize the role of each protein in their network, the efficient bioinformatical and computational analysis methods are required. We propose a systematic and mathematical method which can analyze the protein -protein interaction network rigorously and enable us to capture the biological and physical essence of a topological character and stability of protein -protein network, and sensitivity of each protein along the biological pathway of their network. We set up a Laplacian matrix of spectral graph theory based on the protein-protein network of yeast proteome, and perform an eigenvalue analysis and apply a perturbation method on a Laplacian matrix, which result in recognizing the center of protein cluster, the identity of hub proteins around it and their relative sensitivities. Identifying the topology of protein -protein network via a Laplacian matrix, we can recognize the important relation between the biological pathway of yeast proteome and the formalism of master equation. The results of our systematic and mathematical analysis agree well with the experimental findings of yeast proteome. The biological function and meaning of each protein cluster can be explained easily. Our rigorous analysis method is robust for understanding various kinds of networks whether they are biological, social, economical...etc

• 한국정보과학회논문지:소프트웨어및응용
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• 제34권1호
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• pp.70-78
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• 2007

얼굴 인식 시스템의 성능은 조명 변화로 인하여 발생하는 개인내 (intra-person) 차이가 개인간 (inter-person)의 차이보다 클 수 있기 때문에 조명 변화에 많은 영향을 받는다. 본 연구에서는 이러한 문제를 해결하기 위해서 대칭형 bilinear 모델을 이용하여 조명 요소와 신원 요소를 분리하는 방법을 제안한다. Bilinear 모델로 조명 요소와 신원 요소를 얻기 위한 translation 과정은 반복적 역행렬을 구하는 것이 요구되는데 입력 데이타에 따라 수렴하지 않는 경우가 발생할 수 있다. 이러한 문제를 완화하기 위해서 ridge regression 모델과 bilinear 모델을 결합한 ridge regressive bilinear 모델을 제안하였다. 제안된 모델은 조명 요소와 신원 요소의 분산을 적절히 줄여줌으로서 bilinear 모델에 안정성을 제공하며, 인식에 더 많은 고차원 요소 정보를 이용하게 함으로써 인식 성능을 높여 준다. 실험 결과에서 제안한 ridge regressive bilinear 모델이 bilinear 모델, 고유얼굴(eigenface) 방법, Quotient image 보다 좋은 인식 성능을 보여줌을 확인 할 수 있다.

• The Journal of Asian Finance, Economics and Business
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• 제7권9호
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• pp.135-145
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• 2020

This paper provides the practical application of a linear shrinkage framework on Vietnam stock market. The cumulative data points observed in this analysis are 468 weeks from January 2011 to December 2019. All the companies listed on Ho Chi Minh City Stock Exchange (HOSE), except the companies under two years period from Initial Public Offering (IPO), are considered. The cumulative number of stocks picked is therefore 350 companies. The VNINDEX, which is the Vietnam Stock Index, is used as a reference index for shrinking to a single-index model. The empirical results show that the shrinkage of covariance matrix for portfolio optimization gives the promising results for the investors on Vietnam stock market. The shrinkage method helps the investors to produce the optimal portfolio in the sense of having higher profit with lower levels of risk compared to the portfolio of the traditional SCM method. Moreover, the portfolio turnover of shrinkage method is always kept at low magnitudes, and this makes the shrinkage portfolios save much transaction costs and reduce the liquidity risks in the trading process. In addition, the ability of shrinkage method in making profit is once again confirmed by the Alpha coefficient that achieves a high positive value.

• 대한수학회지
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• 제45권2호
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• pp.425-433
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• 2008

Let R be a ring with identity $1_R$ and let U(R) denote the group of all units of R. A ring R is called locally finite if every finite subset in it generates a finite semi group multiplicatively. In this paper, some results are obtained as follows: (1) for any semilocal (hence semiperfect) ring R, U(R) is a finite (resp. locally finite) group if and only if R is a finite (resp. locally finite) ring; U(R) is a locally finite group if and only if U$(M_n(R))$ is a locally finite group where $M_n(R)$ is the full matrix ring of $n{\times}n$ matrices over R for any positive integer n; in addition, if $2=1_R+1_R$ is a unit in R, then U(R) is an abelian group if and only if R is a commutative ring; (2) for any semiperfect ring R, if E(R), the set of all idempotents in R, is commuting, then $R/J\cong\oplus_{i=1}^mD_i$ where each $D_i$ is a division ring for some positive integer m and |E(R)|=$2^m$; in addition, if 2=$1_R+1_R$ is a unit in R, then every idempotent is central.

• 한국지능시스템학회논문지
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• 제26권1호
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• pp.50-55
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• 2016

본 논문은 특이섭동을 포함한 비선형 시스템을 위한 샘플치 제어 기법을 논한다. 비선형 시스템은 타카기--수게노(Takagi--Sugeno: T--S) 퍼지모델 형태로 표현됨을 가정한다. 새로운 리아푸노프 함수와 추가적인 항등식을 이용하여 선형행렬부등식 형태의 샘플치 폐루프 T--S 퍼지시스템의 점근적 안정도 조건을 제시한다. 분석결과에 대한 몇 가지 논의점을 언급한다. 모의실험에 의하여 제안된 기법의 타당성을 보인다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권3호
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• pp.1028-1046
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• 2022

Genome-wide association studies (GWAS) aim to find the significant genetic variants for common complex disease. However, genotype data has privacy information such as disease status and identity, which make data sharing and research difficult. Differential privacy is widely used in the privacy protection of data sharing. The current differential privacy approach in GWAS pays no attention to raw data but to statistical data, and doesn't achieve equilibrium between utility and privacy, so that data sharing is hindered and it hampers the development of genomics. To share data more securely, we propose a differential privacy preserving approach of data sharing for GWAS, and achieve the equilibrium between privacy and data utility. Firstly, a reasonable disturbance interval for the genotype is calculated based on the expected utility. Secondly, based on the interval, we get the Nash equilibrium point between utility and privacy. Finally, based on the equilibrium point, the original genotype matrix is perturbed with differential privacy, and the corresponding random genotype matrix is obtained. We theoretically and experimentally show that the method satisfies expected privacy protection and utility. This method provides engineering guidance for protecting GWAS data privacy.